What is the Delirium Bibliography? The searchable Delirium Bibliography page is one of our most popular features, allowing you to quickly gain access to the literature on delirium and acute care of older persons. It is primarily intended for clinicians and researchers interested in exploring these topics. The NIDUS team keeps it updated for you on a monthly basis!
How to Search for Articles: Search by author, title, year, and/or keywords. Each article is indexed by keywords taken from MEDLINE and other relevant databases. Click on the title of the article to read the abstract, journal, etc.
Reference Information
- Title
- Acute Brain Dysfunction: Development and Validation of a Daily Prediction Model.
- Authors
- Marra, A. Pandharipande, P. P. Shotwell, M. S. Chandrasekhar, R. Girard, T. D. Shintani, A. K. Peelen, L. M. Moons, K. Dittus, R. S. Ely, E. W. Vasilevskis, E. E.
- Year
- 2018
- Journal
- Chest
- Abstract
BACKGROUND: To develop and validate a dynamic risk model to predict daily changes in acute brain dysfunction (i.e., delirium and coma), discharge and mortality in intensive care unit (ICU) patients. METHODS: Using data from a multicenter prospective ICU cohort, we developed a daily Acute Brain Dysfunction-prediction model (ABD-pm) using multinomial logistic regression that estimated 15 transition probabilities (from 1 of 3 brain function states [normal, delirious, or comatose] to 1 of 5 possible outcomes [normal, delirious, comatose, ICU discharge, and dead]) using baseline and daily risk factors. Model discrimination was assessed using predictive characteristics such as negative predictive value [NPV]. Calibration was assessed by plotting empirical versus model-estimated probabilities. Internal validation was performed by bootstrap procedure. RESULTS: We analyzed data from 810 patients (6711 daily transitions). The ABD-pm included individual risk factors: mental status, age, pre-existing cognitive impairment, baseline and daily severity of illness, and daily administration of sedatives. The model yielded very high NPVs for “next day” delirium (NPV=0.823), coma (NPV= 0.892), normal cognitive state (NPV=0.875), ICU discharge (NPV=0.905), and mortality (NPV=0.981). The model demonstrated outstanding calibration when predicting the total number of patients expected to be in any given state across predicted risk. CONCLUSIONS: We developed and internally validated a dynamic risk model that predicts the daily risk for one of three cognitive states, ICU discharge, or mortality. The ABD-pm may be useful for predicting the proportion of patients for each outcome state across entire ICU populations to guide quality, safety, and care delivery activities.
- PMID
- Keywords
Coma
Delirium
Intensive Care Unit
Mortality
Prediction
- Page(s)
- Volume
- Issue
| Title | Authors | Journal | Year | Keywords |
|---|---|---|---|---|
| Undiagnosed delirium is frequent and difficult to predict: Results from a prevalence survey of a tertiary hospital. | Lange, P. W. Lamanna, M. Watson, R. Maier, A. B. | J Clin Nurs | 2019 |
Undiagnosed delirium |