Artificial intelligence driven clustering of blood pressure profiles reveals frailty in orthostatic hypertension.

Gravity, an invisible but constant force , challenges the regulation of blood pressure when transitioning between postures. As physiological reserve diminishes with age, individuals grow more susceptible to such stressors over time, risking inadequate haemodynamic control observed in orthostatic hypotension. This prevalent condition is characterized by drops in blood pressure upon standing; however, the contrary phenomenon of blood pressure rises has recently piqued interest.

The usage of anticholinergic medications in a low- and middle-income country: a longitudinal comparison of 2013-15 and 2020-22 datasets.

Background: While the effects of anticholinergic drug use have been increasingly highlighted, trends in anticholinergic use remain poorly understood.

Aim: To determine the changes in frequency and pattern of anticholinergic drug use within a low- and middle-income country.

Method: Comparisons were made between population-based datasets collected from Malaysian residents aged 55 years and older in 2013-15 and 2020-22.

Fall risk prediction using temporal gait features and machine learning approaches.

Introduction: Falls have been acknowledged as a major public health issue around the world. Early detection of fall risk is pivotal for preventive measures. Traditional clinical assessments, although reliable, are resource-intensive and may not always be feasible.

Predictive value of the World falls guidelines algorithm within the AGELESS-MELoR cohort.

Aim: The World Falls Guidelines (WFG) Task Force published a falls risk stratification algorithm in 2022. However, its adaptability is uncertain in low- and middle-income settings such as Malaysia due to different risk factors and limited resources. We evaluated the effectiveness of the WFG risk stratification algorithm in predicting falls among community-dwelling older adults in Malaysia.