Physician risk assessment and APACHE scores in cardiac care units

Clin Cardiol. 1999 May;22(5):366-8. doi: 10.1002/clc.4960220514.


Background: The need to correct outcome data for case mix is well recognized, but risk assessment for coronary care unit (CCU) patients remains problematic.

Hypothesis: This study determined the feasibility of using physicians' opinions to predict mortality for CCU patients and compared their results to Acute Physiology and Chronic Health Evaluation II (APACHE II) scores.

Methods: A prospective observational study was performed on consecutive patients admitted to a university-affiliated Veterans Affairs Medical Center CCU over a 2-month period. Physician assessment of likely mortality during hospitalization, obtained using an MD Prognosis Score ranging from 1 (best) to 7 (worst), was compared with APACHE II scores.

Results: MD Prognosis Scores were obtained on 122 of the 237 eligible patients (51% response rate) and averaged 2.3 +/- 1.4 (mean +/- standard deviation). APACHE II scores on these patients averaged 9.9 +/- 4.8 (range 2-29) with very poor correlation between the two methods (r = 0.3). Of the four patients who died, three had MD prognosis scores of 7. None of the survivors had scores of 7 and only three had scores of 6. APACHE II did not predict a high likelihood that any of the patients would die (none with > 90% likelihood of mortality).

Conclusions: APACHE scores are inadequate for cardiac patients. Although physicians can identify CCU patients most likely to die, reliance on physician scoring systems is limited by difficulties in obtaining their opinion. A new method of risk assessment for acutely ill cardiac patients is needed if CCU outcomes are to be compared across institutions.

Publication types

  • Research Support, U.S. Gov't, Non-P.H.S.

MeSH terms

  • Coronary Care Units / statistics & numerical data*
  • Coronary Disease / diagnosis
  • Coronary Disease / mortality*
  • Feasibility Studies
  • Hospital Mortality
  • Hospitals, Veterans / statistics & numerical data
  • Humans
  • Minnesota / epidemiology
  • Physicians, Family*
  • Prognosis
  • Prospective Studies
  • Risk Assessment
  • Surveys and Questionnaires