Evidence Communication Rules for Policy (ECR-P) critical appraisal tool.

Background: Scientific papers increasingly put forward scientific-based policy recommendations (SPRs) as a means of closing the circle of science, policy and practice. Assessing the quality of such SPRs is crucial, especially within the context of a systematic review. Here, we present ECR-P (Evidence Communication Rules for Policy)-a critical appraisal tool that we have developed, which can be used in assessing not only the quality of SPRs but also the quality of their evidence base and how effectively these have both been communicated.

Evaluation of deprescribing services in frail patients: a systematic review.

Background: Deprescribing, a process of dose reduction or withdrawal of inappropriate medication that no longer has benefit, is a proposed intervention in the care of older adults living with frailty.

Objective/aim: To evaluate the safety, effectiveness, and clinical impact of deprescribing services in frail patients.

Methods: A systematic literature search was performed in November 2023 using Scopus, CINAHL PLUS (EBSCO), MEDLINE (OVID and EMBASE), and Cochrane Library.

Drug utilisation study in hospitalised chronic kidney disease patients, using World Health Organisation prescribing indicators: an observational study.

Background: Chronic kidney disease (CKD) is associated with comorbidities and altered pharmacokinetics, making appropriate prescribing, and monitoring necessary to minimise drug-related problems (DRPs). Therefore, this study aimed to describe the drug-utilisation pattern in hospitalised CKD patients.

Methods: An observational study was conducted in hospitalised adult (≥18 years old) CKD patients in the UK using WHO prescribing indicators, from November 2021 to April 2022 in a large teaching hospital in England from admission until discharge.

Recent methodological advances in federated learning for healthcare.

For healthcare datasets, it is often impossible to combine data samples from multiple sites due to ethical, privacy, or logistical concerns. Federated learning allows for the utilization of powerful machine learning algorithms without requiring the pooling of data. Healthcare data have many simultaneous challenges, such as highly siloed data, class imbalance, missing data, distribution shifts, and non-standardized variables, that require new methodologies to address.

Sedation modality in acute respiratory distress syndrome: does method of sedation affect length of stay, outcomes, or adverse events? A systematic review.

Introduction: Acute respiratory distress syndrome (ARDS) is a life-threatening, diffuse inflammatory pulmonary condition characterised by the Berlin criteria. Incidence of ARDS is estimated at 2.5-19% globally with high mortality and morbidity.