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Abstract Mild sleep deprivation is widespread in many societies worldwide. Electroencephalography (EEG) microstate analysis provides information on spatial and temporal characteristics of resting brain network, serving as an indicator of neurophysiological activities at rest. This study seeks to investigate potential neural markers in EEG following mild sleep deprivation of a single night using EEG microstate analysis. Six-minute resting EEG was conducted on thirty healthy adults within 6 hours of waking in the morning and after at least 18 h of sleep deprivation. Translated and validated Malay language Karolinska Sleepiness Scale was used to assess the participants’ degree of sleepiness. Microstate characteristics analysis was conducted on the final 24 subjects based on four standard microstate maps. Microstate C shows a significant increase in mean duration, coverage and occurrence, while microstate D has significantly higher occurrence after sleep deprivation. This study demonstrates notable changes in resting state EEG microstates following mild sleep deprivation. Present findings deepen our understanding of the brain's spatiotemporal dynamics under this condition and suggest the potential utility of neural markers in this domain as components of composite markers for sleep deprivation.

Abstract The accurate prediction of in-hospital mortality in Asian women after ST-Elevation Myocardial Infarction (STEMI) remains a crucial issue in medical research. Existing models frequently neglect this demographic's particular attributes, resulting in poor treatment outcomes. This study aims to improve the prediction of in-hospital mortality in multi-ethnic Asian women with STEMI by employing both base and ensemble machine learning (ML) models. We centred on the development of demographic-specific models using data from the Malaysian National Cardiovascular Disease Database spanning 2006 to 2016. Through a careful iterative feature selection approach that included feature importance and sequential backward elimination, significant variables such as systolic blood pressure, Killip class, fasting blood glucose, beta-blockers, angiotensin-converting enzyme inhibitors (ACE), and oral hypoglycemic medications were identified. The findings of our study revealed that ML models with selected features outperformed the conventional Thrombolysis in Myocardial Infarction (TIMI) Risk score, with area under the curve (AUC) ranging from 0.60 to 0.93 versus TIMI's AUC of 0.81. Remarkably, our best-performing ensemble ML model was surpassed by the base ML model, support vector machine (SVM) Linear with SVM selected features (AUC: 0.93, CI: 0.89–0.98 versus AUC: 0.91, CI: 0.87–0.96). Furthermore, the women-specific model outperformed a non-gender-specific STEMI model (AUC: 0.92, CI: 0.87–0.97). Our findings demonstrate the value of women-specific ML models over standard approaches, emphasizing the importance of continued testing and validation to improve clinical care for women with STEMI.

BackgroundTraditional risk assessment tools often lack accuracy when predicting the short- and long-term mortality following a non-ST-segment elevation myocardial infarction (NSTEMI) or Unstable Angina (UA) in specific population.ObjectiveTo employ machine learning (ML) and stacked ensemble learning (EL) methods in predicting short- and long-term mortality in Asian patients diagnosed with NSTEMI/UA and to identify the associated features, subsequently evaluating these findings against established risk scores.MethodsWe analyzed data from the National Cardiovascular Disease Database for Malaysia (2006-2019), representing a diverse NSTEMI/UA Asian cohort. Algorithm development utilized in-hospital records of 9,518 patients, 30-day data from 7,133 patients, and 1-year data from 7,031 patients. This study utilized 39 features, including demographic, cardiovascular risk, medication, and clinical features. In the development of the stacked EL model, four base learner algorithms were employed: eXtreme Gradient Boosting (XGB), Support Vector Machine (SVM), Naive Bayes (NB), and Random Forest (RF), with the Generalized Linear Model (GLM) serving as the meta learner. Significant features were chosen and ranked using ML feature importance with backward elimination. The predictive performance of the algorithms was assessed using the area under the curve (AUC) as a metric. Validation of the algorithms was conducted against the TIMI for NSTEMI/UA using a separate validation dataset, and the net reclassification index (NRI) was subsequently determined.ResultsUsing both complete and reduced features, the algorithm performance achieved an AUC ranging from 0.73 to 0.89. The top-performing ML algorithm consistently surpassed the TIMI risk score for in-hospital, 30-day, and 1-year predictions (with AUC values of 0.88, 0.88, and 0.81, respectively, all p < 0.001), while the TIMI scores registered significantly lower at 0.55, 0.54, and 0.61. This suggests the TIMI score tends to underestimate patient mortality risk. The net reclassification index (NRI) of the best ML algorithm for NSTEMI/UA patients across these periods yielded an NRI between 40-60% (p < 0.001) relative to the TIMI NSTEMI/UA risk score. Key features identified for both short- and long-term mortality included age, Killip class, heart rate, and Low-Molecular-Weight Heparin (LMWH) administration.ConclusionsIn a broad multi-ethnic population, ML approaches outperformed conventional TIMI scoring in classifying patients with NSTEMI and UA. ML allows for the precise identification of unique characteristics within individual Asian populations, improving the accuracy of mortality predictions. Continuous development, testing, and validation of these ML algorithms holds the promise of enhanced risk stratification, thereby revolutionizing future management strategies and patient outcomes.

Key Clinical Message The high‐risk “Shark Fin” electrocardiogram (ECG) pattern has been associated with transmural ischemia but can also result from electrolyte anomalies. Therefore, the decision for invasive coronary catheterization requires a detailed history and dedicated biochemical tests. Abstract Pseudo‐infarction ECG pattern resembling “Shark Fin” was demonstrated in a 76‐year‐old lady with a previous total thyroidectomy who presented with unspecific symptoms. An incidental finding of hypokalemia and hypocalcemia was thought to be related to delayed onset hypoparathyroidism. Potential etiologies like coronary vasospasm and catecholamine‐associated myocardial injury were suggested.

Coronary physiology assessment is an important factor in guiding myocardial revascularization. A growing body of research highlights the value of using fractional flow reserve, FFR and other pressure-based indicators for functional assessment of stable coronary stenoses. Invasive functional coronary assessment techniques have evolved from intracoronary wire-based to wire-free approaches as a result of technological advancements. In addition, several software programs on the market have been thoroughly investigated and validated against invasive FFR, and have shown good accuracy and correlation. However, use of FFR remains modest. Hence, this review provides an overview of angiography-based FFR solutions and compares their technologies. Additionally, a systematic scoping review was performed to understand the research landscape in wire-free coronary physiology assessment, to complement the narratives of existing FFR trials on wire-free FFR. Furthermore, future developments and strategies that could expand the use of wire-free computed coronary functional assessment in the Asia Pacific region are discussed.

Abstract Background Data on clinical characteristics of acute decompensated heart failure (ADHF) in Malaysia especially in East Malaysia is lacking. Methods This is a prospective observational study in Sarawak General Hospital, Medical Department, from October 2017 to September 2018. Patients with primary admission diagnosis of ADHF were recruited and followed up for 90 days. Data on patient’s characteristics, precipitating factors, medications and short-term clinical outcomes were recorded. Results Majority of the patients were classified in lower socioeconomic group and the mean age was 59 years old. Hypertension, diabetes mellitus and dyslipidaemia were the common underlying comorbidities. Heart failure with ischemic aetiology was the commonest ADHF admission precipitating factor. 48.6% of patients were having preserved ejection fraction HF and the median NT-ProBNP level was 4230 pg/mL. Prescription rate of the evidence-based heart failure medication was low. The in-patient mortality and the average length of hospital stay were 7.5% and 5 days respectively. 43% of patients required either ICU care or advanced cardiopulmonary support. The 30-day, 90-day mortality and readmission rate were 13.1%, 11.2%, 16.8% and 14% respectively. Conclusion Comparing with the HF data from West and Asia Pacific, the short-term mortality and readmission rate were high among the ADHF patients in our study cohort. Maladaptation to evidence-based HF prescription and the higher prevalence of cardiovascular risk factors in younger patients were among the possible issues to be addressed to improve the HF outcome in regions with similar socioeconomic background.

BackgroundAlthough the burden of premature myocardial infarction (MI) is high in Malaysia, direct evidence on the determinants of MI in this multi-ethnic population remains sparse. ObjectiveThe Malaysian Acute Vascular Events Risk (MAVERIK) study is a retrospective case-control study established to investigate the genomic, lipid-related, and other determinants of acute MI in Malaysia. In this paper, we report the study protocol and early results. MethodsBy June 2019, we had enrolled approximately 2500 patients with their first MI and 2500 controls without cardiovascular disease, who were frequency-matched by age, sex, and ethnicity, from 17 hospitals in Malaysia. For each participant, serum and whole blood have been collected and stored. Clinical, demographic, and behavioral information has been obtained using a 200-item questionnaire. ResultsTobacco consumption, a history of diabetes, hypertension, markers of visceral adiposity, indicators of lower socioeconomic status, and a family history of coronary disease were more prevalent in cases than in controls. Adjusted (age and sex) logistic regression models for traditional risk factors indicated that current smoking (odds ratio [OR] 4.11, 95% CI 3.56-4.75; P30 kg/m2; OR 1.19, 95% CI 1.05-1.34; P=.009) were associated with MI in age- and sex-adjusted models. ConclusionsThe MAVERIK study can serve as a useful platform to investigate genetic and other risk factors for MI in an understudied Southeast Asian population. It should help to hasten the discovery of disease-causing pathways and inform regionally appropriate strategies that optimize public health action. International Registered Report Identifier (IRRID)RR1-10.2196/31885

Advanced age, diabetes, and chronic kidney disease not only increase the risk for ischaemic events in chronic coronary syndromes (CCS) but also confer a high bleeding risk during antiplatelet therapy. These special populations may warrant modification of therapy, especially among Asians, who have displayed characteristics that are clinically distinct from Western patients. Previous guidance has been provided regarding the classification of high-risk CCS and the use of newer-generation P2Y12 inhibitors (i.e. ticagrelor and prasugrel) after acute coronary syndromes (ACS) in Asia. The authors summarise evidence on the use of these P2Y12 inhibitors during the transition from ACS to CCS and among special populations. Specifically, they present recommendations on the roles of standard dual antiplatelet therapy, shortened dual antiplatelet therapy and single antiplatelet therapy among patients with coronary artery disease, who are either transitioning from ACS to CCS; elderly; or with chronic kidney disease, diabetes, multivessel coronary artery disease and bleeding events during therapy.

BackgroundSex and gender differences in acute coronary syndrome (ACS) have been well studied in the western population. However, limited studies have examined the trends of these differences in a multi-ethnic Asian population.ObjectivesTo study the trends in sex and gender differences in ACS using the Malaysian NCVD-ACS Registry.MethodsData from 24 hospitals involving 35,232 ACS patients (79.44% men and 20.56% women) from 1st. Jan 2012 to 31st. Dec 2016 were analysed. Data were collected on demographic characteristics, coronary risk factors, anthropometrics, treatments and outcomes. Analyses were done for ACS as a whole and separately for ST-segment elevation myocardial infarction (STEMI), Non-STEMI and unstable angina. These were then compared to published data from March 2006 to February 2010 which included 13,591 ACS patients (75.8% men and 24.2% women).ResultsWomen were older and more likely to have diabetes mellitus, hypertension, dyslipidemia, previous heart failure and renal failure than men. Women remained less likely to receive aspirin, beta-blocker, angiotensin-converting enzyme inhibitor (ACE-I) and statin. Women were less likely to undergo angiography and percutaneous coronary intervention (PCI) despite an overall increase. In the STEMI cohort, despite a marked increase in presentation with Killip class IV, women were less likely to received primary PCI or fibrinolysis and had longer median door-to-needle and door-to-balloon time compared to men, although these had improved. Women had higher unadjusted in-hospital, 30-Day and 1-year mortality rates compared to men for the STEMI and NSTEMI cohorts. After multivariate adjustments, 1-year mortality remained significantly higher for women with STEMI (adjusted OR: 1.31 (1.09-1.57), pConclusionWomen continued to have longer system delays, receive less aggressive pharmacotherapies and invasive treatments with poorer outcome. There is an urgent need for increased effort from all stakeholders if we are to narrow this gap.

Background Because of a nonresponse to aspirin (aspirin resistance), patients with acute coronary syndrome (ACS) are at increased risk of developing recurrent event. The in vitro platelet function tests have potential limitations, making them unsuitable for the detection of aspirin resistance. We investigated whether miR‐19b‐1‐5p could be utilized as a biomarker for aspirin resistance and future major adverse cardio‐cerebrovascular (MACCE) events in patients with ACS. Methods and Results In this cohort study, patients with ACS were enrolled from multiple tertiary hospitals in Christchurch, Hong Kong, Sarawak, and Singapore between 2011 and 2015. MiR‐19b‐1‐5p expression was measured from buffy coat of patients with ACS (n=945) by reverse transcription quantitative polymerase chain reaction. Platelet function was determined by Multiplate aggregometry testing. MACCE was collected over a mean follow‐up time of 1.01±0.43 years. Low miR‐19b‐1‐5p expression was found to be related to aspirin resistance as could be observed from sustained platelet aggregation in the presence of aspirin (‐Log‐miR‐19b‐1‐5p, [unstandardized beta, 44.50; 95% CI, 2.20–86.80; P

Routine coagulation tests do not enable rapid, accurate determination of direct oral anticoagulant (DOAC) therapy. The ecarin clotting assay (ECA), performed on the ClotPro viscoelastic testing device, may enable sensitive and specific detection of dabigatran. We assessed the association between trough plasma dabigatran concentration and clotting time (CT) in the ClotPro ECA, in patients with non-valvular atrial fibrillation (NVAF). Each patient provided a single venous blood sample, ∼1 hour before dabigatran dosing. The study included 118 patients, of whom 64 were receiving dabigatran 110 mg twice daily and 54 were receiving 150 mg twice daily. ECA CT was moderately correlated with trough plasma dabigatran concentration ( r = 0.80, p < 0.001). Slight trends toward increased plasma dabigatran concentration and prolonged ECA CT were apparent with 150 mg versus the 110 mg dose (differences not statistically significant). Individuals with creatinine clearance below 50 mL/minute had significantly higher plasma dabigatran concentrations and significantly prolonged ECA CT versus those with creatinine clearance ≥50 mL/minute. In conclusion, this preliminary study has demonstrated that CT in the ClotPro ECA reflects the plasma concentration of dabigatran in patients with NVAF. The ECA could potentially be used to assess the impact of dabigatran on a patient’s coagulation status.

OBJECTIVES: To assess whether gender differences exist in the clinical presentation, angiographic severity, management and outcomes in patients with coronary artery disease (CAD). METHODS: The study comprised of 1,961 women and 8,593 men who underwent percutaneous coronary intervention (PCI) and were included in the Malaysian NCVD-PCI Registry from 2007-2009. Significant stenosis was defined as ≥70% stenosis in at least one of the epicardial vessels. RESULTS: Women were significantly older and had significantly higher rates of diabetes mellitus, hypertension, chronic renal failure, new onset angina and prior history of heart failure whereas smokers and past history of myocardial infarction were higher in men. In the ST-elevation myocardial infarction (STEMI) cohort, more women were in Killip class III-IV, had longer door-to-balloon time (169.5 min. vs 127.3 min, p

BACKGROUND: Risk stratification in ST-elevation myocardial infarction (STEMI) is important, such that the most resource intensive strategy is used to achieve the greatest clinical benefit. This is essential in developing countries with wide variation in health care facilities, scarce resources and increasing burden of cardiovascular diseases. This study sought to validate the Thrombolysis In Myocardial Infarction (TIMI) risk score for STEMI in a multi-ethnic developing country. METHODS: Data from a national, prospective, observational registry of acute coronary syndromes was used. The TIMI risk score was evaluated in 4701 patients who presented with STEMI. Model discrimination and calibration was tested in the overall population and in subgroups of patients that were at higher risk of mortality; i.e., diabetics and those with renal impairment. RESULTS: Compared to the TIMI population, this study population was younger, had more chronic conditions, more severe index events and received treatment later. The TIMI risk score was strongly associated with 30-day mortality. Discrimination was good for the overall study population (c statistic 0.785) and in the high risk subgroups; diabetics (c statistic 0.764) and renal impairment (c statistic 0.761). Calibration was good for the overall study population and diabetics, with χ2 goodness of fit test p value of 0.936 and 0.983 respectively, but poor for those with renal impairment, χ2 goodness of fit test p value of 0.006. CONCLUSIONS: The TIMI risk score is valid and can be used for risk stratification of STEMI patients for better targeted treatment.

Diabetes mellitus is among the most prevalent chronic diseases affecting the world's population today. With the increasing costs associated with diabetes treatments and management, finding the effective early diabetes detection and screening tools or methods has become the overarching goal for most contemporary diabetes research. Machine learning methods offer a new approach to diabetes analytics that is well-suited to today's Big Data requirements. They could overcome many constraints inherent in many traditional statistical modeling approaches. In this paper, we offer concise yet detailed discussions on the current progress in diabetes analytics. We also point to several promising research directions in this area. [ABSTRACT FROM AUTHOR]

Acute myocardial infarction (AMI) is associated with heightened thrombin generation. There are limited data relating to thrombin generation and left ventricular (LV) scarring and LV dilatation in post-MI LV remodeling. We studied 113 patients with ST-segment elevation myocardial infarction (STEMI) who had undergone primary percutaneous coronary intervention (PPCI) (n = 76) or pharmaco-invasive management (thrombolysis followed by early PCI, n = 37). Endogenous thrombin potential (ETP) was measured at baseline, 1 month and 6 months. Cardiovascular magnetic resonance imaging was performed at baseline and 6 months post-MI. Outcomes studied were an increase in scar change, which was defined as an increase in left ventricular infarct size of any magnitude detected by late gadolinium enhancement, adverse LV remodeling, defined as dilatation (increase) of left ventricular end-diastolic volume (LVEDV) by more than 20% and an increase in left ventricular ejection fraction (LVEF). The mean age was 55.19 ± 8.25 years and 91.2% were men. The baseline ETP was similar in the PPCI and pharmaco-invasive groups (1400.3 nM.min vs. 1334.1 nM.min, p = 0.473). Each 10-unit increase in baseline ETP was associated with a larger scar size (adjusted OR 1.020, 95% CI 1.002–1.037, p = 0.027). Baseline ETP was not associated with adverse LV remodeling or an increase in LVEF. There was no difference in scar size or adverse LV remodeling among patients undergoing PPCI vs. pharmaco-invasive management or patients receiving ticagrelor vs. clopidogrel. Enhanced thrombin generation after STEMI is associated with a subsequent increase in myocardial scarring but not LV dilatation or an increase in LVEF at 6 months post-MI.

Summary: We identified a plasma signature of 11 C14 to C26 ceramides and 1 C16 dihydroceramide predictive of major adverse cardiovascular events in patients with acute myocardial infarction (AMI). Among patients undergoing coronary artery bypass surgery, those with recent AMI, compared with those without recent AMI, showed a significant increase in 5 of the signature’s 12 ceramides in plasma but not simultaneously-biopsied aortic tissue. In contrast, a rat AMI model, compared with sham control, showed a significant increase in myocardial concentrations of all 12 ceramides and up-regulation of 3 ceramide-producing enzymes, suggesting ischemic myocardium as a possible source of this ceramide signature. Key Words: acute coronary syndrome, ceramides, dihydroceramides, major adverse cardiovascular and cerebrovascular events, prognosis, risk prediction