Category: 8. Health

  • Vomiting to Arrest: A 37-Year-Old’s Bizarre Diagnosis

    Vomiting to Arrest: A 37-Year-Old’s Bizarre Diagnosis

    Key Takeaways

    A 37-year-old man with a history of Roux-en-Y gastric bypass and chronic alcohol use was found collapsed at home after a possible 48-hour period.

    Shortly after initial mobilisation by emergency responders, he developed sudden cardiac arrest, with return of spontaneous circulation achieved within 2 minutes.

    Following transport and hospital admission, the patient remained hypotensive and required ICU admission with mechanical ventilation.

    A whole-body CT scan performed during transfer from the emergency department to the ICU revealed extensive air in the epidural space extending from the cervical to thoracic spine, along with pneumomediastinum surrounding the great vessels. No pneumothorax or free fluid was noted.

    The case reported by Jérôme Dehon, MD, a resident physician in emergency medicine and critical care, and colleagues at the Université Catholique de Louvain in Brussels, Belgium, documents a rare and dramatic clinical condition.

    The Patient and His History

    The patient was brought to the emergency department after being found collapsed at home, with a possible 48-hour delay before the discovery.

    Shortly after the initial mobilisation by the emergency responders, he experienced a sudden cardiac arrest. Cardiopulmonary resuscitation was initiated immediately, and return of spontaneous circulation was achieved within 2 minutes after a single dose of intravenous epinephrine.

    Despite fluid resuscitation, the patient remained hypotensive after admission to the emergency department and was transferred to the ICU for vasopressor support and further evaluation.

    He was sedated, intubated, and mechanically ventilated, and his recent postcardiac arrest status further limited the possibility of a reliable neurologic assessment.

    Findings and Diagnosis

    The patient’s vital signs were continuously monitored. A whole-body CT scan performed during the transfer from the emergency department to the ICU revealed extensive air in the epidural space from the cervical to thoracic spine, along with pneumomediastinum surrounding the great vessels in the absence of pneumothorax or free fluid.

    Collateral history from the patient’s family revealed multiple episodes of severe vomiting in the days before presentation.

    Given the patient’s surgical history and radiologic findings, an oesophageal perforation was initially suspected. An upper endoscopy was performed but showed no evidence of a significant fistula or visible perforation.

    After sedation was weaned, neurologic examination revealed no focal deficits. Transient vertical nystagmus was observed and resolved following empirical thiamine supplementation.

    Although a brain MRI performed 2 weeks later showed no structural abnormalities suggestive of Wernicke encephalopathy, the clinical response supported this working diagnosis in the context of prior bariatric surgery and chronic alcohol use.

    The patient’s clinical status improved steadily with supportive treatment. Follow-up CT imaging showed complete resolution of both pneumomediastinum and pneumorachis.

    Alveolar barotrauma secondary to repeated vomiting was considered the most likely cause, resulting in air dissection into the mediastinum and epidural space.

    Discussion

    Spontaneous pneumorachis, defined as the presence of air in the spinal canal without trauma or recent instrumentation, is an exceptionally rare entity. Reliable epidemiologic data on its frequency in Germany are lacking, but it is considered exceedingly rare. This case report “serves as a reminder that while the Macklin effect offers a plausible mechanism for air dissection into the epidural space, potentially life-threatening conditions such as oesophageal rupture must always be actively excluded. The striking radiological findings initially raised concerns regarding life-threatening pathology; however, the clinical course proved benign under conservative management. The case reminds us that dramatic imaging should not overshadow clinical reasoning and that management must remain rooted in structured, evidence-based assessment,” the author concluded.

    This article was translated from Univadis Germany.

    Continue Reading

  • Doctors fight vaccine mistrust as Romania hit by measles outbreak


    DHAKA: Abdur Rahman Tarif was talking to his sister Meherunnesa over the phone when the voice on the other end of the call suddenly fell silent.

    In that moment, Tarif knew something bad had happened. He rushed home, dodging the exchange of fire between security forces and protesters on the streets of Dhaka. When he finally arrived, he discovered his parents tending to his bleeding sister.

    A stray bullet had hit Meherunnesa’s chest while she was standing beside the window of her room, Tarif said. She was taken to a hospital where doctors declared her dead.

    Meherunnesa, 23, was killed on Aug. 5 last year, the same day Bangladesh’s former Prime Minister Sheikh Hasina was forced to flee the country in a massive student-led uprising, which ended her 15-year rule. For much of Bangladesh, Hasina’s ouster was a moment of joy. Three days later, Nobel Peace Prize laureate Muhammad Yunus took over the country as head of an interim government, promising to restore order and hold a new election after necessary reforms.

    A year on, Bangladesh is still reeling from that violence, and Hasina now faces trial for crimes against humanity, in absentia as she is in exile in India. But despite the bloodshed and lives lost, many say the prospect for a better Bangladesh with a liberal democracy, political tolerance and religious and communal harmony has remained a challenge.

    “The hope of the thousands who braved lethal violence a year ago when they opposed Sheikh Hasina’s abusive rule to build a rights-respecting democracy remains unfulfilled,” said Meenakshi Ganguly, deputy Asia director at Human Rights Watch, a New York-based human rights group.

    Stalled change

    Bangladesh’s anti-government movement exacted a heavy price. Hundreds of people, mostly students, were killed in violent protests. Angry demonstrators torched police stations and government buildings. Political opponents often clashed with each other, sometimes leading to gruesome killings.

    Like many Bangladeshis, Tarif and his sister took part in the uprising, hoping for a broader political change, particularly after when one of their cousins was shot and killed by security forces.

    “We could not stay home and wanted Sheikh Hasina to go,” 20-year-old Tarif said. “Ultimately we wanted a country without any discrimination and injustice.”

    Today, his hopes lie shattered. “We wanted a change, but I am frustrated now,” he said.

    After taking the reins, the Yunus-led administration formed 11 reform commissions, including a national consensus commission that is working with major political parties for future governments and the electoral process.

    Bickering political parties have failed to reach a consensus on a timetable and process for elections. Mob violence, political attacks on rival parties and groups, and hostility to women’s rights and vulnerable minority groups by religious hard-liners have all surged.

    Some of the fear and repression that marked Hasina’s rule, and abuses such as widespread enforced disappearances, appear to have ended, rights groups say. However, they accuse the new government of using arbitrary detention to target perceived political opponents, especially Hasina’s supporters, many of whom have been forced to go into hiding.

    Hasina’s Awami League party, which remains banned, says more than two dozen of its supporters have died in custody over the last one year.

    Human Rights Watch in a statement on July 30 said the interim government “is falling short in implementing its challenging human rights agenda.” It said violations against ethnic and other minority groups in some parts of Bangladesh have continued.

    “The interim government appears stuck, juggling an unreformed security sector, sometimes violent religious hard-liners, and political groups that seem more focused on extracting vengeance on Hasina’s supporters than protecting Bangladeshis’ rights,” said Ganguly.

    Yunus’ office routinely rejects these allegations.

    Growing political uncertainty

    Bangladesh also faces political uncertainty over a return to democratically held elections.

    Yunus has been at loggerheads with the Bangladesh Nationalist Party, or BNP, now the main contender for power. The party headed by former Prime Minister Khaleda Zia has demanded elections either in December or February next year. Yunus has said they could be held in April.

    The interim government has also cleared the way for the Islamists, who were under severe pressure during Hasina’s regime, to rise, while the student leaders who spearheaded the uprising have formed a new political party. The students’ party demands that the constitution be rewritten, if needed entirely, and says it won’t allow the election without major reforms.

    Meanwhile, many hard-line Islamists have either fled prison or have been released, and the Jamaat-e-Islami, the country’s largest Islamist party, which has a controversial past, is now aspiring to a role in government. It often bitterly criticizes the BNP, equating it with Hasina’s Awami League, and recently held a massive rally in Dhaka as a show of power. Critics fear that greater influence of the Islamist forces could fragment Bangladesh’s political landscape further.

    “Any rise of Islamists demonstrates a future Bangladesh where radicalization could get a shape where so-called disciplined Islamist forces could work as a catalyst against liberal and moderate forces,” political analyst Nazmul Ahsan Kalimullah said.

    Worries also remain over whether the government is ultimately capable of enacting reforms.

    “People’s expectation was (that) Yunus government will be focused and solely geared toward reforming the electoral process. But now it’s a missed opportunity for them,” Kalimullah said.

    A frustrated population

    For some, not much has changed in the last year.

    Meherunnesa’s father, Mosharraf Hossain, said the uprising was not for a mere change in government, but symbolized deeper frustrations. “We want a new Bangladesh … It’s been 54 years since independence, yet freedom was not achieved,” he said.

    Tarif echoed his father’s remarks, adding that he was not happy with the current state of the country.

    “I want to see the new Bangladesh as a place where I feel secure, where the law enforcement agencies will perform their duties properly, and no government will resort to enforced disappearances or killings like before. I want to have the right to speak freely,” he said.

    Continue Reading

  • China trio diagnosed with bacterial infection after eating ‘nutritious’ cooked sheep placenta

    China trio diagnosed with bacterial infection after eating ‘nutritious’ cooked sheep placenta

    Three people in China had to be hospitalised after they ate sheep placenta for “nutritious” purposes, sparking an online discussion about the custom.

    A woman, surnamed Zhang, in southern China’s Guangdong province was reported to have developed frequent fevers and lost 5kg in weight over a short period after she cooked the “dish”.

    She went to hospital and was diagnosed with brucellosis, a type of bacterial infection spread from animals to humans.

    One of the victims suffered serious weight loss and fevers after eating the sheep placenta “dish”. Photo: Shutterstock

    Zhang’s sister and brother-in-law were diagnosed with the same disease after eating the “tonic”.

    The placenta is an organ that forms in the uterus during pregnancy and is considered a highly nutritious ingredient in China.

    In Traditional Chinese Medicine, the placenta is known as ziheche.

    It is believed to strengthen the immune system, treat fatigue, infertility and a lack of energy.

    Traditional beliefs hold that cooked sheep placenta is a “tonic” able to treat a number of ailments. Photo: Shutterstock
    Traditional beliefs hold that cooked sheep placenta is a “tonic” able to treat a number of ailments. Photo: Shutterstock

    Continue Reading

  • New research unveils vast influence of B vitamins on health and disease

    New research unveils vast influence of B vitamins on health and disease

    Eight essential nutrients make up the suite of B vitamins also known as the B complex. Researchers from Tufts University and elsewhere have revealed that these B vitamins influence a vast spectrum of human health and disease, including cognitive function, cardiovascular health, gastric bypass recovery, neural tube defects, and even cancer.

    “It’s hard to study the B vitamins in isolation,” says gastroenterologist Joel Mason, senior scientist at the Jean Mayer USDA Human Nutrition Research Center on Aging (HNRCA) and professor at the Gerald J. and Dorothy R. Friedman School of Nutrition Science and Policy and Tufts University School of Medicine. “Four of these B-vitamins cooperate as co-factors in many critical activities in cells in what we call ‘one carbon metabolism’.”

    One carbon metabolism is a series of pathways that allow for the transfer of single-carbon units to cells for essential processes such as DNA synthesis, amino acid metabolism, and more. It’s their role in all these crucial biological functions that make the B vitamins so important-and so challenging to tease out how they contribute positively and, perhaps negatively, to human health.

    Mason and two additional researchers who spent their careers studying one or more of the B vitamins explain what we currently know about how the five of the most prominently researched B vitamins impact or improve cognitive as well as cardiovascular health.

    Cognitive Health, B12, and Folate

    One of the most active areas for B vitamin research is cognitive health. By the age of 75-80, 40% of people have a diminished ability to absorb food-bound B12, says Mason. This deficiency leads to a decline in nerve health, particularly in the spine and brain, which can contribute to the risk of developing dementia in older adults. 

    For decades, clinicians and researchers thought measuring plasma B12 was accurate enough to determine if supplementation was needed. However, Mason says, while many elderly people may have B12 levels that are in the ‘low to normal’ range, they are simultaneously developing neurological deficits linked to vitamin B12 deficiency. 

    The contribution of vitamin B12 deficiency to cognitive decline and the vascular disease that results in many cases of dementia is under-diagnosed and under-reported.”


    Irwin H. Rosenberg, Jean Mayer University Professor Emeritus, Tufts University

    Rosenberg is also a former dean of the Friedman School of Nutrition Science and Policy who also taught pharmacology at the School of Medicine. 

    “Age-related cognitive decline is not just Alzheimer’s,” says Rosenberg. “We’ve lumped together many kinds of brain dysfunction under one name. And in doing so, we’ve overlooked how critical blood vessels-and by extension, nutrition-are to preserving brain function.”

    The pathology of Alzheimer’s disease described the abnormal buildup of two proteins in the brain-amyloid and tau-which clump together, forming plaques and tangles which are believed to disrupt brain cell function. 

    Yet Rosenberg says cerebrovascular disease and small vessel disease, which in some cases are connected to B vitamin deficiency, is more prevalent with cognitive decline and dementia than the buildup of harmful proteins in the brain, which has been the focus of so much research and drug development to treat Alzheimer’s disease. Treating people with drugs meant to address the protein buildup will not work if the cause of dementia symptoms is a B12 deficiency.

    Testing to identify whether cognitive decline and dementia symptoms may be caused by a B12 deficiency is therefore imperative, he says.

    “B12 tests measure all B12 in your system, even though approximately 80% is inactive,” says Paul Jacques, senior scientist at the HNRCA and professor at the Friedman School of Nutrition Science and Policy.

    To pinpoint a B12 deficiency requires two additional tests. One, called the MMA test, measures levels of methymalonic acid, an acid produced during certain aspects of metabolism requiring adequate B12. “It can be elevated with even a mild B12 deficiency, indicating a potential higher risk of dementia,” says Jacques.

    A second test measures levels of an amino acid, homocysteine, which is also a byproduct of metabolism requiring B12. If only homocysteine levels are elevated, a folate deficiency may be the problem. If both MMA and homocysteine are high, a B12 deficiency is the likely culprit.

    If a patient presents with neurological issues or signs of dementia, conducting all three tests will narrow down if a B vitamin deficiency is involved-and which B vitamin it is.

    “Unlike changes that we are unable to see in patients being given expensive anti-amyloid antibody drugs to treat Alzheimer’s disease, there is actually evidence that fairly early in the course of cognitive decline we can slow the process if the underlying cause is elevated homocysteine or B12-related deficiency,” says Rosenberg. “It’s my recommendation that patients, with or without anemia, should be screened for elevated homocysteine or B12 deficiency because that may be one of the reversible factors in their cognitive decline.”

    This isn’t a new theory. Two decades ago, studies like the Framingham Heart Study showed that elevated homocysteine predicted brain atrophy and a higher risk of dementia. More recently, trials such as VITACOG and FACT have shown that B vitamin supplementation can slow brain shrinkage and improve cognitive performance in those at risk.

    “There is an enormous amount of education needed around this issue,” Rosenberg says. “We hope to convince cardiologists, neurologists, and internists to measure B12 and homocysteine levels as part of the evaluation of cognitive impairment. Even the modest effects from vitamins that cost pennies a day can be very meaningful in those who will benefit, especially when you compare vitamin supplementation to costly drugs that are getting much more attention yet may have the same or even less benefit.”

    B12 and Dementia

    Jacques and colleagues currently are leading a study using data from about 2,500 middle-aged and older adults in the Framingham Heart Study, all of whom were free of dementia in the 1990s and all of whom received B12, MMA, and homocysteine testing for the last 20+ years.

    “The risk of dementia and late-stage Alzheimer’s begins to increase when one is 75 years old or older, but evidence suggests that some of the pathological changes associated with dementia and Alzheimer’s may start to develop 20+ years before clinical symptoms and diagnosis occurs,” says Jacques. “This study should give us a good handle on whether B12 is related to cognitive decline and dementia. If so, hopefully we can identify a simple, inexpensive intervention that could be started years in advance and before real damage occurs.”

    Jacques is also looking at the role folate (B9) may play in the development of cognitive issues, specifically the influence high levels of folate might have on B12 and cognitive health.

    In the 1950s, people with anemia were treated with folic acid, the synthetic form of folate. Unfortunately, it became clear that while pharmaceutical level treatment with folic acid alleviated anemia, it often masked or exacerbated B12 deficiency. “Scientists observed that people with low B12 and high folic acid concentrations tended to have cognitive issues,” Jacques says.

    More recent research suggested that it wasn’t total B12 concentrations that folic acid might be affecting, but perhaps just one component, holoTC, which is the form of vitamin B12 that is crucial for transporting and using B12 in cells and is considered a potentially better indicator of vitamin B12 status. 

    Jacques and colleagues are conducting two studies to tease apart the issues involved. “In the first, our B vitamin and brain aging study, we will look at the influence high folate status has on the relationships between B12 and cognitive health. A second study we are doing in collaboration with Rutgers will look at the effect of high folic acid in the blood on the two forms of B12 -holoTC and unbound cobalamin.”

    Heart disease, cholesterol, and stroke

    B vitamins have also stirred excitement among researchers because of their possible role in heart disease and stroke prevention, but thus far their utility as a clinical treatment remains limited.

    Scientists discovered in the early 2000s that riboflavin (B2) could decrease blood pressure very effectively. It is believed that riboflavin improves a biochemical reaction mediated by a gene called MTHFR (methylenetetrahydrofolate reductase) that helps the body use folate. Riboflavin is only effective in reducing blood pressure specifically in patients with the MTHFR 677 TT genotype, however.

    Vitamins B6, B12, and folate help the body rid itself of homocysteine, which in overabundance had been linked to an increased risk of heart attacks and strokes, as well as dementia. However, a number of clinical trials in the 1980s showed that B6, B12, and folate supplementation didn’t decrease heart attacks, but did slightly lower the risk of strokes.

    Niacin (B3) can lower LDL (the so-called “bad cholesterol”) and raise HDL (the so-called “good cholesterol”). “But it has to be taken in such large doses that it often causes very uncomfortable flushing, like hot flashes,” says Mason. “People often can’t tolerate taking it, and other drug options are available that lower blood LDL that do not have such unpleasant side effects.”

    Chronic inflammation and B6

    Perhaps most promising for the future is the role vitamin B6 may play in curbing inflammation, which has been identified as an underlying feature of many chronic diseases, from heart disease to diabetes to arthritis to dementia.

    A number of animal studies, plus some human studies, suggest that supplemental B6 can reduce inflammation. “Again, we are talking about giving B vitamins at an appropriate pharmaceutical level under the care of a clinician,” cautions Mason. “B6 can be toxic in large amounts.” He sees this research as an area to watch in the years ahead.

    Continue Reading

  • Johns Hopkins uncovers protein’s unexpected role in brain signaling

    Johns Hopkins uncovers protein’s unexpected role in brain signaling

    Researchers at Johns Hopkins Medicine say they unexpectedly found new information about a protein’s special role in getting brain cells to communicate at the right time and place in experiments with genetically engineered mice.

    The finding about the protein intersectin, they say, advances scientific understanding of a key process in how the mammalian brain forms memories and learns, and may help advance treatments for cognitive disorders including Down syndrome, Alzheimer’s disease and Huntington’s disease.

    A report of the new findings, funded in part by the National Institutes of Health, was published July 8 in the journal Nature Neuroscience

    Specifically, the researchers found that intersectin keeps tiny, message-carrying bubbles inside brain cells in a particular location until they are ready to be released to activate a neighboring brain cell. The protein does so by creating a physical boundary between these bubbles, similar to how oil separates from water.

    Message transfer from brain cell to brain cell is key to information processing, learning and forming memories. The bubbles, synaptic vesicles, are housed within the synapse – the connection point where brain cells communicate.

    In typical synapses within the brains of mammals, 300 synaptic vesicles are clustered together in the intersection between any two brain cells, but only a few of these vesicles are used for such message transfer, researchers say. Pinpointing how a synapse knows which vesicles to use has long been a target of research by those who study the biology and chemistry of thought.

    We found that these tiny bubbles have a distinct domain where they want to be. Keeping them at particular locations within a synapse enables the brain to decide how and when to use them while thinking and processing information.”


    Shigeki Watanabe, PhD, Study Lead and Associate Professor, Cell Biology, Johns Hopkins Medicine

    In an effort to better understand the operation of these synaptic vesicles, Watanabe and his team designed a study that first focused on endocytosis, a process in which brain cells recycle synaptic vesicles after they are used for neuronal communication.

    Already aware of intersectin’s general role in endocytosis and neuronal communication, the scientists genetically engineered mice to lack the gene that codes for intersectin. However, and somewhat to their surprise, Watanabe says removing the protein did not appear to halt endocytosis in brain cells.

    The research team refocused their experiments, taking a closer look at the synaptic vesicles themselves.

    Using a high-resolution fluorescence microscope to observe where intersectin is in a synapse, the researchers found it in between vesicles that are used for neuronal communication and those that are not, as if they are physically separating the two.

    To further understand the role of intersectin at this location, they used an electron microscope to visualize synaptic vesicles in action across one billionth of a meter. In all the nerve cells from mice lacking this protein, the scientists say synaptic vesicles close to the membrane were absent from the release zone of the synapse, the place where the bubbles would discharge to nearby neurons.

    “This suggested that intersectin regulates release, rather than recycling, of these vesicles at this location of the synapse,” says Watanabe.

    Using a technique called zap and freeze microscopy, the scientists stimulated neurons in the brains of mice to capture the movement of synaptic vesicles on a millisecond timescale and at a nanometer resolution.

    In normal mice, the scientists saw vesicles fusing with the brain cell membrane within a millisecond after stimulation. Then, new synaptic vesicles came and filled the vacated release sites of the synapse within about 15 milliseconds.

    In two genetically engineered lines of mice, one lacking intersectin and another lacking the endophilin protein, which binds to intersectin, new vesicles could not be recruited to the vacated release sites. Similarly, vesicles within nerve cells of mice with mutations that blocked the interaction of these two proteins also slowed the local replenishment of synaptic vesicles that carry information from neuron to neuron.

    “When information is processed in the brain, this replenishment process needs to happen in just a few milliseconds,” says Watanabe. “When you don’t have vesicles staged and ready to go at the release sites or the active zones, then neurotransmission cannot continue.”

    In future research, the scientists say they aim to better understand how intersectin shuttles new synaptic vesicles to release sites.

    Source:

    Journal references:

    Ogunmowo, T. H., et al. (2024). Intersectin and endophilin condensates prime synaptic vesicles for release site replenishment. Nature Neuroscience. doi.org/10.1038/s41593-025-02002-4

     

    Continue Reading

  • Alexander JW, Supp DM. Role of arginine and Omega-3 fatty acids in wound healing and infection. Adv Wound Care (New Rochelle). 2014;3(11):682–90.

    Google Scholar 

  • Yu W, Shi K, Cao W, Lv J, Guo Y, Pei P, Xia Q, Du H, Chen Y, Yang L, et al. Association between fish consumption and risk of chronic obstructive pulmonary disease among Chinese men and women: an 11-Year Population-Based cohort study. J Nutr. 2022;152(12):2771–7.

    Google Scholar 

  • Bonaccio M, Ruggiero E, Di Castelnuovo A, Costanzo S, Persichillo M, De Curtis A, Cerletti C, Donati MB, de Gaetano G, Iacoviello L. Fish intake is associated with lower cardiovascular risk in a mediterranean population: prospective results from the Moli-sani study. Nutr Metabolism Cardiovasc Diseases: NMCD. 2017;27(10):865–73.

    Google Scholar 

  • Chen J, Jayachandran M, Bai W, Xu B. A critical review on the health benefits of fish consumption and its bioactive constituents. Food Chem. 2022;369:130874.

    Google Scholar 

  • Das UN. Essential fatty acids: biochemistry, physiology and pathology. Biotechnol J. 2006;1(4):420–39.

    Google Scholar 

  • Scaglia N, Chatkin J, Chapman KR, Ferreira I, Wagner M, Selby P, Allard J, Zamel N. The relationship between omega-3 and smoking habit: a cross-sectional study. Lipids Health Dis. 2016;15:61.

    Google Scholar 

  • Zevin S, Jacob P 3rd, Benowitz N. Cotinine effects on nicotine metabolism. Clin Pharmacol Ther. 1997;61(6):649–54.

    Google Scholar 

  • Bramer SL, Kallungal BA. Clinical considerations in study designs that use cotinine as a biomarker. Biomarkers. 2003;8(3–4):187–203.

    Google Scholar 

  • Agaku IT, King BA. Validation of self-reported smokeless tobacco use by measurement of serum cotinine concentration among US adults. Am J Epidemiol. 2014;180(7):749–54.

    Google Scholar 

  • Alshaarawy O, Xiao J, Shankar A. Association of serum cotinine levels and hypertension in never smokers. Hypertension. 2013;61(2):304–8.

    Google Scholar 

  • Soleimani F, Dobaradaran S, De-la-Torre GE, Schmidt TC, Saeedi R. Content of toxic components of cigarette, cigarette smoke vs cigarette butts: A comprehensive systematic review. Sci Total Environ. 2022;813:152667.

    Google Scholar 

  • Phaniendra A, Jestadi DB, Periyasamy L. Free radicals: properties, sources, targets, and their implication in various diseases. Indian J Clin Biochem. 2015;30(1):11–26.

    Google Scholar 

  • Spitale RC, Cheng MY, Chun KA, Gorell ES, Munoz CA, Kern DG, Wood SM, Knaggs HE, Wulff J, Beebe KD, et al. Differential effects of dietary supplements on metabolomic profile of smokers versus non-smokers. Genome Med. 2012;4(2):14.

    Google Scholar 

  • Cade JE, Margetts BM. Relationship between diet and smoking–is the diet of smokers different? J Epidemiol Community Health. 1991;45(4):270–2.

    Google Scholar 

  • Block RC, Harris WS, Pottala JV. Determinants of blood cell Omega-3 fatty acid content. Open Biomark J. 2008;1:1–6.

    Google Scholar 

  • Murff HJ, Tindle HA, Shrubsole MJ, Cai Q, Smalley W, Milne GL, Swift LL, Ness RM, Zheng W. Smoking and red blood cell phospholipid membrane fatty acids. Prostaglandins Leukot Essent Fat Acids. 2016;112:24–31.

    Google Scholar 

  • Pawlosky RJ, Hibbeln JR, Salem N Jr. Compartmental analyses of plasma n-3 essential fatty acids among male and female smokers and nonsmokers. J Lipid Res. 2007;48(4):935–43.

    Google Scholar 

  • Hukkanen J, Jacob P 3rd, Benowitz NL. Metabolism and disposition kinetics of nicotine. Pharmacol Rev. 2005;57(1):79–115.

    Google Scholar 

  • Zhu X, Cheang I, Tang Y, Shi M, Zhu Q, Gao R, Liao S, Yao W, Zhou Y, Zhang H, et al. Associations of serum carotenoids with risk of All-Cause and cardiovascular mortality in hypertensive adults. J Am Heart Association. 2023;12(4):e027568.

    Google Scholar 

  • Virani SS, Morris PB, Agarwala A, Ballantyne CM, Birtcher KK, Kris-Etherton PM, Ladden-Stirling AB, Miller M, Orringer CE, Stone NJ. 2021 ACC expert consensus decision pathway on the management of ASCVD risk reduction in patients with persistent hypertriglyceridemia: A report of the American college of cardiology solution set oversight committee. J Am Coll Cardiol. 2021;78(9):960–93.

    Google Scholar 

  • Phillips JA. Dietary guidelines for americans, 2020–2025. Workplace Health Saf. 2021;69(8):395.

    Google Scholar 

  • Amiry GY, Haidary M, Azhdari-Zarmehri H, Beheshti F, Ahmadi-Soleimani SM. Omega-3 fatty acids prevent nicotine withdrawal-induced exacerbation of anxiety and depression by affecting oxidative stress balance, inflammatory response, BDNF and serotonin metabolism in rats. Eur J Pharmacol. 2023;947:175634.

    Google Scholar 

  • Bilski P, Li MY, Ehrenshaft M, Daub ME, Chignell CF. Vitamin B6 (pyridoxine) and its derivatives are efficient singlet oxygen quenchers and potential fungal antioxidants. Photochem Photobiol. 2000;71(2):129–34.

    Google Scholar 

  • Sadeghi-Ardekani K, Haghighi M, Zarrin R. Effects of omega-3 fatty acid supplementation on cigarette craving and oxidative stress index in heavy-smoker males: A double-blind, randomized, placebo-controlled clinical trial. J Psychopharmacol (Oxford England). 2018;32(9):995–1002.

    Google Scholar 

  • Rabinovitz S. Effects of omega-3 fatty acids on tobacco craving in cigarette smokers: A double-blind, randomized, placebo-controlled pilot study. J Psychopharmacol. 2014;28(8):804–9.

    Google Scholar 

  • Murff HJ, Greevy RA, Sternlieb S, Gilliam K, King S, Sanghani R, Tindle HA. The fish oil to reduce tobacco use iN expectant mothers (FORTUNE) feasibility trial. Am J Obstet Gynecol MFM. 2022;4(6):100707.

    Google Scholar 

  • Tur JA, Bibiloni MM, Sureda A, Pons A. Dietary sources of Omega 3 fatty acids: public health risks and benefits. Br J Nutr. 2012;107(Suppl 2):S23–52.

    Google Scholar 

  • Scoditti E, Massaro M, Garbarino S, Toraldo DM. Role of diet in chronic obstructive pulmonary disease prevention and treatment. Nutrients 2019, 11(6).

  • Skeie E, Strand E, Pedersen ER, Bjørndal B, Bohov P, Berge RK, Svingen GF, Seifert R, Ueland PM, Midttun Ø, et al. Circulating B-vitamins and smoking habits are associated with serum polyunsaturated fatty acids in patients with suspected coronary heart disease: a cross-sectional study. PLoS ONE. 2015;10(6):e0129049.

    Google Scholar 

  • Ulvik A, Ebbing M, Hustad S, Midttun Ø, Nygård O, Vollset SE, Bønaa KH, Nordrehaug JE, Nilsen DW, Schirmer H, et al. Long- and short-term effects of tobacco smoking on Circulating concentrations of B vitamins. Clin Chem. 2010;56(5):755–63.

    Google Scholar 

  • Yanbaeva DG, Dentener MA, Creutzberg EC, Wesseling G, Wouters EF. Systemic effects of smoking. Chest. 2007;131(5):1557–66.

    Google Scholar 

  • Superko HR, Superko AR, Lundberg GP, Margolis B, Garrett BC, Nasir K, Agatston AS. Omega-3 fatty acid blood levels clinical significance update. Curr Cardiovasc Risk Rep. 2014;8(11):407.

    Google Scholar 

  • Tavilani H, Nadi E, Karimi J, Goodarzi MT. Oxidative stress in COPD patients, smokers, and non-smokers. Respir Care. 2012;57(12):2090–4.

    Google Scholar 

  • Louhelainen N, Rytilä P, Haahtela T, Kinnula VL, Djukanović R. Persistence of oxidant and protease burden in the airways after smoking cessation. BMC Pulm Med. 2009;9:25.

    Google Scholar 

  • Zhang B, Xiong K, Cai J, Ma A. Fish consumption and coronary heart disease: A Meta-Analysis. Nutrients 2020, 12(8).

  • van Bussel BC, Henry RM, Schalkwijk CG, Ferreira I, Feskens EJ, Streppel MT, Smulders YM, Twisk JW, Stehouwer CD. Fish consumption in healthy adults is associated with decreased Circulating biomarkers of endothelial dysfunction and inflammation during a 6-year follow-up. J Nutr. 2011;141(9):1719–25.

    Google Scholar 

  • Lim WY, Chuah KL, Eng P, Leong SS, Lim E, Lim TK, Ng A, Poh WT, Tee A, Teh M, et al. Meat consumption and risk of lung cancer among never-smoking women. Nutr Cancer. 2011;63(6):850–9.

    Google Scholar 

  • Chi CF, Hu FY, Wang B, Li ZR, Luo HY. Influence of amino acid compositions and peptide profiles on antioxidant capacities of two protein hydrolysates from skipjack tuna (Katsuwonus pelamis) dark muscle. Mar Drugs. 2015;13(5):2580–601.

    Google Scholar 

  • Gu M, Ren J, Sun W, You L, Yang B, Zhao M. Isolation and identification of antioxidative peptides from frog (Hylarana guentheri) protein hydrolysate by consecutive chromatography and electrospray ionization mass spectrometry. Appl Biochem Biotechnol. 2014;173(5):1169–82.

    Google Scholar 

  • Erdogan H, Fadillioglu E, Ozgocmen S, Sogut S, Ozyurt B, Akyol O, Ardicoglu O. Effect of fish oil supplementation on plasma oxidant/antioxidant status in rats. Prostaglandins Leukot Essent Fat Acids. 2004;71(3):149–52.

    Google Scholar 

  • Bhattacharya A, Sun D, Rahman M, Fernandes G. Different ratios of eicosapentaenoic and docosahexaenoic omega-3 fatty acids in commercial fish oils differentially alter pro-inflammatory cytokines in peritoneal macrophages from C57BL/6 female mice. J Nutr Biochem. 2007;18(1):23–30.

    Google Scholar 

  • Caleja C, Barros L, Antonio AL, Oliveira MB, Ferreira IC. A comparative study between natural and synthetic antioxidants: evaluation of their performance after incorporation into biscuits. Food Chem. 2017;216:342–6.

    Google Scholar 

  • Wennberg M, Tornevi A, Johansson I, Hörnell A, Norberg M, Bergdahl IA. Diet and lifestyle factors associated with fish consumption in men and women: a study of whether gender differences can result in gender-specific confounding. Nutr J. 2012;11:101.

    Google Scholar 

Continue Reading

  • Breath and Bottle: The Impact of Pharmacotherapy for Alcohol Use Disor

    Breath and Bottle: The Impact of Pharmacotherapy for Alcohol Use Disor

    Introduction

    Chronic obstructive pulmonary disease (COPD) is a prevalent chronic respiratory disease, affecting 213.4 million individuals worldwide, with China alone reporting a prevalence of 8.6% in adults.1 Environmental exposures and comorbid conditions, have been implicated in the pathogenesis of COPD exacerbations.2,3 Alcohol consumption are strongly associated with an elevated risk of adverse clinical outcomes, particularly in patients requiring hospitalization or emergency interventions. Alcohol use disorder (AUD) is characterized by persistent patterns of excessive alcohol consumption despite adverse health or social consequences, leading to impaired control over intake and heightened vulnerability to comorbid conditions such as COPD.4 In subpopulations of COPD patients with comorbid AUD, the risk of hospital readmission is significantly heightened, with a 1-year post-discharge mortality rate of 22%.5

    As with other alcohol-related health conditions, complete abstinence from alcohol remains the cornerstone of optimal management, though achieving this goal is often challenging.6 In contrast, Pharmacotherapeutic interventions for alcohol dependence, however, have demonstrated efficacy in achieving and sustaining abstinence among patients with AUD.7 Addiction treatment modalities also play a critical role in mitigating the progression of AUD-related comorbidities.8 Nevertheless, the potential role of AUD pharmacotherapy in preventing COPD exacerbations remains poorly understood.

    Given the potential benefits of addiction pharmacotherapy for COPD patients with co-existing AUD, this study aims to evaluate differences in COPD-related clinical manifestations (eg, lung function, time to first exacerbation, and hospitalization rates) between COPD patients with co-existing AUD who receive addiction treatment and those who do not. The study was designed to explore whether AUD medication could effectively slow COPD progression, reduce the risk of exacerbation, and improve patients’ quality of life. Through this study, we hope to provide more concrete basis for clinical treatment and how to comprehensively consider addiction treatment to optimize the management of COPD.

    Methods

    Data Sources

    This retrospective cohort study included patients admitted to the psychiatry, health checkup, emergency, and internal medicine departments of The Affiliated Encephalopathy Hospital of Zhengzhou University from January 1, 2015, to December 1, 2024. The study included individuals diagnosed with COPD who exhibited high-risk alcohol consumption. Data were extracted retrospectively from the hospital’s electronic medical records system. Data collected included patient demographic characteristics, clinical diagnosis of COPD, records of acute exacerbations and length of hospital stay, spirometry data, severity and scores of COPD-related symptoms and dyspnea, activities of daily living, exercise tolerance, and AUD questionnaire results. The study employed an opt-out methodology for patient enrollment, in accordance with institutional ethical guidelines. This study complied with the Declaration of Helsinki and was approved by the Affiliated Encephalopathy Hospital of Zhengzhou University Research Ethics Committee (Approval No. 2024–001-01). Patient data confidentiality was strictly maintained, with anonymized records used for analysis. The Institutional Review Board granted a waiver for informed consent, considering the retrospective nature of our study.

    Patients were included if they had: (1) Patients were included if they met the following criteria: (1) high-risk drinking, defined as an Alcohol Use Disorder Identification Test (AUDIT-C) score of >8, and (2) a diagnosis of AUD among incident COPD patients.9 Patients were excluded for the following reasons: (1) death or no follow-up within one year of COPD diagnosis, (2) use of AUD medications in the year prior to COPD diagnosis, and (3) age under 18 years or over 90 years at the time of COPD diagnosis. (4) patients suffering from bronchial asthma, bronchiectasis, cystic fibrosis, or cancer.10 (5) during the study period or reversal of COPD diagnosis within 3 months.11 Patients meeting the criteria were categorized into two groups based on whether they received medication for alcohol use disorder (MAUD): (1) the MAUD group and (2) the no-MAUD group.

    Exposure

    Patients who received medication for AUD disulfiram, acamprosate, naltrexone, gabapentin, topiramate, varenicline or baclofen for at least 7 days within 30 days of the diagnosis of COPD were considered to be in the exposed group (MAUD group).12

    Covariates

    Clinically important confounders were selected, including age (>70 years), body mass index (<18.5, >25 kg/m2), history of previous hospital admission for COPD, exercise tolerance and dyspnea, mental status on admission, History of using nicotine as well as other nonalcoholic substances, and receipt of non-pharmacological psychotherapy.13

    Outcomes

    The primary end point was the time to the first COPD acute exacerbation. Acute exacerbations of COPD were categorized as either moderate or severe. Specifically, according to the Rome proposal’s standardized thresholds, exacerbations were classified as moderate if they required treatment with short-acting bronchodilators in combination with antibiotics and/or oral corticosteroids. In contrast, exacerbations were deemed severe if they necessitated a visit to the emergency department or hospitalization due to a significant worsening of the patient’s condition.14 If more than 2 acute exacerbations of any severity were identified within 14 days, the events were counted as the same event, and the date of the acute exacerbation was recorded as the date of the first acute exacerbation. Secondary end points included the annual rate of moderate to severe exacerbations, lung function, length of hospital stay, quality-of-life scores, and survival.

    Statistical Analysis

    For continuous variables, comparisons between the two groups were conducted using either the independent samples t-test (for normally distributed data) or the Mann–Whitney U-test (for non-normally distributed data). Categorical variables were assessed using the Chi-square test or Fisher’s exact test, as appropriate. Kaplan-Meier curves were utilized to depict time-to-event data, with differences analyzed using the Log rank test. Cox proportional hazards regression was employed to estimate hazard ratios (HRs) and their corresponding 95% confidence intervals (CIs) for the time to first exacerbation between the two groups. A P-value threshold of <0.05 was set to determine statistical significance. All statistical analyses were performed using SAS® version 9.4. The proportional hazards assumption was evaluated using Schoenfeld residuals to ensure no time-dependent covariate effects. The multicollinearity among covariates was assessed by calculating variance inflation factors. The model fit was examined via the Akaike Information Criterion and log-likelihood ratio tests to compare nested models.

    To address potential confounding, propensity scores were calculated. These scores represented the probability of a patient being prescribed a specific medication for AUD, estimated using a logistic regression model that adjusted for known confounders. The propensity scores were derived using baseline covariates through multivariable logistic regression analysis.

    Results

    Patient Characteristics

    Following application of the selection criteria (Figure 1), 635 patients (7.1%) from a total of 8,939 COPD patients were included in the final analysis cohort. The patients were mainly male (n=569, 89.6%), with a mean age of 57.4 years. Of these, 229 patients had received at least 7 days of AUD treatment following their COPD diagnosis. 13.1% patients received treatment for > 3 months. The duration of AUD treatment was <3 months 199 cases (86.9%). The average age of MAUD group was 58.1 years, of which 89.1% (n = 204) were 50–70 years old. The mean age of patients in the no-MAUD group was 57.0 years, with 87.5% (n = 355) of patients aged between 50 and 70 years. (Table 1). Among patients treated with AUD, 105 (45.9%) used disulfiram, 77 (33.6%) were exposed to naltrexone, 16 (7.0%) received acamprosate, and 31 had used more than two drugs. During follow-up, cessation events included death (5 patients, 0.8%), loss to follow-up (defined as no medical contact for >12 months; 23 patients, 3.6%), and administrative censoring at the study cutoff date (December 1, 2024). All events were right-censored in survival analyses to avoid bias in estimating time-to-first exacerbation.

    Table 1 Characteristics of Subjects Presenting to the COPD Patients with AUD

    Figure 1 Flowchart of patient selection.

    Factors Associated with Receipt of MAUD

    In the multivariate regression model, the confounders most closely associated with the use of AUD medications included age, sex, body mass index (BMI), smoking status, activities of daily living, history of pulmonary function testing, history of hospitalization, mental status, use of psychotropic medications, and comorbidities. To ensure optimal matching between the two groups, we initially computed propensity scores using a probit regression model based on the covariates outlined earlier. Subsequently, we assessed the balance of observed covariates through a love plot, utilizing the standardized mean difference (SMD) as a metric. A threshold of |SMD| < 0.1 was adopted to indicate satisfactory balance (Figure 2). The covariates included in the propensity score model were selected based on their established clinical relevance to both AUD management and COPD outcomes. Adjusting for these factors allows for a more robust estimation of the specific effect of AUD pharmacotherapy on COPD exacerbations, independent of these important clinical characteristics.

    Figure 2 Clinical relevance of covariate balance after matching. Standardized mean differences (SMD) demonstrate successful balancing of key clinical factors between MAUD and non-MAUD groups after propensity scoring (all |SMD| <0.1).

    Incidence of Acute Exacerbations of COPD After Medical Addiction Therapy

    We present the condition of COPD exacerbations in the MAUD and no-MAUD groups (Table 2). A total of 173 patients had an exacerbation of COPD. There were 42 patients in the MAUD group, 12 of whom had severe exacerbations. In the no-MAUD group, 126 patients had exacerbations, and a higher proportion had severe exacerbations (P=0.03), with 41 having to be hospitalized. The annual rate of acute exacerbation (number of episodes/patient/year) in MAUD group was significantly lower than that in no-MAUD group. The difference between MAUD group and no-MAUD group in the occurrence of COPD exacerbation was 12.7% (P<0.001). The unadjusted odds ratio (OR) for the MAUD group compared with the no-MAUD group was 0.49 (95% CI: 0.41–0.57). And after weighting propensity scores, we found that adjusted OR was 0.43 (95% CI: 0.38–0.55). Regarding respiratory support, COPD patients who did not undergo AUD treatment were more frequently documented with respiratory failure and had a higher likelihood of requiring mechanical ventilation upon arrival (P<0.001). In contrast, COPD patients receiving medical treatment for AUD exhibited higher partial pressures of oxygen (P<0.001) and lower partial pressures of arterial carbon dioxide (P<0.001).

    Table 2 Outcomes of COPD Patients with Co-Existing AUD in Two Groups

    In a multivariate analysis, we found that any medical treatment for AUD was associated with reduced odds of COPD exacerbations (Table 3). And receiving naltrexone (OR= 0.41), disulfiram (OR=0.37), or acamprosate (OR=0.55) was independently associated with decreased odds of COPD exacerbations.

    Table 3 Odds Ratios for the COPD Exacerbations After Addiction Treatment

    Association Between AUD Medications and Time to First Exacerbation

    The time interval from 30 days post-diagnosis to the first COPD exacerbation was assessed among patients with AUD. After adjusting for follow-up duration using Cox proportional hazards regression, the time to first exacerbation was found to be significantly longer in the MAUD group compared to patients who did not receive addiction treatment (P<0.001). The median time to the first exacerbation was 38.5 months in the MAUD group and 26.9 months in the no-MAUD group (unadjusted hazard ratio (HR) 0.78, adjusted HR 0.72, Table 4). In the moderate and severe exacerbation subgroups, the time to the first exacerbation was longer in the MAUD group than in the no-MAUD group, similar to the results overall. The adjusted HR was consistent with the unadjusted HR. The proportional hazards assumption was assessed via Schoenfeld residuals (P=0.15). No significant time-dependent effects were detected, confirming the robustness of the Cox model.

    Table 4 Hazard Ratios for COPD Exacerbations

    Discussion

    This retrospective study sought to evaluate the association between AUD pharmacotherapy and the risk of future COPD exacerbations. Our findings indicate a significantly reduced annualized exacerbation rate among COPD patients with comorbid AUD who received addiction pharmacotherapy. In patients with COPD, excessive alcohol consumption may exacerbate the clinical manifestations of the disease. Alcohol not only directly damage the lung immune system and aggravate respiratory tract inflammation, but also aggravate COPD symptoms by affecting patients’ smoking behavior, medication compliance and disease management.15 However, previous randomized controlled trials for COPD excluded patients with AUD, little is known about the role of AUD pharmacotherapy in the prevention of exacerbations in COPD patients. Our study adds to this gap in the therapeutic field. In this cohort study, patients treated with disulfiram had the lowest rates of COPD exacerbations during follow-up. In addition to its effect on reducing alcohol intake, disulfiram also has anti-anxiety effects.16 Given the underuse of addiction treatment in COPD patients, we believe that the results of this study highlight the importance of addiction treatment in COPD patients with AUD.

    The underlying biological mechanism for the protective effect of MAUD on COPD exacerbations observed in this study may be related to the blocking of multiple harmful effects of alcohol on the respiratory system. The detrimental effects of alcohol on COPD progression are mediated through multiple interconnected biological pathways. Chronic alcohol consumption impairs alveolar macrophage function. This immune dysfunction increases susceptibility to respiratory infections.17 This immune suppression is further exacerbated by alcohol-induced depletion of glutathione, leading to elevated reactive oxygen species levels that damage airway epithelium and amplify neutrophilic inflammation.18 A critical synergy exists between alcohol and smoking, while combined exposure upregulates matrix metalloproteinases, accelerating emphysematous alveolar destruction.19 Additionally, alcohol also interferes with COPD therapies, pharmacokinetic interactions may occur, as alcohol competes with CYP450-mediated drug metabolism, altering the clearance of theophylline.20

    The high recurrence rate of AUD necessitates long-term medical intervention.21 In this study, the group of patients with COPD and AUD was likely to be in a highly frail state.22 AUD not only directly aggravate the physiological burden of COPD, but also its accompanying mental health problems and social dysfunction, further damage the patient’s self-management ability and treatment compliance. Frailty may be an important reason for its high readmission rate and poor prognosis. In addressing the healthcare needs of patients with both obstructive lung disease and AUD, AUD treatment emerges as a promising strategy to enhance healthcare utilization efficiency within this vulnerable patient population.23 Therefore, AUD pharmacotherapy has the importance of synergistically addressing physical and psychosocial factors of frailty.

    Our study provides evidence that treatment of addictive drugs can improve the prognosis of patients with COPD and is expected to save the health care system the cost of treating related comorbidities. Compared with resource-intensive cognitive behavioral interventions for AUD and associated comorbidities, pharmacological interventions can be used as a treatment that can be easily implemented and expanded.24 This is particularly important given the shortage of available resources for mental health and addiction intervention treatment.25 Our research will be instrumental in refining clinical guidelines and optimizing therapeutic interventions for this complex patient population.

    However, the current literature presents limitations in detailing the prevalence of acute COPD exacerbations among these patients. The criteria for diagnosing acute exacerbations are often inconsistently applied, leading to ambiguity in the reported incidence rates. This gap underscores the necessity for future prospective studies to elucidate the specific subgroups of patients who stand to gain the most from combined treatment strategies.

    Our observational study has some limitations. First, the retrospective study cohorts were underrepresented. Although we accounted for a variety of confounding factors in the multivariate analyses, there were geographic limitations, and the participants may not be representative of the general population. Longitudinal evaluation is essential to determine the protective effect of AUD pharmacotherapy on lung function.26 Longitudinal data need to be collected frequently over a considerable period of time, but it is difficult to reduce the risk of recall bias in this study. Second, our primary objective was to concentrate on the highest-risk cohorts that could potentially benefit from addiction treatment. The cases we analyzed were primarily characterized by moderate-to-severe AUD. Mild AUD cases might not have been fully identified or documented due to several factors. These factors include patients underreporting their alcohol consumption, apprehensions about the stigma associated with accurate alcohol reporting, and obstacles in systematically recording cases. Third, the impact of AUD on access to care, treatment availability, and treatment adherence is a notable limitation. This limitation may introduce statistical noise and bias into the analysis.

    Conclusion

    This study provides evidence of an association between AUD pharmacotherapy and a reduced incidence of COPD exacerbations. This study suggests that in the absence of contraindications to addiction treatment, clinicians may consider the use of addiction treatment for AUD as a means of preventing COPD exacerbations.

    Author Contributions

    All authors made a significant contribution to the work reported, whether that is in the conception, study design, execution, acquisition of data, analysis and interpretation, or in all these areas; took part in drafting, revising or critically reviewing the article; gave final approval of the version to be published; have agreed on the journal to which the article has been submitted; and agree to be accountable for all aspects of the work.

    Funding

    This work was supported by the Henan Provincial Key Research and Development Program (Grant No. 242102310203).

    Disclosure

    The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

    References

    1. Nayia P, Ian DP, Simon C. The Lancet COPD Commission: broader questions remain. Lancet. 2023;401(10388):1568–1569. doi:10.1016/s0140-6736(23)00556-1

    2. Sanjay R. Chronic obstructive pulmonary disease: 10 years of precision-guided success. Lancet Respir Med. 2023;11(3):227–228. doi:10.1016/s2213-2600(23)00013-9

    3. Stephanie AC, Benjamin MS, Mona B, Nirupama P. Chronic obstructive pulmonary disease. Lancet. 2022;399(10342):2227–2242. doi:10.1016/s0140-6736(22)00470-6

    4. Bailey KL, Samuelson DR, Wyatt TA. Alcohol use disorder: a pre-existing condition for COVID-19? Alcohol. 2021;90:11–17. doi:10.1016/j.alcohol.2020.10.003

    5. MacMurdo M, Lopez R, Udeh BL, Zein JG. Alcohol use disorder and healthcare utilization in patients with chronic asthma and obstructive lung disease. Alcohol. 2021;93:11–16. doi:10.1016/j.alcohol.2021.03.002

    6. Jürgen R, Robin R. Cultural specificity in alcohol use disorders. Lancet. 2022;399(10327):e7–e8. doi:10.1016/s0140-6736(15)00123-3

    7. Raymond FA, William RM, Stephanie SOM, Allen Z, James DH. Pharmacotherapy and behavioral intervention for alcohol dependence. JAMA. 2006;296(14):1727. doi:10.1001/jama.296.14.1728

    8. Rabiee A, Mahmud N, Falker C, Garcia-Tsao G, Taddei T, Kaplan DE. Medications for alcohol use disorder improve survival in patients with hazardous drinking and alcohol-associated cirrhosis. Hepatol Commun. 2023;7(4):e0093. doi:10.1097/hc9.0000000000000093

    9. Schwarzinger M, Thiébaut SP, Baillot S, Mallet V, Rehm J. Alcohol use disorders and associated chronic disease – a national retrospective cohort study from France. BMC Public Health. 2017;18(1):43. doi:10.1186/s12889-017-4587-y

    10. Hsieh MJ, Chen NH, Cheng SL, et al. comparing clinical outcomes of tiotropium/olodaterol, umeclidinium/vilanterol and indacaterol/glycopyrronium fixed-dose combination therapy in patients with chronic obstructive pulmonary disease in Taiwan: a multicenter cohort study. Int J Chronic Obstr. 2022;17:967–976. doi:10.2147/copd.s353799

    11. Kaluza J, Harris HR, Linden A, Wolk A. Alcohol consumption and risk of chronic obstructive pulmonary disease: a prospective cohort study of men. Ame j epidemiol. 2019;188(5):907–916. doi:10.1093/aje/kwz020

    12. Jannat S, Breah J, Danya MQ. Self-reported treatment need and barriers to care for adults with opioid use disorder: the US national survey on drug use and health, 2015 to 2019. Am J Public Health. 2022;112(2):284–295. doi:10.2105/ajph.2021.306577

    13. Vögele C, von Leupoldt A. Mental disorders in chronic obstructive pulmonary disease (COPD). Respir Med. 2008;102(5):764–773. doi:10.1016/j.rmed.2007.12.006

    14. Bartolomé R, Leonardo F, Shawn DA, et al. An updated definition and severity classification of chronic obstructive pulmonary disease exacerbations: the Rome proposal. Am J Respir Crit Care Med. 2021;204(11):1251–1258. doi:10.1164/rccm.202108-1819

    15. Sterling SA, Palzes VA, Lu Y, et al. Associations between medical conditions and alcohol consumption levels in an adult primary care population. JAMA Network Open. 2020;3(5):e204687–e204687. doi:10.1001/jamanetworkopen.2020.4687

    16. Lanz J, Biniaz-Harris N, Kuvaldina M, Jain S, Lewis K, Fallon BA. Disulfiram: mechanisms, applications, and challenges. Antibiotics. 2023;12(3):524. doi:10.3390/antibiotics12030524

    17. He S, Tian R, Zhang X, et al. PPARγ inhibits small airway remodeling through mediating the polarization homeostasis of alveolar macrophages in COPD. Clin Immunol. 2023;250:109293. doi:10.1016/j.clim.2023.109293

    18. Mizumura K, Gon Y. Iron-regulated reactive oxygen species production and programmed cell death in chronic obstructive pulmonary disease. Antioxidants. 2021;10(10):1569. doi:10.3390/antiox10101569

    19. Christopoulou ME, Papakonstantinou E, Stolz D. Matrix metalloproteinases in chronic obstructive pulmonary disease. Int J Mol Sci. 2023;24(4):3786. doi:10.3390/ijms24043786

    20. Badwaik JB, Akolawala UT, Uplanchiwar VP. Alcohols and pharmaceuticals–a drug interaction study. Int J Newgen Res Pharm Healthcare. 2024;2(2):211–219. doi:10.61554/ijnrph.v2i2.2024.105

    21. MacKillop J, Agabio R, Feldstein ESW, et al. Hazardous drinking and alcohol use disorders. Nat Rev Dis Primers. 2022;8(80):1. doi:10.1038/s41572-022-00406-1

    22. Ora L, Mannix J, Morgan L, Gregory L, Luck L, Wilkes L. Chronic obstructive pulmonary disease and advance care planning: a synthesis of qualitative literature on patients’ experiences. Chronic Illness. 2022;18(2):221–233. doi:10.1177/1742395321990109

    23. Mellinger JL, Medley S, Kidwell KM, et al. Improving alcohol treatment engagement using integrated behavioral interventions in alcohol-associated liver disease: a randomized pilot trial. Hepatol Commun. 2023;7(10):e0181. doi:10.1097/hc9.0000000000000181

    24. Kiluk BD, Benitez B, DeVito EE, et al. A digital cognitive behavioral therapy program for adults with alcohol use disorder: a randomized clinical trial. JAMA Network Open. 2024;7(9):e2435205–e2435205. doi:10.1001/jamanetworkopen.2024.35205

    25. Bohman H, Låftman SB, Alaie I, Ssegonja R, Jonsson U. Adult mental health outcomes of adolescent depression and co-occurring alcohol use disorder: a longitudinal cohort study. Eur Child Adolesc Psychiatry. 2025;34(1):1649–1659. doi:10.1007/s00787-024-02596-3

    26. Matsunaga K, Harada M, Suizu J, Oishi K, Asami-Noyama M, Hirano T. Comorbid conditions in chronic obstructive pulmonary disease: potential therapeutic targets for unmet needs. J Clin Med. 2020;9(10):3078. doi:10.3390/jcm9103078

    Continue Reading

  • New research highlights exercise’s broad impact in Parkinson’s disease

    New research highlights exercise’s broad impact in Parkinson’s disease

    It was the early 2000s when researchers first showed that exercise can help relieve the tremors that are common with Parkinson’s Disease.

    So far, researchers haven’t been able to explain how exercise helps. But they may be getting closer to an answer.

    A novel study conducted at University Hospitals and the VA Northeast Ohio Healthcare System, through its Cleveland Functional Electrical Stimulation (FES) Center, provides clues, as it shows that long-term dynamic exercise programs might have wider restorative effects on the brain signals of Parkinson’s Disease (PD) patients than researchers previously thought.

    Researchers used recordings from participants’ deep brain stimulation devices to try to assess how long-term exercise programs might be re-activating connections damaged by Parkinson’s Disease.

    Unlike previous studies, this investigation sought to decode the brain changes linked to motor symptom relief; both with the help of second-generation DBS devices and a long-term dynamic cycling exercise regimen in Parkinson’s patients.

    Details on the study are published in the June 2025 issue of Clinical Neurophysiology. The pilot investigation, funded by a VA Merit Award from the Department of Veterans Affairs along with philanthropic funds to the Department of Neurology at University Hospitals (Penni and Stephen Weinberg Chair in Brain Health) was led by UH & VA neurologist Aasef Shaikh MD, PhD, who is also Vice Chair for Research at University Hospitals, Professor of Neurology, and Associate Medical Director of the Cleveland FES Center. Prajakta Joshi, lead author of the article, is a PhD candidate in biomedical engineering at the Shaikh Lab that is part of the University Hospitals and the Cleveland FES Center at the Louis Stokes Cleveland VA Medical Center.

    We have already established over years of study that dynamic cycling regimens are beneficial for treating Parkinson’s tremor. The latest study adds the use of deep brain stimulation and an ongoing exercise program to visualize how long-term exercise might be rewiring neural connections in the brain.”


    Aasef Shaikh, MD, PhD, Vice Chair, Research, University Hospitals

    Another unique and critical part of the study, Dr. Shaikh added, was the collaboration between the two medical systems, which provided a larger pool of potential participants for recruiting purposes.

    About the study

    Participants with Parkinson’s Disease – including military Veterans – were required to take part in 12 dynamic cycling sessions over a four-week period.

    All study participants had previously been implanted with deep brain stimulation devices to treat their motor symptoms; while simultaneously measuring the brain signals in the region where the electrodes are implanted.

    Another critical aspect of the study was the adaptive cycling regimen investigators used. This technology empowers the bike to learn how patients perform while biking.

    For example, viewing the connected game screen, riders are instructed to pedal up to 80 rpm, and to maintain that speed for about 30 minutes. Meanwhile, their pedaling intensity is shown by an on-screen balloon, and riders have to keep the balloon aloft over water but within specific parameters on screen.

    However, the adaptive quality of the bike keeps riders guessing as to how much effort to apply. The bike’s motor assists them in attaining 80 rpm, but also adds and reduces resistance depending on the rider’s level of effort. Researchers believe this push and pull mechanism is particularly beneficial in treating Parkinson’s symptoms.

    Kent State University PhD candidate Lara Shigo, a co-author of the study, acknowledges 80 RPMs is faster than a person would naturally choose to ride, but says the level doesn’t cause fatigue because the bike’s motor assists the rider in attaining that level.

    Exciting findings

    Brain signal recordings were captured from participants’ implanted DBS electrodes to assess participants’ brain signals before and after each exercise session.

    “Our goal was to understand the immediate and long-term effects of the exercise in that region of the brain where the electrodes are implanted, which is also the same area where Parkinson’s pathology is evident,” Dr. Shaikh said.

    Researchers did not observe immediate brain signal changes, but after 12 sessions, they saw a measurable change in the brain signals responsible for motor control and movement.

    Joshi and the team observed that while modern DBS systems offer a novel window into brain activity, they are limited to capturing signals only from the regions where the electrodes are implanted. As a result, other brain areas that may also contribute to the observed patterns could remain unmonitored.

    The key insight, Joshi explains: “There may be a broader circuit involved. Numerous upstream and downstream pathways could be influenced by exercise, and it’s possible that we’re inducing a network-level change that drives the improvement in motor symptoms.” Additional work could help provide answers, Joshi adds. “The good news is that our next investigations could bring us closer to revolutionary and personalized treatments for PD.”

    Patient success

    Amanda “Mandy” Ensman, 59, was diagnosed with PD 12 years ago and participated in the study. “I knew I needed to start exercising. It really does make a difference,” she explained. “Biking helped me with a variety of symptoms I was struggling with, including my gait, walking and increased my energy levels.”

    Mandy now regularly participates in physical therapy regularly at InMotion, where the study took place. The gym holds workout classes and programs that are geared specifically towards PD patients.

    Source:

    Journal reference:

    Joshi, P., et al. (2024). Electrophysiological correlates of dynamic cycling in Parkinson’s disease. Clinical Neurophysiology. doi.org/10.1016/j.clinph.2025.03.018

    Continue Reading

  • Trends in Antibiotic Resistance in Uropathogens at Mbarara Regional Re

    Trends in Antibiotic Resistance in Uropathogens at Mbarara Regional Re

    Introduction

    Urinary tract infections (UTIs) refer to the infection of the bladder and kidneys having clinical manifestations including cystitis, pyelonephritis, prostatitis, urosepsis, and catheter-associated UTIs.1 These infections are clinically divided into complicated, uncomplicated, and acute pyelonephritis.2 Urinary tract infections are among the most prevalent bacterial infections affecting over 14 million cases reported annually posing significant health and economic burden worldwide.3 Women are disproportionately affected due to their anatomical and physiological features, with 27–48% experiencing recurrent infections.4,5

    In Uganda, the national prevalence of UTIs is approximately 24.92%, with higher rates in the Western region including Mbarara District, and the Northern region where the prevalence has reached up to 71.94% and this has been attributed to demographic factors such as age, gender, hygiene practices, and comorbidities, such as diabetes and catheter use.6

    Gram-negative bacteria, particularly Escherichia coli, are the leading uropathogens responsible for UTIs. Other significant pathogens include Klebsiella pneumoniae, Staphylococcus aureus, and Enterococcus faecalis.6 However, uropathogens have developed resistance to routinely used antibiotics7, such as penicillins, cephalosporins and fluoroquinolones, and tetracyclines from 10% to 20%8,9 in 2014 to approximately 44.6–95.7% in 202110,11 posing a challenge for empirical treatment of UTIs. Furthermore, self-treatment and emerging antimicrobial-resistant patterns play an important role in controlling UTIs in Uganda.10,12

    Antibiotic resistance is a consequence of inappropriate broad-spectrum antibiotic use, inadequate infection control methods, and environmental contamination by pharmaceutical waste.5,10,13

    Regardless of the growing threat of antimicrobial resistance, there is scant local data to guide empiric therapy in Uganda. The specific objectives were to describe the frequency and distribution of isolated uropathogens by specimen type and patient demographic characteristics, and to evaluate temporal trends in antimicrobial resistance, including the prevalence of multidrug-resistant (MDR) and extensively drug-resistant (XDR) phenotypes among these isolates.

    Therefore, this study aimed to analyze the prevalence of common uropathogens and their antimicrobial resistance patterns among patients at Mbarara Regional Referral Hospital (MRRH).

    Methods and Materials

    Study Design and Setting

    The retrospective study was conducted at Mbarara Regional Referral Hospital (MRRH) – Microbiology Department, a tertiary-level teaching hospital in south-western Uganda. MRRH has over 600 inpatient beds and is affiliated with Mbarara University of Science and Technology (MUST), the main campus for teaching undergraduate and postgraduate health sciences programs. The clinic has departments for internal medicine, pediatrics, surgery, obstetrics, and diagnostic services. The microbiology lab is staffed with trained microbiologists and can perform routine bacterial culture, biochemical identification, and antimicrobial susceptibility testing (AST). Culture data from 1st January 2019 to 31st March 2024 were retrieved from WHONET, a data platform supported by WHO and used globally for surveillance of antimicrobial resistance (AMR).

    Inclusion and Exclusion Criteria

    Urine specimens were encompassed if they were culture positive and either obtained via midstream urine (MSU) or catheterization and contained a bacterial load of ≥105 colony-forming units per milliliter (CFU/mL). Only information with complete demographic data (age, sex), valid organism identification, and AST profiles were included. To avoid duplication due to repeated infections or prolonged time of stay, only a single patient isolate per patient was used. Excluded were patient records with inadequate demographic data, missing AST values, or uncertain species identification. Staphylococcus aureus and other potential skin flora were also excluded when isolated from non-sterile samples due to their established role as contaminants of urine samples without catheters.14–16

    Culture Methods and Identification

    The cultures for all urine samples were processed within a two-hour period of sample collection. With the assistance of a 0.01 mL calibrated sterile loop, each sample was inoculated on MacConkey agar, blood agar, and chocolate agar (HiMedia, India). Cystine-lactose-electrolyte-deficient (CLED) agar was used occasionally to suppress swarming by Proteus species. Plates were incubated aerobically at 37°C for 24 hours. Significant bacteriuria was signaled by growth ≥105 CFU/mL, as per WHO GLASS and CLSI recommendations.17 Identification of the isolate started with Gram staining and colony morphology examination. Gram-negative pathogens were identified further by oxidase, SIM (sulfur, indole, motility), triple sugar iron (TSI), and citrate tests. Gram-positive isolates were identified by catalase and coagulase tests.14

    Antimicrobial Susceptibility Testing

    AST was carried out by Kirby–Bauer disc diffusion method on Mueller–Hinton agar (HiMedia, India). Results were interpreted using CLSI M100 (33rd edition, 2023) guidelines.17 Antibiotics tested reflected empirically prescribed options in Uganda and included beta-lactams (ampicillin, amoxicillin-clavulanate, ceftriaxone), aminoglycosides (gentamicin), fluoroquinolones (ciprofloxacin, ofloxacin), sulfonamides (sulfamethoxazole), nitrofurans (nitrofurantoin), carbapenems (imipenem, meropenem), and erythromycin and chloramphenicol. Conservative intermediate susceptibility interpretation was considered resistant, as outlined by WHO guidelines. Quality control was ensured by testing for standard reference strains (Escherichia coli ATCC 25922, P. aeruginosa ATCC 27853, and S. aureus ATCC 25923) on a weekly basis to ensure disc potency and medium performance.17

    Isolate Selection for Analysis

    Isolates were grouped into three categories including true uropathogens, conditional pathogens (often isolated but not necessarily pathogenic), and probable contaminants.14,18 Only true uropathogens with ≥25 isolates were preserved for future AMR and multi-drug resistance (MDR) testing to ensure statistical power. They included Escherichia coli, Klebsiella spp., Klebsiella pneumoniae, Citrobacter spp., and Enterococcus spp., microorganisms known to be the most prevalent etiologic urinary tract infection (UTI) pathogens worldwide.15–17,19 Although S. aureus was repeatedly isolated, it was excluded on microbiological and epidemiological grounds, because its recovery from non-catheterized urine is typically indicative of contamination rather than infection.14–17,19

    Classification of Resistance

    Resistance was defined as non-susceptibility to one or more agents. Multidrug resistance (MDR) was defined as resistance to greater than one drug in three antimicrobial classes by international consensus.20 A graded classification system was also used: R0 = no resistance, R1 = one class, R2 = two classes, R3 = three classes, and R4 = four or more classes of resistance.21 This stratification allowed a gradient interpretation of resistance severity and was used in descriptive tables. Phenotypic resistance mechanisms were inferred where possible: isolates resistant to third-generation cephalosporins were classified as presumptive ESBL producers; carbapenem resistance suggested carbapenemase production; and others were labeled classical MDR in the absence of a known mechanism.

    Statistical Analysis

    Data were cleaned and manipulated using Python 3.8 inside Google Colab. Cleaning and transformation were done with the pandas and numpy libraries. Chi-square tests were used to investigate association between categorical variables with the scipy.stats module, and the significance threshold was taken as p < 0.05. To evaluate resistance patterns over time, quarterly resistance ratios were calculated for each organism-antibiotic pair. Time trend analysis was performed using the Mann–Kendall non-parametric test of the pymannkendall package, a method used to identify monotonic trends in non-parametric microbiological surveillance data.22–25 A 3-quarter rolling average was applied to smooth fluctuations, and a p-value ≤0.05 was considered statistically significant.

    Results

    Patient Demographics and Dataset Overview

    The data set comprised 939 unique patient records each representing a culture-positive urine sample. The average age of all patient records is 40 years old, with an 18-year standard deviation. The recorded age ranges from newborns (0 years) to 105 years. The median age is 38 years old, while the 25th percentile of the population is 27 years of age or younger. With an IQR of 25 years, the 75th percentile indicates that 75% of the subjects are 52 years of age or younger. There are 648 (69.0%) females in this dataset, and 291 (31.0%) male, giving a ratio of 1:0.4.

    Uropathogen Distribution

    Among the 939 isolates, Escherichia coli was the most isolated pathogen, accounting for 428 isolates (45.6%), followed by Klebsiella spp. with 385 isolates (41.0%). Klebsiella pneumonia was identified in 58 isolates (6.2%) while Citrobacter spp. and Enterococcus spp. contributed 42 (4.5%) and 26 (2.8%) isolates, respectively.

    Distribution of Uropathogens by Gender

    Female patients were 648 (69.0%) and 291 (31.0%) to males. Escherichia coli was the most frequent isolate, being recovered in 303 out of 428 female-related isolates (70.8%) and 125 out of 428 (29.2%) from males as shown in Figure 1. A predominance of female-related samples was also observed for Klebsiella spp. (252/385, 65.5%), with the disparity was most marked for Klebsiella pneumoniae, since 46 of 58 isolates (79.3%) were from females. Citrobacter spp. showed a similar trend (32/42, 76.2%), while Enterococcus spp. had a more equal sex distribution (15/26, 57.7% female). Organism-specific chi-square tests of independence revealed no statistically significant associations between sex and isolate distribution for any of the five organisms: Citrobacter spp. (χ² = 0.373, p = 0.5412), Enterococcus spp. (χ² = 0.469, p = 0.4936), Escherichia coli (χ² = 0.217, p = 0.6411), Klebsiella pneumoniae (χ² = 1.121, p = 0.2898), and Klebsiella spp. (χ² = 0.730, p = 0.3930).

    Figure 1 Distribution of the most common uropathogenic isolates (≥25 isolates) by sex and organism (n = 939). Each organism is represented by three bars: blue for total isolates, green for isolates from female patients, and red for isolates from male patients. Organisms include Escherichia coli, Klebsiella spp., Klebsiella pneumoniae, Citrobacter spp., and Enterococcus spp.

    Prevalence of Urine Pathogens and Age

    The five most frequently identified uropathogens showed distinct distribution patterns across patient age groups. The uropathogens showed distinct patterns across patient age groups. Escherichia coli was most isolated from cultures from individuals from the 46- to 65-year-old age group (99/428, 23.1%) followed by the 36- to 45-year-old (92/428, 21.5%), and 26- to 35-year-old groups (84/428, 19.6%). Klebsiella spp. showed a distinct peak in the 26–35 age group (120/385, 31.2%) and remained prevalent in the 46–65 (82/385, 21.3%) and 36–45 (69/385, 17.9%) age groups. Klebsiella pneumonia showed the same trend with the majority being recovered from cultures from individuals between the age group 46–65 years (19/58, 32.8%) and 15–25 years (13/58, 22.4%). Citrobacter spp. were found predominantly in adults 36–45 years (12/42, 28.6%) and 46–65 years (10/42, 23.8%), whereas Enterococcus spp. reached the 36–45 (9/26, 34.6%) and 26–35 (7/26, 26.9%) age groups. A chi-square test of independence confirmed a statistically significant association between the type of uropathogen recovered and the age group of individuals from whom the culture-positive urine samples were obtained (χ² = 39.83, df = 20, p = 0.0052). The greatest deviations from expected frequencies were noted among Escherichia coli and Klebsiella spp. within the 26–35 and 46–65-year age group (Figure 2).

    Figure 2 Distribution of the most common uropathogenic isolates (≥25 isolates) by age group. Each group of bars represents a single organism. Bars are color-coded by age group: blue for 0–14 years, green for 15–24 years, Orange for 25–44 years, purple for 45–64 years, and red for ≥65 years. Bar heights reflect the proportion of isolates from each age group, expressed as percentages.

    There is a statistically significant association between organism type, age category, and sex (χ² = 74.886, df = 26, p < 0.0001). Frequency pattern trends anticipated that Escherichia coli isolates were more frequently isolated from female urine samples in every age group especially among females aged 46–65 years (anticipated: 67.996) compared to males (31.004). Following the same trend, Klebsiella spp. showed a more anticipated recovery in females, especially in the 26–35 years age group (82.419 vs 37.581 for males). Although less frequently recovered, Citrobacter spp., Klebsiella pneumoniae, and Enterococcus spp. also exhibited differences in recovery frequencies among age–sex subgroups.

    Overall and Organism-Specific Antibiotic Resistance

    A total of 893 (95.1%) were resistant to at least one tested antibiotic. Klebsiella spp. was the most resistant with 382 out of 385 isolates (99.2%) being resistant to at least one antibiotic. This was followed by Escherichia coli (396/428, 92.5%), Enterococcus spp. (25/26, 96.2%), and Klebsiella pneumoniae (54/58, 93.1%). Citrobacter spp. reported the lowest resistance rate among the top five organisms, having 36 out of 42 isolates (85.7%) resistant.

    Trends in Antibiotic Resistance and Statistical Significance 2019–2024

    Highest resistance rates were observed sulfamethoxazole showing resistance in 619 of 676 isolates (91.6%), followed closely by ampicillin (274/300, 91.3%). High bacterial resistance to Erythromycin was observed with 16 of 22 isolates (72.7%) demonstrating resistance. Over half of the pathogens were also resistant to clindamycin (306/563, 54.4%), chloramphenicol (326/611, 53.4%), and amoxicillin/clavulanic acid (324/621, 52.2%). Resistance to ceftriaxone and ciprofloxacin was 46.0% and 28.1%, respectively. Lower rates were seen with gentamicin (18.2%) and nitrofurantoin (22.1%).

    In contrast, bacteria showed lower resistance rates to carbapenems with 10.3% and 8.7% resistance to Imipenem and Meropenem, respectively, as shown in Table 1.

    Table 1 Resistance Rates to Common Antimicrobial Agents in Urine Cultures at Mbarara Regional Referral Hospital, 2019–2024

    A detailed summary of the resistance of the uropathogens to different antibiotics is presented in Table 2. Resistance was defined as non-susceptibility to the tested antibiotic (R No [%]), with the total number of isolates tested (T) indicated for each combination. Escherichia coli demonstrated significant resistance to several antibiotics, with the highest resistance observed to Ampicillin (174/190, 91.6%), followed by Sulfamethoxazole (240/274, 87.6%) and Clindamycin (148/199, 74.4%). Escherichia coli resistance to Chloramphenicol was (214/341, 62.8%) and Clindamycin (122/313, 39.0%). Klebsiella pneumoniae displayed significant resistance to Ampicillin (27/28, 96.4%) and Sulfamethoxazole (24/36 isolates, 66.7%), while also showing moderate resistance to Ceftriaxone (15/22 isolates, 68.2%) and Clindamycin (29/32, 90.6%). Citrobacter spp. were most resistant to Ampicillin (3/3, 100%), Ciprofloxacin (13/18, 72.2%), and Sulfamethoxazole (16/23, 69.6%). Resistance to Chloramphenicol was also high (4/7, 57.1%). Enterococcus spp. were most resistant to Erythromycin (16/22, 72.7%) and Chloramphenicol (7/10, 70.0%). Sulfamethoxazole resistance was found in 13 of 14 isolates (92.9%).

    Table 2 Distribution of the Most Common Uropathogens and Their Resistance to Common Antibiotics at Mbarara Regional Referral Hospital From January 1, 2019, to December 31, 2024

    Temporal Mono Resistance Trends

    For analysis of trends of mono resistance over time, quarterly data over the period of 2019 to 2024 were analyzed by comparing them using the Mann-Kendall trend test. Rising resistance was observed in Klebsiella spp. against Ceftriaxone (τ = 0.581, p = 0.0028), Cefotaxime (τ = 0.5909, p = 0.0090), and Imipenem (τ = 0.3099, p = 0.0415). An increasing trend of Escherichia coli was observed against Cefotaxime (τ = 0.3791, p = 0.0291). As shown in Figure 3a and Table 3, while raw quarterly resistance values (blue line) fluctuate, the 3-quarter rolling average (orange dashed line) reveals a sustained upward trajectory, confirming these trends. On the other hand, declining resistance was observed for Amoxicillin/Clavulanic Acid between Klebsiella spp. (τ = –0.5238, p = 0.0068) and Escherichia coli (τ = –0.3421, p = 0.0378) as shown in Table 3. This decline is evident in Figure 3b, where both raw values and rolling averages indicate a consistent downward pattern. No statistically significant trends toward antibiotic resistance (p ≥ 0.05) were detected for the majority of organism–antibiotic pairs under study. These included resistance of Klebsiella spp. and Escherichia coli to agents in widespread use such as Gentamicin, Ciprofloxacin, Sulfamethoxazole, and Chloramphenicol. Six organism–antibiotic combinations were omitted from the trend analysis due to sparse data (<12 quarters) and primarily affected Citrobacter spp., Klebsiella pneumoniae, and Enterococcus spp.

    Table 3 Significant Trends in Antimicrobial Resistance Among Escherichia coli and Klebsiella spp. From 2019 to 2024

    Figure 3 Antimicrobial resistance trends among urinary isolates from Mbarara Regional Referral Hospital (MRRH), 2019–2024. (a) The pattern of resistance to cefotaxime among Escherichia coli is increasing (p = 0.029); (b) There is declining resistance to amoxicillin/clavulanic acid in Klebsiella spp. (p = 0.007). Dots: raw percentages of resistance for each quarter. Dashed lines: 3-quarter rolling average, used to reduce short-term fluctuations and expose longer-term trends.

    The observed directional patterns including increasing cefotaxime resistance in Escherichia coli and decreasing amoxicillin/clavulanic acid resistance in Klebsiella spp. reinforce the value of combining visual smoothing with statistical trend analysis. Through the use of 3-quarter rolling averages coupled with Mann–Kendall trend analysis, we were able to detect persistent, monotonic trends in AMR that would have been obscured by quarterly fluctuation.

    Multidrug Resistance Patterns (MDR) Among Uropathogens

    The resistance pattern of bacterial isolates by resistance levels (R0 to >R7) shows elevated resistance to multiple antibiotics in major uropathogens, as shown in Table 4. Escherichia coli carried a high resistant burden with only 7.5% of the isolates being fully susceptible to all antibiotics tested (R0). The majority were resistant to at least three antibiotics, notably at R2 (32.7%), R3 (22.0%), and R4 (12.1%). Klebsiella spp. displayed a similar trend, where 42.3% were resistant to three antibiotics (R3) and 26.3% to four and above (R4–>R7), and only 0.8% of the isolates were fully susceptible as shown in Table 5.

    Table 4 Distribution of Bacterial Isolates Across Antibiotic Resistance Categories (R0 to R7) From Sensitivity to Increasing Resistance to Multiple Antibiotics Among Patients at Mbarara Regional Referral Hospital From January 1, 2019, to December 31, 2024

    Table 5 Summary of Organisms, Resistance, and MDR Patterns by Specimen Type

    Klebsiella pneumoniae presented with a more ominous resistance profile with 12.1% of the isolates resistant to at least seven antibiotics. Enterococcus spp. had elevated levels of resistance with 76.9% isolates in R2–R4 with none of them with greater than four-drug resistance.

    Of 939 urine isolates tested, 534 (56.9%) were classified as multidrug-resistant (MDR), 356 (37.9%) were resistant to one or two groups of antimicrobials, and 46 (4.9%) were susceptible. An additional 3 isolates (0.3%) met the criteria for extensively drug-resistant (XDR) phenotype. Of the MDR strains, 374 (70%) were extended-spectrum β-lactamase (ESBL) producers, most commonly in Escherichia coli and Klebsiella spp. One MDR isolate (0.2%) was classified as carbapenemase-producing Klebsiella pneumoniae (KPC), and one (0.2%) produced ESBL and KPC enzymes. The remaining 158 MDR isolates (29.6%) were resistant to more than three antimicrobial classes with no detection of a known resistance mechanism and belonged to the classical MDR category. Among the XDR isolates, one expressed ESBL alone, one KPC alone, and one co-produced ESBL and KPC. None of the strains met the criteria for vancomycin-resistant Enterococcus spp. (VRE), or pan-drug-resistant (PDR) phenotypes.

    A phenotypic analysis of MDR and XDR phenotypes per organism is demonstrated in Figure 4. Of the 194 MDR Escherichia coli, 141 (72.7%) were ESBL producers, and 53 (27.3%) did not have a phenotypic mechanism identified. In Klebsiella spp. (n = 285), 199 (69.8%) were ESBL producers. Of the 28 MDR Klebsiella pneumoniae isolates, 17 (60.7%) were ESBL-positive, 2 (7.1%) expressed KPC, 2 (7.1%) co-produced ESBL and KPC, and 7 (25.0%) showed no phenotypic mechanism. Three additional Klebsiella pneumoniae isolates met criteria for XDR, including one ESBL producer, one KPC producer, and one co-producing both. In 21 MDR Citrobacter spp. isolates, 18 (85.7%) were ESBL producers, and 3 (14.3%) did not have any detected mechanism. All 9 MDR Enterococcus spp. isolates did not have phenotypic evidence of vancomycin resistance.

    Figure 4 Distribution of MDR and XDR among most common uropathogenic isolates. Each bar represents the relative distribution of phenotypic resistance mechanisms among multidrug-resistant (MDR) and extensively drug-resistant (XDR) isolates for organisms with ≥25 resistant isolates. The phenotypes are distinguished by color: Orange (MDR: ESBL), light blue (MDR: ESBL, KPC), green (MDR: KPC), dark blue (MDR: no detected mechanism), yellow (XDR: ESBL), brown (XDR: ESBL, KPC), and pink (XDR: KPC). Organisms included are Citrobacter spp., Enterococcus spp., Escherichia coli, Klebsiella pneumoniae, and Klebsiella spp.

    The prevalence of resistance classes among MDR and XDR uropathogens is depicted in Figures 4 and 5. β-Lactam resistance was the highest among all uropathogens, covering 100.0% of Enterococcus spp. (9/9), 96.4% of Klebsiella pneumoniae (27/28), 90.7% of Escherichia coli (176/194), and 90.5% of Citrobacter spp. (19/21). Sulfonamide resistance was also high, and it was highest among Klebsiella spp. (92.6%, 264/285) and Escherichia coli (68.0%, 132/194). Fluoroquinolone resistance ranged from 17.5% for Klebsiella spp. to 39.3% for Klebsiella pneumoniae. Resistance to aminoglycosides was found in 22.2% to 28.6% of Gram-negative uropathogens. Macrolide resistance was found only in Enterococcus spp. (66.7%, 6/9). Carbapenem resistance was found in 23.8% of Citrobacter spp. and 14.3% of Klebsiella pneumoniae. Amphenicol resistance was found in 58.2% of Klebsiella spp. and 39.3% of Klebsiella pneumoniae, while resistance to nitrofurans was highest in Klebsiella pneumoniae (39.3%) and Escherichia coli (13.9%).

    Figure 5 Resistance class profiles of MDR and XDR uropathogens isolated at Mbarara Regional Referral Hospital, 2019–2024.The heat map presents the number and percentage of isolates (n/N, %) resistant to at least one agent within each antibiotic class. Organisms are shown on the y-axis and antibiotic classes along the x-axis. Darker shading reflects higher MDR burden.

    Quarterly MDR Trends

    Quarterly temporal trends in multidrug resistance (MDR) among uropathogens exhibited organism-specific variability as shown in Figure 6. Trend direction and significance were assessed using the Mann-Kendall non-parametric trend test. Escherichia coli demonstrated a statistically significant increasing trend in MDR proportions over time (p = 0.015. There was no significant temporal trend in MDR ratios for Klebsiella spp. (p = 0.207), Klebsiella pneumoniae (p = 1.000), or Enterococcus spp. (p = 0.333).

    Figure 6 Quarterly trends in multidrug resistance (MDR) among predominant uropathogens isolated at Mbarara Regional Referral Hospital between 2019 and 2024. Panels depict 3-quarter rolling average MDR proportions for (a) Klebsiella spp., (b) Escherichia coli, (c) Klebsiella pneumoniae, and (d) Enterococcus spp. Trends were assessed using the Mann–Kendall test; corresponding p-values are displayed within each plot. A horizontal reference line at 50% indicates the mid-threshold for MDR burden.

    Despite the absence of monotonic trends in a few of the species, MDR levels were consistently high throughout the entire duration of the study. Klebsiella pneumoniae tended to have MDR percentages of or near 100% in many quarters but with huge variations. Enterococcus spp. experienced an elevation in short-term MDR from 2021 to 2022 but dropped. Klebsiella spp. experienced MDR rates far beyond the 50% mark for the majority of portions but with huge quarter-to-quarter variability.

    Specimen-Type Distribution of Resistance and MDR Patterns

    Organism-specific resistance and MDR pattern analysis stratified by specimen type revealed considerable differences. The vast majority of isolates were from midstream urine (97.9%, n=919), while catheter-derived samples comprised a minority proportion (2.1%, n=20). Of the catheter samples, the predominant organism was Escherichia coli (55.0%), followed by Klebsiella pneumoniae (25.0%) and Citrobacter spp. (20.0%). All catheter specimen isolates were 100% resistant, with MDR in 70.0% overall. Significantly, 100% of the catheter Citrobacter spp. were MDR, followed by 72.7% Escherichia coli and 40.0% Klebsiella pneumoniae.

    Escherichia coli was the predominant organism in midstream urine cultures (45.4%), followed by Klebsiella spp. (41.9%), but less often were Klebsiella pneumoniae, Citrobacter spp., and Enterococcus spp. The resistance rates for these organisms were all high and ranged from 84.2% among Citrobacter spp. to 99.2% among Klebsiella spp. Prevalence of MDR among midstream isolates was also high, with the highest recorded in Klebsiella spp. (74.0%), followed by Klebsiella pneumoniae (45.3%), Escherichia coli (44.4%), Citrobacter spp. (44.7%), and Enterococcus spp. (34.6%). These findings highlight specimen type-specific variation in resistance and MDR prevalence among leading uropathogens.

    Discussion

    The study is in agreement with the global observation that females are disproportionately affected by urinary tract infections (UTIs). The higher prevalence of UTIs in females may be attributed to anatomical differences, such as the shorter urethra, which facilitates bacterial entry into the urinary tract, and hormonal changes which may alter vaginal and urinary flora, and anterior vaginal prolapse.26–28

    Furthermore, Escherichia coli was the most frequently isolated organism in this study, particularly among females (70.8%), aligning with global findings that identify Escherichia coli as the leading cause of community-acquired and healthcare-associated urinary tract infections (UTIs).27,29,30 Comparable studies from Uganda,9,31,32 Sub-Saharan Africa29,33,34 Asia,35,36 and America37 revealed Escherichia coli prevalence rates of 30–70% that is consistent with our findings, highlighting its global clinical importance. This may be attributed to the virulence factors of Escherichia coli, like as adhesins, hemolysins, and biofilm-formation, which enhance its ability to colonize the urinary tract.38 While Klebsiella spp., Klebsiella pneumoniae, and Citrobacter spp. also showed a female predominance, Enterococcus spp. were more evenly distributed by sex.

    The difference in aetiological agents among males and females underscores the importance of gender considerations in diagnosing and treating urinary tract infections, as the prevalence of specific organisms may significantly vary between male and female patients.

    Age distribution highlighted two high-risk populations; young adults (26–45 years) and the elderly (>65 years). In young adults, social factors such as increased sexual activity and contraceptive use may contribute to the high incidence of urinary tract infections while in the elderly, comorbid conditions such as diabetes, weakened immunity, and frequent catheterization may contribute to a higher prevalence of UTIs.39,40 These trends are in line with recent reports demonstrating age-specific colonization by dominant uropathogens.41,42 This distinct distribution of urinary tract infections among the age groups highlights the need for age-appropriate diagnostic and treatment choices.

    Moreover, Escherichia coli was disproportionately recovered from cultures taken from females in all age groups, most notably those between 46 and 65 years old, a finding substantiated by the existence a significant organism–age–sex interaction (χ² = 74.886, df = 26, p < 0.0001). This age group-specific prevalence testifies to the multivariate etiology of UTIs and yet again emphasizes the importance of considering host biology as well as habits in epidemiologic risk stratification. These findings are consistent with other research noting female gender and reproductive-age exposures as essential determinants of pathogen recovery profiles.43,44 Incorporating sex-specific empiric therapies and targeted surveillance for high-risk patients may improve clinical outcomes and antimicrobial stewardship.

    According to these patterns of populations, a comprehensive analysis of susceptibility to antimicrobials revealed staggering baseline resistance among uropathogens to several commonly prescribed antibiotics. The study highlights the rising antimicrobial resistance among Uropathogens to commonly used antibiotics such as ampicillin (91.3%) and sulfamethoxazole (91.6%) reflecting inadequate treatment options. Unfortunately, such findings are very similar to previous studies done in other regions of Uganda11,45 as well as in the world, particularly in low- and middle-income countries (LMICs) such as Ethiopia46 and the Democratic Republic of Congo.47 In contrast, high-income countries report lower resistance rates to first-line antibiotics due to improved regulated antibiotic use39,48 emphasizing the need for policy interventions in Uganda.

    In Klebsiella spp., rising mono resistance to Imipenem (τ = 0.3099, p = 0.0415) is of particular concern because carbapenems are drugs of last resort for complicated infections. The 3-quarter moving average also confirmed long-term increasing trends in these patterns of resistance, establishing the clinical importance of these findings. This trend is worrisome because cephalosporins, a subgroup of beta-lactams are commonly used for both community-acquired and healthcare-associated infections in Uganda.49,50 This puts their continued effectiveness as keystone drugs at risk. Similarly, increasing gentamicin resistance, a primary aminoglycoside used on more than one level of care contributes to empiric treatment limitations, particularly to Escherichia coli.

    Conversely, there was a statistically significant decline in resistance to Amoxicillin/Clavulanic Acid for Klebsiella spp. and Escherichia coli. This shift can be interpreted as evidence of reduced prescribing pressure or improved stewardship and laboratory accuracy. Evidence elsewhere testifies to this possibility. For example, 2010 study demonstrated that restriction of AMC use in hospital settings was associated with a precipitous drop in Escherichia coli resistance, from 37% to 11% within one year (p < 0.0001), illustrating the capacity for fast action on targeted antibiotic policy on resistance trends.51

    On the other hand, resistance to Gentamicin and Ciprofloxacin did not statistically vary over time. The two medications, however, recorded relatively high frequencies of resistance in our study limiting their applicability as empirical drugs irrespective of stability. This corresponds with observations made from Uganda and other regions,32,52 where resistance to aminoglycoside and fluoroquinolone is not insignificant among isolates of Escherichia coli and Staphylococcus aureus. Most concerning is the uniformly high frequency of the resistance to Sulfamethoxazole, which was greater than 90% for the entire study period. Even in the absence of an upward trend, resistance of this magnitude renders the drug clinically irrelevant for empiric use in this context. This result is consistent with previous reports in Southeast Asia and East Africa,30,33,53 reinforcing the importance of not only tracking resistance trends, but recognizing when frequency alone is sufficient to disqualify an agent from therapeutic consideration. These results highlight the limitations of static antibiograms in settings with high burdens. It is only through longitudinal surveillance and statistical modeling, such as Mann-Kendall trend analysis, which early trends in resistance can be detected and acted upon. This underlines the need not only to monitor resistance frequencies, but also to monitor their directionality over time, guiding enhanced antimicrobial stewardship and treatment planning.

    Furthermore, MDR patterns in the present study are alarming and widespread. Over half (56.9%) of all isolates were found to be multidrug-resistant (MDR), with an additional subgroup possessing criteria for extensive drug resistance (XDR). The most alarming species was Klebsiella pneumoniae with more than two-thirds (69%) of its isolates being resistant to three or more agents, and more than 12% showing resistance to seven or more agents. Of MDR Klebsiella pneumoniae, 60.7% were ESBL producers and others had carbapenemase phenotypes such as KPC alone or in combination. The high rates of MDR reported in this work are fueled by intrinsic as well as acquired mechanisms. Gram-negative bacteria like Escherichia coli and Klebsiella pneumoniae carry extended-spectrum β-lactamases (ESBLs) that break down penicillins and cephalosporins, making these widely used drugs ineffective. In addition, efflux pumps, reduced outer membrane permeability, and plasmid-borne resistance genes are also responsible for MDR phenotypes. These mechanisms represent global reports of MDR in Africa, Asia, Europe, and the Americas and not only restricted in Uganda.

    Although carbapenemase-producing isolates were rare in this study, their presence in Klebsiella pneumoniae alongside high levels of classical multidrug resistance remains a cause for concern. Carbapenem resistance, often facilitated by carbapenemase-producing Enterobacterales (CPE), is an international public health threat. Examples of such genes as KPC, NDM, and OXA-48, usually harbored on mobile genetic elements, facilitate horizontal gene transfer and spread of resistance.40 While carbapenem resistance remains uncommon in Uganda,41 its increasing frequency in India54 and other low- and middle-income nations (LMICs) calls for enhanced monitoring and the preservation of carbapenems as drugs of last resort.

    Temporal trends using Mann–Kendall trend testing showed an increasing trend over time in MDR Escherichia coli isolates that was statistically significant (p = 0.015), aligning with other regional and international reports of rising multidrug resistance.55,56 The consistently high MDR rates particularly for K. pneumonia indicate a continued resistance burden that remains to be tackled.

    The integration of longitudinal statistical modeling, such as Mann–Kendall trend analysis, allows early warning about resistance increase and informs adaptive antimicrobial stewardship policy. Infection control needs to be directed by more than frequency, but by direction of resistance, allowing timely intervention and preserving effective antimicrobial therapy.

    This study relied only on secondary data and this may introduce biases and limit generalizability. Additionally, small sample sizes for less common pathogens and catheter-derived specimens reduce statistical power, and therefore larger prospective studies to confirm these findings. Future research should also explore the molecular mechanisms underlying resistance in these pathogens, which could inform the development of targeted therapies and diagnostics.

    Conclusion

    This study highlights the significant burden of AMR among uropathogens at Mbarara Regional Referral Hospital, with Escherichia coli as the most prevalent pathogen. High resistance rates were observed for commonly used antibiotics, and rising trends in cefotaxime, ceftriaxone, and imipenem resistance were detected, particularly among Escherichia coli and Klebsiella spp. Multidrug resistance was widespread, with a significant upward trend in Escherichia coli, emphasizing the need for urgent interventions, including updated treatment guidelines and functional surveillance systems. The Mann–Kendall trend test proved useful for identifying sustained changes in resistance over time. This analysis provides a solid basis for further study with more elaborate time-series models, such as SARIMA and Bayesian models, to refine trend estimation and resistance prediction. The findings support the imperative of refreshing empirical treatment guidelines, enhancing regular diagnostic capacity, and expanding antimicrobial stewardship efforts.

    Data Sharing Statement

    The datasets used and analyzed during the current study are available from the corresponding author upon reasonable request. Additionally, the Python code utilized for data analysis has been cleaned and uploaded to GitHub to facilitate replication and future collaborations. You can access the repository at https://github.com/nakatoconstance/MDR2020_2021.git.

    Ethics Statement

    The study is under a big project “AMR Surveillance, Modelling Antimicrobial Pharmaceutical Needs and PCR/Herbal/Biotechnological Products Development” in Uganda. Approval was obtained from Busitema University Faculty of Health Sciences REC with REC number BUFHS-2022-15. This study did not interface with patients as the clinical isolates were obtained from patients under routine hospital procedures.

    Funding

    The study obtained funding from the Government of Uganda under a larger project entitled Pathogen Epidemiological Studies no OP-STI-PRESIDEPATHOGEN-2021/2022/21.

    Disclosure

    The authors confirm that they had no conflicts of interest.

    References

    1. Foxman B. Urinary tract infection syndromes: occurrence, recurrence, bacteriology, risk factors, and disease burden. Infect Dis Clinics. 2014;28(1):1–13. doi:10.1016/j.idc.2013.09.003

    2. Bilsen MP, Jongeneel RMH, Schneeberger C, et al. Definitions of Urinary Tract Infection in Current Research: a Systematic Review. Open Forum Infect Diseases. 2023;10(7). doi:10.1093/ofid/ofad332.

    3. Bischoff S, Walter T, Gerigk M, Ebert M, Vogelmann R. Empiric antibiotic therapy in urinary tract infection in patients with risk factors for antibiotic resistance in a German emergency department. BMC Infect Dis. 18(1):56. doi:10.1186/s12879-018-2960-9

    4. Micali S, Isgro G, Bianchi G, Miceli N, Calapai G, Navarra M. Cranberry and recurrent cystitis: more than marketing? Crit Rev Food Sci Nutr. 2014;54(8):1063–1075. doi:10.1080/10408398.2011.625574

    5. Yang X, Chen H, Zheng Y, Qu S, Wang H, Yi F. Disease burden and long-term trends of urinary tract infections: a worldwide report. Front Public Health. 2022;10:888205. doi:10.3389/fpubh.2022.888205

    6. Makeri D, Dilli PP, Nyaketcho D, Pius T. Prevalence of Urinary Tract Infections in Uganda: a Systematic Review and Meta-Analysis. Open Access Lib J. 2023;10(8):1–15.

    7. Yang X, Chen H, Zheng Y, Wang H, Yi F. Disease burden and long term trends of urinary tract infections: A worldwide report. Frontiers in public health. 2022;10:888205.

    8. Bazira J, Boum IIY, Sempa J, et al. Trends in antimicrobial resistance of Staphylococcus aureus Isolated from clinical samples at Mbarara Regional Referral Hospital in Rural Uganda. British Microbiology Research Journal. 2014;4(10):1084–1091. doi:10.9734/BMRJ/2014/9751

    9. Ampaire L, Butoto A, Orikiriza P, Muhwezi O. Bacterial and Drug Susceptibility Profiles of Urinary Tract Infection in Diabetes Mellitus Patients at Mbarara Regional Referral Hospital, Uganda. 2015.

    10. Odoki M, Almustapha Aliero A, Tibyangye J, et al. Prevalence of bacterial urinary tract infections and associated factors among patients attending hospitals in Bushenyi district, Uganda. Int J Microbiol. 2019;2019:1–8. doi:10.1155/2019/4246780

    11. Johnson B, Stephen BM, Joseph N, Asiphas O, Musa K, Taseera K. Prevalence and bacteriology of culture-positive urinary tract infection among pregnant women with suspected urinary tract infection at Mbarara regional referral hospital, South-Western Uganda. BMC Pregnancy Childbirth. 2021;21(1):1–9. doi:10.1186/s12884-021-03641-8

    12. Olamijuwon E, Keenan K, Mushi MF, et al. Treatment seeking and antibiotic use for urinary tract infection symptoms in the time of COVID-19 in Tanzania and Uganda. J Global Health. 2024;14:1.

    13. Akram M, Shahid M, Khan AU. Etiology and antibiotic resistance patterns of community-acquired urinary tract infections in JNMC Hospital Aligarh, India. Ann Clinic Microbiol Antimicrob. 2007;6(1):1–7. doi:10.1186/1476-0711-6-4

    14. Cheesbrough M. District Laboratory Practice in Tropical Countries, Part 2. Cambridge university press; 2005.

    15. Nicolle LE. Catheter associated urinary tract infections. Antimicrob Resist Infect Control. 2014;3(1):1–8. doi:10.1186/2047-2994-3-23

    16. Flores-Mireles AL, Walker JN, Caparon M, Hultgren SJ. Urinary tract infections: epidemiology, mechanisms of infection and treatment options. Nat Rev Microbiol. 2015;13(5):269–284. doi:10.1038/nrmicro3432

    17. Pierce VM, Bhowmick T, Simner PJ. Guiding antimicrobial stewardship through thoughtful antimicrobial susceptibility testing and reporting strategies: an updated approach in 2023. J Clin Microbiol. 2023;61(11):e00074–22. doi:10.1128/jcm.00074-22

    18. Moskaluk AE, VandeWoude S. Current topics in dermatophyte classification and clinical diagnosis. Pathogens. 2022;11(9):957. doi:10.3390/pathogens11090957

    19. Gupta K, Hooton TM, Naber KG, et al. International clinical practice guidelines for the treatment of acute uncomplicated cystitis and pyelonephritis in women: a 2010 update by the Infectious Diseases Society of America and the European Society for Microbiology and Infectious Diseases. Clinl Infect Dis. 2011;52(5):e103–e20. doi:10.1093/cid/ciq257

    20. Magiorakos A-P, Srinivasan A, Carey RB, et al. Multidrug-resistant, extensively drug-resistant and pandrug-resistant bacteria: an international expert proposal for interim standard definitions for acquired resistance. Clin Microbiol Infect. 2012;18(3):268–281. doi:10.1111/j.1469-0691.2011.03570.x

    21. Tilahun M, Sharew B, Shibabaw A. Antimicrobial resistance profile and associated factors of hospital-acquired gram-negative bacterial pathogens among hospitalized patients in northeast Ethiopia. BMC Microbiol. 2024;24(1):339. doi:10.1186/s12866-024-03485-0

    22. Robledo J, Maldonado N, Robledo C, Ceballos Naranjo L, Hernández Galeano V, Pino JJ. Changes in Antimicrobial Resistance and Etiology of Blood Culture Isolates: results of a Decade (2010–2019) of Surveillance in a Northern Region of Colombia. Infect Drug Resist. 2022;Volume 15:6067–6079. doi:10.2147/IDR.S375206

    23. Sodagari HR, Sohail MN, Varga C. Temporal, regional, and demographic differences among antimicrobial-resistant domestic Campylobacter jejuni human infections across the United States, 2013–2019. Int J Antimicrob Agents. 2025;65(5):107467. doi:10.1016/j.ijantimicag.2025.107467

    24. Tchole AIM, Ye R-Z, Xu Q, et al. Epidemiological behaviour and interventions of malaria in Niger, 2010–2019: a time-series analysis of national surveillance data. Malaria J. 2024;23(1):30. doi:10.1186/s12936-024-04835-z

    25. Wang Z, Wang Y, Zhang S, Wang S, Xu Z, Feng Z. Trend analysis and prediction of gonorrhea in mainland China based on a hybrid time series model. BMC Infect Dis. 2024;24(1):113. doi:10.1186/s12879-023-08969-4

    26. Jelly P, Verma R, Kumawat R, Choudhary S, Chadha L, Sharma R. Occurrence of urinary tract infection and preventive strategies practiced by female students at a tertiary care teaching institution. J Educ Health Promotion. 2022;11(1):122. doi:10.4103/jehp.jehp_750_21

    27. Alkhafaji RTH, Jayashankar M. Etiological Agents of Urinary Tract Infection (UTI). 2022. doi:10.32628/IJSRST22925

    28. Zare M, Vehreschild MJ, Wagenlehner F. Management of uncomplicated recurrent urinary tract infections. BJU Int. 2022;129(6):668–678. doi:10.1111/bju.15630

    29. Mwang’onde BJ, Mchami JI. The aetiology and prevalence of urinary tract infections in Sub-Saharan Africa: a Systematic Review. J Health Biological Sci. 2022;10(1):1–7. doi:10.12662/2317-3076jhbs.v10i1.4501.p1-7.2022

    30. Mancuso G, Midiri A, Gerace E, Marra M, Zummo S, Biondo C. Urinary tract infections: the current scenario and future prospects. Pathogens. 2023;12(4):623. doi:10.3390/pathogens12040623

    31. Turyatunga G. The Prevalence of Bacterial Pathogens associated with Urinary Tract Infection (UTI) among Patients attending Kam Medical Consult Clinic, Uganda. Student’s J Health Research Africa. 2021;2(6):8.

    32. Odongo I, Ssemambo R, Kungu JM. Prevalence of Escherichia coli and its antimicrobial susceptibility profiles among patients with UTI at Mulago Hospital, Kampala, Uganda. Interdisciplinary Perspectiv Infect Dis. 2020;2020(1):8042540. doi:10.1155/2020/8042540

    33. Maldonado-Barragán A, Mshana SE, Keenan K, et al. Predominance of multidrug-resistant (MDR) bacteria causing urinary tract infections (UTIs) among symptomatic patients in East Africa: a call for action. medRxiv. 2023;2023:23291274.

    34. Adeleye Q, Ndubuisi E, Isa F. Etiologic and Anti-microbial Susceptibility Profiles of Bacterial Urinary Tract Infection and Bacterial Enteritis among Children at a Private Multi-Specialty Healthcare Facility in Abuja, Nigeria: a 5-Year Separate and Comparative Review. Niger J Clin Pract. 2024;27(1):35–46. doi:10.4103/njcp.njcp_299_23

    35. Ma I, Mr I, Khan R, et al. Prevalence, etiology and antibiotic resistance patterns of community-acquired urinary tract infections in Dhaka, Bangladesh. PLoS One. 2022;17(9):e0274423. doi:10.1371/journal.pone.0274423

    36. Sunarno S, Puspandari N, Fitriana F, Nikmah UA, Idrus HH, Panjaitan NSD. Extended spectrum beta lactamase (ESBL)-producing Escherichia coli and Klebsiella pneumoniae in Indonesia and South East Asian countries: GLASS Data 2018. AIMS Microbiol. 2023;9(2):218. doi:10.3934/microbiol.2023013

    37. de Souza HD, Diório GRM, Peres SV, Francisco RPV, Galletta MAK. Bacterial profile and prevalence of urinary tract infections in pregnant women in Latin America: a systematic review and meta-analysis. BMC Pregnancy Childbirth. 2023;23(1):774. doi:10.1186/s12884-023-06060-z

    38. Firoozeh F, Zibaei M, Badmasti F, Khaledi A. Virulence factors, antimicrobial resistance and the relationship between these characteristics in uropathogenic Escherichia coli. Gene Rep. 2022;27:101622. doi:10.1016/j.genrep.2022.101622

    39. Huang L, Huang C, Yan Y, Sun L, Li H. Urinary tract infection etiological profiles and antibiotic resistance patterns varied among different age categories: a retrospective study from a tertiary general hospital during a 12-year period. Front Microbiol. 2022;12:813145. doi:10.3389/fmicb.2021.813145

    40. Lin W-H, Wang M-C, Liu P-Y, et al. Escherichia coli urinary tract infections: host age-related differences in bacterial virulence factors and antimicrobial susceptibility. J Microbiol Immunol Infect. 2022;55(2):249–256. doi:10.1016/j.jmii.2021.04.001

    41. Sharma M, Qanoongo FN, Doley PK, Pegu G, Pegu M. Spectrum and impact of urinary tract infections among adult renal allograft recipients in a tertiary care center of Northeast India. Int Urol Nephrol. 2025;57(1):1–12. doi:10.1007/s11255-024-04163-w

    42. Toufiq Ahmed DSM, Hasan GS, Karim MM, Ahmad MR, Hossin MI, Islam J. Antibiotic Susceptibility and Resistance Trends in Uropathogenic Bacteria: a Regional Perspective. J Neonatal Surg. 2025;14(27):189–195.

    43. Azeez MM, Ogundele DF, Alade WA, Akinlabi AM, Olaniyan MF. Carbapenemase-producing bacteria from Urinary Tract Infection (UTI) cases at University College Hospital, Ibadan, Nigeria. Sokoto J Med Laboratory Sci. 2024;9(3):113–124. doi:10.4314/sokjmls.v9i3.12

    44. Mahmood N, Siddiqui MR, Giasuddin RS, Islam M, Mnkk S. Recurrent Urinary Tract Infection-Etiology, Risk Factors and Outcome in a Tertiary Care Hospital of Bangladesh. Bangladesh J Med. 2024;35(3):173–179. doi:10.3329/bjm.v53i3.75306

    45. Abongomera G, Koller M, Musaazi J, et al. Spectrum of antibiotic resistance in UTI caused by Escherichia coli among HIV-infected patients in Uganda: a cross-sectional study. BMC Infect Dis. 2021;21(1):1–7. doi:10.1186/s12879-021-06865-3

    46. Gebretensaie Y, Atnafu A, Girma S, Alemu Y, Desta K. Prevalence of bacterial urinary tract infection, associated risk factors, and antimicrobial resistance pattern in Addis Ababa, Ethiopia: a cross-sectional study. Infect Drug Resist. 2023;Volume 16:3041–3050. doi:10.2147/IDR.S402279

    47. Irenge CA, Bikioli F, Mulashe PB, et al. Profile of Multidrug Resistant Bacteria in Bukavu Hospitals and Antimicrobial Susceptibility to Escherichia coli, Pseudomonas aeruginosa, Proteus mirabilis and Staphylococcus aureus. Adv Microbiol. 2024;14(04):209–225. doi:10.4236/aim.2024.144015

    48. Alhazmi AH, Alameer KM, Abuageelah BM, et al. Epidemiology and antimicrobial resistance patterns of urinary tract infections: a cross-sectional study from Southwestern Saudi Arabia. Medicina. 2023;59(8):1411. doi:10.3390/medicina59081411

    49. Kutyabami P, Munanura EI, Kalidi R, et al. Evaluation of the Clinical Use of Ceftriaxone among In-Patients in Selected Health Facilities in Uganda. Antibiotics. 2021;10(7):779. doi:10.3390/antibiotics10070779

    50. Kizito M, Lalitha R, Kajumbula H, Ssenyonga R, Muyanja D, Byakika-Kibwika P. Antibiotic prevalence study and factors influencing prescription of WHO watch category antibiotic ceftriaxone in a tertiary care private not for profit hospital in Uganda. Antibiotics. 2021;10(10):1167. doi:10.3390/antibiotics10101167

    51. Matanovic SM, Bergman U, Vukovic D, Wettermark B, Vlahovic-Palcevski V. Impact of restricted amoxicillin/clavulanic acid use on Escherichia coli resistance—antibiotic DU90% profiles with bacterial resistance rates: a visual presentation. Int J Antimicrob Agents. 2010;36(4):369–373. doi:10.1016/j.ijantimicag.2010.05.019

    52. Faine BA, Rech MA, Vakkalanka P, et al. High prevalence of fluoroquinolone‐resistant UTI among US emergency department patients diagnosed with urinary tract infection, 2018–2020. Acad Emergency Med. 2022;29(9):1096–1105. doi:10.1111/acem.14545

    53. Maldonado-Barragán A, Mshana SE, Keenan K, et al. Predominance of multidrug-resistant bacteria causing urinary tract infections among symptomatic patients in East Africa: a call for action. JAC-Antimicrob Resist. 2024;6(1):dlae019. doi:10.1093/jacamr/dlae019

    54. Joshi DN, Shenoy B, Bhavana M, Adhikary R, Shamarao S, Mahalingam A. Prevalence of Carbapenem-Resistant Enterobacteriaceae and the Genes Responsible for Carbapenemase Production in a Tertiary Care Hospital in South India. EMJ. 2023. doi:10.33590/emj/10300425

    55. Mouanga-Ndzime Y, Bisseye C, Longo-Pendy N-M, Bignoumba M, Dikoumba A-C, Onanga R. Trends in Escherichia coli and Klebsiella pneumoniae Urinary Tract Infections and Antibiotic Resistance over a 5-Year Period in Southeastern Gabon. Antibiotics. 2024;14(1):14. doi:10.3390/antibiotics14010014

    56. Marino A, Maniaci A, Lentini M, et al. The Global Burden of Multidrug-Resistant Bacteria. Epidemiologia. 2025;6(2):21. doi:10.3390/epidemiologia6020021

    Continue Reading

  • Liver cancer crisis looming as prevention lags, says Lancet report

    Liver cancer crisis looming as prevention lags, says Lancet report

    A new report from The Lancet reveals that three out of five liver cancer cases worldwide are linked to preventable risk factors, with obesity-related cases on the rise.

    The analysis, published on 29th July, estimates that over 60% of liver cancers could be avoided by addressing viral hepatitis, excessive alcohol consumption, and metabolic dysfunction-associated steatotic liver disease (MASLD), a condition driven by excess fat in the liver.

    Without urgent intervention, the number of new liver cancer cases is projected to nearly double by 2050, reaching 1.52 million annually, with deaths rising from 760,000 to 1.37 million in the same period.

    The situation is particularly urgent in Africa where liver cancer cases are projected to surge significantly by 2050.

    The Lancet Commission on liver cancer warns that MASLD, particularly its severe form, metabolic dysfunction-associated steatohepatitis (MASH), is the fastest-growing cause of liver cancer, expected to increase by 35% by 2050.

    One of the commissioning authors of the report, Professor Hashem El-Serag, a hepatologist at Baylor College of Medicine, believes liver cancer has a perception issue and isn’t being taken seriously enough.

    Rising obesity rates in the U.S., Europe, and Asia are fuelling this trend, with over 55% of U.S. adults predicted to develop MASLD by 2040.

    The situation is similar in Africa where refined sugars and unhealthy diets are becoming increasingly common.

    In Africa in particular Dr Kalebi believes there is less stigma around obesity and that a “pot belly” has cultural links with wealth and prosperity.

    But he makes a link between diet and poverty and believes this is driving much of the rise.

    He says: “Metabolic liver disease or metabolic symptoms in general is actually becoming a poor man’s disease because the people who are poor are the most affected by poor diet because they are taking unhealthy foods. So unhealthy foods are actually becoming a bigger problem among the poor in the third world, in the rural areas because they are not aware. So somebody takes Fanta and Coke with bread for lunch, which is very unhealthy. It used to be seen that these kinds of foods are a sign of affluence, It used to be seen that a pot belly or weight is a sign of affluence, it is actually the other way round. We need to change that narrative.”

    Meanwhile, cases linked to hepatitis B and C are projected to decline slightly due to vaccination and treatment efforts.

    The Commission calls for global action to curb preventable liver cancer, including expanded hepatitis B vaccination, stricter alcohol policies, and early screening for high-risk groups such as individuals with obesity and diabetes.

    If countries reduce liver cancer incidence by 2-5% annually, up to 17 million cases and 15 million deaths could be prevented by 2050.

    Professor Hashem El-Serag believes cases of Hepatitis B and C are what is causing the increased liver cancer rates in Africa and that screening and vaccination in the region is lagging behind the rest of the world.

    However, he stresses obesity – as the continent becomes increasingly ‘westernised’ is also a major factor.

    “Africa is also not immune to the obesity epidemic. With the progressive westernisation of their lifestyle and their diets. So they might be hit with multiple risk factors. A leftover from the old risk factors that really are not moving fast enough. And the emergence of the new risk factors that are happening as a result of globalization,” he says.

    Additional measures include public awareness campaigns, improved early detection, and better integration of palliative care for patients.

    With liver cancer already the sixth most common cancer and third leading cause of cancer deaths worldwide, experts stress that targeted prevention strategies could significantly alter its trajectory.

    Continue Reading