Nur Shahidah

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INTRODUCTION A key aim of triage is to identify those with high risk of cardiac arrest, as they require intensive monitoring, resuscitation facilities, and early intervention. We aim to validate a novel machine learning (ML) score incorporating heart rate variability (HRV) for triage of critically ill patients presenting to the emergency department by(More)
INTRODUCTION This study aims to study how the effect of the location of patient collapses from cardiac arrest, in the residential and non-residential areas within Singapore, relates to certain survival outcomes. MATERIALS AND METHODS A retrospective cohort study of data were done from the Cardiac Arrest and Resuscitation Epidemiology (CARE) project.(More)
BACKGROUND This study was undertaken to validate the use of the modified early warning score (MEWS) as a predictor of patient mortality and intensive care unit (ICU)/ high dependency (HD) admission in an Asian population. METHODS The MEWS was applied to a retrospective cohort of 1 024 critically ill patients presenting to a large Asian tertiary emergency(More)
BACKGROUND Environmental contexts have been shown to predict health behaviours and outcomes either directly or via interaction with individual risk factors. In this paper, we created indexes of socioeconomic disadvantage (SEDI) and socioeconomic advantage (SAI) in Singapore to test the applicability of these concepts in an Asian context. These indices can(More)
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