Bedside tool improves prognostication after cardiac arrest

By Piriya Mahendra

A bedside prediction tool could estimate the probability of favorable neurologic survival in successfully resuscitated patients after in-hospital cardiac arrest, say researchers in the Archives of Internal Medicine.

The prediction tool "offers the potential to provide physicians reliable and valuable prognostic information for discussions with patients and their families after successful resuscitation," remark Paul Chan (Mid America Heart Institute, Kansas City, Missouri, USA) and co-authors.

They identified 42,957 patients from 551 hospitals in the Get With the Guidelines-Resuscitation registry between January 2000 and October 2009. All patients were successfully resuscitated from an in-hospital cardiac arrest.

Two-thirds of the study population were randomly selected for the derivation cohort and one-third for the validation cohort. Within the derivation sample, multivariate analysis was used to identify significant predictors for favorable neurologic survival to discharge.

Favorable neurologic status was defined as the absence of severe neurologic deficits (cerebral performance category of ≤2). The rates of favorable neurologic survival were similar across the derivation and validation cohorts, at 24.6% and 24.5%, respectively.

Favorable neurologic survival was associated with eleven variables. These included young age (≤49 years), initial cardiac arrest rhythm of ventricular fibrillation or pulseless ventricular tachycardia with defibrillation time of 2 minutes or less, baseline neurologic status with disability, and arrest location in a monitored unit.

Short duration of resuscitation (2-4 minutes), absence of mechanical ventilation, and renal insufficiency (serum creatinine >2 mg/dL within 24 hours of cardiac arrest) were also predictors for favorable neurologic survival.

In addition, hepatic insufficiency (direct bilirubin >2 mg/dL and aspartate aminotransferase >2 times upper limit of normal or liver cirrhosis within 24 hours), sepsis, malignant disease, and hypotension prior to arrest were associated with favorable neurologic survival.

The model had "excellent" discrimination, note the authors, with a c-statistic of 0.80 for the derivation and validation cohorts, and calibration.

Based on the coefficients of the model predictors, they developed the Cardiac Arrest Survival Postresuscitation In-hospital (CASPRI) score , where a higher summary score denotes a decreased likelihood for favorable neurologic survival.

Patients in the top decile (CASPRI score <10) had a mean 70.7% probability of favorable neurologic survival, whereas patients in the bottom decile (CASPRI score ≥28) had a 2.8% probability of favorable neurologic survival, showing that "the prediction tool demonstrated the ability to identify patients across a wide range of rates of favorable neurologic survival," the authors say.

"We believe that this tool is simple to use, addresses a critical unmet need for better prognostication after cardiac arrest, and has the potential to enhance communication with patients and families," they conclude.

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