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在斯里兰卡一家三级医疗中心使用新开发的智能手机应用程序根据罗布森分类法评估剖宫产率:一项比较研究。

Evaluation of caesarean rates according to Robson classification using a newly developed smart phone application in a tertiary center in Sri Lanka: a comparative study.

作者信息

Jayasundara Chandana, Piyadigama Indunil, Jayawardane Asanka, Perera Ananda

机构信息

Department of Obstetrics and Gynaecology, Faculty of Medicine, University of Colombo, No 25, Kynsey Road, Colombo 08, Sri Lanka.

St. Joseph's Hospital, Negambo, Sri Lanka.

出版信息

BMC Pregnancy Childbirth. 2025 Jan 31;25(1):104. doi: 10.1186/s12884-025-07165-3.

Abstract

OBJECTIVE

Caesarean section (CS) rates in Sri Lanka have escalated significantly, with projections indicating that over half of all births may involve CS by 2025. To address this rise and mitigate maternal morbidity, it is essential that CS procedures are medically justified. This study evaluates RobsApp®, a novel smartphone application designed to collect high-quality prospective data on CS rates based on the Robson classification.

METHODS

The study utilized RobsApp® for data collection in the Professorial Unit of De Soysa Hospital for Women (DSHW), Sri Lanka. Data were collected prospectively from 1,712 deliveries between April and October 2019. The analysis focused on CS rates across different Robson categories and the quality of the collected data, comparing them with previous data obtained using traditional methods.

RESULTS

The overall CS rate was 33.0%, with Robson category 5a accounting for most cases. Emergency CS constituted 49.6% of all procedures, with cardiotocograph (CTG) abnormalities being the leading indication. The quality of the data collected through RobsApp® met the standards recommended by the Robson guidance, as evidenced by the study's ability to accurately categorize deliveries and assess CS rates.

CONCLUSIONS

RobsApp® has proven to be an effective tool for prospective data collection, aligning well with Robson guidelines and facilitating high-quality data gathering. The study reveals a rising trend in CS rates at DSHW, particularly for reasons beyond previous CS. The inclusion of demographic data and birth weight analysis in future studies will enhance comparisons and insights into reducing CS rates.

ETHICS

Ethical approval was obtained from the Ethical Review Committee, Faculty of Medicine, University of Colombo (Ref - EC-19-024) which waived the need for individual consent. Study adhered to the Helsinki Declaration.

摘要

目的

斯里兰卡的剖宫产率显著上升,预计到2025年,超过一半的分娩可能会采用剖宫产。为应对这一增长并降低孕产妇发病率,剖宫产手术必须有医学依据。本研究评估了RobsApp®,这是一款新型智能手机应用程序,旨在基于罗布森分类法收集有关剖宫产率的高质量前瞻性数据。

方法

该研究在斯里兰卡德索伊萨妇女医院(DSHW)的教授单元中使用RobsApp®进行数据收集。前瞻性收集了2019年4月至10月期间1712例分娩的数据。分析重点在于不同罗布森分类的剖宫产率以及所收集数据的质量,并将其与使用传统方法获得的先前数据进行比较。

结果

总体剖宫产率为33.0%,其中罗布森分类5a占大多数病例。急诊剖宫产占所有手术的49.6%,胎心监护(CTG)异常是主要指征。通过RobsApp®收集的数据质量符合罗布森指南推荐的标准,该研究能够准确分类分娩并评估剖宫产率即证明了这一点。

结论

RobsApp®已被证明是一种有效的前瞻性数据收集工具,与罗布森指南高度契合,有助于收集高质量数据。该研究揭示了DSHW剖宫产率呈上升趋势,尤其是由于先前剖宫产以外的原因。未来研究纳入人口统计学数据和出生体重分析将加强比较并增进对降低剖宫产率的认识。

伦理

获得了科伦坡大学医学院伦理审查委员会的伦理批准(参考编号 - EC-19-024),该委员会免除了个人同意的要求。研究遵循了《赫尔辛基宣言》。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8b93/11786396/f1997fb61481/12884_2025_7165_Fig1_HTML.jpg

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