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脱垂手术术后尿潴留预测模型的建立与验证:一项回顾性队列研究。

Development and validation of a prediction model for postoperative urinary retention after prolapse surgery: A retrospective cohort study.

机构信息

Department of Obstetrics and Gynecology, Kyungpook National University Chilgok Hospital, Daegu, Korea.

Department of Genomic Medicine, Seoul National University Hospital, Seoul, Korea.

出版信息

BMC Womens Health. 2024 Jun 7;24(1):331. doi: 10.1186/s12905-024-03171-3.

Abstract

BACKGROUND

Postoperative urinary retention (POUR), a common condition after prolapse surgery with potential serious sequelae if left untreated, lacks a clearly established optimal timing for catheter removal. This study aimed to develop and validate a predictive model for postoperative urinary retention lasting > 2 and > 4 days after prolapse surgery.

METHODS

We conducted a retrospective review of 1,122 patients undergoing prolapse surgery. The dataset was divided into training and testing cohorts. POUR was defined as the need for continuous intermittent catheterization resulting from a failed spontaneous voiding trial, with passing defined as two consecutive voids ≥ 150 mL and a postvoid residual urine volume ≤ 150 mL. We performed logistic regression and the predicted model was validated using both training and testing cohorts.

RESULTS

Among patients, 31% and 12% experienced POUR lasting > 2 and > 4 days, respectively. Multivariable logistic model identified 6 predictors. For predicting POUR, internal validation using cross-validation approach showed good performance, with accuracy lasting > 2 (area under the curve [AUC] 0.73) and > 4 days (AUC 0.75). Split validation using pre-separated dataset also showed good performance, with accuracy lasting > 2 (AUC 0.73) and > 4 days (AUC 0.74). Calibration curves demonstrated that the model accurately predicted POUR lasting > 2 and > 4 days (from 0 to 80%).

CONCLUSIONS

The proposed prediction model can assist clinicians in personalizing postoperative bladder care for patients undergoing prolapse surgery by providing accurate individual risk estimates.

摘要

背景

脱垂手术后发生的术后尿潴留(POUR)是一种常见的情况,如果不加以治疗,可能会产生严重的后果,而目前对于导尿管拔除的最佳时机仍没有明确的界定。本研究旨在建立和验证一种预测脱垂手术后持续 2 天和 4 天以上的术后尿潴留的模型。

方法

我们对 1122 例接受脱垂手术的患者进行了回顾性研究。数据集分为训练集和测试集。POUR 定义为因自发排尿试验失败而需要持续间歇性导尿,通过定义为两次连续排尿量≥150ml 和残余尿量≤150ml。我们进行了逻辑回归分析,并使用训练集和测试集对预测模型进行了验证。

结果

在患者中,分别有 31%和 12%的患者发生了持续 2 天和 4 天以上的 POUR。多变量逻辑模型确定了 6 个预测因素。对于预测 POUR,使用交叉验证方法的内部验证显示出良好的性能,持续 2 天以上的准确性(曲线下面积[AUC]为 0.73)和持续 4 天以上的准确性(AUC 为 0.75)。使用预先分离的数据进行分割验证也显示出良好的性能,持续 2 天以上的准确性(AUC 为 0.73)和持续 4 天以上的准确性(AUC 为 0.74)。校准曲线表明,该模型能够准确预测持续 2 天和 4 天以上的 POUR(从 0 到 80%)。

结论

该预测模型可以帮助临床医生通过提供准确的个体风险估计,为接受脱垂手术的患者提供个性化的术后膀胱护理。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c176/11157900/51a60a832c81/12905_2024_3171_Fig1_HTML.jpg

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