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预测产后出血:预后模型的系统评价。

Predicting postpartum haemorrhage: A systematic review of prognostic models.

机构信息

School of Nursing and Midwifery, Monash University, Melbourne, Victoria, Australia.

Faculty of Information Technology, Monash University, Melbourne, Victoria, Australia.

出版信息

Aust N Z J Obstet Gynaecol. 2022 Dec;62(6):813-825. doi: 10.1111/ajo.13599. Epub 2022 Aug 2.

Abstract

BACKGROUND

Postpartum haemorrhage (PPH) remains a leading cause of maternal mortality and morbidity worldwide, and the rate is increasing. Using a reliable predictive model could identify those at risk, support management and treatment, and improve maternal outcomes.

AIMS

To systematically identify and appraise existing prognostic models for PPH and ascertain suitability for clinical use.

MATERIALS AND METHODS

MEDLINE, CINAHL, Embase, and the Cochrane Library were searched using combinations of terms and synonyms, including 'postpartum haemorrhage', 'prognostic model', and 'risk factors'. Observational or experimental studies describing a prognostic model for risk of PPH, published in English, were included. The Critical Appraisal and Data Extraction for Systematic Reviews of Prediction Modelling Studies checklist informed data extraction and the Prediction Model Risk of Bias Assessment Tool guided analysis.

RESULTS

Sixteen studies met the inclusion criteria after screening 1612 records. All studies were hospital settings from eight different countries. Models were developed for women who experienced vaginal birth (n = 7), caesarean birth (n = 2), any type of birth (n = 2), hypertensive disorders (n = 1) and those with placental abnormalities (n = 4). All studies were at high risk of bias due to use of inappropriate analysis methods or omission of important statistical considerations or suboptimal validation.

CONCLUSIONS

No existing prognostic models for PPH are ready for clinical application. Future research is needed to externally validate existing models and potentially develop a new model that is reliable and applicable to clinical practice.

摘要

背景

产后出血(PPH)仍然是全球孕产妇死亡和发病的主要原因,其发生率呈上升趋势。使用可靠的预测模型可以识别出高危人群,为管理和治疗提供支持,并改善母婴结局。

目的

系统地识别和评价现有的 PPH 预后模型,并确定其在临床应用中的适用性。

材料和方法

使用术语和同义词的组合,通过 MEDLINE、CINAHL、Embase 和 Cochrane Library 进行检索,包括“产后出血”、“预后模型”和“风险因素”。纳入描述 PPH 风险预测模型的观察性或实验性研究,发表语言为英文。数据提取采用系统评价预测模型研究的批判性评价和数据提取清单,分析采用预测模型风险偏倚评估工具。

结果

经过筛选 1612 条记录,有 16 项研究符合纳入标准。所有研究均来自 8 个不同国家的医院。模型的开发对象为经历阴道分娩的女性(n=7)、剖宫产分娩的女性(n=2)、任何类型分娩的女性(n=2)、患有高血压疾病的女性(n=1)和患有胎盘异常的女性(n=4)。由于使用了不适当的分析方法或遗漏了重要的统计考虑因素或验证不优,所有研究均存在较高的偏倚风险。

结论

目前尚无适用于临床应用的 PPH 预后模型。未来需要进行研究以对现有模型进行外部验证,并可能开发出一种新的、可靠且适用于临床实践的模型。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/af3b/10087871/c1248b498e4f/AJO-62-813-g001.jpg

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