{"title":"Validation of a novel Bayesian predictive algorithm for detection of carbon dioxide retention using retrospective neonatal ICU data.","authors":"Luke T Viehl, Jeffrey L Segar, Zachary A Vesoulis","doi":"10.1038/s41372-025-02369-z","DOIUrl":null,"url":null,"abstract":"<p><strong>Objective: </strong>To validate a novel Bayesian prediction algorithm (IVCO2 index) to calculate the probability of CO<sub>2</sub> retention in neonates using existing medical device outputs.</p><p><strong>Study design: </strong>A retrospective validation study from two level IV NICUs between September 2021 and May 2023. The algorithm calculated probabilities of PaCO<sub>2</sub> 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.</p><p><strong>Results: </strong>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<sub>2</sub> 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.</p><p><strong>Conclusion: </strong>The IVCO2 index accurately predicts CO<sub>2</sub> retention in neonates, offering potential for early detection of ventilation inadequacy without additional invasive monitoring.</p>","PeriodicalId":16690,"journal":{"name":"Journal of Perinatology","volume":" ","pages":""},"PeriodicalIF":2.4000,"publicationDate":"2025-07-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Perinatology","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1038/s41372-025-02369-z","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"OBSTETRICS & GYNECOLOGY","Score":null,"Total":0}
引用次数: 0
Abstract
Objective: To validate a novel Bayesian prediction algorithm (IVCO2 index) to calculate the probability of CO2 retention in neonates using existing medical device outputs.
Study design: A retrospective validation study from two level IV NICUs between September 2021 and May 2023. The algorithm calculated probabilities of PaCO2 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.
Results: 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 PaCO2 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.
Conclusion: The IVCO2 index accurately predicts CO2 retention in neonates, offering potential for early detection of ventilation inadequacy without additional invasive monitoring.
目的:验证一种新的贝叶斯预测算法(IVCO2指数),利用现有医疗器械输出计算新生儿CO2滞留概率。研究设计:在2021年9月至2023年5月期间对两个IV级nicu进行回顾性验证研究。该算法利用多模态生理数据计算PaCO2超过50 mmHg (IVCO2_50)和60 mmHg (IVCO2_60)的概率。通过ROC分析、范围利用率和分辨率/限制分析来评估性能。结果:在180例纳入的新生儿中,分析了1092例动脉血气测量。IVCO2_50和IVCO2_60表现出优异的区分性能(AUC分别为0.87,95% CI 0.85-0.89和0.90,95% CI 0.68-0.93)。PaCO2升高的风险随着指数四分位数的增加呈线性增长。最低评分(高碳酸血症风险降低6倍),而最高评分(bbb99)显示正常碳酸血症风险降低>3倍。结论:IVCO2指数能准确预测新生儿的CO2潴留,为早期发现通气不足提供了可能,无需额外的有创监测。
期刊介绍:
The Journal of Perinatology provides members of the perinatal/neonatal healthcare team with original information pertinent to improving maternal/fetal and neonatal care. We publish peer-reviewed clinical research articles, state-of-the art reviews, comments, quality improvement reports, and letters to the editor. Articles published in the Journal of Perinatology embrace the full scope of the specialty, including clinical, professional, political, administrative and educational aspects. The Journal also explores legal and ethical issues, neonatal technology and product development.
The Journal’s audience includes all those that participate in perinatal/neonatal care, including, but not limited to neonatologists, perinatologists, perinatal epidemiologists, pediatricians and pediatric subspecialists, surgeons, neonatal and perinatal nurses, respiratory therapists, pharmacists, social workers, dieticians, speech and hearing experts, other allied health professionals, as well as subspecialists who participate in patient care including radiologists, laboratory medicine and pathologists.