Predicting obstetric anal sphincter injuries among laboring women: 2 prediction models and 1 risk calculator

Abstract

Abstract Background: Although several prediction models have been developed to estimate the risk of obstetric anal sphincter injuries (OASIS) among laboring women, none have been used in clinical practice because of controversial or unavailable predictors included in the prediction models and the format used to present them. Thus, it is essential to develop evidence-based prediction models for OASIS using known antenatal and modifiable intrapartum factors and to present them in user-friendly formats. Objective: The objective of this study was to develop evidence-based prediction models for OASIS and a risk calculator to present prediction models. Methods: Models were developed based on a systematic review and meta-analysis in which risk factors for OASIS were identified, and the pooled odds ratio for each risk factor was calculated. A logistic regression model was used to develop the prediction models, and MATLAB with a graphical user interface was used to develop the risk calculator. Results: Two prediction models for OASIS were established: Model I and Model II. Model I included 7 known antenatal variables: maternal age, parity, prior cesarean delivery, prepregnancy body mass index, gestational age, estimated birth weight, and fetal position. Model II added 5 modifiable intrapartum variables to Model I: epidural analgesia, labor induction, labor augmentation, episiotomy, and operative vaginal birth. The risk calculator developed by writing the parameters in the logistic regression models into MATLAB scripts included 2 interfaces, each consisting of risk factors for OASIS and the possibility of OASIS occurring. Conclusions: This study developed 2 prediction models and a risk calculator for OASIS based on a systematic review and meta-analysis. Although the models were more scientific in model development methods and predictors included in the prediction models, they should be externally validated and updated to ensure better performance before they can be widely applied to guide clinical practice.