RESUMEN
INTRODUCTION: Urolithiasis affects many people throughout their lives. Among the maternal population, although the morbidity of acute urolithiasis in pregnant women is unremarkable, it is the leading cause of hospitalisation during pregnancy. There is no effective clinical diagnostic tool to help doctors diagnose diseases. Our primary aim was to develop and validate a clinical prediction model based on statistical methods to predict the probability of having disease in pregnant women who visited the emergency department because of urolithiasis-induced colic. METHODS AND ANALYSIS: We will use multivariate logistic regression analysis to build a multivariate regression linear model. A receiver operating characteristic curve plot and calibration plot will be used to measure the discrimination value and calibration value of the model, respectively. We will also use least absolute shrinkage and selection operator regression analysis combined with logistic regression analysis to select predictors and construct the multivariate regression model. The model will be simplified to an application that has been reported before, and users will only need to enter their clinical parameters so that risk probability is automatically derived. ETHICS AND DISSEMINATION: The review and approval documents of the clinical research ethics committee have been received from the ethics committee of our hospital (The Third Affiliated Hospital of Wenzhou Medical University). We will disseminate research findings through presentations at scientific conferences and publication in peer-reviewed journals.
