Evidence map›Paper›PMID 34820341›Full record

ArticleFrontiers in pediatrics2021

Predicting Flow Rate Escalation for Pediatric Patients on High Flow Nasal Cannula Using Machine Learning.

Joshua A Krachman, Jessica A Patricoski, Christopher T Le, Jina Park, Ruijing Zhang, Kirby D Gong, Indranuj Gangan, Raimond L Winslow, Joseph L Greenstein, James Fackler and 2 more

Open access · goldAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Frontiers in pediatrics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.3field-weighted citation impact, top 38% of its field
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, 2 citations in OpenAlex.

  1. [Analysis of ROX Index, ROX-HR Index, and SpOJournal of Korean Academy of Nursing · 2023
    Article
  2. 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

12 authors at 2 institutions in 1 country.

Joshua A KrachmanDepartment of Biomedical Engineering, Institute for Computational Medicine, Johns Hopkins University, Baltimore, MD, United States.
Jessica A PatricoskiDepartment of Biomedical Engineering, Institute for Computational Medicine, Johns Hopkins University, Baltimore, MD, United States.
Christopher T LeDepartment of Biomedical Engineering, Institute for Computational Medicine, Johns Hopkins University, Baltimore, MD, United States.
Jina ParkDepartment of Biomedical Engineering, Institute for Computational Medicine, Johns Hopkins University, Baltimore, MD, United States.
Ruijing ZhangDepartment of Biomedical Engineering, Institute for Computational Medicine, Johns Hopkins University, Baltimore, MD, United States.
Kirby D GongDepartment of Biomedical Engineering, Institute for Computational Medicine, Johns Hopkins University, Baltimore, MD, United States.
Indranuj GanganDepartment of Biomedical Engineering, Institute for Computational Medicine, Johns Hopkins University, Baltimore, MD, United States.
Raimond L WinslowDepartment of Biomedical Engineering, Institute for Computational Medicine, Johns Hopkins University, Baltimore, MD, United States.
Joseph L GreensteinDepartment of Biomedical Engineering, Institute for Computational Medicine, Johns Hopkins University, Baltimore, MD, United States.
James FacklerDepartment of Anesthesiology and Critical Care Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, United States.
Anthony A SochetDepartment of Anesthesiology and Critical Care Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, United States.
Jules P BergmannDepartment of Anesthesiology and Critical Care Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, United States.
Johns Hopkins University · USJohns Hopkins Medicine · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

PubMed holds no abstract for this paper.

Indexed as

acute respiratory failureflow rate escalationhigh flow nasal cannulamachine learningnon-responsepediatric critical care

Identifiers

PMID34820341
PMCPMC8606666
OpenAlexW3214650807

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.