Evidence map›Paper›PMID 40702156›Full record

ArticleJournal of perinatology : official journal of the California Perinatal Association2026

Validation of a novel Bayesian predictive algorithm for detection of carbon dioxide retention using retrospective neonatal ICU data.

Luke T Viehl, Jeffrey L Segar, Zachary A Vesoulis

Abstract readValidation Study
PubMed Publisher
In one paragraph

Article in Journal of perinatology : official journal of the California Perinatal Association, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Luke T ViehlDivision of Newborn Medicine, Department of Pediatrics, Washington University, St. Louis, MO, USA.
Jeffrey L SegarDivision of Neonatology, Department of Pediatrics, Medical College of Wisconsin, Milwaukee, WI, USA.
Zachary A VesoulisDivision of Newborn Medicine, Department of Pediatrics, Washington University, St. Louis, MO, USA. vesoulis_z@wustl.edu.ORCID http://orcid.org/0000-0001-8290-0069

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveTo validate a novel Bayesian prediction algorithm (IVCO2 index) to calculate the probability of CO STUDY

designA retrospective validation study from two level IV NICUs between September 2021 and May 2023. The algorithm calculated probabilities of PaCO

resultsAmong 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

conclusionThe IVCO2 index accurately predicts CO

Indexed as

AlgorithmsCarbon DioxideHypercapniaBayes TheoremBlood Gas AnalysisFemaleHumansInfant, NewbornIntensive Care Units, NeonatalMalePrediction AlgorithmsRetrospective StudiesROC CurveCarbon Dioxide

Identifiers

PMID40702156

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.