Early bispectral index and sedation requirements during therapeutic hypothermia predict neurologic recovery following cardiac arrest.

ABSTRACT

OBJECTIVES: To test the hypothesis that low bispectral index scores and low sedative requirements during therapeutic hypothermia predict poor neurologic outcome. DESIGN: Observational study of a prospectively collected cohort. SETTING: Cardiovascular ICU. PATIENTS One hundred sixty consecutive cardiac arrest patients treated with therapeutic hypothermia. INTERVENTIONS: None. MEASUREMENTS AND RESULTS: Eighty-four of the 141 subjects (60%) who survived hypothermia induction were discharged from the ICU with poor neurologic outcome, defined as a cerebral performance category score of 3, 4, or 5. These subjects had lower bispectral index (p < 0.001) and sedative requirements (p < 0.001) during hypothermia compared with the 57 subjects discharged with good outcome. Early prediction of neurologic recovery was best 7 hours after ICU admission, and median bispectral index scores at that time were 31 points lower in subjects discharged with poor outcome (11 [interquartile range, 4-29] vs 42 [37-49], p < 0.001). Median sedation requirements decreased by 17% (interquartile range, -50 to 0%) 7 hours after ICU admission in subjects with poor outcome but increased by 50% (interquartile range, 0-142%) in subjects with good outcome (p < 0.001). Each 10-point decrease in bispectral index was independently associated with a 59% increase in the odds of poor outcome (95% CI, 32-76%; p < 0.001). The model including bispectral index and sedative requirement correctly reclassified 15% of subjects from good to poor outcome and 1% of subjects from poor to good outcome. The model incorrectly reclassified 1% of subjects from poor to good outcome but did not incorrectly reclassify any from good to poor outcome. CONCLUSIONS: Bispectral index scores and sedative requirements early in the course of therapeutic hypothermia improve the identification of patients who will not recover from brain anoxia. The ability to accurately predict nonrecovery after cardiac arrest could facilitate discussions with families, reduce patient suffering, and limit use of ICU resources in futile cases.