Predictive model for early postoperative stomal complications in colorectal cancer: A systematic review.

Abstract

Background: Stomal complications though small in early postoperative period, but poses significant morbidity, therapeutic challenge, delay in adjuvant treatment and sometimes even leads to mortality. Predictive model for early detection of stomal complications is important to improve the outcome. A model including patients and disease related factors, intraoperative surgical techniques and biochemical markers would be a better determinant to anticipate early stomal complications. Incorporation of emerging tools and technology such as artificial intelligence (AI), will further improve the prediction.

Aim: To identify various risk factors and models for prediction of early post operative stomal complications in colorectal cancer (CRC) surgery.

Methods: Published literatures on early postoperative stomal complications in CRC surgery were systematically reviewed between 1995 and 2024 from online search engines PubMed and MEDLINE.

Results: Twenty-four observational studies focused on identifying various risk factors for early post operative stomal complications in CRC surgery were analyzed. Stomal complications in CRC are influenced by several factors such as disease factors, patient-specific characteristics, and surgical techniques. There are some biomarkers and tools loke AI which may play significant roles in early detection.

Conclusion: Careful analysis of these factors, changes in biochemical parameters, and application of AI, a predictive model for stomal complications can be generated, to help in early detection, prompt action to achieve better outcomes.