Beatriz Korc-Grodzicki1, Sung W Sun, Qin Zhou, Alexia Iasonos, Bryan Lu, James C Root, Robert J Downey, William P Tew. 1. *Geriatrics Service, Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, NY †Department of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, New York, NY ‡Department of Psychiatry and Behavioral Sciences, Memorial Sloan Kettering Cancer Center, New York, NY §Thoracic Service, Department of Surgery, Memorial Sloan Kettering Cancer Center, New York, NY; and ¶Gynecologic Medical Oncology Service, Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, NY.
Abstract
OBJECTIVE: This study aimed to describe the implementation of preoperative geriatric assessment (GA) in patients undergoing major cancer surgery and to determine predictors of postoperative delirium. BACKGROUND: Geriatric surgical patients have unique vulnerabilities and are at increased risk of developing postoperative delirium. METHODS: Geriatricians at Memorial Sloan Kettering Cancer Center risk-stratify surgical patients with solid tumors, ages 75 years and older, using preoperative GA, which includes basic and instrumental activities of daily living (ADLs, IADLs), cognition (Mini-Cog test), history of falls, nutritional state, and comorbidities (Charlson Comorbidity Index). The Geriatrics Service evaluates patients for postoperative delirium using the confusion assessment method. A retrospective review was performed. The associations between GA and postoperative outcomes were evaluated. Univariate logistic regression analysis was performed to determine the predictive value of GA for postoperative delirium, and a multivariate model was built. RESULTS: In total, 416 patients who received preoperative evaluation by the Geriatrics Service between September 1, 2010, and December 31, 2011, were included. Delirium occurred in 19% of patients. Patients with delirium had longer length of hospital stay (P < 0.001) and greater likelihood of discharge to a rehabilitation facility (P < 0.001). Charlson Comorbidity Index score, history of falls, dependent on IADL, and abnormal Mini-Cog test results predicted postoperative delirium on univariate analysis. Developed using a stepwise selection method, a multivariate model to predict delirium is presented including Charlson Comorbidity Index score (P = 0.032), dependence IADLs (P = 0.011), and falls history (P = 0.056). CONCLUSIONS: Preoperative GA is feasible and may achieve a better understanding of older patients' perioperative risks, including delirium.
OBJECTIVE: This study aimed to describe the implementation of preoperative geriatric assessment (GA) in patients undergoing major cancer surgery and to determine predictors of postoperative delirium. BACKGROUND: Geriatric surgical patients have unique vulnerabilities and are at increased risk of developing postoperative delirium. METHODS: Geriatricians at Memorial Sloan Kettering Cancer Center risk-stratify surgical patients with solid tumors, ages 75 years and older, using preoperative GA, which includes basic and instrumental activities of daily living (ADLs, IADLs), cognition (Mini-Cog test), history of falls, nutritional state, and comorbidities (Charlson Comorbidity Index). The Geriatrics Service evaluates patients for postoperative delirium using the confusion assessment method. A retrospective review was performed. The associations between GA and postoperative outcomes were evaluated. Univariate logistic regression analysis was performed to determine the predictive value of GA for postoperative delirium, and a multivariate model was built. RESULTS: In total, 416 patients who received preoperative evaluation by the Geriatrics Service between September 1, 2010, and December 31, 2011, were included. Delirium occurred in 19% of patients. Patients with delirium had longer length of hospital stay (P < 0.001) and greater likelihood of discharge to a rehabilitation facility (P < 0.001). Charlson Comorbidity Index score, history of falls, dependent on IADL, and abnormal Mini-Cog test results predicted postoperative delirium on univariate analysis. Developed using a stepwise selection method, a multivariate model to predict delirium is presented including Charlson Comorbidity Index score (P = 0.032), dependence IADLs (P = 0.011), and falls history (P = 0.056). CONCLUSIONS: Preoperative GA is feasible and may achieve a better understanding of older patients' perioperative risks, including delirium.
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