Scala Arianna, Bifulco Giuseppe, Borrelli Anna, Egidio Rosanna, Triassi Maria, Improta Giovanni
Department of Public Health, University of Naples Federico II, Naples, 80131, Italy.
"Federico II" University Hospital, Naples, 80131, Italy.
BMC Public Health. 2025 Jan 20;25(1):238. doi: 10.1186/s12889-025-21530-z.
The incidence of caesarean sections (CSs) has increased significantly in recent years, especially in developed countries. This study aimed to identify the factors that most influence the length of hospital stay (LOS) after a CS, using data from 9,900 women who underwent CS at the "Federico II" University Hospital of Naples between 2014 and 2021.
Various artificial intelligence models were employed to analyze the relationships between the LOS and a set of independent variables, including maternal and foetal characteristics. The analysis focused on identifying the model with the best predictive performance and specific comorbidities impacting LOS.
A multiple linear regression model determined the highest R-value (0.815), indicating a strong correlation between the identified variables and LOS. Significant predictors of LOS included abnormal foetuses, cardiovascular disease, respiratory disorders, hypertension, haemorrhage, multiple births, preeclampsia, previous delivery complications, surgical complications, and preoperative LOS. In terms of classification models, the decision tree yielded the highest accuracy (75%).
The study concluded that certain comorbidities, such as cardiovascular disease and preeclampsia, significantly impact LOS following a CS. These findings can assist hospital management in optimizing resource allocation and reducing costs by focusing on the most influential factors.
近年来剖宫产率显著上升，尤其是在发达国家。本研究旨在利用2014年至2021年间在那不勒斯“费德里科二世”大学医院接受剖宫产的9900名女性的数据，确定对剖宫产后住院时间影响最大的因素。
采用多种人工智能模型分析住院时间与一系列独立变量之间的关系，包括母体和胎儿特征。分析重点是确定预测性能最佳的模型以及影响住院时间的特定合并症。
多元线性回归模型确定的R值最高（0.815），表明所确定的变量与住院时间之间存在强相关性。住院时间的显著预测因素包括胎儿异常、心血管疾病、呼吸系统疾病、高血压、出血、多胎妊娠、先兆子痫、既往分娩并发症、手术并发症和术前住院时间。在分类模型方面，决策树的准确率最高（75%）。
该研究得出结论，某些合并症，如心血管疾病和先兆子痫，对剖宫产后的住院时间有显著影响。这些发现可帮助医院管理层通过关注最具影响力的因素来优化资源分配并降低成本。
