Development of a clinical prediction score for congestive heart failure diagnosis in the emergency care setting: The Brest score

Am J Emerg Med. 2016 Dec;34(12):2277-2283. doi: 10.1016/j.ajem.2016.08.023. Epub 2016 Aug 14.

Abstract

Objective: To derive and validate a clinical prediction rule of acute congestive heart failure obtainable in the emergency care setting.

Design: Derivation of the score was performed on a retrospective 927 patients cohort admitted to our Emergency Department for dyspnea. The prediction model was externally validated on an independent 206-patient prospective cohort.

Interventions and measures: During the derivation phase, variables associated with acute congestive heart failure were included in a multivariate regression model. Logistic regression coefficients were used to assign scoring points to each variable. During the validation phase, every diagnosis was confirmed by an independent adjudication committee.

Results: The score comprised 11 variables: age ≥65 years (1 point), seizure dyspnea (2 points), night outbreak (1 point), orthopnea (1 point), history of pulmonary edema (2 points), chronic pulmonary disease (-2 points), myocardial infarction (1 point), crackles (2 points), leg edema (1 point), ST-segment abnormality (1 point), atrial fibrillation/flutter (1 point) on electrocardiography. In the validation step, 30 patients (14.6%) had a low clinical probability of acute congestive heart failure (score ≤3), of which only 2 (6.7%) had a proven acute cardiogenic pulmonary edema. The prevalence of acute congestive heart failure was 58.5% in the 94 patients with an intermediate probability (score of 4-8) and 91.5% in the 82 patients (39.8%) with a high probability (score ≥9).

Conclusion: This score of acute congestive heart failure based on easily available and objective variables is entirely standardized. Applying the score to dyspneic adult emergency patients may enable a more rapid and efficient diagnostic process.

Publication types

  • Validation Study

MeSH terms

  • Aged
  • Aged, 80 and over
  • Decision Support Techniques*
  • Dyspnea / etiology
  • Emergency Service, Hospital*
  • Female
  • Heart Failure / complications
  • Heart Failure / diagnosis*
  • Humans
  • Logistic Models
  • Male
  • Middle Aged
  • Multivariate Analysis
  • Probability
  • Prospective Studies
  • Retrospective Studies
  • Risk Factors