INTRODUCTION: Reported morbidity varies widely for laparoscopic cholecystectomy (LC). A reliable method to determine complication risk may be useful to optimize care. We developed an integer-based risk score to determine the likelihood of major complications following LC. METHODS: Using the Nationwide Inpatient Sample 1998-2006, patient discharges for LC were identified. Using previously validated methods, major complications were assessed. Preoperative covariates including patient demographics, disease characteristics, and hospital factors were used in logistic regression/bootstrap analyses to generate an integer score predicting postoperative complication rates. A randomly selected 80% was used to create the risk score, with validation in the remaining 20%. RESULTS: Patient discharges (561,923) were identified with an overall complication rate of 6.5%. Predictive characteristics included: age, sex, Charlson comorbidity score, biliary tract inflammation, hospital teaching status, and admission type. Integer values were assigned and used to calculate an additive score. Three groups stratifying risk were assembled, with a fourfold gradient for complications ranging from 3.2% to 13.5%. The score discriminated well in both derivation and validation sets (c-statistic of 0.7). CONCLUSION: An integer-based risk score can be used to predict complications following LC and may assist in preoperative risk stratification and patient counseling.
INTRODUCTION: Reported morbidity varies widely for laparoscopic cholecystectomy (LC). A reliable method to determine complication risk may be useful to optimize care. We developed an integer-based risk score to determine the likelihood of major complications following LC. METHODS: Using the Nationwide Inpatient Sample 1998-2006, patient discharges for LC were identified. Using previously validated methods, major complications were assessed. Preoperative covariates including patient demographics, disease characteristics, and hospital factors were used in logistic regression/bootstrap analyses to generate an integer score predicting postoperative complication rates. A randomly selected 80% was used to create the risk score, with validation in the remaining 20%. RESULTS:Patient discharges (561,923) were identified with an overall complication rate of 6.5%. Predictive characteristics included: age, sex, Charlson comorbidity score, biliary tract inflammation, hospital teaching status, and admission type. Integer values were assigned and used to calculate an additive score. Three groups stratifying risk were assembled, with a fourfold gradient for complications ranging from 3.2% to 13.5%. The score discriminated well in both derivation and validation sets (c-statistic of 0.7). CONCLUSION: An integer-based risk score can be used to predict complications following LC and may assist in preoperative risk stratification and patient counseling.
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