• Jonathan M Weimer, Amy S Nowacki, and Jennifer A Frontera.
• 1Cleveland Clinic Lerner College of Medicine, Cerebrovascular Center of the Neurological Institute, Cleveland Clinic, Cleveland, OH. 2Quantitative Health Sciences Department, Cleveland Clinic, Cleveland, OH.
• Crit. Care Med. 2016 Jun 1; 44 (6): 1161-72.

ObjectivesWithdrawal of life-sustaining therapy may lead to premature limitations of life-saving treatments among patients with intracranial hemorrhage, representing a self-fulfilling prophecy. We aimed to determine whether our algorithm for the withdrawal of life-sustaining therapy decision would accurately identify patients with a high probability of poor outcome, despite aggressive treatment.DesignRetrospective analysis of prospectively collected data.SettingTertiary-care Neuro-ICU.PatientsIntraparenchymal, subdural, and subarachnoid hemorrhage patients.InterventionsBaseline demographics, clinical status, and hospital course were assessed to determine the predictors of in-hospital mortality and 12-month death/severe disability among patients receiving maximal therapy. Multivariable logistic regression models developed on maximal therapy patients were applied to patients who underwent withdrawal of life-sustaining therapy to predict their probable outcome had they continued maximal treatment. A validation cohort of propensity score-matched patients was identified from the maximal therapy cohort, and their predicted and actual outcomes compared.Measurements And Main ResultsOf 383 patients enrolled, there were 128 subarachnoid hemorrhage (33.4%), 134 subdural hematoma (35.0%), and 121 intraparenchymal hemorrhage (31.6%). Twenty-six patients (6.8%) underwent withdrawal of life-sustaining therapy and died, 41 (10.7%) continued maximal therapy and died in hospital, and 316 (82.5%) continued maximal therapy and survived to discharge. The median predicted probability of in-hospital death among withdrawal of life-sustaining therapy patients was 35% had they continued maximal therapy, whereas the median predicted probability of 12-month death/severe disability was 98%. In the propensity-matched validation cohort, 16 of 20 patients had greater than or equal to 80% predicted probability of death/severe disability at 12 months, matching the observed outcomes and supporting the strength and validity of our prediction models.ConclusionsThe withdrawal of life-sustaining therapy decision may contribute to premature in-hospital death in some patients who may otherwise have been expected to survive to discharge. However, based on probability models, nearly all of the patients who underwent withdrawal of life-sustaining therapy would have died or remained severely disabled at 12 months had maximal therapy been continued. Withdrawal of life-sustaining therapy may not represent a self-fulfilling prophecy.

22 keywords...

hide…