Comparison of Sodium-Glucose Cotransporter-2 Inhibitor and Dipeptidyl Peptidase-4 Inhibitor on the Risks of New-Onset Atrial Fibrillation, Stroke and Mortality in Diabetic Patients: A Propensity Score-Matched Study in Hong Kong.

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.

Risk stratification of sudden cardiac death in asymptomatic female Brugada syndrome patients: A literature review.

BACKGROUND AND OBJECTIVES: Risk stratification in Brugada syndrome remains a difficult problem. Given the male predominance of this disease and their elevated risks of arrhythmic events, affected females have received less attention. It is widely known that symptomatic patients are at increased risk of sudden cardiac death (SCD) than asymptomatic patients, while this might be true in the male population; recent studies have shown that this association might not be significant in females. Over the past few decades, numerous markers involving clinical symptoms, electrocardiographic (ECG) indices, and genetic tests have been explored, with several risk-scoring models developed so far. The objective of this study is to review the current evidence of clinical and ECG markers as well as risk scores on asymptomatic females with Brugada syndrome. FINDINGS: Gender differences in ECG markers, the yield of genetic findings, and the applicability of risk scores are highlighted. CONCLUSIONS: Various clinical, electrocardiographic, and genetic risk factors are available for assessing SCD risk amongst asymptomatic female BrS patients. However, due to the significant gender discrepancy in BrS, the SCD risk amongst females is often underestimated, and there is a lack of research on female-specific risk factors and multiparametric risk scores. Therefore, multinational studies pooling female BrS patients are needed for the development of a gender-specific risk stratification approach amongst asymptomatic BrS patients.

Diagnostic and prognostic value of serum C-reactive protein in heart failure with preserved ejection fraction: a systematic review and meta-analysis.

Heart failure (HF) is a major epidemic with rising morbidity and mortality rates that encumber global healthcare systems. While some studies have demonstrated the value of CRP in predicting (i) the development of HFpEF and (ii) long-term clinical outcomes in HFpEF patients, others have shown no such correlation. As a result, we conducted the following systematic review and meta-analysis to assess both the diagnostic and prognostic role of CRP in HFpEF. PubMed and Embase were searched for studies that assess the relationship between CRP and HFpEF using the following search terms: (((C-reactive protein) AND ((preserved ejection fraction) OR (diastolic heart failure))). The search period was from the start of database to August 6, 2019, with no language restrictions. A total of 312 and 233 studies were obtained from PubMed and Embase respectively, from which 19 studies were included. Our meta-analysis demonstrated the value of a high CRP in predicting the development of not only new onset HFpEF (HR: 1.08; 95% CI: 1.00-1.16; P = 0.04; I2 = 22%), but also an increased risk of cardiovascular mortality when used as a categorical (HR: 2.52; 95% CI: 1.61-3.96; P < 0.0001; I2 = 19%) or a continuous variable (HR: 1.24; 95% CI: 1.04-1.47; P = 0.01; I2 = 28%), as well as all-cause mortality when used as a categorical (HR: 1.78; 95% CI: 1.53-2.06; P < 0.00001; I2 = 0%) or a continuous variable: (HR: 1.06; 95% CI: 1.02-1.06; P = 0.003; I2 = 61%) in HFpEF patients. CRP can be used as a biomarker to predict the development of HFpEF and long-term clinical outcomes in HFpEF patients, in turn justifying its use as a simple, accessible parameter to guide clinical management in this patient population. However, more prospective studies are still required to not only explore the utility and dynamicity of CRP in HFpEF but also to determine whether risk stratification algorithms incorporating CRP actually provide a material benefit in improving patient prognosis.

Multi-parametric system for risk stratification in mitral regurgitation: A multi-task Gaussian prediction approach.

BACKGROUND: We hypothesized that a multi-parametric approach incorporating medical comorbidity information, electrocardiographic P-wave indices, echocardiographic assessment, neutrophil-to-lymphocyte ratio (NLR) and prognostic nutritional index (PNI) calculated from laboratory data can improve risk stratification in mitral regurgitation (MR). METHODS: Patients diagnosed with mitral regurgitation between 1 March 2005 and 30 October 2018 from a single centre were retrospectively analysed. Outcomes analysed were incident atrial fibrillation (AF), transient ischemic attack (TIA)/stroke and mortality. RESULTS: This study cohort included 706 patients, of whom 171 had normal inter-atrial conduction, 257 had inter-atrial block (IAB) and 266 had AF at baseline. Logistic regression analysis showed that age, hypertension and mean P-wave duration (PWD) were significant predictors of new-onset AF. Low left ventricular ejection fraction (LVEF), abnormal P-wave terminal force in V1 (PTFV1) predicted TIA/stroke. Age, smoking, hypertension, diabetes mellitus, hypercholesterolaemia, ischemic heart disease, secondary mitral regurgitation, urea, creatinine, NLR, PNI, left atrial diameter (LAD), left ventricular end-diastolic dimension, LVEF, pulmonary arterial systolic pressure, IAB, baseline AF and heart failure predicted all-cause mortality. A multi-task Gaussian process learning model demonstrated significant improvement in risk stratification compared to logistic regression and a decision tree method. CONCLUSIONS: A multi-parametric approach incorporating multi-modality clinical data improves risk stratification in mitral regurgitation. Multi-task machine learning can significantly improve overall risk stratification performance.

Clinical characteristics, risk factors and outcomes of cancer patients with COVID-19: A population-based study.

INTRODUCTION: Cancer patients may be susceptible to poorer outcomes in COVID-19 infection owing to the immunosuppressant effect of chemotherapy/radiotherapy and cancer growth, along with the potential for nosocomial transmission due to frequent hospital admissions. METHODS: This was a population-based retrospective cohort study of COVID-19 patients who presented to Hong Kong public hospitals between 1 January 2020 and 8 December 2020. The primary outcome was a composite endpoint of requirement for intubation, ICU admission and 30-day mortality. RESULTS: The following study consisted of 6089 COVID-19 patients (median age 45.9 [27.8.1-62.7] years; 50% male), of which 142 were cancer subjects. COVID-19 cancer patients were older at baseline and tended to present with a higher frequency of comorbidities, including diabetes mellitus, hypertension, chronic obstructive pulmonary disease, ischemic heart disease, ventricular tachycardia/fibrillation and gastrointestinal bleeding (p < 0.05). These subjects also likewise tended to present with higher serum levels of inflammatory markers, including D-dimer, lactate dehydrogenase, high sensitivity troponin-I and C-reactive protein. Multivariate Cox regression showed that any type of cancer presented with an almost four-fold increased risk of the primary outcome (HR: 3.77; 95% CI: 1.63-8.72; p < 0.002) after adjusting for significant demographics, Charlson comorbidity index, number of comorbidities, past comorbidities and medication history. This association remained significant when assessing those with colorectal (HR: 5.07; 95% CI: 1.50-17.17; p < 0.009) and gastrointestinal malignancies (HR: 3.79; 95% CI: 1.12-12.88; p < 0.03), but not with lung, genitourinary, or breast malignancies, relative to their respective cancer-free COVID-19 counterparts. CONCLUSIONS: COVID-19 cancer patients are associated with a significantly higher risk of intubation, ICU admission and/or mortality.

Predictive value of neutrophil-to-lymphocyte ratio for atrial fibrillation and stroke in type 2 diabetes mellitus: The Hong Kong Diabetes Study.

INTRODUCTION: Neutrophil-to-lymphocyte ratio (NLR) is a routinely available biomarker that reflects systemic inflammation. The study evaluated the predictive value of NLR for ischemic stroke and atrial fibrillation (AF) in patients with type 2 diabetes mellitus. METHODS: This was a population-based cohort study of patients with type 2 diabetes mellitus and complete blood count tests at baseline between 1 January 1st, 2009, and 31 December, 2009, at government-funded hospitals/clinics in Hong Kong. Follow-up was until 31 December, 2019, or death. RESULTS: A total of 85,351 patients (age = 67.6 ± 13.2 years old, male = 48.8%, follow-up = 3101 ± 1441 days) were included. Univariable Cox regression found that increased NLR at quartiles 2, 3 and 4 was significantly associated with higher risks of new-onset ischemic stroke (hazard ratio [HR]: 1.28 [1.20-1.37], p < .001, HR: 1.41 [1.32-1.51], p < .001 and HR: 1.38 [1.29-1.47], p < .001) and AF (HR: 1.09 [1.02-1.17], p < .015; HR: 1.28 [1.20-1.37], p < .001; HR: 1.39 [1.31-1.49], p < .001) compared to quartile 1. On multivariable analysis, NLR remained a significant predictor of ischemic stroke risk for quartiles 2 and 3 (quartile 2: HR: 1.14 [1.05, 1.22], p = .001; quartile 3: HR: 1.14 [1.06, 1.23], p < .001) but not quartile 4 (HR: 1.08 [0.994, 1.17], p = .070). NLR was not predictive of AF after adjusting for confounders (quartile 2: HR: 0.966 [0.874, 1.07], p = .499; quartile 3: HR: 0.978 [0.884, 1.08], p = .661; quartile 4: HR: 1.05 [0.935, 1.16], p = .462). CONCLUSION: NLR is a significant predictor of new-onset ischaemic stroke after adjusting for significant confounders in Chinese type 2 diabetes patients.

Spiked Helmet Electrocardiographic Sign-A Systematic Review of Case Reports.

First reported in 2011, the spiked helmet sign (SHS) is an electrocardiographic pattern of ST-segment elevation anecdotally associated with poor prognosis. This study aims to systematically evaluate the electrocardiographic characteristics, clinical presentations, and outcomes of all cases of SHS reported in the literature. PubMed, Scopus, Web of Science, and EMBASE were searched electronically from their inception until November 2022. The Joanna Briggs Institute Critical Appraisal Checklist for Case Reports was used to critically appraise included studies. Studies written in English describing at least one patient with SHS were included. Altogether, 26 case reports or series describing 39 patients with SHS were included. All included studies were rated of acceptable quality. Associated conditions were heterogeneous, with intracranial hemorrhagic complications being the most common (9 patients), followed by pneumothorax (6 patients) or severe pneumonia (4 patients), bowel ischemia or obstruction (6 patients), and autonomic dysfunction (3 patients with Takotsubo cardiomyopathy and 3 patients with spinal injury, cocaine overuse, and stellate gangliectomy). Two patients had multiple complications and 12 other patients suffered from sepsis, myocardial infarction, etc. Clinical outcomes were reported for 32 patients, of whom 19 (59%) died during hospitalization (6 patients with pneumothorax or pneumonia, 4 patients with intracranial hemorrhagic complications, 2 patients with bowel ischemia or obstruction, and 7 patients due to other reasons). SHS may be associated with poor prognosis, necessitating its prompt recognition by clinicians and swift evaluation for underlying causes. Larger studies are needed to elucidate its prevalence, clinical implications, and precipitating mechanisms.

Development of an Electronic Frailty Index for Predicting Mortality and Complications Analysis in Pulmonary Hypertension Using Random Survival Forest Model.

Background: The long-term prognosis of the cardio-metabolic and renal complications, in addition to mortality in patients with newly diagnosed pulmonary hypertension, are unclear. This study aims to develop a scalable predictive model in the form of an electronic frailty index (eFI) to predict different adverse outcomes. Methods: This was a population-based cohort study of patients diagnosed with pulmonary hypertension between January 1st, 2000 and December 31st, 2017, in Hong Kong public hospitals. The primary outcomes were mortality, cardiovascular complications, renal diseases, and diabetes mellitus. The univariable and multivariable Cox regression analyses were applied to identify the significant risk factors, which were fed into the non-parametric random survival forest (RSF) model to develop an eFI. Results: A total of 2,560 patients with a mean age of 63.4 years old (interquartile range: 38.0-79.0) were included. Over a follow-up, 1,347 died and 1,878, 437, and 684 patients developed cardiovascular complications, diabetes mellitus, and renal disease, respectively. The RSF-model-identified age, average readmission, anti-hypertensive drugs, cumulative length of stay, and total bilirubin were among the most important risk factors for predicting mortality. Pair-wise interactions of factors including diagnosis age, average readmission interval, and cumulative hospital stay were also crucial for the mortality prediction. Patients who developed all-cause mortality had higher values of the eFI compared to those who survived (P < 0.0001). An eFI ≥ 9.5 was associated with increased risks of mortality [hazard ratio (HR): 1.90; 95% confidence interval [CI]: 1.70-2.12; P < 0.0001]. The cumulative hazards were higher among patients who were 65 years old or above with eFI ≥ 9.5. Using the same cut-off point, the eFI predicted a long-term mortality over 10 years (HR: 1.71; 95% CI: 1.53-1.90; P < 0.0001). Compared to the multivariable Cox regression, the precision, recall, area under the curve (AUC), and C-index were significantly higher for RSF in the prediction of outcomes. Conclusion: The RSF models identified the novel risk factors and interactions for the development of complications and mortality. The eFI constructed by RSF accurately predicts the complications and mortality of patients with pulmonary hypertension, especially among the elderly.

Metformin versus sulphonylureas for new onset atrial fibrillation and stroke in type 2 diabetes mellitus: a population-based study.

AIMS: To gain insights on the cardiovascular effects of metformin and sulphonylurea, the present study compares the rates of incident atrial fibrillation, stroke, cardiovascular mortality and all-cause mortality between metformin and sulphonylurea users in type 2 diabetes mellitus. METHODS: This was a retrospective population-based cohort study of type 2 diabetes mellitus patients receiving either sulphonylurea or metformin monotherapy between January 1, 2000, and December 31, 2019. The primary outcome was new-onset AF or stroke. Secondary outcomes were cardiovascular, non-cardiovascular and all-cause mortality. Propensity score matching (1:2 ratio) between sulphonylurea and metformin users was performed, based on demographics, CHA-DS-VASc score, past comorbidities and medication use. Cox regression was used to identify significant risk factors. Competing risk analysis was conducted using cause-specific and subdistribution hazard models. Sensitivity analyses using propensity score stratification, high-dimensional propensity score and inverse probability of treatment weighting were conducted. Subgroup analyses were conducted for age and gender in the matched cohort. RESULTS: A total of 36,228 sulphonylurea users and 72,456 metformin users were included in the propensity score-matched cohort. Multivariable Cox regression showed that sulphonylurea users had higher risks of incident AF (hazard ratio [HR]: 2.89, 95% confidence interval [CI]: 2.75-3.77; P < 0.0001), stroke (HR: 3.23, 95% CI: 3.01-3.45; P < 0.0001), cardiovascular mortality (HR: 3.60, 95% CI: 2.62-4.81; P < 0.0001) and all-cause mortality (HR: 4.35, 95% CI: 3.16-4.75; P < 0.0001) compared to metformin users. Similarly, significant results were observed using cause-specific and subdistribution hazard models. Sensitivity analysis using techniques based on the propensity score also yielded similar results. CONCLUSIONS: Sulphonylurea use was associated with higher risks of incident AF, stroke, cardiovascular mortality and all-cause mortality compared to metformin. Males and patients older than 65 years with sulphonylurea use were exposed to the highest risks.

Incident heart failure and myocardial infarction in sodium-glucose cotransporter-2 vs. dipeptidyl peptidase-4 inhibitor users.

AIMS: This study aimed to compare the rates of major cardiovascular adverse events in sodium-glucose cotransporter-2 inhibitors (SGLT2I) and dipeptidyl peptidase-4 inhibitors (DPP4I) users in a Chinese population. SGLT2I and DPP4I are increasingly prescribed for type 2 diabetes mellitus patients. However, few population-based studies are comparing their effects on incident heart failure or myocardial infarction. METHODS AND RESULTS: This was a population-based retrospective cohort study using the electronic health record database in Hong Kong, including type 2 diabetes mellitus patients receiving either SGLT2I or DPP4I from 1 January 2015 to 31 December 2020. Propensity score matching was performed in a 1:1 ratio based on demographics, past comorbidities, and non-SGLT2I/DPP4I medications with nearest neighbour matching (caliper = 0.1). Univariable and multivariable Cox models were used to identify significant predictors for new-onset heart failure, new-onset myocardial infarction, cardiovascular mortality, and all-cause mortality. Sensitivity analyses with competing risk models and multiple propensity score matching approaches were conducted. A total of 41 994 patients (58.89% males, median admission age at 58 years old, interquartile range [IQR]: 51.2-65.3) were included with a median follow-up of 5.6 years (IQR: 5.32-5.82). In the matched cohort, SGLT2I use was significantly associated with lower risks of new-onset heart failure (hazard ratio [HR]: 0.73, 95% confidence interval [CI]: [0.66, 0.81], P < 0.0001), myocardial infarction (HR: 0.81, 95% CI: [0.73, 0.90], P < 0.0001), cardiovascular mortality (HR: 0.67, 95% CI: [0.53, 0.84], P < 0.001), and all-cause mortality (HR: 0.26, 95% CI: [0.24, 0.29], P < 0.0001) after adjusting for significant demographics, past comorbidities, and non-SGLT2I/DPP4I medications. CONCLUSIONS: SGLT2 inhibitors are protective against adverse cardiovascular events including new-onset heart failure, myocardial infarction, cardiovascular mortality, and all-cause mortality. The prescription of SGLT2I is preferred when taken into consideration individual cardiovascular and metabolic risk profiles in addition to drug-drug interactions.

Gender-specific clinical risk scores incorporating blood pressure variability for predicting incident dementia.

INTRODUCTION: The present study examined the gender-specific prognostic value of blood pressure (BP) and its variability in the prediction of dementia risk and developed a score system for risk stratification. MATERIALS AND METHODS: This was a retrospective, observational population-based cohort study of patients admitted to government-funded family medicine clinics in Hong Kong between January 1, 2000 and March 31, 2002 with at least 3 blood pressure measurements. Gender-specific risk scores for dementia were developed and tested. RESULTS: The study consisted of 74 855 patients, of whom 3550 patients (incidence rate: 4.74%) developed dementia over a median follow-up of 112 months (IQR= [59.8-168]). Nonlinear associations between diastolic/systolic BP measurements and the time to dementia presentation were identified. Gender-specific dichotomized clinical scores were developed for males (age, hypertension, diastolic and systolic BP and their measures of variability) and females (age, prior cardiovascular, respiratory, gastrointestinal diseases, diabetes mellitus, hypertension, stroke, mean corpuscular volume, monocyte, neutrophil, urea, creatinine, diastolic and systolic BP and their measures of variability). They showed high predictive strengths for both male (hazard ratio [HR]: 12.83, 95% confidence interval [CI]: 11.15-14.33, P value < .0001) and female patients (HR: 26.56, 95% CI: 14.44-32.86, P value < .0001). The constructed gender-specific scores outperformed the simplified systems without considering BP variability (C-statistic: 0.91 vs 0.82), demonstrating the importance of BP variability in dementia development. CONCLUSION: Gender-specific clinical risk scores incorporating BP variability can accurately predict incident dementia and can be applied clinically for early disease detection and optimized patient management.

Efficacy of vasopressin, steroid, and epinephrine protocol for in-hospital cardiac arrest resuscitation: a systematic review and meta-analysis of randomized controlled trials with trial sequential analysis.

OBJECTIVES: To assess the effect of vasopressin, steroid and epinephrine (VSE) combination therapy on return of spontaneous circulation (ROSC) after in-hospital cardiac arrest (IHCA), and test the conclusiveness of evidence using trial sequential analysis (TSA). METHODS: The systematic search included PubMed, EMBASE, Scopus, and Cochrane Central Register of Controlled Trials. Randomized controlled trials (RCTs) that included adult patients with IHCA, with at least one group receiving combined VSE therapy were selected. Data was extracted independently by two reviewers. The main outcome of interest was ROSC. Other outcomes included survival to hospital discharge or survival to 30 and 90 days, with good neurological outcomes. RESULTS: We included a total of three RCTs (n = 869). Results showed that VSE combination therapy increased ROSC (risk ratio = 1.41; 95% CI: 1.25-1.59) as compared to placebo. TSA demonstrated that the existing evidence is conclusive. This was also validated by the alpha-spending adjusted relative risk (1.32 [1.16, 1.49], P < 0.0001). Other outcomes could not be meta-analysed due to differences in timeframe in the included studies. CONCLUSIONS: VSE combination therapy administered in cardiopulmonary resuscitation led to improved rates of ROSC. Future trials of VSE therapy should evaluate survival to hospital discharge, neurological function and long-term survival.

The Impact of Cardiac Comorbidity Sequence at Baseline and Mortality Risk in Type 2 Diabetes Mellitus: A Retrospective Population-Based Cohort Study.

Introduction: The presence of multiple comorbidities increases the risk of all-cause mortality, but the effects of the comorbidity sequence before the baseline date on mortality remain unexplored. This study investigated the relationship between coronary heart disease (CHD), atrial fibrillation (AF) and heart failure (HF) through their sequence of development and the effect on all-cause mortality risk in type 2 diabetes mellitus. Methods: This study included patients with type 2 diabetes mellitus prescribed antidiabetic/cardiovascular medications in public hospitals of Hong Kong between 1 January 2009 and 31 December 2009, with follow-up until death or 31 December 2019. The Cox regression was used to identify comorbidity sequences predicting all-cause mortality in patients with different medication subgroups. Results: A total of 249,291 patients (age: 66.0 ± 12.4 years, 47.4% male) were included. At baseline, 7564, 10,900 and 25,589 patients had AF, HF and CHD, respectively. Over follow-up (3524 ± 1218 days), 85,870 patients died (mortality rate: 35.7 per 1000 person-years). Sulphonylurea users with CHD developing later and insulin users with CHD developing earlier in the disease course had lower mortality risks. Amongst insulin users with two of the three comorbidities, those with CHD with preceding AF (hazard ratio (HR): 3.06, 95% CI: [2.60−3.61], p < 0.001) or HF (HR: 3.84 [3.47−4.24], p < 0.001) had a higher mortality. In users of lipid-lowering agents with all three comorbidities, those with preceding AF had a higher risk of mortality (AF-CHD-HF: HR: 3.22, [2.24−4.61], p < 0.001; AF-HF-CHD: HR: 3.71, [2.66−5.16], p < 0.001). Conclusions: The sequence of comorbidity development affects the risk of all-cause mortality to varying degrees in diabetic patients on different antidiabetic/cardiovascular medications.

Territory-wide cohort study of Brugada syndrome in Hong Kong: predictors of long-term outcomes using random survival forests and non-negative matrix factorisation.

OBJECTIVES: Brugada syndrome (BrS) is an ion channelopathy that predisposes affected patients to spontaneous ventricular tachycardia/fibrillation (VT/VF) and sudden cardiac death. The aim of this study is to examine the predictive factors of spontaneous VT/VF. METHODS: This was a territory-wide retrospective cohort study of patients diagnosed with BrS between 1997 and 2019. The primary outcome was spontaneous VT/VF. Cox regression was used to identify significant risk predictors. Non-linear interactions between variables (latent patterns) were extracted using non-negative matrix factorisation (NMF) and used as inputs into the random survival forest (RSF) model. RESULTS: This study included 516 consecutive BrS patients (mean age of initial presentation=50±16 years, male=92%) with a median follow-up of 86 (IQR: 45-118) months. The cohort was divided into subgroups based on initial disease manifestation: asymptomatic (n=314), syncope (n=159) or VT/VF (n=41). Annualised event rates per person-year were 1.70%, 0.05% and 0.01% for the VT/VF, syncope and asymptomatic subgroups, respectively. Multivariate Cox regression analysis revealed initial presentation of VT/VF (HR=24.0, 95% CI=1.21 to 479, p=0.037) and SD of P-wave duration (HR=1.07, 95% CI=1.00 to 1.13, p=0.044) were significant predictors. The NMF-RSF showed the best predictive performance compared with RSF and Cox regression models (precision: 0.87 vs 0.83 vs. 0.76, recall: 0.89 vs. 0.85 vs 0.73, F1-score: 0.88 vs 0.84 vs 0.74). CONCLUSIONS: Clinical history, electrocardiographic markers and investigation results provide important information for risk stratification. Machine learning techniques using NMF and RSF significantly improves overall risk stratification performance.

Development of a predictive risk model for all-cause mortality in patients with diabetes in Hong Kong.

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.

Fragmented QRS Is Independently Predictive of Long-Term Adverse Clinical Outcomes in Asian Patients Hospitalized for Heart Failure: A Retrospective Cohort Study.

Background: Fragmented QRS (fQRS) results from myocardial scarring and predicts cardiovascular mortality and ventricular arrhythmia (VA). We evaluated the prevalence and prognostic value of fQRS in Asian patients hospitalized for heart failure. Methods and Results: This was a retrospective cohort study of adult patients hospitalized for heart failure between 1st January 2010 and 31st December 2016 at a tertiary center in Hong Kong. The baseline ECG was analyzed. QRS complexes (<120 ms) with fragmented morphology in ≥2 contiguous leads were defined as fQRS. The primary outcome was a composite of cardiovascular mortality, VA, and sudden cardiac death (SCD). The secondary outcomes were the components of the primary outcome, myocardial infarction, and new-onset atrial fibrillation. In total, 2,182 patients were included, of whom 179 (8.20%) had fQRS. The follow-up duration was 5.63 ± 4.09 years. fQRS in any leads was associated with a higher risk of the primary outcome (adjusted hazard ratio (HR) 1.428 [1.097, 1.859], p = 0.001), but not myocardial infarction or new-onset atrial fibrillation. fQRS in >2 contiguous leads was an independent predictor of SCD (HR 2.679 [1.252, 5.729], p = 0.011). In patients without ischaemic heart disease (N = 1,396), fQRS in any leads remained predictive of VA and SCD (adjusted HR 3.526 [1.399, 8.887], p = 0.008, and 1.873 [1.103, 3.181], p = 0.020, respectively), but not cardiovascular mortality (adjusted HR 1.064 [0.671, 1.686], p = 0.792). Conclusion: fQRS is an independent predictor of cardiovascular mortality, VA, and SCD. Higher fQRS burden increased SCD risk. The implications of fQRS in heart failure patients without ischaemic heart disease require further studies.

Sodium-Glucose Cotransporter 2 (SGLT2) Inhibitors vs. Dipeptidyl Peptidase-4 (DPP4) Inhibitors for New-Onset Dementia: A Propensity Score-Matched Population-Based Study With Competing Risk Analysis.

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 <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 < 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 < 0.0001), cerebrovascular (0.88 vs. 3.88%, p < 0.0001), and cardiovascular mortality (0.49 vs. 3.75%, p < 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 < 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 < 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 < 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.

Soluble suppression of tumorigenicity 2 (sST2) for predicting disease severity or mortality outcomes in cardiovascular diseases: A systematic review and meta-analysis.

OBJECTIVES: 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. METHODS: PubMed and Embase were searched until 23rd June 2021 for studies that evaluated the relationship between sST2 levels and cardiovascular disease severity or mortality. RESULTS: 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; I 2: 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; I 2: 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; I 2: 0%) and elevated levels were associated with increased mortality risk (HR: 1.64, 95% CI: 1.27-2.12, P < 0.001; I 2: 82%). sST2 levels were significantly higher in severe disease compared to less severe disease (MD: 1.56 ± 0.46 ng/ml; P = 0.001; I 2: 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; I 2: 80%) and elevated levels were significantly associated with increased mortality risk (HR: 1.32, 95% CI: 1.04-1.68, P < 0.05; I 2: 57%). CONCLUSIONS: 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.