Public articles linked to the same research event.
JMIR Medical Informatics This systematic review searched PubMed, MEDLINE, Embase, PsycINFO, and Web of Science from inception to November 11, 2025, and included 29 studies that developed, validated, or evaluated multivariable prediction models using routinely collected electronic health record or administrative data to predict acute mental status deterioration during adult hospital admissions, all operationalized as delirium; using CHARMS and TRIPOD/TRIPOD-AI for data extraction and PROBAST for risk of bias, it found that the evidence clustered into four overlapping prediction tasks (admission or early-stay risk stratification, perioperative or postoperative prediction, dynamic intensive care unit prediction, and external validation or workflow evaluation of existing tools), that most studies were retrospective co
This systematic review searched PubMed, MEDLINE, Embase, PsycINFO, and Web of Science from inception to November 11, 2025, and included 29 studies that developed, validated, or evaluated multivariable prediction models using routinely collected electronic health record or administrative data to predict acute mental status deterioration during adult hospital admissions, all operationalized as delirium; using CHARMS and TRIPOD/TRIPOD-AI for data extraction and PROBAST for risk of bias, it found that the evidence clustered into four overlapping prediction tasks (admission or early-stay risk stratification, perioperative or postoperative prediction, dynamic intensive care unit prediction, and external validation or workflow evaluation of existing tools), that most studies were retrospective co
This systematic review searched PubMed, MEDLINE, Embase, PsycINFO, and Web of Science from inception to November 11, 2025, and included 29 studies that developed, validated, or evaluated multivariable prediction models using routinely collected electronic health record or administrative data to predict acute mental status deterioration during adult hospital admissions, all operationalized as delirium; using CHARMS and TRIPOD/TRIPOD-AI for data extraction and PROBAST for risk of bias, it found that the evidence clustered into four overlapping prediction tasks (admission or early-stay risk stratification, perioperative or postoperative prediction, dynamic intensive care unit prediction, and external validation or workflow evaluation of existing tools), that most studies were retrospective co
This systematic review searched PubMed, MEDLINE, Embase, PsycINFO, and Web of Science from inception to November 11, 2025, and included 29 studies that developed, validated, or evaluated multivariable prediction models using routinely collected electronic health record or administrative data to predict acute mental status deterioration during adult hospital admissions, all operationalized as delirium; using CHARMS and TRIPOD/TRIPOD-AI for data extraction and PROBAST for risk of bias, it found that the evidence clustered into four overlapping prediction tasks (admission or early-stay risk stratification, perioperative or postoperative prediction, dynamic intensive care unit prediction, and external validation or workflow evaluation of existing tools), that most studies were retrospective co