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评估一种用于估计产科肛门括约肌损伤风险的新预测模型。

Evaluation of a new prediction model for the estimation of risk of obstetrical anal sphincter injuries.

作者信息

André Kristin, Stuart Andrea, Källén Karin

机构信息

Department of Obstetrics and Gynecology, Helsingborg Hospital, Helsingborg, Sweden; Department of Clinical Sciences, Lund University, Lund, Sweden.

Department of Obstetrics and Gynecology, Helsingborg Hospital, Helsingborg, Sweden; Department of Clinical Sciences, Lund University, Lund, Sweden.

出版信息

Am J Obstet Gynecol. 2025 Jul 8. doi: 10.1016/j.ajog.2025.07.005.

Abstract

BACKGROUND

Obstetrical anal sphincter injuries are complications of vaginal birth that have the potential to cause substantial maternal morbidity. Predicting these injuries might help to improve maternal care as well as antenatal counseling and patient education. Previous attempts to create prediction models have in many cases involved variables only known postpartum, which limits their use in an antenatal setting. Other models include parameters that are not applicable to a Northern European population.

OBJECTIVE

This study aimed to develop and validate a clinically useful model for the prediction of risk of obstetrical anal sphincter injuries.

STUDY DESIGN

The model was developed using a retrospective nationwide cohort from the Swedish Medical Birth Register consisting of 1,209,421 deliveries between 2005 and 2016. After exclusion criteria (cesarean delivery, forceps delivery, missing data) were applied, the data set was randomly divided into a development data set (n=422,011) and a validation data set (n=422,010). In the development data set, all variables were assessed using univariable analysis with modified Poisson regression. A prediction model was then built using multivariate analysis with modified Poisson regression, wherein variables with P≤.2 were included. Both forward and backward selection were used, and variables with P≥.05 were excluded. Validation was performed by evaluating the agreement between the predicted and observed rate of obstetrical anal sphincter injuries after the prediction model was applied to the validation data set.

RESULTS

Antenatal variables associated with increased risk of obstetrical anal sphincter injury included primiparity, previous cesarean delivery, previous sphincter injury, increasing age, increasing birthweight, and maternal origin from sub-Saharan Africa or South/Southeast Asia. Smoking, increasing maternal height, and body mass index appeared to lower the risk. Vacuum extraction also increased the risk of sphincter injury. We developed 1 model including the previously mentioned antenatal parameters and 1 model also including vacuum extraction. The final prediction model including instrumental delivery can be used for predicting the risk of sphincter injury for delivery with or without vacuum extraction with higher accuracy. This model demonstrated strong discrimination with an AUC of 0.79 (95% confidence interval, 0.78-0.79), and was able to predict risks up to 24% with moderate to high accuracy.

CONCLUSION

Using antenatally available data, obstetrical anal sphincter injuries can be predicted with moderate certainty. This prediction model has been externally validated and can be used for individualized antenatal counseling and identification of persons at high risk for whom preventative strategies might improve outcomes. Further validation in other populations outside of Scandinavia is recommended before clinical implementation.

摘要

背景

产科肛门括约肌损伤是阴道分娩的并发症,有可能导致严重的产妇发病。预测这些损伤可能有助于改善产妇护理以及产前咨询和患者教育。以往建立预测模型的尝试在很多情况下涉及的变量仅在产后才知道,这限制了它们在产前环境中的应用。其他模型包含的参数不适用于北欧人群。

目的

本研究旨在开发并验证一种临床上有用的模型,用于预测产科肛门括约肌损伤的风险。

研究设计

该模型是使用瑞典医疗出生登记处的全国性回顾性队列开发的,该队列包括2005年至2016年间的1,209,421例分娩。应用排除标准(剖宫产、产钳助产、数据缺失)后,将数据集随机分为一个开发数据集(n = 422,011)和一个验证数据集(n = 422,010)。在开发数据集中,所有变量均使用修正泊松回归的单变量分析进行评估。然后使用修正泊松回归的多变量分析建立预测模型,其中纳入P≤0.2的变量。同时使用向前和向后选择,并排除P≥0.05的变量。在将预测模型应用于验证数据集后,通过评估预测的和观察到的产科肛门括约肌损伤发生率之间的一致性来进行验证。

结果

与产科肛门括约肌损伤风险增加相关的产前变量包括初产、既往剖宫产、既往括约肌损伤、年龄增加、出生体重增加以及母亲来自撒哈拉以南非洲或南亚/东南亚。吸烟、母亲身高增加和体重指数似乎会降低风险。真空吸引也会增加括约肌损伤的风险。我们开发了1个包含上述产前参数的模型和1个还包含真空吸引的模型。包含器械助产的最终预测模型可用于更准确地预测有无真空吸引分娩时括约肌损伤的风险。该模型显示出很强的区分能力,曲线下面积为0.79(95%置信区间,0.78 - 0.79),并且能够以中度到高度的准确性预测高达24%的风险。

结论

利用产前可得的数据,可以有一定把握地预测产科肛门括约肌损伤。这个预测模型已经经过外部验证,可用于个性化的产前咨询以及识别那些采取预防策略可能改善结局的高危人群。在临床实施之前,建议在斯堪的纳维亚以外的其他人群中进行进一步验证。

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