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The incidence of PAS has significantly increased with rising rates of uterine surgeries; however, cases of placenta percreta complicated by uterointestinal injury remain rare [10, 11]. This case is important due to its unique presentation: the patient sought medical attention 34 days postpartum with fever and vaginal bleeding. Imaging revealed a myometrial mass and surgical exploration confirmed placental penetration through the uterine corpus with associated small bowel injury. Such delayed diagnoses often occur because placental tissue overlying uterine defects obscures signs of intra-abdominal hemorrhage [12], and the insidious clinical manifestations pose significant challenges for early detection.

In this case, neither prenatal nor early postpartum ultrasonography definitively indicated placenta percreta. Although a 1-week postpartum ultrasound revealed no abnormalities, the emergence of fetid vaginal bleeding and elevated hCG levels at 28 days postpartum suggested retained viable placental tissue. Subsequent MRI showed abnormal thickening of the anterior uterine wall and fundus but lacked classic signs of placenta percreta (e.g., disruption of the serosal layer). These observations align with the reported literature: Horgan et al. emphasized the limited sensitivity of ultrasound in detecting small uterine defects obscured by placental tissue [13], while placental obstruction of the defect may restrict intra-abdominal hemorrhage, resulting in atypical imaging manifestations [12]. Similar to a case described by O’Connor et al., the asymptomatic progression in this patient underscores the necessity for increased clinical vigilance in high-risk populations [14].

The patient’s history of surgical myomectomy for multiple uterine smooth muscle tumors is a critical factor underpinning the development and severity of this complication. Uterine surgery, including myomectomy, creates scar tissue that disrupts the normal endometrial-myometrial interface. This scar tissue provides a potential nidus for abnormal placental adherence, significantly elevating the risk for PAS disorders [3, 6]. In this case, the extensive dense adhesions encountered intraoperatively between the uterus, omentum, bowel, and bladder were likely a direct consequence of the prior myomectomy. These adhesions not only complicated the surgical exploration and increased the technical difficulty of the procedure but also potentially masked early signs of placental penetration and facilitated the adherence and subsequent erosion of the placental tissue into the adjacent small bowel. The location and depth of the myomectomy scars likely dictated the site of placental penetration, ultimately leading to the rare but serious bowel injury observed.

Furthermore, the attempted manual placental removal in the context of suspected PAS warrants careful analysis. While retained placenta necessitates clinical intervention, mechanical disruption in PAS-affected uteri may potentially exacerbate myometrial defects [12]. This could facilitate deeper placental penetration into adjacent structures, as suggested by the bowel injury in this case. Current guidelines recommend that in suspected PAS, gentle extraction techniques and avoidance of forceful traction should be prioritized to minimize iatrogenic injury [3, 9].

Placenta percreta can be clinically challenging to be differentiated from retained placental tissue or gestational trophoblastic neoplasia (GTN) due to overlapping manifestations (e.g., vaginal bleeding, infection). In this case, definitive differentiation was achieved through the integration of imaging features, hCG levels, and intraoperative pathological findings, reducing the risk of misdiagnosis. The low hCG level (246 mIU/mL) and its rapid postoperative decline to undetectable levels within one week, combined with the absence of trophoblastic proliferation on histopathology, definitively excluded GTN. Furthermore, the absence of classic uterine rupture symptoms (e.g., sudden-onset abdominal pain) further complicated diagnostic efforts. Consistent with reported cases, Zuckerwise et al. documented that only 3% of PAS-related uterine ruptures are associated with sepsis, mainly associated with delayed diagnosis [15]. The patient’s fever and leukocytosis align with these characteristics, emphasizing the critical need for prompt recognition in atypical presentations.

Intraoperatively, placental penetration through the uterine corpus with dense adhesions to the small bowel resulted in partial bowel wall necrosis. Such intestinal injuries occur in only 2–3% of PAS cases [16], yet Marcellin et al. emphasize that bowel involvement is strongly associated with multi-organ injury and increased risks of postoperative complications [16]. However, bladder invasion is more frequently reported due to its anatomical proximity to the lower uterine segment [3]. In this case, the lesion was successfully addressed via subtotal hysterectomy and partial bowel resection. Postoperative pathology confirmed extensive villous infiltration into the myometrium and small bowel serosal necrosis, highlighting the need for multidisciplinary collaboration in managing complex PAS. Further, extensive adhesions between the uterus, omentum, and bowel—likely attributable to the patient’s previous myomectomy—further corroborate uterine surgical history as a core risk factor for PAS [3, 6].

Although FIGO proposes conservative management for patients without active bleeding [9], this patient underwent definitive surgery due to completed childbearing, severe infection, and anemia. Zuckerwise et al. demonstrated that delayed surgical intervention increases sepsis risk [15]. In this case, timely surgery after infection control prevented clinical deterioration. The management of bowel injury (partial resection with anastomosis) adhered to individualized therapeutic principles: despite limited bowel involvement, localized necrosis suggested that conservative repair might elevate postoperative enterocutaneous fistula risk, justifying aggressive resection as a judicious approach.

Gastrointestinal (GI) cancers, which affect the stomach, colon, pancreas, and other digestive organs, are rising at an alarming rate in younger adults, especially those under 50. Experts are calling it one of the most concerning trends in cancer today.

A new medical review published in the journal JAMA this week has revealed that GI cancers are now the fastest-growing group of cancers among adults under 50 in the US. The review examined over 115 research papers and major global and American cancer databases, making it one of the most detailed reports yet on this topic.

While the exact reason behind the spike still remains unclear, doctors believe a mix of modern lifestyle factors, genetics, and possibly even gut health could be the reason behind the rise.

Sharp rise in GI cancers among the young

Colorectal cancer (which includes colon and rectal cancer) is leading this rise. According to the American Cancer Society, diagnoses of colorectal cancer in Americans under 50 have been increasing by about 2 per cent every year since 2011. Globally, there were around 185,000 early-onset colorectal cancer cases reported in 2022, 21,000 of those in the US alone.

“This really points to the importance of improving screening and early detection,” said Dr. Kimmie Ng, co-author of the review and director of the Young-Onset Colorectal Cancer Center at Dana-Farber Cancer Institute.

Until recently, colon cancer was mostly seen in older adults. But now, even people in their 20s, 30s, and 40s are being diagnosed. One well-known example is actor Chadwick Boseman, who died from colon cancer in 2020 at just 43.

The new review also found rising rates of pancreatic, stomach, and oesophageal cancers in young adults. These cancers are especially dangerous because they’re often caught late, when they’re harder to treat.

What could be causing this?

Doctors still don’t fully understand why GI cancers are increasing in younger people, but they do have some theories.

“The leading theory is that there is no single leading theory,” said Dr. Scott Kopetz, a GI cancer expert from MD Anderson Cancer Center.

Many researchers believe lifestyle choices play a major role. Obesity, lack of exercise, unhealthy diets, smoking, and alcohol use are all known risk factors. One study included in the JAMA review found that women who drank a lot of sugary beverages during their teenage years had a higher risk of developing early-onset colon cancer.

“It’s really what people were doing or exposed to when they were infants, children, or teens that’s probably contributing to their cancer risk as young adults,” said Dr. Ng.

The role of gut health and microbiome

Some experts also suspect that changes in our gut microbiome—the bacteria and organisms that live in our digestive tract—might be connected. The modern diet, increased use of antibiotics, exposure to chemicals, and even microplastics may be affecting gut health in ways scientists are only beginning to understand.

“We don’t yet know what a healthy microbiome truly looks like,” said Dr. John Marshall, chief medical consultant at the Colorectal Cancer Alliance. “But something has clearly changed over the past few decades.”

Genetics may also play a role

The review found that 15 per cent to 30 per cent of young adults with GI cancer carry genetic mutations that may have made them more likely to get cancer early. Because of this, Dr. Ng recommends that anyone under 50 who is diagnosed with a GI cancer should be tested for hereditary conditions.

Still, the majority of young adults who develop these cancers don’t have a strong family history, which suggests that environmental or lifestyle factors are also heavily involved.

Screening is the key

Doctors stress that early detection can save lives. In fact, improved screening is one reason survival rates have gone up in recent years.

For colorectal cancer, screening is recommended starting at age 45 for people at average risk. This usually involves a colonoscopy or a stool test. But for pancreatic, stomach, and oesophageal cancers, there are currently no routine screenings in the US, which makes early detection much harder.

“This is why we need new tools to screen people for these other cancers,” Dr. Ng said.

Younger patients often have worse outcomes

Surprisingly, the review found that younger patients with GI cancers tend to have worse outcomes, even though they often receive more aggressive treatments, including surgery, radiation, and chemotherapy.

One reason may be that doctors don’t usually suspect cancer in younger patients. Common symptoms like stomach pain, constipation, reflux, or fatigue are often brushed off or misdiagnosed.

“My feeling is that we’re catching these cancers later because no one thinks of GI cancers when a young person complains of vague symptoms,” said Dr. Howard Hochster, director of gastrointestinal oncology at Rutgers Cancer Institute.

Even when these cancers are caught early, younger people still seem to have a lower survival rate.

“That makes us wonder—are the cancers that appear in younger people more aggressive or somehow different biologically?” Dr. Ng said.

What you can do

While researchers continue to search for clearer answers, there are a few things young adults can do to reduce their risk:

• Follow a healthy diet rich in fruits, vegetables, and fibre
• Limit processed foods, red meat, alcohol, and sugary drinks
• Stay physically active
• Avoid smoking
• Get screened for colon cancer starting at age 45, or earlier if you have risk factors
• Talk to your doctor about any persistent digestive symptoms, no matter your age

“This isn’t something you can ignore anymore,” said Dr. Ng. “GI cancers are no longer just a concern for older adults. We need to pay attention, ask questions, and take steps to protect ourselves.”

Introduction

The world’s second most fatal disease is stroke, which also accounts for a significant portion of the economic burden.¹ The public health issue that is most significant in low-income and middle-of-the-road countries is stroke. From 1990 to 2019, stroke-related deaths increased by 70%, while the prevalence of strep throats increased 102% and Disability Adjusted Life Years (DALY) rates rose 143% globally.² With a disability rate of 3,382.2 per 100,000 people, Indonesia is one of the countries in Southeast Asia with the highest number of fatalities. The Southeast Asia Region has been separated and categorized according to either geographical or organizational factors. Although the World Health Organization (WHO) covers all countries from east of India to south of China, the SEAR is made up of 11 member nations, including Bangladesh, Bhutan, India and Indonesia. The South East Asian Region (SEAR) makes up 25% of the world’s population and can cover as much as 3% of global land. Presently, this region is responsible for almost half of the stroke burden in developing countries and is also the primary cause of stroke mortality worldwide.^2,3

A significant proportion of stroke survivors are severely disabled, while a high percentage have recurrent strokes. There is a significant gap between the accessibility of stroke care services and the prevalent stroke burden in this locality. The low- and middle-income countries are where SEAR is located, and it does not have sufficient infrastructure or skilled personnel.⁴ The challenges of providing consistent stroke care in this area are not solely due to the aging population, geographical differences, and sociocultural factors. The SEAR has not adequately addressed the issue of stroke in acute care, with low rates of thrombolysis, mechanical thrombectomy, and availability stroke units.^4,5 Rehabilitation professionals’ inability to provide services and their lack of knowledge and skills are causing significant neglect towards rehabilitation after strokes. The unacknowledged but crucial task of reintegrating into society is another issue in this region. In Indonesia, the latest Riset Kesehatan Dasar (Riskesdas) study indicates that the overall prevalence is 10.9/1,000,000, with different provinces reporting levels, including Papua which has the lowest level at 4.9/100,000,000.⁶

Rapid evaluation and intervention are crucial in addressing acute stroke, which is based on the notion that “time is brain”.^7–9 This applies to the limited time frame for determining intravenous thrombolysis therapy and mechanical thrombectomy. The World Stroke Association has established intravenous thrombolysis with recombinant-tissue plasminogen activator (r-TPA) as the gold standard treatment for acute ischemic stroke.¹⁰ The procedure involves the administration of r-tPA through intravenous injections. According to the AHA/ASA, mechanical thrombectomy is performed within 6–24 hours, and symptoms appear every hour, so IV-tPA should be administered within 4.5 hours. With every minute of untreated stroke, one may lose their neurological recovery chances.¹¹

The contribution of pre-hospital factors is relatively large, resulting in delays in thrombolytic action. Basically, this is multifactorial related to patients, transportation, referral systems, and delays in entering and leaving the hospital, but most of them are caused by contacting emergency services. This may be because the patient or his family believes that the symptoms he has experienced are not severe enough for medical treatment. Whereas Emergency Room (ER) visits associated with more severe symptoms of stroke demonstrated an earlier timeline, less severe ones contributed to a delay of admission.^12,13

In addition to pre-hospital and in-hospital causes of delay, there is the gap in access to health services between urban and rural settings as another one of the important barriers in utilizing thrombolysis, especially in SEAR. Only around 3% to 5% of acute stroke patients received IV r-tPA, based on a recent analysis.¹⁴ The number of stroke experts in small hospitals located in rural areas has been a primary cause for the low rate of utilization.¹⁵ Rural and urban areas are found to have life expectancy rates which are associated with very significant disparities.¹⁵ Such a striking difference was seen in stroke mortality between the two areas.¹⁵ Based on Vital Statistics data, the mortality rate due to stroke in rural and urban areas rose from 15% to 25% from 1999 to 2010 and then decreased to 8% in 2019. Another cause for the deaths in the area is the high incidence of stroke in rural areas.¹⁴

Further studies showed that patients with acute stroke living in rural areas had less intravenous thrombolysis therapy compared to urban patients. This is because of the slow diffusion of new treatments and technologies to rural hospitals, and a lack of resources to have access to specialized stroke care or central hospitals. Besides that, the lack of specialist doctors in rural hospitals is also a factor in this gap. Especially, when stroke patients need time to travel long distances to seek adequate stroke care, this lengthens the time from symptom onset to therapy.¹⁶ Inter-hospital transportation factors also play an important role in treatment delays, which directly affects the effectiveness of thrombolytic interventions.¹⁷

For this reason, health service providers, based on those things, have to design regionalization efforts or centralization of acute stroke care by utilizing technology such as telehealth and referral systems. Recent studies have identified that stroke telehealth programs, also known as telestroke, can safely and effectively extend the use of intravenous thrombolysis and subsequently improve stroke patients’ clinical outcomes.¹⁸ Telestroke is an innovation within telemedicine, which refers to a method of identifying, assessing, treating, and monitoring stroke patients remotely using internet technology. Telestroke can speed up diagnosis and treatment in acute stroke through direct video consultations between doctors and patients separated by distance.¹⁸ In a “hub-and-spoke” model, stroke specialist doctors at primary health centers (hubs) can cooperate with the source facility (spoke) to provide timely remote care. Telestroke is able to reduce “door-to-needle time” and reduce morbidity and mortality due to stroke in a cost-efficient manner. Increasing access to care for stroke by telestroke is a promising innovation for rural areas. It is hoped that telestroke will help bridge this gap by allowing hospitals in rural areas to provide a level of care similar to hospitals that have specialists in stroke care.¹⁹

There is still limited published study explaining the effectiveness of telestroke itself in improving the clinical outcomes of acute stroke patients, especially in SEAR countries. Therefore, this narrative review will assess the effectiveness of telestroke in improving clinical outcomes of acute stroke patients in South East Asia Region (SEAR).

Role of Telestroke in Acute Stroke

Telestroke and Door-to-Needle (DTN) Time

Telestroke consultations are experiencing a phenomenal surge in popularity globally, with the number of instances increasing.^20,21 Telestroke programs have reported an important outcome in the treatment of acute ischemic stroke, with increased use of thrombolytic therapy.¹⁵ Among patients treated at tertiary stroke centers, telestroke has been found to increase the rates of thrombolysis therapy, particularly in hospitals without stroke units and with no adverse events associated with them. In the United States, thrombolysis is mostly done using a drip-and-ship model, with some assistance from telestroke consultations. Telestroke services have broadened beyond the initial focus of thrombolysis treatment for acute stroke to encompass post-alteplase follow-up, non-emergent consults, and supportive care to enable patients to remain under local care.²¹

Dutta et al found that intravenous thrombolysis, which involved telephone consultation, teleradiology, and local doctors, was safe and effective in managing stroke in hospitals with a structured stroke care system. Among the 22 minutes that were added to Door-to-Needle (DTN) time by Telecare, 14 minutes of it was directly related to the remote consultation process, while another 20 minutes was recorded as slow processing outside normal working hours.²² The study conducted by Fong et al suggests that using telestroke to manage patients without a specialist doctor in on-site neurology can be equally effective and safe. The shortage of neurologists on site for acute stroke services outside of regular hours can be resolved by telestroke.²³

Acute stroke patients can be treated safely and with minimal delay by neurological examination using a web and a drip and treat protocol as researched by Nardetto et al. The satisfactory results of onset-to-door (OTD) and door-to-CT scan (DTC) times have been presented by this study in both telemedicine and non-telemedicine procedures. However, the starting time for therapy is still quite long, especially in hub centers. This is induced by the presence of second level confirmation at the hub center itself, such as a brain MRI or ultrasound scan, to determine the right diagnosis before treating the patients in the acute phase; this causes delays in treatment. These conclusions indicate that the findings from this study present the reliability of telestroke in making available the facility of follow-up monitoring by specialists for the patients and receipt of as intensive care in a stroke unit, particularly crucial hours following thrombolysis. An achievement considered to increase more access for the patients to more specialist care is wherever they might be staying and is due to telestroke.²⁴

The TRUST-tPA study is the other one on the therapeutic trial conducted to test the efficacy of telemedicine of patients suffering from acute stroke and proves that telestroke can increase patient access to r-tPA fivefold as opposed to the usual care group, while the trial did not result in clinical outcome improvement. It results from the patient characteristics; in the telestroke group, they are higher in age as well as increased NIHSS.²⁵

Alteplase given within 4.5 hours from the time the symptoms of acute stroke began to appear will be able to reduce the patients’ disabilities for the long term. Timely tPA administration offers significant benefits that have been considered related to speed: earlier initiation yielding superior long-term functional outcome along with fewer complications. Recent guidelines recommend a door-to-needle time of less than 60 minutes from arrival to the hospital.²⁶ Better DTN times have been associated with improved clinical outcomes, such as reduced symptomatic intracranial hemorrhage, reduced inpatient mortality, and improved functional outcomes. However, only about 30% of the patients receive tPA within this time frame successfully.²⁷

Based on research conducted by Martínez-Sánchez et al, telestroke can increase tPA use and better decision-making, as well as reduce unnecessary patient transfers. Additionally, telestroke can also reduce DTN time contributing to better clinical outcomes. In this study, telestroke allowed tPA administration to be performed at the spoke center; thus, the DTN time was reduced by approximately 77 minutes, with a median time of 66 minutes in the group telestroke, faster than many previous telestroke studies.²⁸

Raulot et al revealed that the intra-hospital or DTN time was longer in local hospitals using telestroke compared with stroke units because of the preparatory procedures in setting up a video conference between the spoke and the hub. However, ultimately, the overall onset-to-needle (OTN) time had similar results. This research also thus suggests that telestroke implementation should be targeted at >30-minute centers from a stroke unit.²⁹

Al Kasab et al reported that the percentage of patients who achieved DTN time thresholds was lower in spoke than in hub hospitals. This study demonstrated that stroke patients at spoke hospitals with telestroke received tPA has administered at spoke hospitals lately. This is because of the inexperience of the spoke hospital in the treatment of stroke and time required to carry out telestroke consultations and brain imaging. This study also suggested that the DTN times in spoke hospitals can be improved. This can be done with various interventions such as training, education, and increasing comfort or confidence of medical staff at spoke hospitals in treating acute stroke patients.³⁰

Improvement in Stroke Outcome

Most of the telestroke networks remotely use the NIHSS assessment of the stroke. NIHSS performed remotely has a degree of reliability equivalent to an in-person examination in both sub-acute and acute stroke patients.¹⁵ This assessment by telemedicine can be done without significant delays in time. Furthermore, the results of the assessment using NIHSS through telemedicine are very reliable because it has consistent results even though carried out by different assessors. This is reinforced by the very good correlation (r = 0.9552), between NIHSS performed at the bedside and at a remote location. NIHSS can be performed on a variety of devices and technologies: computer, laptop, and mobile video.³¹ Remote video assessment using smartphone was evaluated in a study showing an excellent level of “agreement” on most of the NIHSS components.¹⁵

In addition to NIHSS assessments, most stroke care studies and reports use 90-day functional studies as long-term outcome indicators in monitoring post-stroke patient outcomes. The expectation, therefore, exists that telestroke networks should follow these standards within the stroke care systems. One of the most applied assessment tools of outcomes in this measure is mRS, which ought to be measured at 90 days post-stroke. The mRS assessment is a trained, certified, person-to-person test that can be either in person or completed over the telephone, but sometimes obtaining long-term follow-up is tough and requires more than the capacity of a few telestroke systems. In such cases, interim indicators of the patient’s functional outcome include short-term outcome indicators such as in-hospital mortality, NIHSS within 24 hours, mRS score at the time of discharge, information about the location to which the patient is discharged may indicate the improvement in the patient’s condition.¹⁵

The contribution of Martínez-Sánchez et al presented evidence for telestroke to decrease three-month mRS by reducing DTN time. At this point, it is possible that early intravenous thrombolysis after ischemic stroke may lead to better clinical outcomes.²⁸ Previous studies stated that there was no difference in clinical outcomes in patients with Large Vessel Occlusion (LVO) who were first treated at a spoke hospital and at the Comprehensive Stroke Centre (CSC). However, this study shows that there are differences in the distribution of reperfusion therapy. More patients with telestroke received IV r-tPA, but less and needed longer access to mechanical thrombectomy. This finding is relevant in areas where the distance between the spoke center and the CSC is quite large.³²

Implementation of Telestroke in SEAR

Health care systems in the SEAR are characterized by their heterogeneous nature, with a complex combination of public and private delivery, including government insurance and high-out-of-pocket funding. Thailand and Singapore have the highest level of public health coverage, respectively. The implementation of Universal Health Coverage (UHC) in Thailand since 2002 has resulted in stroke being covered under public health, but the use of thrombolysis remains low (0.18–8.04%).²⁹ Bhutan’s citizens can receive UHC as well. Most SEAR countries have access to UHC, but its use is restricted due to poor affordability. In most countries, the increasing demand for high-quality healthcare and rising education levels have spurred a push towards privatization. India’s healthcare system comprises of primary, secondary, and tertiary level hospitals with 3 levels. Across different regions, there is a wide range of accessibility and affordability for physicians as well as facilities due to the prevalence of private health care, lack of social insurance, and large urban-rural divide. Nepal relies heavily on out-of-pocket funding for its healthcare.³⁰ Notwithstanding the health sector’s increased policy priority, public investment in healthcare is below US$20 per capita, and private ownership controls more than two-thirds of hospital beds.^33,34 Decentralization of healthcare systems in low and middle income countries (LMICs), including Indonesia, has replaced devolution to district/local governments since 2001. These changes in the health system have put pressure on the public sector to adapt, evolve and provide.^31,35 Due to the significant need to restructure healthcare delivery and financing, various innovative financing schemes have been introduced throughout the region.^36–38 In India, the Ayushman Bharat Yojana and PM-JAY scheme is a government-funded initiative that provides comprehensive healthcare services, including secondary and tertiary healthcare insurance, to patients with strokes, who can also receive intravenous thrombolysis, mechanical thrombectomy, or Stroke Unit (SU) care.^39,40 The use of mobile phone technology, which has revolutionized telestroke care in SEAR countries, is being harnessed to provide stroke care. This trend is especially evident in countries like India, where numerous trials have been started on app-based, technology-driven, affordable telestroke models of care.⁴¹ Twenty-six patients were successfully thrombolysed at 9 district hospitals in North India through a trial using telestroke models, with the hub and spoke tunable model being used by only 2 tertiary hospitals and 17 districts hospitals.⁴² No neurologist was present on site. Telestroke care has gained recognition in Indonesia and Nepal for challenging terrain.^43,44

The SMART-India app is a telephone application to provide low-cost telestroke services from a neurologist and physiotherapist to doctors in district hospitals. This application allows doctors to transmit patient data, such as CT scans, to make clinical decisions in patient management. This application also facilitates interaction between doctors and physiotherapists in the tele-rehab module. It is hoped that this application will meet the rehabilitation needs of stroke survivors in rural areas with limited resources in low and middle income countries, such as India.⁴²

Changi General Hospital (CGH) is an acute regional hospital in Singapore that treats around 150,000 emergency patients every year. CGH provides 24-hour telestroke services with a hub-and-spoke model. Eligible patients will come to CGH as spokes and be evaluated by neurologists at the National Neuroscience Institute (NNI) as hubs. The telestroke workflow is achieved through four Plan-Do-Study-Act (PDSA) cycles. The aim of the PDSA cycle is to evaluate the five phases of telestroke for more precise monitoring. The five phases are: (1) patient arrival at the ER until stroke alert; (2) stroke alert until completion of CT imaging; (3) completion of CT imaging to stroke activation; (4) stroke activation to decision for tPA; and (5) decision for tPA until administration of tPA. The study shows that new measures can reduce DTN time delays. Even though it did not reach a DTN time of less than 60 minutes, there was a significant increase in DTN time which was comparable to other centers that used telestroke, namely 61–106 minutes. Median time to obtain imaging (ED arrival time to brain CT) increased from 17 minutes to 13 minutes. The average time for videoconference and adjudication by a neurologist (phase 4) increased from 35 minutes to 26 minutes. Ultimately, these quality improvements may reduce the overall median time to DTN for acute ischemic stroke patients receiving thrombolysis after using telestroke program.^5,45,46

Factors Influencing Implementation of Telestroke in SEAR

The implementation of telestroke requires the effective training and education of health workers. Despite the existence of pre-existing consensus stroke protocols, telestroke’s implementation was linked to a specific training program for spoke hospital physicians. Studies have revealed that the implementation of stroke reperfusion strategies in educational programs and stroke protocols can lead to a decrease in DTN time to effective tPA administration. The telestroke group’s improvement in tPA administration may be partly due to the need for physician education and compliance with stroke management guidelines at spoke hospitals, and also government policy for telestroke financing program.^8,9,37,38

Public knowledge about stroke symptoms and their associated signs is inadequate in SEAR. Awareness studies from India have revealed that 23–48% of participants were unaware about stroke warning symptoms, and over half had no knowledge of any risk factors or treatments. The average stroke awareness among patients with stroke in Sri Lanka was found to be 47.79%, but higher levels of awareness were observed in those with more extensive education.⁷ The failure to acknowledge early symptoms of stroke and sociocultural beliefs in indigenous modalities like faith healing leads many patients to overlook the need for effective medical treatment. The inadequate organization of pre-hospital services contributes to the challenge of accessing stroke-ready centers.¹⁰ Most countries lack the standard Emergency Medical Services (EMS) systems that are currently in place and vary in their accessibility. Although the SEAR shares a significant burden of strokes in India, there is no established system for managing it.¹¹ Most patients arrive at hospitals in either self-owned or hired private vehicles. Only 1–13% of patients in India use EMS to get to the hospital, as opposed to 50% from high-income countries.^12,47 The 108-ambulance system is utilized in 22 out of 28 states and 2 out of 8 union territories in India. The emphasis is on maternal and trauma care, while paramedical staff lacking stroke care education. The national ambulance transport system Suwaseriya is available to patients in Sri Lanka from 1990.¹³ While this service has gained more public awareness and usage, training for paramedics in stroke recognition and fast-track referrals is still required. Nepal’s landslides and primitive ambulance services pose challenges in providing timely care. Notwithstanding the improved system architecture in Thailand, past studies indicate that only 5.5–20.5% of stroke victims use EMS-based management strategies.^14,15 EMS fails to organize the integration of fast-track protocols with their systems, resulting in only half of suspected stroke patients being sent to appropriate stroke centers.¹⁶ A strong referral system is reported by Maldives. Despite the Maldives’ scattered island-flunge location, its air and sea ambulance services are highly developed and equipped to facilitate rapid patient transport and referral.¹⁷

According to a separate study, medical and paramedical teams were trained in specific workshops to treat patients during the acute phase of stroke. This training equips the hub team to obtain precise information about the patient from the spoke team staff. The management of patients at branch hospitals was standardized to enable access to video conferencing, imaging, and care. The operation of the telestroke system is under the supervision of neurologists and radiologists who are available 24/7. By relying on the hub team’s expertise, they can expedite the decision-making process for the spoke team.^8,35,36

Trials that have encountered obstacles in the TRUST-tPA trial include those that involve video conferencing time, such as collecting history and administering NIHSS to individuals with comprehensive neurological examination. This can hinder patient progress due to the importance of OTT timing in achieving good clinical outcomes. Furthermore, imaging at the endorsed hospital is not accessible. A compact disc is necessary for its storage. The telestroke team experienced a significant increase in videoconference time and CT imaging visualization time.⁸

Stroke care services in SEAR countries require urgent strengthening and improvement. Multidisciplinary approach should account geographical, cultural/social/economic differences. Setting realistic targets and achieving context-appropriate goals is part of the Global Stroke Action Plan, which recognizes that different systems may be involved in stroke care across the world.^10,36,37 To ensure effective primary prevention and reduce treatment delays, it is essential to raise awareness about stroke and risk factors. Behavioral modification programs for stroke awareness and government policies, such as taxes, are necessary to control lifestyle determinants.¹⁰ Countries lacking skilled workers should adopt hub-and spoke, task-sharing, and physician-led models of stroke care as effective approaches. The use of telestroke networks, digital technology, and mobile apps for knowledge sharing can occur both within and between countries.^21,35,36 Further research is needed on the effectiveness and implementation of telestroke in SEAR.

Conclusion

Increasing access to stroke care via telestroke is a promising innovation for rural areas, especially in SEAR. It is hoped that telestroke can bridge this gap, allowing hospitals in rural areas to provide care equivalent to hospitals that have stroke specialists. Achieving equitable stroke care in SEAR requires the implementation of evidence-based policymaking, which involves a multidisciplinary approach with active participation from stakeholders such as stakeholders (eg healthcare policymakers for telestroke financing program), government agencies, and ministries of health. Enhancing social literacy on stroke through the wide dissemination of stroke awareness programs, specialized stroke recognition training for paramedical staff, establishment of a national stroke hotline number to expedite referrals, and the adoption of hospital prenotification is necessary in order to improve telestroke healthcare services.

Disclosure

The author reports no conflicts of interest in this work.

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Introduction

Hospitalization rates among the general population in the UK have increased faster than population growth.¹ From 1999 to 2019, there has been a 105% increase in rate of hospitalization for respiratory diseases,^1,2 rising from ninth to fourth most common cause of hospitalization. By 2019, UK respiratory hospitalizations (31,597.7 admissions per million people) were more common than endocrine, nutritional, and metabolic disease hospitalizations (including type-II diabetes mellitus [T2DM], at 7288.3 admissions per million people), and circulatory system hospitalizations (26,627.5 admissions per million people). Chronic obstructive pulmonary disease (COPD) affects approximately 5% of UK residents aged 40 years and older³ and contributes greatly to hospitalization admission and readmission rates. Additionally, prevalence of COPD³ and hospital admission rates within COPD⁴ have risen.

Comorbid cardiovascular disease (CVD) is frequent in people with COPD (9% to 60%, depending on CVD type).⁵ COPD is also associated with major adverse cardiovascular events (MACE),⁶ and, moreover, severe exacerbations of COPD requiring hospitalization are associated with 3.18-fold increase in subsequent non-fatal MACE over a mean of 1.2 years.⁷ In addition to COPD-associated morbidity, COPD also has a high mortality burden, accounting for 30,000 deaths annually in the UK.⁸ Significant predictors of COPD mortality (in addition to age, male sex, and CVD) include hospitalization for acute exacerbation and hospital readmission within 30 days.⁹

Given the severity of outcomes associated with COPD and the burden of COPD hospitalizations on health systems, understanding the effect of hospitalization amongst people with COPD has important implications for clinical practice as this may provide an opportunity to optimize care and prevent re-admissions and death. We, therefore, aimed, in a COPD population from a large UK-based primary care longitudinal dataset broadly representative of the English population, to investigate the association between hospitalization (by hospitalization type [elective or emergency], and hospitalization cause [cardiovascular, respiratory, or non-cardiorespiratory]) and subsequent risk of (i) non-fatal MACE and (ii) mortality.

Materials and Methods

Data Source

The study population was defined from primary care records using the Clinical Practice Research Datalink (CPRD) Aurum database (May 2022 build).¹⁰ CPRD Aurum data are de-identified, routinely collected, electronic healthcare records covering ~20% of the UK population, and are representative of age, sex, and region.¹¹ Aurum data were linked with Hospital Episodes Statistics (HES) secondary care data,¹² Index of Multiple Deprivation (IMD) socioeconomic data,¹³ and Office of National Statistics (ONS) mortality data¹⁴ (see pg. 2 in the supplementary document for linkage practices).

Study Participants

Inclusion criteria were (1) COPD diagnosis (validated methodology,¹⁵ codelist: https://github.com/NHLI-Respiratory-Epi/Hospitalisations-MACE-in-COPD), (2) aged ≥40-years-old, (3) current or ex-smokers, (4) data in CPRD between 1st January 2010 to 31st December 2019, (5) registered at primary care provider ≥one year before study start, and (6) data of “research quality”¹¹ (see supplement for CPRD practices).

Exposures, Outcomes, and Study Design

Study Groups and Design

We conducted a prospective cohort study. Broadly, the exposure was hospitalization. We stratified hospitalization by type (elective or emergency), cause (all-cause, respiratory, cardiovascular, and non-cardiorespiratory, using ICD-10 codes), and cause-type (eg, cardiovascular-emergency). For the exposed group, start of follow-up was date of hospital discharge (after meeting inclusion criteria). For the control group (no hospitalization), start of follow-up was the latest date on which all inclusion criteria were met. In the absence of the outcome, patients were followed up for one year, or until end of CPRD registration or study period (Figure 1).

Outcomes

Outcomes included (i) non-fatal MACE, and (ii) mortality (codelists: https://github.com/NHLI-Respiratory-Epi/Hospitalisations-MACE-in-COPD). MACE was defined using secondary care ICD-10 codes as acute coronary syndrome (ACS), arrhythmia, heart failure (HF), or ischemic stroke (stroke). People who died during follow-up for the non-fatal MACE analysis were censored. Mortality was defined using ICD-10 codes in ONS data, and was stratified into all-cause mortality, COPD-specific mortality, and cardiovascular-specific mortality.

Statistical Analysis

Baseline Characteristics and Covariates

Baseline characteristics were taken nearest as possible to start of follow-up date (see supplement for specific time-related definitions). Characteristics were described as mean (standard deviation) for continuous data, and as counts (percentage) for categorical data. We described age, sex, smoking status (ex or current), body mass index (BMI, underweight:<18.5kg.m⁻²; healthy weight: 18.5–24.9kg.m⁻²; overweight: 25.0–29.9kg.m⁻²; obese:>30kg.m⁻²), socioeconomic deprivation (IMD quintiles, IMD1=least deprived to IMD5=most deprived); COPD acute exacerbations, MRC dyspnea scale, GOLD airflow obstruction group, short-acting bronchodilators, COPD medications (long-acting bronchodilators and inhaled corticosteroids), asthma, depression, anxiety, gastro-esophageal reflux disease (GORD/GERD), lung cancer, hypertension, T2DM, and cardiovascular history (ACS, arrhythmia, MI, HF, or stroke; recorded in primary or secondary care) (codelists:https://github.com/NHLI-Respiratory-Epi/Hospitalisations-MACE-in-COPD).

Primary Analysis

We calculated absolute event rates (number and percentage), incidence rates (IR, per 1000-person-years), and implemented Cox proportional hazard regressions for (i) MACE and (ii) mortality (all-cause, cardiovascular-specific, and COPD-specific). Cox models were adjusted for aforementioned baseline characteristics except BMI, MRC score, and GOLD group due to missing-not-at-random. Analyses were done using Stata 17.¹⁶

Sensitivity Analyses

We conducted multiple sensitivity analyses, including (i) regressions adjusted for all covariates (including BMI, MRC score, and GOLD group), (ii) regressions amongst individuals without hospitalization in the year preceding follow-up, and (iii) doubly robust propensity score-adjusted regressions¹⁷ to address confounding by indication in those hospitalized versus those not hospitalized. We applied Bonferroni corrections.

Secondary Analysis

We conducted a descriptive analysis, calculating percentage of primary cause of death of people in each study sub-stratum (eg, emergency-cardiovascular hospitalization).

Ethical Approval and Patient Consent

CPRD has NHS Health Research Authority (HRA) Research Ethics Committee (REC) approval to allow the collection and release of anonymised primary care data for observational research [NHS HRA REC reference number: 05/MRE04/87]. Each year CPRD obtains Section 251 regulatory support through the HRA Confidentiality Advisory Group (CAG), to enable patient identifiers, without accompanying clinical data, to flow from CPRD contributing GP practices in England to NHS Digital, for the purposes of data linkage [CAG reference number: 21/CAG/0008]. The protocol for this research was approved by CPRD’s Research Data Governance (RDG) Process (protocol number: 22_002514) and the approved protocol is available upon request. Linked pseudonymised data was provided for this study by CPRD. Data is linked by NHS Digital, the statutory trusted third party for linking data, using identifiable data held only by NHS Digital. Select general practices consent to this process at a practice level with individual patients having the right to opt-out.

Results

Descriptive Characteristics

Amongst 312,121 COPD patients, 238,831 (76.5%) had at least one hospitalization (Figure 2). Patients hospitalized were approximately five years older than those not hospitalized. More men (53.5%) than women (46.5%) were hospitalized. Prevalence of hypertension was higher amongst those hospitalized (51.6%) than not hospitalized (38.1%). Similarly, cardiovascular history was higher in people hospitalized (28.2%, aligning approximately with the population [24.0%]) versus those not hospitalized (10.4%). COPD exacerbations distribution differed slightly between groups, where those hospitalized tended to have fewer people in the “no exacerbations” group and more in the “any moderate, 1 severe” group. Additionally, people admitted as emergency cases tended to have fewer people in the “no exacerbations” group and more in the “any moderate, 1 severe” group, across hospitalization causes. Finally, patients not hospitalized (10.1%) had a low prevalence of triple therapy prescription versus those hospitalized (30.4%). Cause- and type-specific hospitalization descriptive statistics are available in the supplement (Table E1).

Figure 2 Description of inclusion criteria, study cohort, and individual study groups. Summary statistics are presented as Number [percentage] or as mean (standard deviation). Additional details of CPRD data research quality can be found in the supplement. Abbreviations: CPRD, Clinical Practice Research Datalink; GP, General Practitioner; COPD, chronic obstructive pulmonary disease; HES, Hospital Episode Statistics; IMD, Index of Multiple Deprivation; ONS, Office of National Statistics.

Sensitivity Analyses

We conducted several sensitivity analyses. Regression outputs were almost identical across the primary analysis and sensitivity analyses. We, therefore, report primary analysis outputs within this manuscript, and we report all sensitivity analysis results in the online data supplement (Tables E2–E6).

Hospitalization and MACE

Elective and Emergency Hospitalization and MACE

Across the whole cohort, there were 12,059 (3.9%) MACEs. The number of events amongst people hospitalized and not hospitalized was 11,881 (5.0%) and 248 (0.3%), with an incidence rate per 1000 person-years (IR) [95% confidence interval {95% CI}] of 51.0 [50.1, 51.9] and 3.4 [3.0, 3.8], respectively. MACE rate (IR [95% CI]) was 33.3 [32.3, 34.4] among electively hospitalized patients, and 70.0 [68.4, 71.6] in emergency hospitalized patients. There was a similar trend in MACE rates between patients hospitalized electively and as emergencies across all specific hospitalization causes (cardiovascular, respiratory, or non-cardiorespiratory), the highest rates of which were in cardiovascular hospitalizations, followed by respiratory hospitalizations and non-cardiorespiratory hospitalizations (Table E7 for individual event rates).

Hospitalization was strongly associated with subsequent MACE, whether elective (adjusted hazard ratio {aHR} [95% CI]=7.04 [6.19, 8.07]) or emergency (aHR [95% CI]=8.85 [7.78, 10.06]). Across all hospitalization causes, emergency hospitalization was more strongly associated with subsequent MACE versus elective hospitalization. Although all hospitalization causes and types were associated with subsequent MACE, cardiovascular hospitalizations were most strongly associated (elective: aHR [95% CI]=17.90 [15.45, 20.74]; emergency: aHR [95% CI]=19.83 [16.76, 22.40]), than were respiratory (elective: aHR [95% CI]=6.61 [5.31, 8.22]; emergency: aHR [95% CI]=7.22 [6.19, 8.43]) and non-cardiorespiratory (elective: aHR [95% CI]=6.17 [5.42, 7.03]; emergency: aHR [95% CI]=7.44 [6.52, 8.49]) (Figure 3).

Figure 3 Association between hospitalization cause and type and subsequent MACE among people with COPD. Each hospitalization group substratum (eg, cardiovascular elective hospitalization) is compared with people with COPD without hospitalization as the control group. **Indicates statistical significance. Abbreviation: MACE, Major Adverse Cardiovascular Event (acute coronary syndrome OR heart failure OR arrhythmia OR ischaemic stroke).

Hospitalization and Mortality

Elective (All-Cause) Hospitalization and Mortality

Across 122,362 electively hospitalized patients, there were 6511 (5.3% of elective hospitalizations) subsequent all-cause deaths (IR [95% CI]=54.6 [53.3, 56.0]) (Table E8). COPD-specific mortality following any elective hospitalization accounted for 843 deaths (0.7% of elective hospitalizations) and accounted for 3.5% of all deaths (Table E9). Cardiovascular-specific mortality following elective hospitalization accounted for 1084 deaths (0.9% of elective hospitalizations) and accounted for 4.4% of all deaths (Table E10). In general, mortality rates were lower following elective hospitalizations than emergency hospitalizations, across all hospitalization causes.

All-cause elective hospitalization was associated with increased all-cause mortality (aHR [95% CI]=1.32 [1.25, 1.38]), but deceased COPD-specific (aHR [95CI%]=0.58 [0.53, 0.65]) and cardiovascular-specific mortality (aHR [95% CI]=0.56 [0.51, 0.61]) (Figure 4).

Figure 4 Association between hospitalization cause and type and subsequent mortality ((A) All-cause mortality, (B) Cardiovascular-specific, and (C) COPD-specific mortality) among people with COPD. Each hospitalization group substratum (eg, cardiovascular elective hospitalization) is compared with people with COPD without hospitalization as the control group. Note: **Indicates statistical significance.

Elective (Cardiovascular-, Respiratory-, and Noncardiorespiratory-Specific) Hospitalization and Mortality

(i) All-cause mortality

The highest rate (IR [95% CI]) of all-cause mortality amongst patients electively hospitalized were amongst those hospitalized for respiratory causes (83.1 [74.4, 92.7), followed by non-cardiorespiratory causes (54.3 [53.0, 55.8]) and cardiovascular causes (45.3 [41.0, 50.1) (Table E8). There was a significant association between all-cause mortality and all-cause elective hospitalization (aHR [95% CI]=1.32 [1.25, 1.38]), respiratory elective hospitalization (aHR [95% CI]=1.99 [1.77, 2.24]) and non-cardiorespiratory elective hospitalization (aHR [95% CI]=1.31 [1.25, 1.38]), but not cardiovascular electively hospitalization (Figure 4).

(ii) COPD-specific mortality

COPD-specific mortality rate (IR [95% CI]) was highest amongst patients electively hospitalized for respiratory causes (14.5 [11.2, 18.8]), followed by non-cardiorespiratory causes (6.7 [6.2, 7.2]) and cardiovascular causes (6.6 [5.1, 8.5]) (Table E9). Elective hospitalization was associated with a reduction in COPD-specific mortality for any hospitalization cause (aHR [95% CI]=0.58 [0.53, 0.65]), cardiovascular cause (aHR [95% CI]=0.53 [0.40, 0.70]), and non-cardiorespiratory cause (aHR [95% CI]=0.53 [0.45, 0.59]), but not respiratory cause (Figure 4).

(iii) Cardiovascular disease-specific mortality

Cardiovascular-specific mortality rate (IR [95% CI]) was highest amongst patients electively hospitalized for cardiovascular causes (19.8 [17.0, 23.0]), followed by respiratory causes (11.5 [8.6, 15.4]), and non-cardiorespiratory causes (7.9 [7.4, 8.5]) (Table E10). There were significantly fewer cardiovascular-specific deaths among elective hospitalizations (aHR [95% CI]=0.56 [0.51, 0.61]) and non-cardiorespiratory elective hospitalizations (aHR [95% CI]=0.50 [0.45, 0.55]), but there was no association between COPD-specific mortality and respiratory elective hospitalizations or cardiovascular elective hospitalizations (Figure 4).

Emergency (All-Cause) Hospitalization and Mortality

Amongst 116,469 emergency hospitalized patients, there were 15,672 (13.5% of emergency hospitalizations) subsequent all-cause deaths (IR [95% CI]=146.5 [144.2, 148.8]) (Table E8). COPD-specific mortality following any emergency hospitalization accounted for 4545 deaths (3.9% of emergency hospitalizations) and accounted for 18.7% of all deaths (Table E9). Cardiovascular-specific mortality following any emergency hospitalization accounted for 3265 deaths (2.8% of emergency hospitalizations) and accounted for 13.4% of all deaths (Table E10). Moreover, compared with those not hospitalized, all-cause emergency hospitalization was associated with an increased all-cause mortality (aHR [95% CI]=2.49 [2.37, 2.61]), COPD-specific mortality (aHR [95% CI]=1.53 [1.39, 1.67]), but not cardiovascular-specific mortality (aHR [95% CI]=1.08 [0.99, 1.18]) (Figure 4).

Emergency (Cardiovascular-, Respiratory-, and Noncardiorespiratory-Specific) Hospitalization and Mortality

(i) All-cause mortality

When stratified by emergency hospitalization cause, mortality rate (IR [95% CI]) was highest in patients hospitalized for respiratory causes (161.0 [157.0, 165.1), followed by all emergency hospitalizations (146.5 [144.2, 148.8]); and were similar in non-cardiorespiratory causes (139.5 [136.4, 142.7]) and cardiovascular causes (134.8 [129.0, 140.9]) (Table E8). Emergency hospitalization was associated with increased all-cause mortality across all hospitalization causes (aHR [95% CI]: all-cause=2.49 [2.37, 2.61]; non-cardiorespiratory=2.60 [2.47 to 2.73]; respiratory=1.99 [1.85, 2.14]; cardiovascular=1.99 [1.85, 2.14]) (Figure 4).

(ii) COPD-specific mortality

COPD-specific mortality rates (IR [95% CI]) were highest in respiratory emergency hospitalizations (68.6 [66.1, 71.2]), followed by all-cause hospitalization (39.9 [38.8, 41.1]), and similar rates in non-cardiorespiratory causes (24.1 [22.9, 25.4]) and cardiovascular causes (25.0 [22.6, 27.6]) (Table E9). COPD-specific mortality was associated with respiratory emergency hospitalization (aHR [95% CI]=2.01 [1.77, 2.27]) and all-cause emergency hospitalization (aHR [95% CI]=1.53 [1.39, 1.67]), but not with cardiovascular emergency hospitalization or non-cardiorespiratory emergency hospitalization (Figure 4).

(iii) Cardiovascular disease-specific mortality

Cardiovascular-specific mortality rate (IR [95% CI] was highest for patients admitted as cardiovascular emergencies (57.2 [53.5, 61.1]), followed by similar rates in all-cause emergency hospitalizations (28.5 [27.5, 29.5]), respiratory emergency hospitalizations (24.3 [22.8, 25.8]), and non-cardiorespiratory emergency hospitalizations (24.0 [22.7, 25.2]) (Table E10). In addition, cardiovascular emergency hospitalizations were associated with increased cardiovascular mortality (aHR [95% CI]=1.64 [1.45, 1.85]), but respiratory emergency hospitalizations were associated with reduced cardiovascular hospitalizations (aHR [95% CI]=0.78 [0.67, 0.89]). There was no association between cardiovascular mortality and all-cause emergency hospitalization or non-cardiorespiratory hospitalization (Figure 4).

Cause of Death

We conducted a descriptive analysis of the primary cause of death stratified by hospitalization cause and type. Amongst patients who were hospitalized, 24,364 (7.8%) died, versus 2181 (3.0%) of people not hospitalized. The ICD-10 chapters with the highest frequency of events included Chapter II (neoplasms), Chapter IX (circulatory system), and Chapter X (respiratory system) (Figure 5). Although the number of deaths differed between study groups, distribution of cause was similar. Across all hospitalization causes, the proportion of deaths was greater amongst emergency hospitalizations versus elective hospitalizations (Figure 5 and Table E11).

Figure 5 Primary cause of death amongst people with COPD by ICD10 chapter and hospitalization cause and type. Cause of death obtained from first position ICD10 code in Office of National Statistics linked data. Figure shows only causes of death that represented at least 1% of deaths within the whole population. More granular information can be found in Table E11.

Discussion

Statement of Principal Findings

We demonstrated, in a nationally representative population of people with COPD, that hospitalization for any cause is strongly associated with subsequent one-year MACE rates. Scaling our results according to the wider COPD population,^3,18 approximately two million people with COPD will have some type of hospitalization, and, amongst them, approximately 106,000 will have a MACE within one year, suggesting a missed opportunity for optimizing cardiovascular care in this population. Secondly, we demonstrated that the relationship between hospitalization and subsequent one-year mortality is influenced by hospitalization cause and type. Emergency hospitalization was generally associated with increased one-year all-cause mortality, with cause-specific mortality aligning with the reason for hospitalization. This may be a recording artifact as cause of death likely mirrors the reason for hospitalization. In a COPD population, physicians do not routinely look for CVDs when the reason for admission is a COPD exacerbation, while cardiologists also do not frequently consider COPD and its pathophysiological consequences on CVD.⁵ All-cause and non-cardiorespiratory elective hospitalizations were associated with reduced cause-specific mortality, likely as people will be at their “fittest” for an elective procedure. Nevertheless, elective hospitalizations were associated with increased all-cause mortality. Finally, for respiratory and cardiovascular hospitalizations, subsequent cause-specific mortality patterns reflected initial hospitalization cause. We are not suggesting that hospitalizations cause MACE and mortality; rather, we are highlighting that people who are ill enough to be hospitalized are more at risk of these adverse outcomes, and that the hospitalization itself is a point of contact with the healthcare system for adverse event-vulnerable patients to receive more effective management of disease.

Contextualization with Literature

To our knowledge, this is the first study to examine adverse outcomes (MACE and cause-specific mortality) of COPD patients following various types and causes of hospitalization. MACE risk increases significantly following hospitalization for an acute exacerbation of COPD,⁷ however this study highlights that risk is not limited to exacerbations. Previous literature has demonstrated that hospitalization for transient conditions, such as infection, are associated with subsequent MACE.^19–22 COPD has been highlighted as a risk factor for post-hospitalization MACE following infection.^20,23 We have demonstrated that MACE risk in the COPD population (2.8% to 15.7% depending on hospitalization cause and type) is far higher than risk identified in previous literature for a general population and that it is, furthermore, comparable with MACE risk amongst a population of medium-to-high frailty (6.9% to 9.1%).²⁴ We have also demonstrated that MACE risk in people with COPD is high, irrespective of hospitalization cause and type.

We also demonstrated the relationship between hospitalization cause and type with mortality. To our knowledge, ours is the first study to evaluate the relationship between admission type subsequent cause-specific mortality. Other studies investigating mortality amongst different cause-specific hospitalized populations (ranging from infectious hospitalizations [Covid-19 and influenza²⁵ or tuberculosis²⁶]; to chronic disease-related hospitalizations [cancer,²⁷ acute pancreatitis,²⁸ and alcoholic liver disease²⁹]) demonstrated that mortality risk is largely linked to the condition itself, with cardiovascular death ranking after causes related to the condition in question. For example, people hospitalized with alcoholic liver disease were most likely to die of malignancies in the gastrointestinal tract or T2DM,²⁹ both of which frequently occur in people with alcohol disorders. There may, however, be unmeasured factors mediating coded causes of death, as CVD has previously been coded as an underlying cause of death amongst diabetic patients if patients died in hospital, had an autopsy, or were from geographical areas known to have higher prevalence of cardiovascular risk factors (higher BMI and systolic blood pressure).³⁰ Rates of all-cause mortality in our study were comparable with cardiovascular cohorts hospitalized for acute coronary syndromes.³¹ Whilst, on the whole, people admitted electively are likely to be at their fittest for optimal management, those admitted electively for a respiratory hospitalization (eg, for lung volume reduction surgery), are likely to be sicker than those admitted for a cardiovascular cause.

Limitations and Strengths

Limitations of this study include potential misclassification of disease (due to overlapping symptomatic presentation in cardiovascular and respiratory events), and hospitalization cause tending to align with listed cause of death. Cause of death may have been misdiagnosed based on the hospitalization (eg, if someone was hospitalized for a pre-existing COPD-related cause, their cause of death may also have been COPD-related, resulting in a potential underestimation of cardiovascular-related deaths in a COPD population). We did not consider hospitalizations that may have occurred between first hospitalization of follow-up (exposure) and the outcome, the cause of which may have been associated with MACE or mortality. We could not consider medications or CVD-related risk management decisions taken whilst patients were in hospital for their initial exposure hospitalization. We acknowledge that it is not possible to determine, from this analysis, whether hospitalization itself is the risk factor for subsequent MACE, or whether the people hospitalized are at greater risk of MACE due to unmeasured confounding. However, (i) elective procedures and hospitalizations would typically occur amongst people who are healthier, yet these patients still demonstrate elevated MACE risk, and (ii) the messaging of our paper does not change: awareness of elevated MACE (and mortality) risk following hospitalization remains important for all clinicians treating COPD patients. Despite limitations, our study had several strengths. We investigated several aspects of the relationship between hospitalization and adverse outcomes in people with COPD (hospitalization cause and type, and cause-specific mortality and MACE). Our data source is representative of the UK population with high completeness of diagnostic coding. Our methodology (including cohort identification,¹⁵ codelist design,³² and covariate algorithms³³) has been used and validated in previous research. We conducted several sensitivity analyses to ensure findings remained robust, including incorporating propensity scores within models to address confounding by indication.

Clinical and Policy Implications

People with COPD who are hospitalized, regardless of cause or type of hospitalization, are at high risk of subsequent MACE, providing an opportunity for primary prevention either at the point of initial hospitalization or immediately following. CVD is also under-recognized and undertreated amongst people with COPD,⁵ amplifying the importance of taking advantage of opportunities to increase diagnostic screening, before adverse events (such as MACE and mortality) occur. Every healthcare encounter for people with COPD should be considered an opportunity to address and mitigate potential underlying CVD, COPD itself, and the COPD-CVD pathophysiological interplay. Furthermore, given the elevated MACE and mortality risk, there is an invisible burden of hospitalization of people with COPD that may not be immediately obvious, particularly when the hospitalization was an emergency but was not COPD-related.

Conclusion

Hospitalization of people with COPD, regardless of cause and type, is associated with one-year MACE and is most strongly associated following a cardiovascular hospitalization. Addressing MACE risk at every healthcare interaction is a critical part of COPD care. Hospitalization type and cause play a role in mortality of COPD patients, where elective hospitalizations are generally associated with reduced cardiorespiratory mortality, emergency hospitalizations are generally associated with increased mortality. Cause-specific mortality is generally associated with the initial hospitalization cause. Attention to the increased risk adverse outcomes in the year after hospitalization amongst COPD patients, particularly MACE outcomes, may provide a policy opportunity to provide primary prevention.

Data Sharing Statement

Datasets generated and/or analysed in this study are not publicly available, however, data are available on request from the CPRD. Their provision requires the purchase of a license, and this license does not permit the authors to make them publicly available to all. This work used data from the version collected in May 2022 and has clearly specified the data selected in the Methods section. To allow identical data to be obtained by others, via the purchase of a license, the codelists will be provided upon request. Licenses are available from the CPRD (http://www.cprd.com): The Clinical Practice Research Datalink Group, The Medicines and Healthcare products Regulatory Agency, 10 South Colonnade, Canary Wharf, London E14 4PU.

AI Statement

No artificial intelligence (AI) was used in any stage of this research, nor in the write-up of the manuscript or supplementary materials.

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 funded by AstraZeneca as Externally Sponsored Research (grant number: ESR-22-22019) and supported by the NIHR Imperial Biomedical Research Centre (BRC).

Disclosure

AEI has received grants from the British Heart Foundation (BHF). HRW has received grants from Health Data Research UK (HDR UK) and NIHR Imperial Biomedical Research Centre (BRC). JKQ has been supported by institutional research grants from the Medical Research Council, NIHR, UK Research and Innovation (UKRI), Health Data Research, GSK, BI, AZ, Insmed, Sanofi and received personal fees for advisory board participation, consultancy or speaking fees from GlaxoSmithKline, Evidera, Chiesi, AstraZeneca. The authors report no other conflicts of interest in this work.

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