Readmission After Ileostomy Creation: Retrospective Review of a Common and Significant Event

Abstract

Objective: To evaluate causes and predictors of readmission after new ileostomy creation.

Background: New ileostomates have been reported to have higher readmission rates compared with other surgical patients, but data on predictors are limited.

Methods: A total of 1114 records at 2 associated hospitals were reviewed to identify adults undergoing their first ileostomy. Primary outcome was readmission within 60 days of surgery. Multiple logistic regression was used to identify independent predictors; area under the receiver-operator characteristic curves (AUC) were used to evaluate age-stratified models in secondary analysis.

Results: In all, 407 patients underwent new ileostomy; 58% had cancer, 31% IBD; 49% underwent LAR, 27% colectomy, and 14% proctocolectomy. Median length of stay was 8 days. Among the patients, 39% returned to hospital, and 28% were readmitted (n = 113) at a median of 12 days postdischarge. The most common causes of readmission were dehydration (42%), intraperitoneal infections (33%), and extraperitoneal infections (29%). Dehydration was associated with later, longer, and repeated readmission. Independent significant predictors of readmission were Clavien-Dindo complication grade 3 to 4 [odds ratio (OR) 6.7], Charlson comorbidity index (OR 1.4 per point), and loop stoma (OR 2.2); longer length of stay (OR 0.5) and age 65 years or older (OR 0.4) were protective. Cohort stratification above or below age 65 revealed that older patient readmissions were more predictable (AUC 0.84) with more preventable causes, whereas younger patient readmissions were difficult to predict or prevent (AUC 0.65).

Conclusions: Readmissions are most commonly caused by dehydration, and are predicted by serious complications, comorbidity burden, loop stoma, shorter length of stay, and age. Readmissions in older patients are easier to predict, representing an important target for improvement.

Figure 1

Inclusion and Exclusion Flow Chart

Figure 2

Receiver Operator Characteristic (ROC) curves for age-stratified regression analyses of readmission with area under the curve statistic. Models include only variables with p<0.10; model results were converged upon by both forward and backward stepwise regression. Variables in older age model: living alone, Charlson Comorbidity Index, history of recent abdominal surgery, loop vs. end stoma, Clavien-Dindo complication grade, length of stay. For younger age model: Clavien-Dindo complication grade, discharge on Lomotil.