Predicting the risk of postoperative constipation in middle-aged and elderly patients with lower limb fractures using machine learning algorithms

This dataset contains de-identified clinical data from a cohort of middle-aged and elderly patients who underwent surgery for lower limb fractures. The data were collected to support the development and validation of machine learning models for predicting the risk of postoperative constipation.

The variables encompass patient demographics, pre-operative comorbidities, surgical details, medication use, and postoperative outcomes, with the target variable being the occurrence of constipation within a specified postoperative period. The dataset is provided in a structured format (e.g., .excel) to facilitate reuse in predictive analytics and clinical research.