Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2017 Jan;55(1):4-11.
doi: 10.1080/15563650.2016.1222616. Epub 2016 Sep 20.

The need for ICU admission in intoxicated patients: a prediction model

Affiliations
Free article

The need for ICU admission in intoxicated patients: a prediction model

Raya Brandenburg et al. Clin Toxicol (Phila). 2017 Jan.
Free article

Abstract

Context: Intoxicated patients are frequently admitted from the emergency room to the ICU for observational reasons. The question is whether these admissions are indeed necessary.

Objective: The aim of this study was to develop a model that predicts the need of ICU treatment (receiving mechanical ventilation and/or vasopressors <24 h of the ICU admission and/or in-hospital mortality).

Materials and methods: We performed a retrospective cohort study from a national ICU-registry, including 86 Dutch ICUs. We aimed to include only observational admissions and therefore excluded admissions with treatment, at the start of the admission that can only be applied on the ICU (mechanical ventilation or CPR before admission). First, a generalized linear mixed-effects model with binominal link function and a random intercept per hospital was developed, based on covariates available in the first hour of ICU admission. Second, the selected covariates were used to develop a prediction model based on a practical point system. To determine the performance of the prediction model, the sensitivity, specificity, positive, and negative predictive value of several cut-off points based on the assigned number of points were assessed.

Results: 9679 admissions between January 2010 until January 2015 were included for analysis. In total, 632 (6.5%) of the patients admitted to the ICU eventually turned out to actually need ICU treatment. The strongest predictors for ICU treatment were respiratory insufficiency, age >55 and a GCS <6. Alcohol and "other poisonings" (e.g., carbonmonoxide, arsenic, cyanide) as intoxication type and a systolic blood pressure ≥130 mmHg were indicators that ICU treatment was likely unnecessary. The prediction model had high sensitivity (93.4%) and a high negative predictive value (98.7%).

Discussion and conclusion: Clinical use of the prediction model, with a high negative predictive value (98.7%), would result in 34.3% less observational admissions.

Keywords: Critical care; costs; outcome; overdose; poisoning.

PubMed Disclaimer

Similar articles

Cited by

MeSH terms