Risk factors and indications for 30-day readmission after primary surgery for epithelial ovarian cancer

上皮性卵巢癌初次手术后30天内再入院的风险因素和指征

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Abstract

BACKGROUND: To identify patients at risk for postoperative morbidities, we evaluated indications and factors associated with 30-day readmission after epithelial ovarian cancer surgery. METHODS: Patients undergoing primary surgery for epithelial ovarian cancer between January 2, 2003, and December 29, 2008, were evaluated. Univariable and multivariable logistic regression models were fit to identify factors associated with 30-day readmission. A parsimonious multivariable model was identified using backward and stepwise variable selection. RESULTS: In total, 324 (60.2%) patients were stage III and 91 (16.9%) were stage IV. Of all 538 eligible patients, 104 (19.3%) were readmitted within 30 days. Cytoreduction to no residual disease was achieved in 300 (55.8%) patients, and 167 (31.0%) had measurable disease (≤1 cm residual disease). The most common indications for readmission were surgical site infection (SSI; 21.2%), pleural effusion/ascites management (14.4%), and thromboembolic events (12.5%). Multivariate analysis identified American Society of Anesthesiologists score of 3 or higher (odds ratio, 1.85; 95% confidence interval, 1.18-2.89; P = 0.007), ascites [1.76 (1.11-2.81); P = 0.02], and postoperative complications during initial admission [grade 3-5 vs none, 2.47 (1.19-5.16); grade 1 vs none, 2.19 (0.98-4.85); grade 2 vs none, 1.28 (0.74-2.21); P = 0.048] to be independently associated with 30-day readmission (c-index = 0.625). Chronic obstructive pulmonary disease was the sole predictor of readmission for SSI (odds ratio, 3.92; 95% confidence interval, 1.07-4.33; P = 0.04). CONCLUSIONS: Clinically significant risk factors for 30-day readmission include American Society of Anesthesiologists score of 3 or higher, ascites and postoperative complications at initial admission. The SSI and pleural effusions/ascites are common indications for readmission. Systems can be developed to predict patients needing outpatient management, improve care, and reduce costs.

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