Identifying infected emergency department patients admitted to the hospital ward at risk of clinical deterioration and intensive care unit transfer

Acad Emerg Med. 2010 Oct;17(10):1080-5. doi: 10.1111/j.1553-2712.2010.00872.x.

Abstract

Objectives: An important challenge faced by emergency physicians (EPs) is determining which patients should be admitted to an intensive care unit (ICU) and which can be safely admitted to a regular ward. Understanding risk factors leading to undertriage would be useful, but these factors are not well characterized.

Methods: The authors performed a secondary analysis of two prospective, observational studies of patients admitted to the hospital with clinically suspected infection from an urban university emergency department (ED). Inclusion criteria were as follows: adult ED patient (age 18 years or older), ward admission, and suspected infection. The primary outcome was transfer to an ICU within 48 hours of admission. Using multiple logistic regression, independent predictors of early ICU transfer were identified, and the area under the curve for the model was calculated.

Results: Of 5,365 subjects, 93 (1.7%) were transferred to an ICU within 48 hours. Independent predictors of ICU transfer included respiratory compromise (odds ratio [OR] = 2.5, 95% confidence interval [CI] = 1.4 to 4.3), congestive heart failure (CHF; OR = 2.2, 95% CI = 1.4 to 3.6), peripheral vascular disease (OR = 2.0, 95% CI = 1.1 to 3.7), systolic blood pressure (sBP) < 100 mm Hg (OR = 1.9, 95% CI = 1.2 to 2.9), heart rate > 90 beats/min (OR = 1.8, 95% CI = 1.1 to 2.8), and creatinine > 2.0 (OR = 1.8, 95% CI = 1.1 to 2.8). Cellulitis was associated with a lower likelihood of ICU transfer (OR = 0.33, 95% CI = 0.15 to 0.72). The area under the curve for the model was 0.73, showing moderate discriminatory ability.

Conclusions: In this preliminary study, independent predictors of ICU transfer within 48 hours of admission were identified. While somewhat intuitive, physicians should consider these factors when determining patient disposition.

Publication types

  • Research Support, N.I.H., Extramural

MeSH terms

  • Adult
  • Age Factors
  • Aged
  • Aged, 80 and over
  • Bacteremia / diagnosis*
  • Bacteremia / mortality
  • Bacteremia / therapy
  • Cohort Studies
  • Confidence Intervals
  • Critical Illness / mortality
  • Critical Illness / therapy
  • Decision Making
  • Emergency Medicine / standards
  • Emergency Medicine / trends
  • Emergency Service, Hospital / organization & administration*
  • Female
  • Hospital Mortality / trends
  • Hospital Units / organization & administration*
  • Hospitals, University
  • Humans
  • Intensive Care Units / organization & administration*
  • Kaplan-Meier Estimate
  • Length of Stay
  • Logistic Models
  • Male
  • Middle Aged
  • Odds Ratio
  • Patient Admission
  • Patient Selection
  • Patient Transfer / organization & administration*
  • Prospective Studies
  • Risk Factors
  • Sex Factors
  • Survival Analysis
  • Time Factors