Evidence map›Paper›PMID 38424493›Full record

Observational studyBMC pediatrics2024

Individualized estimation of arterial carbon dioxide partial pressure using machine learning in children receiving mechanical ventilation.

Hye-Ji Han, Bongjin Lee, June Dong Park

Erratum issuedAbstract readObservational Study
In one paragraph

Observational study in BMC pediatrics, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

3 authors.

Hye-Ji HanDepartment of Pediatrics, Seoul National University College of Medicine, Seoul National University Children's Hospital, Seoul, 03080, Republic of Korea.
Bongjin LeeDepartment of Pediatrics, Seoul National University College of Medicine, Seoul National University Children's Hospital, Seoul, 03080, Republic of Korea. pedbjl@snu.ac.kr.
June Dong ParkDepartment of Pediatrics, Seoul National University College of Medicine, Seoul National University Children's Hospital, Seoul, 03080, Republic of Korea.

Funding

National Research Foundation of Korea 2023R1A2C1007095Seoul National University Hospital 03-2022-0370
6 · The paper itself

Abstract

backgroundMeasuring arterial partial pressure of carbon dioxide (PaCO

methodsThis retrospective observational study included pediatric patients (< 18 years) admitted to the pediatric intensive care unit of a tertiary children's hospital and received mechanical ventilation between January 2021 and June 2022. Clinical information, including mechanical ventilation parameters and laboratory test results, was used for machine learning. Linear regression, multilayer perceptron, and extreme gradient boosting were implemented. The dataset was divided into 7:3 ratios for training and testing. Model performance was assessed using the R

resultsWe analyzed total 2,427 measurements from 32 patients. The median (interquartile range) age was 16 (12-19.5) months, and 74.1% were female. The PaCO2 and EtCO2 were 63 (50-83) mmHg and 43 (35-54) mmHg, respectively. A significant discrepancy of 19 (12-31) mmHg existed between EtCO

conclusionsWe developed machine learning models to non-invasively estimate PaCO

Indexed as

Carbon DioxideRespiration, ArtificialCapnographyFemaleHumansInfantMalePartial PressureReproducibility of ResultsCarbon DioxideBlood gas analysisCapnographyMachine learningMechanical ventilationRespiratory Dead Space

Identifiers

PMID38424493
PMCPMC10902995

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.