新生儿死亡率预测评分可以帮助临床医生及时做出临床决定,通过在需要时促进早期入院来挽救新生儿的生命。它还可以帮助减少不必要的录取。
■该研究旨在开发和验证阿姆哈拉地区公立医院28天内新生儿死亡的预后风险评分,埃塞俄比亚。
该模型是在2021年7月至2022年1月期间,在六家医院使用经过验证的新生儿近错过评估量表和365名新生儿的前瞻性队列开发的。使用接收器工作特性曲线下的面积评估模型的准确性,校准带,和乐观的统计数据。使用500次重复自举技术进行内部验证。决策曲线分析用于评估模型的临床实用性。
■总共,365名新生儿中有63人死亡,新生儿死亡率为17.3%(95%CI:13.7-21.5)。确定了六个潜在的预测因子并将其包括在模型中:怀孕期间的贫血,妊娠高血压,胎龄小于37周,出生窒息,5分钟Apgar评分小于7,出生体重小于2500g。模型的AUC为84.5%(95%CI:78.8-90.2)。通过内部效度解释过拟合的模型预测能力为82%。决策曲线分析显示较高的临床效用表现。
■新生儿死亡率预测评分有助于早期发现,临床决策,and,最重要的是,及时对高危新生儿进行干预,最终拯救埃塞俄比亚的生命。
主要发现:在埃塞俄比亚测试的新生儿死亡率预后风险评分具有很高的准确性,决策曲线分析显示临床效用表现增加。增加的知识:这里开发的工具可以帮助医疗保健提供者识别高危新生儿并做出及时的临床决定以挽救生命。对政策和行动的全球健康影响:这些发现有可能在当地情况下应用,以识别高风险新生儿并做出可以提高儿童存活率的治疗决定。
UNASSIGNED: A neonatal mortality prediction score can assist clinicians in making timely clinical decisions to save neonates\' lives by facilitating earlier admissions where needed. It can also help reduce unnecessary admissions.
UNASSIGNED: The study aimed to develop and validate a prognosis risk score for neonatal mortality within 28 days in public hospitals in the Amhara region, Ethiopia.
UNASSIGNED: The model was developed using a validated neonatal near miss assessment scale and a prospective cohort of 365 near-miss neonates in six hospitals between July 2021 and January 2022. The model\'s accuracy was assessed using the area under the receiver operating characteristics curve, calibration belt, and the optimism statistic. Internal validation was performed using a 500-repeat bootstrapping technique. Decision curve analysis was used to evaluate the model\'s clinical utility.
UNASSIGNED: In total, 63 of the 365 neonates died, giving a neonatal mortality rate of 17.3% (95% CI: 13.7-21.5). Six potential predictors were identified and included in the model: anemia during pregnancy, pregnancy-induced hypertension, gestational age less than 37 weeks, birth asphyxia, 5 min Apgar score less than 7, and birth weight less than 2500 g. The model\'s AUC was 84.5% (95% CI: 78.8-90.2). The model\'s predictive ability while accounting for overfitting via internal validity was 82%. The decision curve analysis showed higher clinical utility performance.
UNASSIGNED: The neonatal mortality predictive score could aid in early detection, clinical decision-making, and, most importantly, timely interventions for high-risk neonates, ultimately saving lives in Ethiopia.
Main findings: This prognosis risk score for neonatal mortality tested in Ethiopia had high performance accuracy and the decision curve analysis showed increased clinical utility performance.Added knowledge: The tool developed here can aid healthcare providers in identifying high-risk neonates and making timely clinical decisions to save lives.Global health impact for policy and action: The findings have the potential to be applied in local contexts to identify high-risk neonates and make treatment decisions that could improve child survival rates.