CONTEXT: Coma is a state of profound unresponsiveness that can occur as a serious perioperative complication. The study of risk factors for, and sequelae of, postoperative coma has been limited due to the rarity of the event. OBJECTIVE: To determine the incidence, risk factors and impact of postoperative coma in a large patient population. DESIGN: Observational study using a prospectively gathered national dataset. PATIENTS: Data from 858 606 patients were analysed. MAIN OUTCOME MEASURES: The incidence of postoperative coma of more than 24-h duration was identified. Logistic regression was used to identify independent predictors and develop a risk model of postoperative coma in derivation and validation cohorts; 30-day mortality was also analysed. RESULTS: The incidence of postoperative coma was 0.06%. Multivariate analysis revealed the following independent predictors: liver disease, systemic sepsis, age at least 63 years, renal disease, emergency operation, cardiac disease, hypertension, prior neurological disease, diabetes mellitus and BMI 25 to 29.99 kg m (protective). These predictors were incorporated into a risk index classification; odds ratios for postoperative coma increased from 2.5 with one risk factor to 18.4 with three. Coma was associated with 74.2% all-cause mortality; coma associated with cardiac arrest had a 1.9-fold higher mortality. CONCLUSION: This is the largest study of postoperative coma ever reported and will be useful for determining risk of coma of more than 24 h duration when evaluating an unresponsive patient following surgery. Data on prognosis will aid medical and ethical decision-making for the comatose surgical patient.
CONTEXT: Coma is a state of profound unresponsiveness that can occur as a serious perioperative complication. The study of risk factors for, and sequelae of, postoperative coma has been limited due to the rarity of the event. OBJECTIVE: To determine the incidence, risk factors and impact of postoperative coma in a large patient population. DESIGN: Observational study using a prospectively gathered national dataset. PATIENTS: Data from 858 606 patients were analysed. MAIN OUTCOME MEASURES: The incidence of postoperative coma of more than 24-h duration was identified. Logistic regression was used to identify independent predictors and develop a risk model of postoperative coma in derivation and validation cohorts; 30-day mortality was also analysed. RESULTS: The incidence of postoperative coma was 0.06%. Multivariate analysis revealed the following independent predictors: liver disease, systemic sepsis, age at least 63 years, renal disease, emergency operation, cardiac disease, hypertension, prior neurological disease, diabetes mellitus and BMI 25 to 29.99 kg m (protective). These predictors were incorporated into a risk index classification; odds ratios for postoperative coma increased from 2.5 with one risk factor to 18.4 with three. Coma was associated with 74.2% all-cause mortality; coma associated with cardiac arrest had a 1.9-fold higher mortality. CONCLUSION: This is the largest study of postoperative coma ever reported and will be useful for determining risk of coma of more than 24 h duration when evaluating an unresponsive patient following surgery. Data on prognosis will aid medical and ethical decision-making for the comatose surgical patient.
Authors: Robert E Freundlich; Jessica W Newman; Kevin K Tremper; Jill M Mhyre; Sachin Kheterpal; Theodore J Sanford; Alan R Tait Journal: Anesthesiol Res Pract Date: 2015-01-13