EuroSCORE and the patients undergoing coronary bypass surgery at Santa Casa de São Paulo

Rev Bras Cir Cardiovasc. 2008 Apr-Jun;23(2):262-7. doi: 10.1590/s0102-76382008000200017.
[Article in English, Portuguese]

Abstract

Objective: The aim of this study was to assess the performance of the European Risk System in Cardiac Operations (EuroSCORE) model to predict mortality in patients undergoing myocardial revascularization at the Division of Cardiovascular Surgery of Santa Casa de São Paulo Medical School.

Methods: From May 2005 to November 2006, 100 consecutive patients undergoing coronary artery bypass surgery were retrospectively analyzed. The records of these patients were reviewed in order to retrieve those variables included in the EuroSCORE risk scoring method. The correlation of predicted and observed mortality was compared. Statistical analysis was performed using chi-square test for univariate analysis and Hosmer-Lemeshow Test for logistic regression model.

Results: Hospital mortality was 5%. For EuroSCORE univariate analysis, findings were as follows: score 0-2 predicted mortality 0.40%, observed 0.00%; score 3-5 predicted mortality 1.45%, observed 0.00%; score greater than 6 predicted mortality 3.15%, observed 7.94%. Although these differences, p-value was 0.213 with no statistical significance. The p-value for the Hosmer-Lemeshow Test was < 0.001 indicating poor calibration of the model for this sample.

Conclusion: The EuroSCORE model is a simple, objective system to estimate hospital mortality. However, to validate the logistic regression analysis, it is necessary hundreds of patients, which limit its widespread application.

Publication types

  • Comparative Study

MeSH terms

  • Adult
  • Aged
  • Aged, 80 and over
  • Brazil
  • Chi-Square Distribution
  • Coronary Artery Bypass / mortality*
  • Coronary Disease / diagnosis
  • Coronary Disease / surgery*
  • Female
  • Hospital Mortality
  • Humans
  • Logistic Models
  • Male
  • Middle Aged
  • Retrospective Studies
  • Risk Assessment / methods*
  • Risk Factors