Published online Oct 27, 2023. doi: 10.4240/wjgs.v15.i10.2123
Peer-review started: July 4, 2023
First decision: July 19, 2023
Revised: August 1, 2023
Accepted: August 15, 2023
Article in press: August 15, 2023
Published online: October 27, 2023
Processing time: 115 Days and 0.1 Hours
Low anterior resection syndrome (LARS) is a common complication of anus-preserving surgery in patients with colorectal cancer, which significantly affects patients' quality of life.
To determine the relationship between the incidence of LARS and patient quality of life after colorectal cancer surgery and to establish a LARS prediction model to allow perioperative precision nursing.
We reviewed the data from patients who underwent elective radical resection for colorectal cancer at our institution from April 2013 to June 2020 and completed the LARS score questionnaire and the European Organization for Research and Treatment of Cancer Core Quality of Life and Colorectal Cancer Module questionnaires. According to the LARS score results, the patients were divided into no LARS, mild LARS, and severe LARS groups. The incidence of LARS and the effects of this condition on patient quality of life were determined. Univariate and multivariate analyses were performed to identify independent risk factors for the occurrence of LARS. Based on these factors, we established a risk prediction model for LARS and evaluated its performance.
Among the 223 patients included, 51 did not develop LARS and 171 had mild or severe LARS. The following quality of life indicators showed significant di
The quality of life of patients with LARS after colorectal cancer surgery is significantly reduced.
Core Tip: Low anterior resection syndrome (LARS) is a common complication of anus-preserving surgery in patients with colorectal cancer. In this study, we found that LARS significantly affected patients’ quality of life after colorectal cancer surgery, and that perioperative precision nursing could significantly reduce the incidence of LARS and improve patients’ quality of life. Furthermore, we established a LARS prediction model, which showed excellent performance in predicting the occurrence of LARS after colorectal cancer surgery. This prediction model can enable implementation of perioperative precision nursing to improve the quality of life of patients with LARS.