Viehl Luke T, Segar Jeffrey L, Vesoulis Zachary A
Division of Newborn Medicine, Department of Pediatrics, Washington University, St. Louis, MO, USA.
Division of Neonatology, Department of Pediatrics, Medical College of Wisconsin, Milwaukee, WI, USA.
J Perinatol. 2025 Jul 23. doi: 10.1038/s41372-025-02369-z.
To validate a novel Bayesian prediction algorithm (IVCO2 index) to calculate the probability of CO retention in neonates using existing medical device outputs.
A retrospective validation study from two level IV NICUs between September 2021 and May 2023. The algorithm calculated probabilities of PaCO exceeding 50 mmHg (IVCO2_50) and 60 mmHg (IVCO2_60) using multimodal physiologic data. Performance was assessed through ROC analysis, range utilization, and resolution/limitation analysis.
Among 180 included neonates, 1092 arterial blood gas measurements were analyzed. IVCO2_50 and IVCO2_60 demonstrated excellent discriminatory performance (AUC 0.87, 95% CI 0.85-0.89 and AUC 0.90, 95% CI 0.68-0.93, respectively). The risk of elevated PaCO scaled linearly with increasing index quartiles. Minimum scores (<1) showed >6-fold reduction in hypercapnia risk, while maximum scores (>99) demonstrated >3-fold reduction in normocapnia risk.
The IVCO2 index accurately predicts CO retention in neonates, offering potential for early detection of ventilation inadequacy without additional invasive monitoring.
验证一种新型贝叶斯预测算法(IVCO2指数),该算法可利用现有医疗设备输出数据计算新生儿二氧化碳潴留的概率。
一项回顾性验证研究,研究对象来自2021年9月至2023年5月期间的两家四级新生儿重症监护病房(NICU)。该算法使用多模态生理数据计算动脉血二氧化碳分压(PaCO₂)超过50 mmHg(IVCO2_50)和60 mmHg(IVCO2_60)的概率。通过ROC分析、范围利用率分析和分辨率/局限性分析对算法性能进行评估。
在纳入研究的180例新生儿中,共分析了1092次动脉血气测量结果。IVCO2_50和IVCO2_60显示出优异的鉴别性能(AUC分别为0.87,95%CI 0.85 - 0.89和AUC 0.90,95%CI 0.68 - 0.93)。PaCO₂升高的风险随指数四分位数的增加呈线性变化。最低分数(<1)显示高碳酸血症风险降低>6倍,而最高分数(>99)显示正常碳酸血症风险降低>3倍。
IVCO2指数能够准确预测新生儿的二氧化碳潴留情况,无需额外的侵入性监测即可早期发现通气不足。