Anteneh Rahel Mulatie, Tesema Getayeneh Antehunegn, Lakew Ayenew Molla, Feleke Sefineh Fenta
Department of Public Health, College of Health Sciences, Debre Tabor University, Debre Tabor, Ethiopia.
Department of Epidemiology and Biostatics, Institute of Public Health, College of Medicine and Health Sciences, University of Gondar, Gondar, Ethiopia.
Front Glob Womens Health. 2024 Dec 18;5:1458457. doi: 10.3389/fgwh.2024.1458457. eCollection 2024.
Adverse birth outcomes are unfavorable outcomes of pregnancy that are particularly common in low- and middle-income countries. At least one ultrasound is recommended to predict adverse birth outcomes in early pregnancy. However, in low-income countries, imaging equipment and trained manpower are scarce. According to our search of the literature, there is no validated risk prediction model for predicting adverse birth outcomes in Ethiopia. Hence, we developed and validated a model and risk score to predict adverse birth outcomes using maternal characteristics during pregnancy for use in resource-limited settings.
A retrospective follow-up study was conducted from 1 January 2016 to 31 May 2021, and a total of 910 pregnant women were included in this study. Participants were selected using a simple random sampling technique. Stepwise, backward multivariable analysis was conducted. The model's accuracy was assessed using density plots, discrimination, and calibration. The developed model was assessed for internal validity using bootstrapping techniques and evaluated for clinical utility using decision curve analysis across various threshold probabilities.
Premature rupture of Membrane, number of fetuses, residence, pregnancy-induced hypertension, antepartum hemorrhage, hemoglobin level, and labor onset remained in the final multivariable prediction model. The area under the curve of the model was 0.77 (95% confidence interval: 0.73-0.812). The developed risk prediction model had a good performance and was well-calibrated and valid. The decision curve analysis indicated the model provides a higher net benefit across the ranges of threshold probabilities.
In general, this study showed the possibility of predicting adverse birth outcomes using maternal characteristics during pregnancy. The risk prediction model using a simplified risk score helps identify high-risk pregnant women for specific interventions. A feasible score would reduce neonatal morbidity and mortality and improve maternal and child health in low-resource settings.
不良分娩结局是妊娠的不良后果，在低收入和中等收入国家尤为常见。建议至少进行一次超声检查以预测早期妊娠的不良分娩结局。然而，在低收入国家，成像设备和受过培训的人力稀缺。根据我们对文献的检索，埃塞俄比亚没有经过验证的预测不良分娩结局的风险预测模型。因此，我们开发并验证了一个模型和风险评分，以利用孕期母亲特征预测不良分娩结局，供资源有限的环境使用。
于2016年1月1日至2021年5月31日进行了一项回顾性随访研究，本研究共纳入910名孕妇。采用简单随机抽样技术选择参与者。进行逐步向后多变量分析。使用密度图、辨别力和校准评估模型的准确性。使用自举技术评估所开发模型的内部有效性，并使用决策曲线分析在各种阈值概率下评估其临床实用性。
胎膜早破、胎儿数量、居住地、妊娠期高血压、产前出血、血红蛋白水平和临产在最终的多变量预测模型中保留。该模型的曲线下面积为0.77（95%置信区间：0.73 - 0.812）。所开发的风险预测模型具有良好的性能，校准良好且有效。决策曲线分析表明，该模型在阈值概率范围内提供了更高的净效益。
总体而言这项研究表明利用孕期母亲特征预测不良分娩结局是有可能的。使用简化风险评分的风险预测模型有助于识别需要特定干预措施的高危孕妇。一个可行的评分将降低低资源环境下的新生儿发病率和死亡率，并改善母婴健康。
