Department of Public Health, College of Health Sciences, Debre Tabor University, Debre Tabor, Ethiopia.
Department of Pediatrics & Child Health, College of Health Sciences, Debre Tabor University, Debre Tabor, Ethiopia.
BMC Pediatr. 2022 Sep 10;22(1):537. doi: 10.1186/s12887-022-03582-x.
Birth asphyxia leads to profound systemic and neurological sequela to decrease blood flow or oxygen to the fetus followed by lethal progressive or irreversible life-long pathologies. In low resource setting countries, birth asphyxia remains a critical condition. This study aimed to develop and validate prognostic risk scores to forecast birth asphyxia using maternal and neonatal characteristics in south Gondar zone hospitals.
Prospective cohorts of 404 pregnant women were included in the model in south Gondar Zone Hospitals, Northwest Ethiopia. To recognize potential prognostic determinants for birth asphyxia, multivariable logistic regression was applied. The model discrimination probability was checked using the receiver operating characteristic curve (AUROC) and the model calibration plot was assessed using the 'givitiR' R-package. To check the clinical importance of the model, a cost-benefit analysis was done through a decision curve and the model was internally validated using bootstrapping. Lastly, a risk score prediction measurement was established for simple application.
Of 404, 108 (26.73%) (95% CI: 22.6-31.3) newborns were exposed to birth asphyxia during the follow-up time. Premature rupture of membrane, meconium aspiration syndrome, malpresentation, prolonged labor, Preterm, and tight nuchal was the significant prognostic predictors of birth asphyxia. The AUROC curve for birth asphyxia was 88.6% (95% CI: 84.6-92.2%), which indicated that the tool identified the newborns at risk for birth asphyxia very well. The AUROC of the simplified risk score algorithm, was 87.9 (95% CI, 84.0- 91.7%) and the risk score value of 2 was selected as the optimal cut-off value, with a sensitivity of 78.87%, a specificity of 83.26%, a positive predictive value of 63.23%, and a negative predictive value of 91.52%.
We established birth asphyxia prediction tools by applying non-sophisticated maternal and neonatal characteristics for resource scares countries. The driven score has very good discriminative ability and prediction performance. This risk score tool would allow reducing neonatal morbidity and mortality related to birth asphyxia. Consequently, it will improve the overall neonatal health / under-five child health in low-income countries.
出生窒息会导致全身和神经系统严重后遗症,导致胎儿血流或氧气减少,随后出现致命的进行性或不可逆的终身病理。在资源匮乏的国家,出生窒息仍然是一种危急情况。本研究旨在利用南冈达尔地区医院的产妇和新生儿特征开发和验证预测出生窒息的预后评分。
前瞻性队列纳入了来自埃塞俄比亚西北南冈达尔地区医院的 404 名孕妇。为了识别出生窒息的潜在预后因素,应用多变量逻辑回归。使用接收者操作特征曲线(AUROC)检查模型的区分概率,并使用“givitiR”R 包评估模型校准图。为了检查模型的临床重要性,通过决策曲线进行成本效益分析,并通过自举进行内部验证。最后,建立了风险评分预测测量,以便于简单应用。
在随访期间,404 名新生儿中有 108 名(26.73%)(95%CI:22.6-31.3)暴露于出生窒息。胎膜早破、胎粪吸入综合征、胎位不正、产程延长、早产和紧颈是出生窒息的显著预后预测因素。出生窒息的 AUROC 曲线为 88.6%(95%CI:84.6-92.2%),表明该工具很好地识别了有出生窒息风险的新生儿。简化风险评分算法的 AUROC 为 87.9%(95%CI,84.0-91.7%),选择风险评分值为 2 作为最佳截断值,其灵敏度为 78.87%,特异性为 83.26%,阳性预测值为 63.23%,阴性预测值为 91.52%。
我们应用简单的产妇和新生儿特征为资源匮乏的国家建立了出生窒息预测工具。驱动评分具有很好的区分能力和预测性能。这种风险评分工具可以降低与出生窒息相关的新生儿发病率和死亡率。因此,它将改善低收入国家的整体新生儿健康/五岁以下儿童健康。