Geriatric Fever Score: a new decision rule for geriatric care

PLoS One. 2014 Oct 23;9(10):e110927. doi: 10.1371/journal.pone.0110927. eCollection 2014.

Abstract

Background: Evaluating geriatric patients with fever is time-consuming and challenging. We investigated independent mortality predictors of geriatric patients with fever and developed a prediction rule for emergency care, critical care, and geriatric care physicians to classify patients into mortality risk and disposition groups.

Materials and methods: Consecutive geriatric patients (≥65 years old) visiting the emergency department (ED) of a university-affiliated medical center between June 1 and July 21, 2010, were enrolled when they met the criteria of fever: a tympanic temperature ≥37.2°C or a baseline temperature elevated ≥1.3°C. Thirty-day mortality was the primary endpoint. Internal validation with bootstrap re-sampling was done.

Results: Three hundred thirty geriatric patients were enrolled. We found three independent mortality predictors: Leukocytosis (WBC >12,000 cells/mm3), Severe coma (GCS ≤ 8), and Thrombocytopenia (platelets <150 10(3)/mm3) (LST). After assigning weights to each predictor, we developed a Geriatric Fever Score that stratifies patients into two mortality-risk and disposition groups: low (4.0%) (95% CI: 2.3-6.9%): a general ward or treatment in the ED then discharge and high (30.3%) (95% CI: 17.4-47.3%): consider the intensive care unit. The area under the curve for the rule was 0.73.

Conclusions: We found that the Geriatric Fever Score is a simple and rapid rule for predicting 30-day mortality and classifying mortality risk and disposition in geriatric patients with fever, although external validation should be performed to confirm its usefulness in other clinical settings. It might help preserve medical resources for patients in greater need.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Academic Medical Centers
  • Aged
  • Aged, 80 and over
  • Critical Care
  • Decision Support Systems, Clinical*
  • Decision Support Techniques
  • Emergency Service, Hospital
  • Emergency Treatment / methods
  • Female
  • Fever / diagnosis*
  • Geriatrics / methods*
  • Humans
  • Intensive Care Units
  • Male
  • Multivariate Analysis
  • Patient Discharge
  • Prospective Studies
  • Risk Assessment / methods*
  • Severity of Illness Index*
  • Taiwan

Grants and funding

This study was supported by grant CMNCKU10305 from the Chi-Mei Medical Center. The funder had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.