Kent and Medway Medical School

BACKGROUND: Timely and comprehensive analyses of causes of death stratified by age, sex, and location are essential for shaping effective health policies aimed at reducing global mortality. The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2023 provides cause-specific mortality estimates measured in counts, rates, and years of life lost (YLLs). GBD 2023 aimed to enhance our understanding of the relationship between age and cause of death by quantifying the probability of dying before age 70 years (70q0) and the mean age at death by cause and sex. This study enables comparisons of the impact of causes of death over time, offering a deeper understanding of how these causes affect global populations. METHODS: GBD 2023 produced estimates for 292 causes of death disaggregated by age-sex-location-year in 204 countries and territories and 660 subnational locations for each year from 1990 until 2023. We used a modelling tool developed for GBD, the Cause of Death Ensemble model (CODEm), to estimate cause-specific death rates for most causes. We computed YLLs as the product of the number of deaths for each cause-age-sex-location-year and the standard life expectancy at each age. Probability of death was calculated as the chance of dying from a given cause in a specific age period, for a specific population. Mean age at death was calculated by first assigning the midpoint age of each age group for every death, followed by computing the mean of all midpoint ages across all deaths attributed to a given cause. We used GBD death estimates to calculate the observed mean age at death and to model the expected mean age across causes, sexes, years, and locations. The expected mean age reflects the expected mean age at death for individuals within a population, based on global mortality rates and the population's age structure. Comparatively, the observed mean age represents the actual mean age at death, influenced by all factors unique to a location-specific population, including its age structure. As part of the modelling process, uncertainty intervals (UIs) were generated using the 2·5th and 97·5th percentiles from a 250-draw distribution for each metric. Findings are reported as counts and age-standardised rates. Methodological improvements for cause-of-death estimates in GBD 2023 include a correction for the misclassification of deaths due to COVID-19, updates to the method used to estimate COVID-19, and updates to the CODEm modelling framework. This analysis used 55 761 data sources, including vital registration and verbal autopsy data as well as data from surveys, censuses, surveillance systems, and cancer registries, among others. For GBD 2023, there were 312 new country-years of vital registration cause-of-death data, 3 country-years of surveillance data, 51 country-years of verbal autopsy data, and 144 country-years of other data types that were added to those used in previous GBD rounds. FINDINGS: The initial years of the COVID-19 pandemic caused shifts in long-standing rankings of the leading causes of global deaths: it ranked as the number one age-standardised cause of death at Level 3 of the GBD cause classification hierarchy in 2021. By 2023, COVID-19 dropped to the 20th place among the leading global causes, returning the rankings of the leading two causes to those typical across the time series (ie, ischaemic heart disease and stroke). While ischaemic heart disease and stroke persist as leading causes of death, there has been progress in reducing their age-standardised mortality rates globally. Four other leading causes have also shown large declines in global age-standardised mortality rates across the study period: diarrhoeal diseases, tuberculosis, stomach cancer, and measles. Other causes of death showed disparate patterns between sexes, notably for deaths from conflict and terrorism in some locations. A large reduction in age-standardised rates of YLLs occurred for neonatal disorders. Despite this, neonatal disorders remained the leading cause of global YLLs over the period studied, except in 2021, when COVID-19 was temporarily the leading cause. Compared to 1990, there has been a considerable reduction in total YLLs in many vaccine-preventable diseases, most notably diphtheria, pertussis, tetanus, and measles. In addition, this study quantified the mean age at death for all-cause mortality and cause-specific mortality and found noticeable variation by sex and location. The global all-cause mean age at death increased from 46·8 years (95% UI 46·6-47·0) in 1990 to 63·4 years (63·1-63·7) in 2023. For males, mean age increased from 45·4 years (45·1-45·7) to 61·2 years (60·7-61·6), and for females it increased from 48·5 years (48·1-48·8) to 65·9 years (65·5-66·3), from 1990 to 2023. The highest all-cause mean age at death in 2023 was found in the high-income super-region, where the mean age for females reached 80·9 years (80·9-81·0) and for males 74·8 years (74·8-74·9). By comparison, the lowest all-cause mean age at death occurred in sub-Saharan Africa, where it was 38·0 years (37·5-38·4) for females and 35·6 years (35·2-35·9) for males in 2023. Lastly, our study found that all-cause 70q0 decreased across each GBD super-region and region from 2000 to 2023, although with large variability between them. For females, we found that 70q0 notably increased from drug use disorders and conflict and terrorism. Leading causes that increased 70q0 for males also included drug use disorders, as well as diabetes. In sub-Saharan Africa, there was an increase in 70q0 for many non-communicable diseases (NCDs). Additionally, the mean age at death from NCDs was lower than the expected mean age at death for this super-region. By comparison, there was an increase in 70q0 for drug use disorders in the high-income super-region, which also had an observed mean age at death lower than the expected value. INTERPRETATION: We examined global mortality patterns over the past three decades, highlighting-with enhanced estimation methods-the impacts of major events such as the COVID-19 pandemic, in addition to broader trends such as increasing NCDs in low-income regions that reflect ongoing shifts in the global epidemiological transition. This study also delves into premature mortality patterns, exploring the interplay between age and causes of death and deepening our understanding of where targeted resources could be applied to further reduce preventable sources of mortality. We provide essential insights into global and regional health disparities, identifying locations in need of targeted interventions to address both communicable and non-communicable diseases. There is an ever-present need for strengthened health-care systems that are resilient to future pandemics and the shifting burden of disease, particularly among ageing populations in regions with high mortality rates. Robust estimates of causes of death are increasingly essential to inform health priorities and guide efforts toward achieving global health equity. The need for global collaboration to reduce preventable mortality is more important than ever, as shifting burdens of disease are affecting all nations, albeit at different paces and scales. FUNDING: Gates Foundation.

BACKGROUND: The relationship between triglyceride-glucose (TyG) index, an emerging marker of insulin resistance, and the risk of incident heart failure (HF) was unclear. This study thus aimed to investigate this relationship. METHODS: Subjects without prevalent cardiovascular diseases from the prospective Kailuan cohort (recruited during 2006-2007) and a retrospective cohort of family medicine patients from Hong Kong (recruited during 2000-2003) were followed up until December 31st, 2019 for the outcome of incident HF. Separate adjusted hazard ratios (aHRs) summarizing the relationship between TyG index and HF risk in the two cohorts were combined using a random-effect meta-analysis. Additionally, a two-sample Mendelian randomization (MR) of published genome-wide association study data was performed to assess the causality of observed associations. RESULTS: In total, 95,996 and 19,345 subjects from the Kailuan and Hong Kong cohorts were analyzed, respectively, with 2,726 cases of incident HF in the former and 1,709 in the latter. Subjects in the highest quartile of TyG index had the highest risk of incident HF in both cohorts (Kailuan: aHR 1.23 (95% confidence interval: 1.09-1.39), PTrend <0.001; Hong Kong: aHR 1.21 (1.04-1.40), PTrend =0.007; both compared with the lowest quartile). Meta-analysis showed similar results (highest versus lowest quartile: HR 1.22 (1.11-1.34), P < 0.001). Findings from MR analysis, which included 47,309 cases and 930,014 controls, supported a causal relationship between higher TyG index and increased risk of HF (odds ratio 1.27 (1.15-1.40), P < 0.001). CONCLUSION: A higher TyG index is an independent and causal risk factor for incident HF in the general population. CLINICAL TRIAL REGISTRATION: URL: https://www.chictr.org.cn ; Unique identifier: ChiCTR-TNRC-11,001,489.

Introduction: The effects of sodium-glucose cotransporter 2 inhibitors (SGLT2I) and dipeptidyl peptidase-4 inhibitors (DPP4I) on new-onset cognitive dysfunction in type 2 diabetes mellitus remain unknown. This study aimed to evaluate the effects of the two novel antidiabetic agents on cognitive dysfunction by comparing the rates of dementia between SGLT2I and DPP4I users. Methods: This was a population-based cohort study of type 2 diabetes mellitus patients treated with SGLT2I and DPP4I between January 1, 2015 and December 31, 2019 in Hong Kong. Exclusion criteria were &amp;lt;1-month exposure or exposure to both medication classes, or prior diagnosis of dementia or major neurological/psychiatric diseases. Primary outcomes were new-onset dementia, Alzheimer's, and Parkinson's. Secondary outcomes were all-cause, cardiovascular, and cerebrovascular mortality. Results: A total of 13,276 SGLT2I and 36,544 DPP4I users (total n = 51,460; median age: 66.3 years old [interquartile range (IQR): 58–76], 55.65% men) were studied (follow-up: 472 [120–792] days). After 1:2 matching (SGLT2I: n = 13,283; DPP4I: n = 26,545), SGLT2I users had lower incidences of dementia (0.19 vs. 0.78%, p &amp;lt; 0.0001), Alzheimer's (0.01 vs. 0.1%, p = 0.0047), Parkinson's disease (0.02 vs. 0.14%, p = 0.0006), all-cause (5.48 vs. 12.69%, p &amp;lt; 0.0001), cerebrovascular (0.88 vs. 3.88%, p &amp;lt; 0.0001), and cardiovascular mortality (0.49 vs. 3.75%, p &amp;lt; 0.0001). Cox regression showed that SGLT2I use was associated with lower risks of dementia (hazard ratio [HR]: 0.41, 95% confidence interval [CI]: [0.27–0.61], P &amp;lt; 0.0001), Parkinson's (HR:0.28, 95% CI: [0.09–0.91], P = 0.0349), all-cause (HR:0.84, 95% CI: [0.77–0.91], P &amp;lt; 0.0001), cardiovascular (HR:0.64, 95% CI: [0.49–0.85], P = 0.0017), and cerebrovascular (HR:0.36, 95% CI: [0.3–0.43], P &amp;lt; 0.0001) mortality. Conclusions: The use of SGLT2I is associated with lower risks of dementia, Parkinson's disease, and cerebrovascular mortality compared with DPP4I use after 1:2 ratio propensity score matching.

BACKGROUND: People with cancer are at increased risk of hospitalisation and death following infection with SARS-CoV-2. Therefore, we aimed to conduct one of the first evaluations of vaccine effectiveness against breakthrough SARS-CoV-2 infections in patients with cancer at a population level. METHODS: In this population-based test-negative case-control study of the UK Coronavirus Cancer Evaluation Project (UKCCEP), we extracted data from the UKCCEP registry on all SARS-CoV-2 PCR test results (from the Second Generation Surveillance System), vaccination records (from the National Immunisation Management Service), patient demographics, and cancer records from England, UK, from Dec 8, 2020, to Oct 15, 2021. Adults (aged ≥18 years) with cancer in the UKCCEP registry were identified via Public Health England's Rapid Cancer Registration Dataset between Jan 1, 2018, and April 30, 2021, and comprised the cancer cohort. We constructed a control population cohort from adults with PCR tests in the UKCCEP registry who were not contained within the Rapid Cancer Registration Dataset. The coprimary endpoints were overall vaccine effectiveness against breakthrough infections after the second dose (positive PCR COVID-19 test) and vaccine effectiveness against breakthrough infections at 3-6 months after the second dose in the cancer cohort and control population. FINDINGS: The cancer cohort comprised 377 194 individuals, of whom 42 882 had breakthrough SARS-CoV-2 infections. The control population consisted of 28 010 955 individuals, of whom 5 748 708 had SARS-CoV-2 breakthrough infections. Overall vaccine effectiveness was 69·8% (95% CI 69·8-69·9) in the control population and 65·5% (65·1-65·9) in the cancer cohort. Vaccine effectiveness at 3-6 months was lower in the cancer cohort (47·0%, 46·3-47·6) than in the control population (61·4%, 61·4-61·5). INTERPRETATION: COVID-19 vaccination is effective for individuals with cancer, conferring varying levels of protection against breakthrough infections. However, vaccine effectiveness is lower in patients with cancer than in the general population. COVID-19 vaccination for patients with cancer should be used in conjunction with non-pharmacological strategies and community-based antiviral treatment programmes to reduce the risk that COVID-19 poses to patients with cancer. FUNDING: University of Oxford, University of Southampton, University of Birmingham, Department of Health and Social Care, and Blood Cancer UK.

Background: Given the rapidly growing burden of cardiovascular disease (CVD) in Asia, this study forecasts the CVD burden and associated risk factors in Asia from 2025 to 2050. Methods: Data from the Global Burden of Disease 2019 study was used to construct regression models predicting prevalence, mortality, and disability-adjusted life years (DALYs) attributed to CVD and risk factors in Asia in the coming decades. Findings: Between 2025 and 2050, crude cardiovascular mortality is expected to rise 91.2% despite a 23.0% decrease in the age-standardised cardiovascular mortality rate (ASMR). Ischaemic heart disease (115 deaths per 100,000 population) and stroke (63 deaths per 100,000 population) will remain leading drivers of ASMR in 2050. Central Asia will have the highest ASMR (676 deaths per 100,000 population), more than three-fold that of Asia overall (186 deaths per 100,000 population), while high-income Asia sub-regions will incur an ASMR of 22 deaths per 100,000 in 2050. High systolic blood pressure will contribute the highest ASMR throughout Asia (105 deaths per 100,000 population), except in Central Asia where high fasting plasma glucose will dominate (546 deaths per 100,000 population). Interpretation: This forecast forewarns an almost doubling in crude cardiovascular mortality by 2050 in Asia, with marked heterogeneity across sub-regions. Atherosclerotic diseases will continue to dominate, while high systolic blood pressure will be the leading risk factor. Funding: This was supported by the NUHS Seed Fund (NUHSRO/2022/058/RO5+6/Seed-Mar/03), National Medical Research Council Research Training Fellowship (MH 095:003/008-303), National University of Singapore Yong Loo Lin School of Medicine's Junior Academic Fellowship Scheme, NUHS Clinician Scientist Program (NCSP2.0/2024/NUHS/NCWS) and the CArdiovascular DiseasE National Collaborative Enterprise (CADENCE) National Clinical Translational Program (MOH-001277-01).

Abstract Aims To examine the effects of sodium-glucose cotransporter-2 inhibitors (SGLT2i) on cardiac remodelling in patients with type 2 diabetes mellitus (T2DM) and/or heart failure (HF), and to explore the subsets of patients who may have greater benefit from SGLT2i therapy. Methods and results Four electronic databases were searched for randomized controlled trials (RCTs) that evaluated the effects of SGLT2i on parameters reflecting cardiac remodelling in patients with T2DM and/or HF. Standardized mean differences (SMDs) or mean differences (MDs) were pooled. Subgroup analyses were performed according to the baseline HF and T2DM, HF type, SGLT2i agent, follow-up duration, and imaging modality. A total of 13 RCTs involving 1251 patients were analysed. Sodium-glucose cotransporter-2 inhibitors treatment significantly improved left ventricular (LV) ejection fraction [SMD, 0.35; 95% confidence interval (CI) (0.04, 0.65); P = 0.03], LV mass [SMD, −0.48; 95% CI (−0.79, −0.18); P = 0.002], LV mass index [SMD, −0.27; 95% CI (−0.49, −0.05); P = 0.02], LV end-systolic volume [SMD, −0.37; 95% CI (−0.71; −0.04); P = 0.03], LV end-systolic volume index [MD, −0.35 mL/m2; 95% CI (−0.64, −0.05); P = 0.02], and E-wave deceleration time [SMD, −0.37; 95% CI (−0.70, −0.05); P = 0.02] in the overall population. Subgroup analyses showed that the favourable effects of SGLT2i on LV remodelling were only significant in HF patients, especially HF with reduced ejection fraction (HFrEF), regardless of glycaemic status. Among the four included SGLT2i, empagliflozin was associated with a greater improvement of LV mass, LV mass index, LV end-systolic volume, LV end-systolic volume index, LV end-diastolic volume, and LV end-diastolic volume index (all P &amp;lt; 0.05). Conclusions Sodium-glucose cotransporter-2 inhibitors treatment significantly reversed cardiac remodelling, improving LV systolic and diastolic function, LV mass and volume, especially in patients with HFrEF and amongst those taking empagliflozin compared with other SGLT2i. Reversed remodelling may be a mechanism responsible for the favourable clinical effects of SGLT2i on HF.

Cardiovascular diseases are one of the leading global causes of mortality. Currently, clinicians rely on their own analyses or automated analyses of the electrocardiogram (ECG) to obtain a diagnosis. However, both approaches can only include a finite number of predictors and are unable to execute complex analyses. Artificial intelligence (AI) has enabled the introduction of machine and deep learning algorithms to compensate for the existing limitations of current ECG analysis methods, with promising results. However, it should be prudent to recognize that these algorithms also associated with their own unique set of challenges and limitations, such as professional liability, systematic bias, surveillance, cybersecurity, as well as technical and logistical challenges. This review aims to increase familiarity with and awareness of AI algorithms used in ECG diagnosis, and to ultimately inform the interested stakeholders on their potential utility in addressing present clinical challenges.

BACKGROUND: Evidence suggests that digital mental health interventions (DMHIs) for common mental health conditions are effective. However, digital interventions, such as face-to-face therapies, pose risks to patients. A safe intervention is considered one in which the measured benefits outweigh the identified and mitigated risks. OBJECTIVE: This study aims to review the literature to assess how DMHIs assess safety, what risks are reported, and how they are mitigated in both the research and postmarket phases and building on existing recommendations for assessing, reporting, and mitigating safety in the DMHI and standardizing practice. METHODS: PsycINFO, Embase, and MEDLINE databases were searched for studies that addressed the safety of DMHIs. The inclusion criteria were any study that addressed the safety of a clinical DMHI, even if not as a main outcome, in an adult population, and in English. As the outcome data were mainly qualitative in nature, a meta-analysis was not possible, and qualitative analysis was used to collate the results. Quantitative results were synthesized in the form of tables and percentages. To illustrate the use of a single common safety metric across studies, we calculated odds ratios and CIs, wherever possible. RESULTS: Overall, 23 studies were included in this review. Although many of the included studies assessed safety by actively collecting adverse event (AE) data, over one-third (8/23, 35%) did not assess or collect any safety data. The methods and frequency of safety data collection varied widely, and very few studies have performed formal statistical analyses. The main treatment-related reported AE was symptom deterioration. The main method used to mitigate risk was exclusion of high-risk groups. A secondary web-based search found that 6 DMHIs were available for users or patients to use (postmarket phase), all of which used indications and contraindications to mitigate risk, although there was no evidence of ongoing safety review. CONCLUSIONS: The findings of this review show the need for a standardized classification of AEs, a standardized method for assessing AEs to statically analyze AE data, and evidence-based practices for mitigating risk in DMHIs, both in the research and postmarket phases. This review produced 7 specific, measurable, and achievable recommendations with the potential to have an immediate impact on the field, which were implemented across ongoing and future research. Improving the quality of DMHI safety data will allow meaningful assessment of the safety of DMHIs and confidence in whether the benefits of a new DMHI outweigh its risks. TRIAL REGISTRATION: PROSPERO CRD42022333181; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=333181.

OBJECTIVE: To compare the effects of sodium-glucose cotransporter 2 inhibitors (SGLT2Is) and dipeptidyl peptidase-4 inhibitors (DPP4Is) on adverse outcomes in diabetic patients in Hong Kong. METHODS: This was a retrospective population-based cohort study of type 2 diabetes mellitus patients (n = 72,746) treated with SGLT2I or DPP4I between January 1, 2015, and December 31, 2020, in Hong Kong. Patients with exposure to both DPP4I and SGLT2I therapy, without complete demographics or mortality data, or who had prior atrial fibrillation (AF) were excluded. The study outcomes were new-onset AF, stroke/transient ischemic attack, cardiovascular mortality and all-cause mortality. Propensity score matching (1:1 ratio) between SGLT2I and DPP4I users was performed. RESULTS: The unmatched study cohort included 21,713 SGLT2I users and 39,510 DPP4I users (total: n = 61,233 patients; 55.37% males, median age: 62.7 years [interquartile range (IQR): 54.6-71.9 years]). Over a median follow-up of 2030 (IQR: 1912-2117) days, 2496 patients (incidence rate [IR]: 4.07%) developed new-onset AF, 2179 patients (IR: 3.55%) developed stroke/transient ischemic attack, 1963 (IR: 3.20%) died from cardiovascular causes and 6607 patients (IR: 10.79%) suffered from all-cause mortality. After propensity score matching (SGLT2I: n = 21,713; DPP4I: n = 21,713), SGLT2I users showed lower incidence of new-onset AF (1.96% vs. 2.78%, standardized mean difference [SMD] = 0.05), stroke (1.80% vs. 3.52%, SMD = 0.11), cardiovascular mortality (0.47% vs. 1.56%, SMD = 0.11) and all-cause mortality (2.59% vs. 7.47%, SMD = 0.22) compared to DPP4I users. Cox regression found that SGLT2I users showed lower risk of new-onset AF (hazard ratio [HR]: 0.68, 95% confidence interval [CI]: [0.56, 0.83], P = 0.0001), stroke (HR: 0.64, 95% CI: [0.53, 0.79], P < 0.0001), cardiovascular mortality (HR: 0.39, 95% CI: [0.27, 0.56], P < 0.0001) and all-cause mortality (HR: 0.44, 95% CI: [0.37, 0.51], P < 0.0001) after adjusting for significant demographics, past comorbidities, medications and laboratory tests. CONCLUSIONS: Based on real-world data of type 2 diabetic patients in Hong Kong, SGLT2I use was associated with lower risk of incident AF, stroke/transient ischemic attack, and cardiovascular and all-cause mortality outcomes compared to DPP4I use.

Metformin is one of the most widely used drugs for type 2 diabetes and it also exhibits cardiovascular protective activity. However, the underlying mechanism of its action is not well understood. Here, we used an adult zebrafish model of heart cryoinjury, which mimics myocardial infarction in humans, and demonstrated that autophagy was significantly induced in the injured area. Through a systematic evaluation of the multiple cell types related to cardiac regeneration, we found that metformin enhanced the autophagic flux and improved epicardial, endocardial and vascular endothelial regeneration, accelerated transient collagen deposition and resolution, and induced cardiomyocyte proliferation. Whereas, when the autophagic flux was blocked, then all these processes were delayed. We also showed that metformin transiently enhanced the systolic function of the heart. Taken together, our results indicate that autophagy is positively involved in the metformin-induced acceleration of heart regeneration in zebrafish and suggest that this well-known diabetic drug has clinical value for the prevention and amelioration of myocardial infarction.

Atrial cardiomyopathy refers to structural and electrical remodelling of the atria, which can lead to impaired mechanical function. While historical studies have implicated atrial fibrillation as the leading cause of cardioembolic stroke, atrial cardiomyopathy may be an important, underestimated contributor. To date, the relationship between atrial cardiomyopathy, atrial fibrillation, and cardioembolic stroke remains obscure. This review summarizes the pathogenesis of atrial cardiomyopathy, with a special focus on neurohormonal and inflammatory mechanisms, as well as the role of adipose tissue, especially epicardial fat in atrial remodelling. It reviews the current evidence implicating atrial cardiomyopathy as a cause of embolic stroke, with atrial fibrillation as a lagging marker of an increased thrombogenic atrial substrate. Finally, it discusses the potential of antithrombotic therapy in embolic stroke with undetermined source and appraises the available diagnostic techniques for atrial cardiomyopathy, including imaging techniques such as echocardiography, computed tomography, and magnetic resonance imaging as well as electroanatomic mapping, electrocardiogram, biomarkers, and genetic testing. More prospective studies are needed to define the relationship between atrial cardiomyopathy, atrial fibrillation, and embolic stroke and to establish a prompt diagnosis and specific treatment strategies in these patients with atrial cardiomyopathy for the secondary and even primary prevention of embolic stroke.

Nearly 30% of ischemic strokes have an unknown cause, which are referred to as cryptogenic strokes (CS). Imaging studies suggest that a large proportion of these patients show features that are consistent with embolism, and thus the term embolic stroke of undetermined source (ESUS) was proposed to describe these CS patients. Atrial cardiomyopathy predisposes to thrombus formation and thus embolic stroke even in the absence of atrial fibrillation (AF). This may provide a mechanistic link with ESUS, suggesting that anticoagulant therapy may be more beneficial than antiplatelet therapy in ESUS patients with atrial cardiomyopathy. The present review discusses the concept of atrial cardiomyopathy and ESUS and the relationship between them based on the mechanisms and clinical evidence, suggests that atrial cardiomyopathy may be a potential mechanism of ESUS, and highlights a theoretical basis that supports that anticoagulant therapy may be more applicable to ESUS patients with atrial cardiomyopathy and aims to help us better understand and identify the risk of ESUS, thereby improving the management of these patients in clinical practice.

Soluble suppression of tumorigenicity 2 (sST2) is a member of the interleukin-1 receptor family. It is raised in various cardiovascular diseases, but its value in predicting disease severity or mortality outcomes has been controversial. Therefore, we conducted a systematic review and meta-analysis to determine whether sST2 levels differed between survivors and non-survivors of patients with cardiovascular diseases, and whether elevated sST2 levels correlated with adverse outcomes. PubMed and Embase were searched until 23rd June 2021 for studies that evaluated the relationship between sST2 levels and cardiovascular disease severity or mortality. A total of 707 entries were retrieved from both databases, of which 14 studies were included in the final meta-analysis. In acute heart failure, sST2 levels did not differ between survivors and non-survivors (mean difference [MD]: 24.2 ± 13.0 ng/ml; P = 0.06; I2: 95%). Elevated sST2 levels tend to be associated with increased mortality risk (hazard ratio [HR]: 1.12, 95 %CI: 0.99–1.27, P = 0.07; I2: 88%). In chronic heart failure, sST2 levels were higher in non-survivors than in survivors (MD: 0.19 ± 0.04 ng/ml; P = 0.001; I2: 0%) and elevated levels were associated with increased mortality risk (HR: 1.64, 95% CI: 1.27–2.12, P < 0.001; I2: 82%). sST2 levels were significantly higher in severe disease compared to less severe disease (MD: 1.56 ± 0.46 ng/ml; P = 0.001; I2: 98%). Finally, in stable coronary artery disease, sST2 levels were higher in non-survivors than survivors (MD: 3.0 ± 1.1 ng/ml; P = 0.005; I2: 80%) and elevated levels were significantly associated with increased mortality risk (HR: 1.32, 95% CI: 1.04–1.68, P < 0.05; I2: 57%). sST2 significantly predicts disease severity and mortality in cardiovascular disease and is a good predictor of mortality in patients with stable coronary artery disease and chronic heart failure.

Southeast Asia has a population of over 680 million people—approximately half the population of India and twice the population of the United States—and is a region marked by rich and complex histories and cultures, dynamic growth, and unique and evolving health challenges.1 Despite the momentum of economic development, health inequalities persist. These inequities have been aggravated since the COVID-19 pandemic, which pushed millions further into poverty, possibly exacerbating health disparities, especially among populations who suffer vulnerabilities.

INTRODUCTION: Patients with diabetes mellitus are risk of premature death. In this study, we developed a machine learning-driven predictive risk model for all-cause mortality among patients with type 2 diabetes mellitus using multiparametric approach with data from different domains. RESEARCH DESIGN AND METHODS: This study used territory-wide data of patients with type 2 diabetes attending public hospitals or their associated ambulatory/outpatient facilities in Hong Kong between January 1, 2009 and December 31, 2009. The primary outcome is all-cause mortality. The association of risk variables and all-cause mortality was assessed using Cox proportional hazards models. Machine and deep learning approaches were used to improve overall survival prediction and were evaluated with fivefold cross validation method. RESULTS: A total of 273 678 patients (mean age: 65.4±12.7 years, male: 48.2%, median follow-up: 142 (IQR=106-142) months) were included, with 91 155 deaths occurring on follow-up (33.3%; annualized mortality rate: 3.4%/year; 2.7 million patient-years). Multivariate Cox regression found the following significant predictors of all-cause mortality: age, male gender, baseline comorbidities, anemia, mean values of neutrophil-to-lymphocyte ratio, high-density lipoprotein-cholesterol, total cholesterol, triglyceride, HbA1c and fasting blood glucose (FBG), measures of variability of both HbA1c and FBG. The above parameters were incorporated into a score-based predictive risk model that had a c-statistic of 0.73 (95% CI 0.66 to 0.77), which was improved to 0.86 (0.81 to 0.90) and 0.87 (0.84 to 0.91) using random survival forests and deep survival learning models, respectively. CONCLUSIONS: A multiparametric model incorporating variables from different domains predicted all-cause mortality accurately in type 2 diabetes mellitus. The predictive and modeling capabilities of machine/deep learning survival analysis achieved more accurate predictions.

Abstract Objectives The effects of sodium-glucose cotransporter 2 inhibitors (SGLT2I) vs dipeptidyl peptidase-4 inhibitors (DPP4I) on the risk of new-onset gout remains unknown. This study aims to compare the effects of SGLT2I against DPP4I on gout risks. Methods This was a retrospective population-based cohort study of patients with type-2 diabetes mellitus treated with SGLT2I or DPP4I between 1 January 2015 and 31 December 2020 in Hong Kong. The study outcomes are new-onset gout and all-cause mortality. Propensity score matching (1:1 ratio) between SGLT2I and DPP4I was performed. Univariable and multivariable Cox regression models were conducted. Competing risks models and multiple approaches based on the propensity score were applied. Results This study included 43 201 patients [median age: 63.23 years old (Interquartile range, IQR): 55.21–71.95, 53.74% males; SGLT2I group: n = 16 144; DPP4I group: n = 27 057] with a median follow-up of 5.59 years (IQR: 5.27–5.81 years) since initial drug exposure. The incidence rate of developing gout [Incidence rate (IR): 2.5; 95% CI: 2.2, 2.9] among SGLT2I users was significantly lower than DPP4I users (IR: 5.2; 95% CI: 4.8, 5.8). SGLT2I was associated with 51% lower risks of gout (HR: 0.49; 95% CI: 0.42, 0.58; P-value &amp;lt; 0.0001) and 51% lower risks of all-cause mortality (HR: 0.49; 95% CI: 0.42, 0.58; P-value &amp;lt; 0.0001) after adjusting for significant demographics, past comorbidities, medications and laboratory results. The results remained consistent on competing risk and other propensity score approaches. Conclusions SGLT2I use was associated with lower risks of new gout diagnosis compared with DPP4I use.

INTRODUCTION: Metabolic abnormalities may exacerbate the risk of adverse outcomes in patients with type 2 diabetes mellitus. The present study aims to assess the predictive value of HbA1c and lipid variability on the risks of sudden cardiac death (SCD) and incident atrial fibrillation (AF). METHODS: The retrospective observational study consists of type 2 diabetic patients prescribed with insulin, who went to publicly funded clinics and hospitals in Hong Kong between January 1, 2009 and December 31, 2009. Variability in total cholesterol, low-density lipoprotein-cholesterol (LDL-C), high-density lipoprotein-cholesterol (HDL-C), triglyceride, and HbA1c were assessed through their SD and coefficient of variation. The primary outcomes were incident (1) ventricular tachycardia/ventricular fibrillation, actual or aborted SCD and (2) AF. RESULTS: A total of 23 329 patients (mean ± SD age: 64 ± 14 years old; 51% male; mean HbA1c 8.6 ± 1.3%) were included. On multivariable analysis, HbA1c, total cholesterol, LDL-C and triglyceride variability were found to be predictors of SCD (p < .05). CONCLUSION: HbA1c and lipid variability were predictive of SCD. Therefore, poor glucose control and variability in lipid parameters in diabetic patients are associated with aborted or actual SCD. These observations suggest the need to re-evaluate the extent of glycemic control required for outcome optimization.

Background Commonly prescribed diabetic medications such as metformin and sulfonylurea may be associated with different arrhythmogenic risks. This study compared the risk of ventricular arrhythmia or sudden cardiac death between metformin and sulfonylurea users in patients with type 2 diabetes. Methods and Results Patients aged ≥40 years who were diagnosed with type 2 diabetes or prescribed antidiabetic agents in Hong Kong between January 1, 2009, and December 31, 2009, were included and followed up until December 31, 2019. Patients prescribed with both metformin and sulfonylurea or had prior myocardial infarction were excluded. The study outcome was a composite of ventricular arrhythmia or sudden cardiac death. Metformin users and sulfonylurea users were matched at a 1:1 ratio by propensity score matching. The matched cohort consisted of 16 596 metformin users (47.70% men; age, 68±11 years; mean follow-up, 4.92±2.55 years) and 16 596 sulfonylurea users (49.80% men; age, 70±11 years; mean follow-up, 4.93±2.55 years). Sulfonylurea was associated with higher risk of ventricular arrhythmia or sudden cardiac death than metformin hazard ratio (HR, 1.90 [95% CI, 1.73-2.08]). Such difference was consistently observed in subgroup analyses stratifying for insulin usage or known coronary heart disease. Conclusions Sulfonylurea use is associated with higher risk of ventricular arrhythmia or sudden cardiac death than metformin in patients with type 2 diabetes.

Abstract Aims The angiotensin receptor–neprilysin inhibitor (ARNI), sacubitril/valsartan, confers additional protective effects compared with angiotensin-converting enzyme inhibitors/angiotensin II receptor blockers (ACEIs/ARBs) in terms of reversed left ventricular (LV) remodelling and improves the prognosis of patients with heart failure (HF). However, few studies have examined the effects of ARNI on the left atrium. Accordingly, this study compared the effects of ARNI and ACEI/ARB on left atrial (LA) remodelling in heart failure with reduced ejection fraction (HFrEF). Methods and results This was a single-centre retrospective study of patients with HFrEF hospitalized at the First Affiliated Hospital of Dalian Medical University between 26 February 2016 and 8 July 2020. Patients were classified into ARNI and ACEI/ARB groups and further subgroups based on the left atrial volume index (LAVI): mildly abnormal (29 mL/m2 ≤ LAVI &amp;lt; 34 mL/m2), moderately abnormal (34 mL/m2 ≤ LAVI &amp;lt; 40 mL/m2), and severely abnormal (LAVI ≥ 40 mL/m2). The primary endpoint was changes in LA parameters by echocardiography. The secondary endpoint was all-cause mortality. A total of 336 patients (mean age: 64.11 ± 12.86, 30.06% female) were included. Except those lost to follow-up, 274 HFrEF patients remained, with 144 cases in the ARNI group and 130 cases in the ACEI/ARB group. Greater reductions from baseline were seen with ARNI in LA diameter (LAD) (P = 0.013, t-test), superior and LA superior–inferior diameter (LASID) (P &amp;lt; 0.0001), LA transverse diameter (LATD) (P &amp;lt; 0.0001), LA volume (LAV) (P &amp;lt; 0.0001), LAVI (P &amp;lt; 0.0001), and LA sphericity index (LASI) (P &amp;lt; 0.0001). Over a mean follow-up of 19.40 months, 97 patients (67.3%) in the ARNI group and 29 patients (22.3%) in the ACEI/ARB group showed LA reverse remodelling (LARR). Kaplan–Meier analysis showed significantly lower overall mortality in the ARNI group compared with the ACEI/ARB group (P = 0.048, log-rank test). The mildly abnormal LAVI group of ARNI patients showed a reduction in mortality compared with ACEI/ARB patients (P = 0.044). However, no significant difference was observed for the moderately abnormal (P = 0.571) or severely abnormal LAVI groups (P = 0.609), suggesting that early initiation of ARNI was associated with a better prognosis. Conclusions In this proof-of-concept study, ARNI use showed greater effects on LARR and was associated with a better prognosis compared with ACEI/ARB use in HFrEF. Early initiation of ARNI in the HF disease process may produce greater benefit, but this needs to be confirmed in future studies.

AIMS: There is an emerging interest in elucidating the natural history and prognosis for patients with heart failure with reduced ejection fraction (HFrEF) in whom left ventricular ejection fraction (LVEF) subsequently improves. The characteristics and outcomes were compared between heart failure with recovered ejection fraction (HFrecEF) and persistent HFrEF. METHODS AND RESULTS: This is a retrospective study of adults who underwent at least two echocardiograms 3 months apart between 1 November 2015 and 31 October 2019 with an initial diagnosis of HFrEF. The subjects were divided into HFrecEF group (second LVEF > 40%, ≥10% absolute improvement in LVEF) and persistent HFrEF group (<10% absolute improvement in LVEF) according to the second LVEF. To further study the characteristics of HFrecEF patients, the cohort was further divided into LVEF improvement of 10-20% and >20% subgroups. The primary outcomes were all-cause mortality and rehospitalization. A total of 1160 HFrEF patients were included [70.2% male, mean (standard deviation) age: 62 ± 13 years]. On the second echocardiogram, 284 patients (24.5%) showed HFrecEF and 876 patients (75.5%) showed persistent HFrEF. All-cause mortality was identified in 23 (8.10%) HFrecEF and 165 (18.84%) persistent HFrEF, whilst 76 (26.76%) and 426 (48.63%) showed rehospitalizations, respectively. Survival analysis showed that the persistent HFrEF subgroup experienced a significantly higher mortality at 12 and 24 months and a higher hospitalization at 12, 24, 48, and more than 48 months following discharge. Multivariate Cox regression showed that persistent HFrEF had a higher risk of all-cause mortality [hazard ratio (HR) 2.30, 95% confidence interval (CI) 1.49-3.56, P = 0.000] and rehospitalization (HR 1.85, 95% CI 1.45-2.36, P = 0.000) than the HFrecEF group. Subgroup analysis showed that the LVEF ≥ 20% improvement subgroup had lower rates of adverse outcomes compared with those with less improvement of 10-20%. CONCLUSIONS: Heart failure with recovered ejection fraction is a distinct HF phenotype with better clinical outcomes compared with those with persistent HFrEF. HFrecEF patients have a relatively better short-term mortality at 24 months but not thereafter.