Effectiveness and Validation of the Italian Translation of the Low Anterior Resection Syndrome Score in an Italian High-Volume University Hospital

FRONTIERS IN SURGERY(2022)

引用 2|浏览8
暂无评分
摘要
Background: The low anterior resection syndrome (LARS) score is a validated questionnaire developed in Denmark to measure the severity of bowel dysfunction after low anterior resection. This retrospective study aimed to assess the effectiveness of the LARS score in the Italian language in a population of Italian patients who underwent low anterior resection for rectal cancer. The convergent and discriminative validity and the test-retest reliability of the score were investigated. Methods: A cohort of two hundred and five patients treated with low anterior resection were enrolled in an Italian high-volume university hospital between January 2000 and April 2018. The Italian version of the LARS score (tested twice), as translated from English original version, a single question on quality of life and the EORTC QLQ-C30 questionnaire were submitted to patients. Results: A high proportion of patients showed a perfect or moderate fit between the LARS score and QoL categories (convergent validity, p < 0.0005). All differences regarding the items of the European Organization for Research and Treatment of Cancer Quality of Life Questionnaire - Core 30 (EORTC QLQ-C30) functional scales were statistically significant (p < 0.0005). The LARS score was able to discriminate between groups of patients who received or did not receive preoperative chemoradiotherapy (p < 0.0005) and those who received total or partial mesorectal excision (p < 0.0005). The test-retest reliability was excellent (intraclass correlation coefficient 0.96). Conclusion: The Italian translation of the LARS score is an easy and reliable tool for assessing bowel dysfunction after low anterior resection and its routine use in clinical practice should be recommended.
更多
查看译文
关键词
rectal cancer, low anterior resection, low anterior resection syndrome, quality of life, functional outcomes
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要