Predicting survival from in-hospital CPR - Meta-analysis and validation of a prediction model

Objective: To better clarify patient factors that predict survival from in-hospital cardiopulmonary resuscitation (CPR), using two methods: 1) meta-analysis and 2) validation of a prediction model, the pre-arrest morbidity (PAM) index. Design: Meta-analysis of previously published studies by standard techniques. Retrospective chart review of validation sample. Setting: University-affiliated teaching hospital. Patients/participants: Meta-analytic sample of 21 previous studies from 1965-1989. The validation sample consisted of all patients surviving resuscitation from the authors' hospital during the period September 1986 to January 1991. A matched sample of patients who did not survive from the same time period was used as the comparison group. Interventions: None. Measurements and main results: The strongest negative predictors of survival, by meta-analysis, were renal failure (r=0.088, p<0.0002), cancer (r=0.08, p<0.0002), and age more than 60 years (r=0.063, p<0.006). Sepsis (r=0.046, p<0.02), recent cerebrovascular accident (CVA) (r=0.038, p<0.04), and congestive heart failure (CHF) class III/IV (r=0.036, p<0.05) were weaker negative predictors. Presence of acute myocardial infarction (AMI) was a significant positive predictor of survival (r=0.15, p<0.0001). The PAM score was highly predictive of survival in a logistic regression model (p<0.0003, R ²=9.6%). No patient who survived to discharge had a PAM score higher than 8. Conclusion: Meta-analysis reveals that the most significant negative predictors of survival from CPR are renal failure, cancer, and age more than 60 years, while AMI is a significant positive predictor. The PAM index is a useful method of stratifying probability of survival from CPR, especially for those patients with high PAM scores, who have essentially no chance of survival.