Development of screening tools to predict the risk of recurrence and related complications following anal fistula surgery: protocol for a prospective cohort study

Abstract

Introduction: Postoperative recurrence and related complications are common and related to poor outcomes in patients with anal fistula (AF). Due to being associated with short-term and long-term cure rates, perioperative complications have received widespread attention following AF surgery. This study aims to identify a set of predictive factors to develop risk prediction models for recurrence and related complications following AF surgery. We plan to develop and validate risk prediction models, using information collected through a WeChat patient-reported questionnaire system combined with clinical, laboratory and imaging findings from the perioperative period until 3-6 months following AF surgery.

Methods and analysis: This is a prospective hospital-based cohort study using a linked database of collected health data as well as the follow-up outcomes for all adult patients who suffered from AF at a tertiary referral hospital in Shanghai, China. We will perform logistic regression models to predict anal fistula recurrence (AFR) as well as related complications (eg, wound haemorrhage, faecal impaction, urinary retention, delayed wound healing and unplanned hospitalisation) during and after AF surgery, and machine learning approaches will also be applied to develop risk prediction models. This prospective study aims to develop the first risk prediction models for AFR and related complications using multidimensional variables. These tools can be used to warn, motivate and empower patients to avoid some modifiable risk factors to prevent postoperative complications early. This study will also provide alternative tools for the early screening of high-risk patients with AFR and related complications, helping surgeons better understand the aetiology and outcomes of AF in an earlier stage.

Ethics and dissemination: The study was approved by the Institutional Review Board of Shuguang Hospital affiliated with Shanghai University of Traditional Chinese Medicine (approval number: 2019-699-54-01). The results of this study will be submitted to international scientific peer-reviewed journals or conferences in surgery, anorectal surgery or anorectal diseases.

Trial registration number: ChiCTR1900025069; Pre-results.

Keywords: colorectal surgery; protocols and guidelines; risk management; surgery.

Figure 1

Flowchart of prediction model development and assessment.