Factors influencing postoperative symptom improvement in hiatal hernia patients and construction of a clinical prediction model

Abstract

Purpose: Our purpose was to analyze the factors influencing the improvement of symptoms postoperatively in patients with a hiatal hernia (HH), and build a clinical prediction model. Methods: The records of 121 patients with a HH who received surgery at the Sixth Affiliated Hospital of Sun Yat-Sen University from April 2019 to October 2022 were retrospectively reviewed. Patients were divided into a good improvement group (88 patients) and a poor improvement group (33 patients) according to the improvement of symptoms postoperatively. Patient demographic and clinical data, and high-resolution manometry (HRM) data were extracted from the records, and data of the 2 groups were compared by univariate analysis. Statistically significant factors (p<0.05) were incorporated into a multivariate logistic regression model to determine independent factors of postoperative symptom improvement. A clinical prediction model and a nomogram were constructed. Receiver operating characteristic (ROC) curve and calibration curve analysis were used to predict the accuracy of the model. Decision curve analysis (DCA) was used to evaluate the clinical applicability of the model. Results: Multivariate logistic regression analysis showed that non-smoking history and level of distal contraction integral (DCI) were independent factors affecting postoperative symptom improvement of HH patients. The accuracy of the test scoring system shows that the C index is 0.878. Conclusion:The Improvement of symptoms postoperatively in HH patients is affected by smoking history and DCI level. The clinical prediction model established based on these results has good efficacy in predicting the outcomes of patients with a HH who undergo surgery.