Category: 8. Health

Biomarkers that could help predict and manage chronic kidney disease (CKD) have been identified in a new study led by the University of Surrey.

The research, funded by Kidney Research UK, and as part of the National Unified Renal Translational Research Enterprise (NURTuRE) CKD study, leveraged data on 2,884 adult CKD patients from across 16 nephrology centres – in which specialists study, prevent, diagnose and treat kidney disease.

The study, which has been published by the Journal of the American Society of Nephrology, examined 21 biomarkers linked to kidney damage, fibrosis, inflammation and cardiovascular disease.

Chronic kidney disease affects millions worldwide and is a major global health issue which is characterized by the gradual loss of kidney function over time, leading to serious health complications.

While established risk factors like age, sex, ethnicity, estimated glomerular filtration rate (eGFR) and urinary albumin-to-creatinine ratio (UACR) remain strong predictors, the research found that a combination of biomarkers, namely sTNFR1, sCD40, UCOL1A1, could be key for predicting kidney failure. A different combination of biomarkers including hs-cTnT, NT-proBNP, suPAR were instead comparably good at predicting all-cause mortality (death from any cause).

Our research shows that these novel biomarker models offer predictive results comparable to established methods, but the key finding here is that we can use these biomarkers to understand the underlying mechanisms of disease progression, potentially paving the way to more personalized treatments and medicines for CKD patients.”

Dr. Tony Onoja, lead author of the study and Research Fellow, University of Surrey

The biomarker signatures identified provide insights into the underlying disease mechanism and associated processes linked to CKD’s progression, including extracellular matrix accumulation, chronic inflammation, and cardiovascular stress. These insights could inform the development of new targeted therapies and more personalized treatments.

Professor Nophar Geifman, senior author of the study and Professor of Health and Biomedical Informatics at the University of Surrey said:

“Our study demonstrates that specific biomarkers can offer a more nuanced understanding of a patient’s disease progression and mortality risk and the disease’s ongoing activity. Further research is needed to evaluate how these biomarkers change in response to current treatments, and their clinical utility in patient care and in personalized medicine.”

Researchers have found why common cuff-based blood pressure readings are inaccurate and how they might be improved, which could improve health outcomes for patients.

High blood pressure, or hypertension, is the top risk factor for premature death, associated with heart disease, strokes and heart attacks. However, inaccuracies in the most common form of blood pressure measurement mean that as many as 30% of cases of high blood pressure could be missed.

The researchers, from the University of Cambridge, built an experimental model that explained the physics behind these inaccuracies and provided a better understanding of the mechanics of cuff-based blood pressure readings.

The researchers say that some straightforward changes, which don’t necessarily involve replacing standard cuff-based measurement, could lead to more accurate blood pressure readings and better results for patients. Their results are reported in the journal PNAS Nexus.

Anyone who has ever had their blood pressure taken will be familiar with the cuff-based method. This type of measurement, also known as the auscultatory method, relies on inflating a cuff around the upper arm to the point where it cuts off blood flow to the lower arm, and then a clinician listens for tapping sounds in the arm through a stethoscope while the cuff is slowly deflated.

Blood pressure is inferred from readings taken from a pressure gauge attached to the deflating cuff. Blood pressure is given as two separate numbers: a maximum (systolic) and a minimum (diastolic) pressure. A blood pressure reading of 120/80 is considered ‘ideal’.

The auscultatory method is the gold standard, but it overestimates diastolic pressure, while systolic pressure is underestimated. We have a good understanding of why diastolic pressure is overestimated, but why systolic pressure is underestimated has been a bit of a mystery.”

Kate Bassil, co-author from Cambridge’s Department of Engineering

“Pretty much every clinician knows blood pressure readings are sometimes wrong, but no one could explain why they are being underestimated – there’s a real gap in understanding,” said co-author Professor Anurag Agarwal, also from Cambridge’s Department of Engineering.

Previous non-clinical studies into measurement inaccuracy used rubber tubes that did not fully replicate how arteries collapse under cuff pressure, which masked the underestimation effect.

The researchers built a simplified physical model to isolate and study the effects of downstream blood pressure – the blood pressure in the part of the arm below the cuff. When the cuff is inflated and blood flow to the lower arm is cut off, it creates a very low downstream pressure. By reproducing this condition in their experimental rig, they determined this pressure difference causes the artery to stay closed for longer while the cuff deflates, delaying the reopening and leading to an underestimation of blood pressure.

This physical mechanism – the delayed reopening due to low downstream pressure – is the likely cause of underestimation, a previously unidentified factor. “We are currently not adjusting for this error when diagnosing or prescribing treatments, which has been estimated to lead to as many as 30% of cases of systolic hypertension being missed,” said Bassil.

Instead of the rubber tubes used in earlier physical models of arteries, the Cambridge researchers used tubes that lay flat when deflated and fully close when the cuff pressure is inflated, the key condition for reproducing the low downstream pressure observed in the body.

The researchers say that there is a range of potential solutions to this underestimation, which include raising the arm in advance of measurement, potentially producing a predictable downstream pressure and therefore predictable underestimation. This change doesn’t require new devices, just a modified protocol.

“You might not even need new devices, just changing how the measurement is done could make it more accurate,” said Agarwal.

However, if new devices for monitoring blood pressure are developed, they might ask for additional inputs which correlate with downstream pressure, to adjust what the ‘ideal’ readings might be for each individual. These may include age, BMI, or tissue characteristics.

The researchers are hoping to secure funding for clinical trials to test their findings in patients, and are looking for industrial or research partners to help refine their calibration models and validate the effect in diverse populations. Collaboration with clinicians will also be essential to implement changes to clinical practice.

The research was supported by the Engineering and Physical Sciences Research Council (EPSRC), part of UK Research and Innovation (UKRI).

Immunizations are the best way to prevent diseases and can often work with the body’s natural defenses to build better protection, according to the World Health Organization (WHO). There are approximately 30 different vaccines, which target diseases such as cervical cancer, COVID-19, diphtheria, hepatitis B, influenza, measles, mpox, mumps, pneumonia, polio, rabies, and yellow fever. According to WHO, immunizations can prevent 3.5 million to 5 million deaths every year.¹

Although vaccines have proven successful, vaccine information is still shared on social media, which can shape behaviors. Evidence-based interventions are important to reduce the effects of misinformation, and efforts can be led by pharmacists.

“When it comes to community pharmacy, it is the most accessible location to get vaccination,” Hashim Zaibak, PharmD, CEO of Hayat Pharmacy, said.² “You can walk into a community pharmacy and get vaccinated 7 days a week. You don’t have to make an appointment; community pharmacies are open on weekends, late in the evening. It’s a lot more convenient for people who are busy to come and get the vaccine in a community pharmacy versus getting it in a clinic or by appointment.”

During the COVID-19 pandemic, there was a rise of vaccine hesitancy due to the use of social media, which became the epicenter of misinformation, according to authors of a study published in the BMJ. Although standard approaches to encourage vaccination included mandatory vaccination and regulation for health care professionals, more contemporary strategies included debunking misinformation via social media.³

“With the COVID-19 pandemic, we saw a lot of misinformation and myths around the COVID-19 vaccines,” Lauren Angelo, PharmD, associate dean for academic affairs at Rosalind Franklin University, said.⁴ “There are some who think getting natural immunity from the disease is better than getting the vaccine. Parents are still concerned that the vaccines will overwhelm their [children’s] immune systems. We know that’s not true.”

Pharmacists can play an important role in vaccination as well as dispelling vaccine misinformation. In a study published in the Journal of the American Pharmacists Association, the authors stated that pharmacists, because of their accessibility and location, are one of the most trusted sources for patients who need health information and care. Further, pharmacists are in a prime position to listen to patients without judgement and offer honest information to address patient concerns.^5,6

“I’m encouraging patients to talk to trusted health care professionals and to not get their advice from social media or the internet or other strangers, focusing on the fact that vaccines have been studied before, during, and after FDA approval,” Laura Knockel, PharmD, BCACP, clinical associate professor at Iowa College of Pharmacy, said.⁷ “They’re more rigorously tested than any other medications because we give them to healthy people, so we have a very, very low tolerance for risk for adverse events. So just really focusing on the fact that our vaccine safety program in the US is very robust even after FDA approval, and so hopefully that will help override some of the conflicting messages that they may be hearing.”

READ MORE: Immunization Resource Center

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REFERENCES

1. World Health Organization. Vaccines and immunization. Accessed August 4, 2025. https://www.who.int/health-topics/vaccines-and-immunization#tab=tab_1

2. Nowosielski B, Zaibak H. Q&A: community pharmacies help increase immunization convenience, uptake. Drug Topics. August 3, 2025. Accessed August 4, 2025. https://www.drugtopics.com/view/community-pharmacies-help-increase-immunization-convenience-uptake

3. Ruggeri K, Vanderslott S, Yamada Y, et al. Behavioural interventions to reduce vaccine hesitancy driven by misinformation on social media. BMJ. 2024;384:e076542. Published 2024 Jan 16. doi:10.1136/bmj-2023-076542

4. Gallagher A, Angelo L. Q&A: Pharmacists Can Overcome Vaccine Hesitancy Through Trust and Communication | APhA 2025. Drug Topics. April 1, 2025. Accessed August 5, 2025. https://www.drugtopics.com/view/q-a-pharmacists-can-overcome-vaccine-hesitancy-through-trust-and-communication-apha-2025

5. Shen AK, Tan ASL. Trust, influence, and community: Why pharmacists and pharmacies are central for addressing vaccine hesitancy. J Am Pharm Assoc (2003). 2022;62(1):305-308. doi:10.1016/j.japh.2021.10.001

6. Accetta RC. The Role of the Pharmacist in Addressing Vaccine Misinformation. Caring for the Ages. August 2025. Accessed August 4, 2025. https://www.caringfortheages.com/article/S1526-4114(25)00166-0/fulltext

7. Gallagher A, Knockel L. Q&A: Expert Highlights Importance of Trusted Sources for Vaccine Information. Drug Topics. July 6, 2025. Accessed August 5, 2025. https://www.drugtopics.com/view/q-a-expert-highlights-importance-of-trusted-sources-for-vaccine-information

Want to ease your sleep apnea and get a better night’s sleep?

Blow through a conch shell, a new pilot clinical trial says.

Regularly blowing through a conch shell for six months, like Disney princess Moana or Anchorman legend Ron Burgundy, significantly improved sleep among a small group of people with sleep apnea.

Patients blowing a conch slept better, felt more alert during the day and had fewer breathing interruptions at night, researchers reported.

Conch blowing might prove a reasonable alternative to using a continuous positive air pressure machine, in which a face mask blows air to keep a patient’s airways open while sleeping, said lead researcher Dr. Krishna Sharma, director and head of pulmonology at the Eternal Heart Care Center and Research Institute in Jaipur, India.

While CPAP is the gold standard treatment for sleep apnea, many patients find it uncomfortable and noisy.

“For people living with obstructive sleep apnea, especially those who find CPAP uncomfortable, unaffordable, or inaccessible, our findings offer a promising alternative,” Sharma said in a news release. “[Conch] blowing is a simple low-cost, breathing technique that could help improve sleep and reduce symptoms without the need for machines or medication.”

Blowing a conch shell, also called shankh blowing, has been part of Indian culture for thousands of years, he explained.

“In my clinical practice, several patients reported feeling more rested and experiencing fewer symptoms after regularly practicing shankh blowing – a traditional yogic breathing exercise involving exhaling through a conch shell,” Sharma said.

Based on these anecdotes, Sharma and colleagues designed a small clinical trial to see if the simple, ancient practice might help people with sleep apnea.

In sleep apnea, a person stops breathing repeatedly during the night because their airway collapses, causing them to wake. Sleep apnea patients often snore loudly, and have a higher risk of high blood pressure, heart disease and stroke.

Researchers think conch blowing might help by exercising the muscles of the airway.

“The way the shankh is blown is quite distinctive. It involves a deep inhalation followed by a forceful, sustained exhalation through tightly pursed lips,” Sharma said.

“This action creates strong vibrations and airflow resistance, which likely strengthens the muscles of the upper airway, including the throat and soft palate — areas that often collapse during sleep in people with obstructive sleep apnea,” he continued. “The shankh’s unique spiraling structure may also contribute to specific acoustic and mechanical effects that further stimulate and tone these muscles.”

Researchers recruited 30 people with moderate sleep apnea and randomly assigned 16 to practice blowing through a conch shell. The other 14 were taught a deep breathing exercise.

All participants were encouraged to practice either conch blowing or deep breathing for a minimum of 15 minutes a day, five days a week.

After six months, the people armed with conch shells were 34% less sleepy during the daytime than those practicing deep breathing, results show. They also reported better sleep.

Sleep lab tests showed that those blowing a conch shell experienced on average four to five fewer episodes during the night in which they breathing stopped during sleep, as well as higher oxygen levels during sleep.

“This is a small study, but we are now planning a larger trial involving several hospitals,” Sharma said. “This next phase will allow us to validate and expand on our findings in a broader, more diverse population and assess how shankh blowing performs over longer periods.”

Future studies also will test to see how conch blowing affects the muscle tone of the airways, and compare the practice directly against standard treatments like CPAP, Sharma said.

Sophia Schiza, head of the European Respiratory Society’s group on sleep-disordered breathing, reviewed the findings. She said conch blowing might fill a need for more treatments for sleep apnea.

“This is an intriguing study that shows the ancient practice of shankh blowing could potentially offer an obstructive sleep apnea treatment for selected patients by targeting muscles training,” Schiza said in a news release.

“A larger study will help provide more evidence for this intervention which could be of benefit as a treatment option or in combination with other treatments in selected obstructive sleep apnea patients,” added Schiza, a professor of pulmonology and sleep disorders at the University of Crete in Greece.

The new study appears in the journal ERJ Open Research.

More information

Johns Hopkins Medicine has more on sleep apnea.

Copyright © 2025 HealthDay. All rights reserved.

A new study from the Gray Faculty of Medical and Health Sciences at Tel Aviv University may mark a breakthrough in the treatment of Eosinophilic Esophagitis (EoE) — a chronic inflammatory disease of the esophagus caused by food allergies. 

EoE leads to difficulty swallowing, chest and abdominal pain, and even growth delays in children. Its prevalence has been steadily increasing over the past decade in Israel and the Western world. In this new study, researchers identified the protein TSLP as a catalyst in the disease’s development, and found that neutralizing it may lead to significant relief of symptoms.

The study, led by Prof. Ariel Munitz and doctoral student Anish Dsilva from the Gray Faculty of Medical and Health Sciences, was conducted in collaboration with Dr. Chen Varol of Ichilov Hospital, Prof. Marc Rothenberg of Cincinnati Children’s Hospital, and the pharmaceutical company AstraZeneca. The research was supported by grants from the Israel Science Foundation, the US-Israel Binational Science Foundation, and the Azrieli Foundation Canada–Israel. The article was published in Allergy, the leading journal in clinical immunology.

Prof. Munitz explains: “Eosinophilic Esophagitis, or EoE, is a type of food allergy. It is a chronic inflammation of the esophagus caused by an abnormal immune response to food — mainly milk, eggs, wheat, nuts, fish, and more. The disease is characterized by an accumulation of eosinophils, a type of white blood cell that is not typically present in a healthy esophagus. EoE is often associated with other allergic conditions such as asthma and atopic dermatitis. It causes difficulty swallowing, food getting stuck in the esophagus, chest and abdominal pain, and growth delays in children. Current treatments require restrictive diets, and in severe cases, patients rely on essential amino acid formulas. Over the past decade, there has been a concerning rise in the prevalence of EoE worldwide, including in Israel. We are studying the disease in depth to understand the involvement of various immune system components in its progression. These components may serve as targets for future treatment for this disease, and for other allergic disorders as well.”

A previous study from Prof. Munitz’s lab, also published in Allergy, presented an experimental model that closely mimics the course and symptoms of EoE in humans. As a direct continuation of that study, the researchers now focused on a specific aspect of the disease, aiming to understand the role of epithelial cells. Prof. Munitz elaborates: “Epithelial cells form a protective outer layer that prevents foreign bodies from entering organs, including the digestive and respiratory systems. In allergic conditions, epithelial cells release various substances in response to encountering an allergen, and these substances trigger the chain of events that initiate the inflammatory process we experience as an allergy attack.”

The researchers found that epithelial cells in the esophagus of the EoE experimental model secreted high levels of two proteins: IL-33 and TSLP. They also discovered that the esophageal tissue in the mouse models contained a variety of immune cells that express receptors for both proteins. The fact that these two proteins are released in EoE, and that there are tissue cells with receptors that can respond to them, indicates that these are active proteins capable of causing the onset of the disease.

The researchers then sought to understand the division of roles between these two proteins in the disease: does each contribute differently, or do they act together? They believed that answering these questions would clarify the mechanisms that trigger EoE, and reveal which could be blocked as a treatment strategy. To this end, they used genetic engineering tools to create experimental models of the disease in which one of the proteins was absent.

The findings were unequivocal: the absence of the IL-33 protein did not significantly change the course of the disease. However, in the absence of TSLP, there was a significant improvement in EoE symptoms — to the point where the disease did not develop at all. Furthermore, a series of experiments in which the researchers neutralized TSLP with an antibody led to a significant reduction in symptoms. Further investigation using sequencing technologies and bioinformatic analyses revealed that TSLP functions as a key regulator of the disease. Based on these findings, the researchers concluded that the TSLP protein could serve as a target for new treatments for chronic esophageal inflammation (EoE).

Munitz concludes: “In this study, we found that the TSLP protein is a central player in EoE — a disease that causes significant suffering and is becoming increasingly prevalent worldwide. We know that pharmaceutical companies are currently developing a variety of antibodies targeting disease-causing proteins, under the broad category of biological therapies, including antibodies against TSLP. We believe these antibodies could serve as an effective treatment for EoE.”

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Published on
12/08/2025 – 16:57 GMT+2

A simple voice recording could one day help doctors spot early signs of throat cancer, according to new research.

In a study published in Frontiers in Digital Health, scientists found that artificial intelligence (AI) could potentially detect abnormal growths on the vocal cords, from benign nodules to early-stage laryngeal cancer, by analysing short voice recordings.

The findings could support efforts to find an easier, faster way to diagnose cancerous lesions on the vocal cords, also known as folds.

“With this dataset we could use vocal biomarkers to distinguish voices from patients with vocal fold lesions from those without such lesions,” said Phillip Jenkins, the study’s lead author and a postdoctoral researcher in clinical informatics at Oregon Health and Science University in the United States.

Why early detection of throat cancer matters

Cancer of the voice box, or larynx, affects more than a million people worldwide and kills roughly 100,000 every year. It is the 20th most common cancer in the world.

Smoking, alcohol use, and certain strains of HPV (human papillomavirus) are key risk factors, and survival rates vary from around 35 per cent to 90 per cent depending on how early the disease is diagnosed, according to Cancer Research UK.

One of the most common warning signs for laryngeal cancer is hoarseness or changes in the voice that last more than three weeks. Other symptoms include a persistent sore throat or cough, difficulty or pain when swallowing, a lump in the neck or throat, and ear pain.

Early detection of laryngeal cancer is crucial because it significantly improves survival rates and treatment outcomes.

Yet current diagnostic methods, including nasal endoscopies and biopsies, are invasive, uncomfortable, and often slow, requiring specialist equipment and expertise that many patients struggle to access quickly.

Developing a simple tool to flag early signs of vocal fold abnormalities through a quick voice recording could transform how throat cancer is detected – making it faster, more affordable and accessible to a wider population.

The next steps for AI-driven diagnosis

The research team examined about 12,500 voice recordings from 306 people across North America. They looked for subtle acoustic patterns, such as changes in pitch, loudness, and harmonic clarity.

The team identified clear differences for men in the harmonic-to-noise ratio and pitch between those with healthy voices, benign lesions, and cancer. No significant patterns were found in women, but the researchers say this may be due to the smaller dataset.

Jenkins said that the results indicate large datasets “could soon help make our voice a practical biomarker for cancer risk in clinical care”.

The next step is to train AI models on larger, professionally labelled datasets and test them in clinical settings. The team would also need to test the system to make sure it works well for both men and women, he said.

“Voice-based health tools are already being piloted,” Jenkins said.

“Building on our findings, I estimate that with larger datasets and clinical validation, similar tools to detect vocal fold lesions might enter pilot testing in the next couple of years”.

Background

Chronic obstructive pulmonary disease (COPD) is a multifactorial lung condition driven by various pathogenic mechanisms, characterized by persistent respiratory symptoms and airflow obstruction.^1,2 The clinical diagnostic criterion for COPD is a forced expiratory volume in 1 second (FEV1) to forced vital capacity (FVC) ratio of less than 0.7, reflecting the proportion of air forcefully exhaled in one second relative to the total volume exhaled after maximal inhalation. The key pathological features of COPD include chronic bronchitis and emphysema. Globally, COPD ranks among the top three causes of death. In 2012, it was responsible for over 3 million deaths, accounting for 6% of all global fatalities, imposing a substantial burden on clinical care and healthcare resources.^3–5 Although COPD remains a major public health challenge, it is both preventable and manageable with appropriate interventions.

The onset of COPD is often considered to be related to multiple factors. Studies have shown that abnormal inflammatory responses are strongly associated with the development of COPD, and these responses are often chronic and destructive. Over the past decade, research has increasingly highlighted the close link between COPD and inflammation.^6,7 Several factors associated with COPD, including dietary patterns, exposure to cigarette smoke, and infections, have been shown to significantly influence inflammation levels.^8,9 Chronic systemic inflammation is a nonspecific defense mechanism of the body in response to external stimuli or internal injury, involving the activation of various cellular and molecular processes. Prolonged inflammation can accelerate the progression of COPD.¹⁰ The systemic inflammation response index (SIRI) is an emerging and promising inflammatory biomarker, calculated based on neutrophil, monocyte, and lymphocyte counts. It serves as an indicator of the body’s systemic inflammatory status and offers a novel perspective for evaluating inflammatory responses. Increasing evidence has demonstrated associations between elevated SIRI levels and various inflammation-related diseases, including osteoarthritis, pancreatic cancer, esophageal cancer, and heart failure. Notably, higher SIRI levels have been linked to increased mortality in patients with heart failure and elevated all-cause mortality among individuals with diabetes. However, the relationship between SIRI and the development of COPD has not yet been fully elucidated.^11–15

The National Health and Nutrition Examination Survey (NHANES) is a comprehensive survey conducted in the United States, utilizing complex, multi-stage, and probability sampling methods to collect nutritional and health information about the population. Through the NHANES database, an increasing number of factors related to human health and diseases have been identified. This cross-sectional study aims to investigate the potential association between COPD and the inflammatory marker SIRI in individuals aged over 40 within the US population. All participants were registered through the NHANES between 2013 and 2018.

Materials and Methods

Data Sources

This is a cross-sectional analysis utilizing data from the National Health and Nutrition Examination Survey (NHANES) (https://www.cdc.gov/nchs/nhanes). NHANES is a national survey conducted by the National Center for Health Statistics (NCHS) of the Centers for Disease Control and Prevention (CDC). It combines interviews and physical examinations. NHANES uses a complex, multi-stage design to collect and analyze data that reflects the non-institutionalized US population. The execution of the study involves two key components: a comprehensive interview conducted at participants’ homes and detailed health examinations carried out at mobile examination centers. Both components of the study are carefully conducted by skilled and certified researchers.

Study Design and Participants

The detailed participant selection process is illustrated in Figure 1. This study analyzed publicly available NHANES data from the 2013–2018 cycles. Detailed information regarding the NHANES sampling design, study procedures, and survey protocols can be accessed on the official website of the National Center for Health Statistics (NCHS). The inclusion criteria for this study were as follows: 1) Age > 40 years; 2) Clear diagnosis of COPD; 3) Complete data on neutrophils, monocytes, and lymphocytes; 4) Exclusion of incomplete information on other essential data.

Figure 1 Flowchart of Patient Inclusion and Exclusion in NHANES 2013–2018.

Calculation of SIRI

Since inflammation levels have a significant impact on COPD, we used SIRI to comprehensively assess its effect on COPD. The calculation of SIRI is as follows: SIRI = N * M / L, where N, M, and L represent the counts of neutrophils, monocytes, and lymphocytes in the peripheral blood after preprocessing, respectively. Based on SIRI levels, participants were divided into three groups according to the 3rd quartiles: Quartile 1 (Q1), Quartile 2 (Q2), and Quartile 3 (Q3).

Inclusion of Covariates

Based on standardized questionnaire surveys, we extracted participants’ sociodemographic characteristics, including age, gender, race, education level, poverty-to-income ratio (PIR), smoking status, obesity, use of diabetic medications or insulin, and hypertension. Additionally, laboratory measurements such as monocyte count, neutrophil count, and lymphocyte count were collected. Missing data for these covariates were excluded from this study. Race/ethnicity was categorized as non-Hispanic White, non-Hispanic Black, Mexican American, and other races. Marital status was divided into married and unmarried. Education level was classified as less than high school and high school or higher. Household income was categorized based on the family PIR into two levels: poor and non-poor. Smoking status was classified as current smoker and non-smoker. Obesity status was categorized as obese and non-obese. Diabetes was categorized as diabetic and non-diabetic.

We obtained personal interview data on the history of COPD from participants aged over 40 in the NHANES, covering the period from 2013 to 2018. The questionnaire item used to determine the history of COPD was: “Has a doctor or other health professional ever told {you/SP} that {you/s/he} had COPD?” (MCQ160o).

Statistical Analysis

In descriptive statistics, continuous variables are expressed as means (± SD), while categorical variables are presented as frequencies or percentages (n, %). When analyzing baseline characteristics, continuous variables with a normal distribution were analyzed using independent sample t-tests, non-normally distributed continuous variables were analyzed using the Wilcoxon rank-sum test, and categorical variables were analyzed using the chi-square test. Additionally, appropriate weighted data were used in the analysis based on the specific situation.

We analyzed the association between SIRI and COPD using multivariable logistic regression. To control for confounding factors, we applied three multivariable logistic regression models: Model 1: Unadjusted; Model 2: Adjusted for age, sex, and race; Model 3: adjusted for all covariates. To investigate the potential non-linear relationship between SIRI and COPD, we performed restricted cubic spline (RCS) analysis. The reference point was set at 1.08, and adjustments were made for age, gender, race, education level, marital status, smoking status, body mass index, hypertension, diabetes, blood cell counts, and other factors. In addition, we conducted subgroup analyses by stratifying participants based on age, gender, race, marital status, smoking status, obesity, and history of hypertension. We also evaluated potential interactions across these subgroups. All analyses were conducted using the statistical software package R 4.4.2, and p < 0.05 was considered statistically significant.

Results

Baseline Analysis of Study Participants Based on COPD Status

The results show that patients with COPD have distinct clinical characteristics, including higher age, smoking rates, metabolic comorbidity burden, and systemic inflammation levels. These factors may collectively contribute to the progression and poor prognosis of COPD. A total of 10,273 participants were included in this study, 595 participants were diagnosed with COPD, and 9678 were diagnosed with non-COPD. In Table 1, there were 4940 males (47.0%) and 5333 females (53.0%). Among the participants, 6743 (70.4%) were aged 41–65 years, and 3530 (29.6%) were over 65 years old. The majority of participants were non-Hispanic White (4004 participants, 69.6%). Significant differences were observed in all baseline variables except for gender, lipids, and BMI (p < 0.05). Among participants diagnosed with COPD, the proportion of smokers was higher. Additionally, the prevalence of metabolic disorders such as hyperlipidemia and hypertension was also higher in this group. Furthermore, the proportion of participants with SIRI in the third quartile was significantly higher compared to those in the first quartile among those diagnosed with COPD.

Table 1 Baseline Characteristics of Study Population

Correlation Between Serum SIRI Levels and COPD

Multivariate logistic regression analysis, adjusted for various confounding variables, showed a positive correlation between SIRI and the prevalence of COPD in all three models. Notably, participants in the highest third (Q3) of SIRI levels had a significantly higher risk of COPD compared to those in the lowest third (Q1). The trends observed in all three models were statistically significant (p < 0.05) (Table 2).

Table 2 Association Between the SIRI and COPD

RCS Analysis

We used RCS curves to investigate whether there is a linear relationship between SIRI and the prevalence of COPD. The results (Figure 2) showed a non-linear correlation between the two variables (P < 0.05). As SIRI levels increased, the risk of COPD gradually rose, suggesting a positive association between systemic inflammation and COPD risk. However, this risk did not continue to rise indefinitely at very high levels of SIRI.

Figure 2 The restricted cubic spline model revealed a significant dose–response relationship between SIRI and COPD (P < 0.05).

Subgroup Analysis

The results of the subgroup analysis (Figure 3) showed that when stratified by age, gender, race, marital status, smoking, obesity, and hypertension, SIRI remained positively correlated with COPD (OR > 1). The results indicated that the association between SIRI and COPD was more pronounced among individuals aged over 65 years. This association also appeared stronger in males compared to females, and was notably enhanced in individuals with elevated blood pressure. Furthermore, interaction tests revealed no significant interactions between SIRI and COPD across subgroups (P > 0.05), suggesting that the positive association remained consistent and did not differ significantly among the various subpopulations.

Figure 3 Subgroup analysis for the association between SIRI and COPD.

Discussion

Until now, there has been a lack of research on the correlation between serum inflammatory marker SIRI and the incidence of COPD. In our current study, we observed a positive correlation between serum SIRI levels and the prevalence of COPD. Higher serum SIRI levels were associated with an increased risk of COPD, and this relationship remained consistent even after adjusting for covariates.

The pathogenesis of COPD remains unclear. Previous studies suggest that its pathogenesis primarily involves inflammation, oxidative stress, and an imbalance between proteases and antiproteases.¹⁶ When the immune system is compromised and the body is unable to compensate, it eventually leads to small airway damage and emphysema. Inflammation is a key factor in the onset and progression of COPD. Airway inflammation in COPD is primarily characterized by the infiltration and proliferation of inflammatory cells, such as neutrophils, lymphocytes, and monocytes/macrophages, which migrate into the airways and lung tissues. These cells can be detected in sputum and bronchoalveolar lavage fluid. The increase in inflammatory cells is often triggered by the activation of cytokines and mediators released by airway epithelial cells in response to inhaled cigarette smoke and particulate matter. Numerous inflammatory mediators, including free radicals, chemokines, cytokines, and growth factors, contribute to the development and progression of COPD.^17–19 A study found²⁰ that the levels of the Neutrophil-to-Lymphocyte Ratio (NLR) in patients with acute exacerbation of COPD were positively correlated with poor outcomes, including mortality, the need for mechanical ventilation, and transfer to the intensive care unit. Another cross-sectional study involving 10,364 participants found²¹ that Systemic Immune-Inflammation Index (SII) was positively correlated with the risk of COPD and showed a non-linear relationship. Compared to composite inflammatory markers like NLR and SII, SIRI may offer distinct advantages in assessing COPD. By incorporating monocytic parameters, SIRI provides a more comprehensive reflection of the chronic inflammatory response and tissue remodeling processes characteristic of COPD. Unlike acute-phase inflammatory proteins such as C-reactive protein (CRP), SIRI, based on the ratio of neutrophils, monocytes, and lymphocytes, is less affected by confounding factors like acute infections, offering better stability and reproducibility in the results. These features make SIRI a promising biomarker for evaluating the inflammatory status of COPD.

The SIRI is calculated based on the number of neutrophils, monocytes, and lymphocytes, reflecting the relative proportion of these three cell types. Neutrophils can be excessively activated in the airways of COPD patients, releasing inflammatory mediators such as interleukin-8, which attract more neutrophils to the affected areas and initiate oxidative stress by releasing oxygen free radicals.²² Therefore, neutrophils are considered key cells in the pathogenesis of COPD. A reduction in lymphocytes is a marker of stress, which can lead to the destruction of alveoli in COPD patients. CD8⁺ cells produce pro-inflammatory cytokines, including interleukin-2(IL-2), interferon-gamma, and TNF-alpha (TNF-α). These cytokines are increased in COPD patients and recruit other inflammatory cells.²³ When the counts of neutrophils and monocytes increase, or when the lymphocyte count decreases, SIRI typically rises. A 20-year comprehensive follow-up study involving 2656 rheumatoid arthritis (RA) patients found²⁴ that serum SIRI was non-linearly positively correlated with all-cause mortality and cardiovascular mortality in RA patients. This correlation was especially prominent in female patients and those with a high BMI. Another study on the relationship between SIRI and the risk of kidney stones found²⁵ a significant positive correlation between SIRI and kidney stones. As SIRI levels increased, the risk of kidney stones gradually rose. Based on the existing literature evidence, we can tentatively infer that SIRI may be an effective biomarker for predicting the development of inflammation-related diseases. It is worth noting that although SIRI has been the subject of research in many different fields, there is still limited research exploring its relationship with COPD.

This study found a significant positive correlation between serum SIRI levels and the prevalence of COPD. In this study, SIRI was divided into three groups: Q1, Q2, and Q3. In all three models adjusted for potential confounding factors, the Q3 group showed a higher prevalence compared to the Q1 group. Subgroup analysis results indicated that this association was consistent across different populations. The study also found a non-linear positive correlation between SIRI and COPD, suggesting that high SIRI levels may be an independent risk factor for COPD. This prospective cohort study involving 10,273 participants found that an increase in SIRI was significantly associated with a higher prevalence of COPD. Based on previous research, the potential mechanism behind this phenomenon may be that an increase in neutrophils in the blood triggers a higher probability of chronic inflammation in the lungs, while the decrease in lymphocytes leads to reduced lung immune function, ultimately resulting in a higher prevalence of COPD.

The findings of this study may provide some insights into the screening and management of COPD. First, SIRI can be derived from routine blood count data, eliminating the need for specialized equipment or additional costs, making it well-suited for primary healthcare settings. Second, for high-risk populations (smokers + age > 40), SIRI could be considered as part of routine screening, serving as an inflammatory monitoring tool for the comprehensive management of COPD. However, several limitations should be acknowledged. First, the NHANES population represents only the US population and may not be applicable to other populations. Second, our study focused on individuals above 40 years old, excluding children and adolescents. Third, due to the cross-sectional design of NHANES, inferring a causal relationship between SIRI and COPD is limited. Fourth, COPD diagnosis relies on self-report, and some important variables, such as lung function data (FEV1%, FVC%, FEV1/FVC), were not included in the analysis, which may introduce bias into the results. Fifth, due to the limitations of the dataset, we were unable to conduct parallel analyses involving NLR and SII. This represents an important area for future research.

Conclusion

In this cross-sectional study based on the NHANES database, we observed that elevated serum SIRI levels were significantly associated with an increased risk of COPD, indicating that SIRI may serve as a potential novel inflammatory marker for predicting the development of COPD. However, due to the study’s observational design, the causal relationship between SIRI and the onset or progression of COPD remains to be confirmed in future prospective studies.

Abbreviations

COPD, Chronic obstructive pulmonary disease; SIRI, Systemic inflammation response index; NHANES, National Health and Nutrition Examination Survey; RCS, restricted cubic spline; FEV1, forced expiratory volume in 1 second; FVC, forced vital capacity; PIR, poverty-to-income ratio; NCHS, National Center for Health Statistics; CDC, Centers for Disease Control and Prevention; 95% CI, 95% confidence interval; OR, Odds ratio.

Data Sharing Statement

The data supporting the findings of this study were obtained from the National Health and Nutrition Examination Survey (NHANES), which is publicly available at https://www.cdc.gov/nchs/nhanes. In accordance with transparency standards, the corresponding author affirms their commitment to making all data supporting this study’s conclusions available upon reasonable request.

Ethics Approval and Consent to Participate

This study was based on publicly available data from the National Health and Nutrition Examination Survey (NHANES), which is conducted by the National Center for Health Statistics (NCHS). All NHANES participants provided written informed consent, and the survey protocol was approved by the NCHS Research Ethics Review Board. As this study involved only secondary analysis of de-identified data, it was exempt from further review by the Institutional Review Board of The Second Affiliated Hospital of Jiaxing University.

Acknowledgments

The authors would like to express their sincere gratitude to all the participants and staff involved in the NHANES for their invaluable contributions and dedication.

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

The study was supported by Zhejiang Provincial Medical and Health Technology Plan (Grant No. 2021PY029).

Disclosure

The authors declare no competing interests.

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