Abstract Purpose of Review The purpose of this review was to synthesize research findings
from recently published randomized controlled trials (RCTs) targeting any phase of …

Aims Machine learning (ML) is widely believed to be able to learn complex hidden
interactions from the data and has the potential in predicting events such as heart failure …

Background The prediction of readmission or death after a hospital discharge for heart
failure (HF) remains a major challenge. Modern healthcare systems, electronic health …

Our aim was to investigate the usefulness of machine learning approaches on linked
administrative health data at the population level in predicting older patients' one-year risk of …

Background Electronic health care data contain rich information on medicine use from which
adherence can be estimated. Various measures developed with medication claims data …

Adherence to cardioprotective medications following myocardial infarction (MI) is commonly
assessed using a binary threshold of 80%. We investigated the relationship between …

Objective To determine independent associations between the use of medicines with
anticholinergic or sedative effects and frailty with outcomes of length of stay (LOS), coronary …

Aim Describe the dispensing patterns for guideline‐recommended medications during 2008
in people with acute coronary syndrome (ACS) and how dispensing varies by gender and …

Introduction Statin use for preventing recurrent acute coronary syndromes (ACS) is low in
older people due to many clinical factors, including frailty. Using the recently developed …

Aims To determine exposure to warfarin and the associated outcomes in a population of
older patients with non-valvular atrial fibrillation (NVAF) Methods Cohort study of patients …