Personalizing renal replacement therapy initiation in the intensive care unit: a reinforcement learning-based strategy with external validation on the AKIKI randomized controlled trials.

Objective: The timely initiation of renal replacement therapy (RRT) for acute kidney injury (AKI) requires sequential decision-making tailored to individuals' evolving characteristics. To learn and validate optimal strategies for RRT initiation, we used reinforcement learning on clinical data from routine care and randomized controlled trials.

Materials And Methods: We used the MIMIC-III database for development and AKIKI trials for validation.

Patients' Perspectives on How to Improve Endometriosis Care: A Large Qualitative Study Within the ComPaRe-Endometriosis e-Cohort.

Endometriosis is a chronic gynecological condition that affects about 10% of women of reproductive age. Despite its prevalence, diagnosis is often delayed, misdiagnosis is common, and treatment options are poor. This study aimed at capturing ideas to improve endometriosis care from the patients' perspectives.

Priorities to improve the care for chronic conditions and multimorbidity: a survey of patients and stakeholders nested within the ComPaRe e-cohort.

Objective: To set priorities to improve consultations, care structures and the healthcare system from the perspective of patients with chronic conditions, care professionals, hospital administrators and health policy makers.

Methods: Adult patients with chronic conditions recruited from the ComPaRe e-cohort in France ranked their 15 most important areas of improvement among 147 previously defined by patients. Priorities at a population level were obtained by using logit models for sets of ranked items in a data set calibrated to represent the French population of patients with chronic conditions.