Assessment of Perioperative Morbidity for Radical Cystectomy in Elderly Patients

• Main Author: Wendel, Elizabeth
• Format: Others
• Language: en
• Published: Harvard University 2015
• Online Access: http://nrs.harvard.edu/urn-3:HUL.InstRepos:17295879

OBJECTIVE: To assess the perioperative morbidity and impact of comorbidities in elderl patients undergoing radical cystectomy (RC) for bladder cancer. PATIENTS AND METHODS: A retrospective study of 52 patients greater than 70 years old undergoing RC for bladder cancer at Brigham and Women’s Hospital from 1995 - 2011. Comorbidity factors, as measured by age, ASA score, age-adjusted Charlson Comorbidity Index (ACCI), BMI, and preoperative GFR were analyzed. Perioperative morbidity was defined as any complication during hospitalization or subsequent 90-day follow-up. We analyzed perioperative complications using the Clavien-Dindo Classification of Surgical Complications, the length of stay (LOS), and onset of toleration of house diet. Multivariate analysis (ordered logistic regression) was used to correlate baseline status with peri- and postoperative morbidity. RESULTS: Thirty-two patients had no complications. Twenty patients (39 %) had at least one complication. 31 % had minor complications (Clavien score 1 or 2), and 8 % had a major complication (Clavien score ≥ 3a). Only one patient needed intervention for a surgical complication. After discharge, the 90-day complication rate was 11.5 % and the 90-day readmission rate was 9.6 %. Perioperative mortality rate was 0 %. 54 % tolerated house diet by one week. The mean LOS was 9.6 days. It was 3.5 days longer in case of complication. Multivariable statistical analysis was done using the method of ordered logistic regression and found that intolerance of house diet after one week was a risk factor for complication (p = 0.02). A Charlson score ≥ 1 (p = 0.01) and an ASA score ≥ 1 (p = 0.03) were risk factors for LOS ≥ 10 days. CONCLUSION: These results suggest that RC can be performed safely in the elderly. Follow-up studies with larger patient populations may determine clearer predictors of outcome.