Background: Considerations about the application of cardiopulmonary resusci
tation (CPR) should include the expected probability of survival. The survi
val probability after CPR maybe more accurately estimated by the occurrence
in time of the prearrest morbidity of patients.
Objective: To identify risk factors for poor survival after CPR in relation
to the dynamics of prearrest morbidity.
Methods: Medical records of CPR patients were reviewed. Prearrest morbidity
was established by categorizing the medical diagnoses according to 3 funct
ional time frames: before hospital admission, on hospital admission, and du
ring hospital admission. Indicators of poor survival after CPR were identif
ied through a logistic regression model.
Results: included in the study were 553 CPR patients with a median age of 6
8 years (age range, 18-98 years); 21.7%, survived to hospital discharge. In
dependent indicators of poor outcome were an age of 70 years or older (odds
ratio [OR] = 0.6, 95% confidence interval [CI] = 0.4-0.9),stroke (OR = 0.3
, 95% CI = 0.1-0.7) or renal failure (OR = 0.31. 95% CI = 0.1-0.8) before h
ospital admission, and congestive heart failure during hospital admission (
OR = 0.4, 95% CI = 0.2-0.9). Indicators of good survival were angina pector
is before hospital admission (OR = 2.1, 95% CI = 1.3-.3.3) or ventricular d
ysrhythmia as the diagnosis on hospital admission (OR = 11.0, 95% CI = 4.1-
33.7). Based on a logistic regression model, 17.4% of our CPR patients (n =
96) were identified as having a high risk for a poor outcome (<10% surviva
l).
Conclusions: Time of prearrest morbidity has a prognostic value for surviva
l after CPR. Patients at risk for poor survival can be identified on or dur
ing hospital admission, but the reliability and validity of the model needs
further research. Although decisions will not be made by the model, its in
formation can be useful for physicians in discussions about patient prognos
es and to make decisions about CPR with more confidence.