Abstract
BACKGROUND: Postoperative ileus (POI) is one of the most common complications after laparoscopic radical cystectomy (LRC). Albeit its high incidence, its risk factors are obscure, and few studies have attempted to explore them. Meanwhile, risk-assessing tools for predicting its happening are lacking. METHODS: Clinical data of 197 patients who underwent LRC between March 2014 and October 2019 were retrospectively collected. All cases of POI were identified and double-checked. Data pertaining to the following categories were extracted as well: patients' general characteristics, preoperative laboratory tests results and preparations, intraoperative and postoperative general items, pathological results. The correlation between candidate risk factors and ileus was analyzed by multivariable binary logistic regression. Clinical and pathophysiological explanations for those results were explored. Finally, a points-based prediction model was developed and validated for predicting the happening of POI. RESULTS: A total of 63 out of 197 patients (31.98%) suffered from POI. Multivariate logistic regression analysis showed chronic constipation, increased dosage of laxative, elevated preoperative serum creatinine level, delayed postoperative ambulation, intestine-related urine derivations were statistically significant for developing POI (P<0.05). No significant differences were found between POI and age, gender, body mass index (BMI), antibiotics, hypertension, diabetes, smoking, hard-drinking, preoperative hemoglobin level, preoperative albumin level, history of previous abdominal surgery, surgery time, intraoperative blood loss, blood transfusion, tumor size, lymph nodes yields, TNM staging and intensive care unit hospitalization. An external cohort had been used for testing the validation of the assessment scale, and the results were promising. CONCLUSIONS: Early recognition is of great importance in protecting vulnerable patients from developing POI, knowing the above-mentioned risk factors and using the assessment scale should help to screen them better. Cases from diverse backgrounds might contribute to a more accurate and complete scale.