Establishment and validation of clinical prediction model for hemorrhoid recurrence after procedure for prolapse and hemorrhoids

Author:

Zhang Yulong1,Sun Shiwei1,Han Zhenguo12ORCID

Affiliation:

1. Third Hospital of Shanxi Medical University, Shanxi Bethune Hospital, Shanxi Academy of Medical Sciences Tongji Shanxi Hospital, Taiyuan, China

2. General Surgery Department, Shanxi Bethune Hospital, Taiyuan, China.

Abstract

This study aimed to establish a clinical model to predict the risk of hemorrhoid recurrence after procedure for prolapse and hemorrhoids. The clinical data of patients who underwent stapler hemorrhoidal mucosal circumcision in Shanxi Bethune Hospital from April 2014 to June 2017 were collected retrospectively and followed up regularly after the operation. Finally, 415 patients were included, which were divided into training group (n = 290) and verification group (n = 125). Logistic regression method was used to select meaningful predictors. The prediction model was constructed with nomographs, and the model was evaluated with correction curve, receiver operating characteristic curve and C index. The decision analysis curve was used to determine the clinical utility of the nomogram. Birth history, muscle attachment, postoperative anal urgency, anal resting pressure, postoperative nutritional index, body mass index, Wexner score, and hemorrhoid grading were included in the nomogram. The area under the curve of the prediction model was 0.813 and 0.679, respectively, in the training and verification groups, and 0.839 and 0.746, respectively, for the 5-year recurrence rate. The C index (0.737) and clinical decision curve showed that the model had high clinical practical value. The prediction model of hemorrhoid recurrence risk after hemorrhoidectomy based on multiple clinical indicators can be used for individualized prediction of hemorrhoid recurrence in patients after hemorrhoidectomy, and early intervention measures can be given to individuals with a high recurrence risk to reduce the risk of recurrence.

Publisher

Ovid Technologies (Wolters Kluwer Health)

Subject

General Medicine

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