Prognostic prediction models for adverse birth outcomes: A systematic review.

IF 4.5 3区 医学 Q1 PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH Journal of Global Health Pub Date : 2024-10-25 DOI:10.7189/jogh.14.04214
Achenef Asmamaw Muche, Likelesh Lemma Baruda, Clara Pons-Duran, Robera Olana Fite, Kassahun Alemu Gelaye, Alemayehu Worku Yalew, Lisanu Tadesse, Delayehu Bekele, Getachew Tolera, Grace J Chan, Yifru Berhan
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引用次数: 0

Abstract

Background: Despite progress in reducing maternal and child mortality worldwide, adverse birth outcomes such as preterm birth, low birth weight (LBW), small for gestational age (SGA), and stillbirth continue to be a major global health challenge. Developing a prediction model for adverse birth outcomes allows for early risk detection and prevention strategies. In this systematic review, we aimed to assess the performance of existing prediction models for adverse birth outcomes and provide a comprehensive summary of their findings.

Methods: We used the Population, Index prediction model, Comparator, Outcome, Timing, and Setting (PICOTS) approach to retrieve published studies from PubMed/MEDLINE, Scopus, CINAHL, Web of Science, African Journals Online, EMBASE, and Cochrane Library. We used WorldCat, Google, and Google Scholar to find the grey literature. We retrieved data before 1 March 2022. Data were extracted using CHecklist for Critical Appraisal and Data Extraction for Systematic Reviews of Prediction Modelling Studies. We assessed the risk of bias with the Prediction Model Risk of Bias Assessment tool. We descriptively reported the results in tables and graphs.

Results: We included 115 prediction models with the following outcomes: composite adverse birth outcomes (n = 6), LBW (n = 17), SGA (n = 23), preterm birth (n = 71), and stillbirth (n = 9). The sample sizes ranged from composite adverse birth outcomes (n = 32-549), LBW (n = 97-27 233), SGA (n = 41-116 070), preterm birth (n = 31-15 883 784), and stillbirth (n = 180-76 629). Only nine studies were conducted on low- and middle-income countries. 10 studies were externally validated. Risk of bias varied across studies, in which high risk of bias was reported on prediction models for SGA (26.1%), stillbirth (77.8%), preterm birth (31%), LBW (23.5%), and composite adverse birth outcome (33.3%). The area under the receiver operating characteristics curve (AUROC) was the most used metric to describe model performance. The AUROC ranged from 0.51 to 0.83 in studies that reported predictive performance for preterm birth. The AUROC for predicting SGA, LBW, and stillbirth varied from 0.54 to 0.81, 0.60 to 0.84, and 0.65 to 0.72, respectively. Maternal clinical features were the most utilised prognostic markers for preterm and LBW prediction, while uterine artery pulsatility index was used for stillbirth and SGA prediction.

Conclusions: A varied prognostic factors and heterogeneity between studies were found to predict adverse birth outcomes. Prediction models using consistent prognostic factors, external validation, and adaptation of future risk prediction models for adverse birth outcomes was recommended at different settings.

Registration: PROSPERO CRD42021281725.

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不良分娩结局的预后预测模型:系统综述。
背景:尽管全球在降低孕产妇和儿童死亡率方面取得了进展,但早产、低出生体重(LBW)、胎龄小(SGA)和死胎等不良出生结局仍是全球健康面临的一大挑战。建立不良出生结局的预测模型可用于早期风险检测和预防策略。在这篇系统性综述中,我们旨在评估现有不良出生结局预测模型的性能,并对其研究结果进行全面总结:我们采用人口、指数预测模型、比较者、结果、时间和环境(PICOTS)方法,从 PubMed/MEDLINE、Scopus、CINAHL、Web of Science、African Journals Online、EMBASE 和 Cochrane Library 检索已发表的研究。我们还使用 WorldCat、Google 和 Google Scholar 查找灰色文献。我们检索了 2022 年 3 月 1 日之前的数据。我们使用预测模型研究系统性综述的批判性评估和数据提取清单(CHecklist for Critical Appraisal and Data Extraction for Systematic Reviews of Prediction Modelling Studies)提取数据。我们使用预测模型偏倚风险评估工具评估了偏倚风险。我们用表格和图表对结果进行了描述性报告:我们纳入了 115 个预测模型,其结果如下:综合不良出生结果(n = 6)、低体重儿(n = 17)、SGA(n = 23)、早产(n = 71)和死胎(n = 9)。样本量从综合不良出生结局(n = 32-549)、低体重儿(n = 97-27 233)、SGA(n = 41-116 070)、早产(n = 31-15 883 784)到死胎(n = 180-76 629)不等。只有 9 项研究是在低收入和中等收入国家进行的。有 10 项研究经过外部验证。不同研究的偏倚风险各不相同,其中 SGA(26.1%)、死胎(77.8%)、早产(31%)、低体重儿(23.5%)和综合不良出生结局(33.3%)预测模型的偏倚风险较高。接收者操作特征曲线下面积(AUROC)是描述模型性能最常用的指标。在报告早产预测性能的研究中,AUROC 从 0.51 到 0.83 不等。预测 SGA、LBW 和死胎的 AUROC 分别为 0.54 至 0.81、0.60 至 0.84 和 0.65 至 0.72。母体临床特征是预测早产和低体重儿最常用的预后指标,而子宫动脉搏动指数则用于预测死胎和SGA:结论:在预测不良出生结局方面,研究发现了各种预后因素和研究间的异质性。建议在不同环境下使用一致的预后因素、外部验证和适应未来不良出生结局风险预测模型:ProCORMBERCO CRD42021281725.
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来源期刊
Journal of Global Health
Journal of Global Health PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH -
CiteScore
6.10
自引率
2.80%
发文量
240
审稿时长
6 weeks
期刊介绍: Journal of Global Health is a peer-reviewed journal published by the Edinburgh University Global Health Society, a not-for-profit organization registered in the UK. We publish editorials, news, viewpoints, original research and review articles in two issues per year.
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