A simple ABCD score to stratify patients with respect to the probability of survival following in-hospital cardiopulmonary resuscitation

Background: Cardiopulmonary resuscitation (CPR) is occurring more frequently at community hospitals but most patients undergoing CPR do not survive to discharge. Tools to predict CPR survival can be improved by the identification of high-yield clinical indicators.Objective: To identify variables associated with survival to discharge following in-hospital cardiac arrest. Methods: Retrospective cohort study of 463,530 hospital admissions from the Nationwide Inpatient Sample (2012-2016). The analysis includes adults (age >= 50) who underwent in-hospital CPR at US community hospitals. Results: Overall survival to discharge was 29.8% (95% CI: 29.5-30.1%). Age was the strongest predictor of survival and had greater prognostic value than the Charlson comorbidity index. Obesity was associated with improved survival (35.9%, 95% CI: 35.1-36.7%), whereas underweight patients had decreased survival (24.0%, 95% CI: 22.2-25.7%). Acute indicators of poor survival included hyperkalemia, hypercalcemia, and sepsis. We generated an ABCD index based upon four high-yield variables (age, body habitus, comorbidity, day of hospital admission). An ABCD score of 2 or less was a sensitive but non-specific predictor of post-CPR survival (96.8% sensitivity, 95% CI: 96.6-97.0), and those with extreme scores differed 3.8-fold with respect to post-CPR survival probability (46.0% versus 12.1%). Conclusion: Age is the strongest predictor of post-CPR survival, but body habitus is also an important indicator that may currently be underutilized. Our results support improved post-CPR survival of obese patients, consistent with an 'obesity paradox'. The ABCD score provides an efficient means of risk-stratifying patients and can be calculated in less than 1 minute.