Prediction of failure to survive following in-hospital cardiopulmonary resuscitation: comparison of two predictive instruments

Resuscitation. 1994 Jul;28(1):21-5. doi: 10.1016/0300-9572(94)90050-7.


The purpose of this study is to compare two clinical predictive rules, the pre-arrest-morbidity (PAM) index and the prognosis-after-resuscitation (PAR) score, which predict failure to survive following in-hospital cardiopulmonary resuscitation (CPR). The study population consisted of 274 consecutive adult patients who underwent CPR at University College Hospital in Galway, Ireland over a 2-year period. The PAM and PAR scores were calculated from the most recent data available for each variable prior to cardiac arrest. Performance of the predictive scores was compared using Student's t-test, Pearson chi-square, Fisher's exact test, and receiver-operating characteristic (ROC) curves where appropriate. The PAM index identified 23 patients with a score > 4, while the PAR score identified 59 patients with a score > 5, none of whom survived. The sensitivity of the PAR score for the prediction of failure to survive was 23.7%, while that of the PAM index was 9.2%; neither index incorrectly identified a patient as a non-survivor who eventually survived. The PAR score also had a greater area under the ROC curve, although this difference was not statistically significant (P = 0.07). In summary, the PAR score performed better than the PAM index in the identification of patients who are unlikely to survive following CPR. Although further confirmation is necessary, it may provide useful prognostic information to physicians and patients involved with decisions about do-not-resuscitate orders.

Publication types

  • Comparative Study

MeSH terms

  • Adolescent
  • Adult
  • Aged
  • Aged, 80 and over
  • Cardiopulmonary Resuscitation*
  • Confidence Intervals
  • Heart Arrest / mortality
  • Heart Arrest / therapy*
  • Humans
  • Inpatients / statistics & numerical data
  • Middle Aged
  • Morbidity
  • Predictive Value of Tests
  • Prognosis
  • Sensitivity and Specificity
  • Survival Rate
  • Time Factors
  • Treatment Failure