Delirium occurrence and association with outcomes in hospitalized COVID-19 patients

Article Geriatrics & Gerontology

Ascertainment of Delirium Status Using Natural Language Processing From Electronic Health Records

Sunyang Fu et al.

Summary: This study developed and validated natural language processing (NLP) algorithms to automatically identify delirium occurrences from electronic health records (EHRs). The algorithms based on the standardized evidence-based CAM framework showed high accuracy and sensitivity in delineating delirium status.

JOURNALS OF GERONTOLOGY SERIES A-BIOLOGICAL SCIENCES AND MEDICAL SCIENCES (2022)

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Article Clinical Neurology

The chronic neuropsychiatric sequelae of COVID-19: The need for a prospective study of viral impact on brain functioning

Gabriel A. de Erausquin et al.

Summary: The impact of SARS-CoV-2 on the central nervous system has raised concerns about the risk of later life cognitive decline, Alzheimer's disease, and other dementia. An international consortium has been formed to study the short and long-term consequences of the virus on the CNS and enroll individuals for evaluations to better understand the underlying biology contributing to AD and dementia.

ALZHEIMERS & DEMENTIA (2021)

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Article Critical Care Medicine

Prevalence and risk factors for delirium in critically ill patients with COVID-19 (COVID-D): a multicentre cohort study

Brenda T. Pun et al.

Summary: This study investigated the prevalence of delirium and coma in critically ill patients with COVID-19, identifying benzodiazepine use and lack of family visitation as modifiable risk factors for delirium. These findings present an opportunity to reduce acute brain dysfunction in patients with COVID-19.

LANCET RESPIRATORY MEDICINE (2021)

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Article Medicine, General & Internal

Predicting Delirium Risk Using an Automated Mayo Delirium Prediction Tool: Development and Validation of a Risk-Stratification Model

Sandeep R. Pagali et al.

Summary: The study developed a delirium risk-prediction tool applicable to different patient populations and validated its reliability in predicting delirium risk at hospital admission. The Mayo Delirium Prediction tool showed good performance in both derivation and validation cohorts, suggesting its potential as an automated tool for delirium risk prediction during hospitalization. Prospective validation studies are needed for further confirmation of its effectiveness.

MAYO CLINIC PROCEEDINGS (2021)

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Review Geriatrics & Gerontology