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应用罗伯逊分类系统分析分娩方式、危险因素和剖宫产率较高的亚组。

An Analysis of the Mode of Delivery, Risk Factors, and Subgroups with High Caesarean Birth Rates Using Robson Classification System.

机构信息

Department of Public Health, Faculty of Medicine, Near East University, Near East Boulevard, 99138, Nicosia, Northern Cyprus.

Dr. Burhan Nalbantoğlu State Hospital Obstetrics and Gynaecology Department, Nicosia, Northern Cyprus.

出版信息

Matern Child Health J. 2024 Apr;28(4):667-678. doi: 10.1007/s10995-023-03783-5. Epub 2023 Oct 15.

Abstract

OBJECTIVE

We aimed to understand the utilization of the mode of delivery and related risk factors. Further aimed to apply the Robson classification system to evaluate the data quality and analyze the CS rates in subgroups.

METHODS

We conducted a retrospective descriptive study by reviewing the medical records of all women who delivered at the State Hospital in 2019. A proforma was developed for extracting data from patient records. All women with six obstetric parameters were categorized into Robson groups to determine the absolute and relative contributions of each group to the overall CS rate.

RESULTS

Of 797 deliveries, 401 (50.2%) were CSs. Being older, being Turkish Cypriot, having preterm births, previous CS, multiple fetuses, and having breech or transverse fetal presentations were related to having higher risks of CS. The most common medical indication for CSs (52.3%) was a history of previous CSs. Robson Group 5 contributed the most (50.7%) to the overall CS rate, with the highest absolute contribution of 21.8%. Group 10 and Group 8 were the second and third highest contributors to the overall CS rate, with relative contributions of 25.3% and 9.0%, respectively.

CONCLUSIONS

Findings revealed the substandard quality of obstetric data and a noticeably high overall CS rate. The top priority should be given to improving the quality of medical records. It underscored the necessity of implementing the Robson classification system as a standard clinical practice to enhance data quality, which helps to effectively evaluate and monitor the CS rates in obstetric populations.

摘要

目的

了解分娩方式的利用情况及其相关危险因素。进一步应用 Robson 分类系统评估数据质量,并分析亚组中 CS 率。

方法

通过回顾 2019 年州立医院所有分娩妇女的病历,进行回顾性描述性研究。制定了一份表格,用于从患者记录中提取数据。将具有 6 个产科参数的所有妇女分为 Robson 组,以确定每个组对总 CS 率的绝对和相对贡献。

结果

797 例分娩中,401 例(50.2%)为剖宫产。年龄较大、土耳其塞浦路斯人、早产、既往剖宫产、多胎和臀位或横位胎儿与剖宫产风险增加相关。剖宫产最常见的医学指征(52.3%)是既往剖宫产史。Robson 组 5 对总 CS 率的贡献最大(50.7%),绝对贡献最高为 21.8%。组 10 和组 8 是总 CS 率的第二和第三大贡献者,相对贡献分别为 25.3%和 9.0%。

结论

研究结果揭示了产科数据质量不达标和总 CS 率明显偏高的问题。首要任务应是提高医疗记录的质量。强调实施 Robson 分类系统作为标准临床实践的必要性,以提高数据质量,有助于有效评估和监测产科人群中的 CS 率。

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