J Korean Soc Emerg Med.  1998 Mar;9(1):39-44.

Prediction of Failure to Survive Following In-hospital Cardiopulmonary Resuscitation

• Kim SM
• Hwang SO
• Lee KH
• Lee JW
• Hong ES
• Lim JC
• Oh BJ
• Lim KS

Abstract

BACKGROUND AND PURPOSE: The purpose of this study is to compare two clinical predictive rules, the pre-arrestmorbidity(PAM) index and the prognosis-after-resuscitation(PAR) score, which predict failure to survive following in-hospital cardiopulmonary resuscitation(CPR). METHOD: The study population consisted of 162 consecutive adult patients who underwent CPR at Wonju Christian Hospital over a year period. The PAM index and PAR score were calculated from the most recent data available for each variable prior to cardiac arrest. Each predictive tool was compared between the group of discharge alive and the group of in-hospital mortality. Performance of the predictive scores was also compared by receiver-operating characteristic(ROC) curves where appropriate.
RESULTS
PAM index of study population was 4.39+/-2.69 and PAR score was 2.99+/-3.36. PAM index in the group of discharge alive was 1.87+/-2.79, and PAM index in the group of ih-hospital mortality was 4.51+/-2.62. PAR score in the group of discharge alive was 0.75+/-1.75, and PAR score in the group of in-hospital mortality was 3.1+/-3.4. The PAM index identified 15 patients with a score>8, while the PAR score identified 39 patients with a score>4, none of whom survived. The sensitivity of the PAR score for the prediction of failure to survive was 25%, while that of the PAM index was 10%; neither index incorrectly identified a patient as a non-survivor who eventually survived. Both of predictive methods were not significantly different in the ROC curve.
CONCLUSION
Although further confirmation is necessary, PAM index and PAR score may provide useful prognostic information to physicians and patients involved with decisions about do-no- resuscitate orders.

MeSH Terms

Adult
Cardiopulmonary Resuscitation*
Gangwon-do
Heart Arrest
Hospital Mortality
Humans
Mortality
ROC Curve