Evidence map›Paper›PMID 34501829›Full record

ArticleInternational journal of environmental research and public health2021

Biosignal-Based Digital Biomarkers for Prediction of Ventilator Weaning Success.

Ji Eun Park, Tae Young Kim, Yun Jung Jung, Changho Han, Chan Min Park, Joo Hun Park, Kwang Joo Park, Dukyong Yoon, Wou Young Chung

Abstract read
In one paragraph

Article in International journal of environmental research and public health, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 citing papers in PubMed.

  1. Review
  2. Article
  3. Article
  4. Position Statement of ISCCM Committee on Weaning from Mechanical Ventilator.Indian journal of critical care medicine : peer-reviewed, official publication of Indian Society of Critical Care Medicine · 2024
    Article
  5. Article
  6. Article
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

9 authors.

Ji Eun ParkDepartment of Pulmonology and Critical Care Medicine, Ajou University School of Medicine, Suwon 16499, Korea.ORCID 0000-0002-3035-6353
Tae Young KimBUD.on Inc., Jeonju 54871, Korea.ORCID 0000-0002-2591-0129
Yun Jung JungDepartment of Pulmonology and Critical Care Medicine, Ajou University School of Medicine, Suwon 16499, Korea.
Changho HanDepartment of Biomedical Systems Informatics, Yonsei University College of Medicine, Yongin 16995, Korea.ORCID 0000-0003-4121-5465
Chan Min ParkDepartment of Biomedical Systems Informatics, Yonsei University College of Medicine, Yongin 16995, Korea.
Joo Hun ParkDepartment of Pulmonology and Critical Care Medicine, Ajou University School of Medicine, Suwon 16499, Korea.
Kwang Joo ParkDepartment of Pulmonology and Critical Care Medicine, Ajou University School of Medicine, Suwon 16499, Korea.
Dukyong YoonBUD.on Inc., Jeonju 54871, Korea.ORCID 0000-0003-1635-8376
Wou Young ChungDepartment of Pulmonology and Critical Care Medicine, Ajou University School of Medicine, Suwon 16499, Korea.ORCID 0000-0002-5435-2787

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

We evaluated new features from biosignals comprising diverse physiological response information to predict the outcome of weaning from mechanical ventilation (MV). We enrolled 89 patients who were candidates for weaning from MV in the intensive care unit and collected continuous biosignal data: electrocardiogram (ECG), respiratory impedance, photoplethysmogram (PPG), arterial blood pressure, and ventilator parameters during a spontaneous breathing trial (SBT). We compared the collected biosignal data's variability between patients who successfully discontinued MV (

Indexed as

Respiration, ArtificialVentilator WeaningBiomarkersHumansIntensive Care UnitsROC CurveBiomarkersbiosignaldigital biomarkermachine learningmechanical ventilatorpredictionweaning

Identifiers

PMID34501829
PMCPMC8430549

What OpenQuestion holds

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Registered trials

None linked

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.