Evidence map›Paper›PMID 37137712›Full record

ArticleRespiratory care2023

Predicting Duration of Invasive Mechanical Ventilation in the Pediatric ICU.

Colin M Rogerson, Samer Abu-Sultaneh, Jeremy M Loberger, Patrick Ross, Robinder G Khemani, L Nelson Sanchez-Pinto

Open access · greenAbstract read
In one paragraph

Article in Respiratory care, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.3field-weighted citation impact, top 39% 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

1 citing paper in PubMed, 1 citations in OpenAlex.

  1. 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

6 authors at 4 institutions in 1 country.

Colin M RogersonIndiana University School of Medicine, Riley Hospital for Children, Indianapolis, Indiana. crogerso@iupui.edu.
Samer Abu-SultanehIndiana University School of Medicine, Riley Hospital for Children, Indianapolis, Indiana.
Jeremy M LobergerUniversity of Alabama at Birmingham, Children's of Alabama, Birmingham, Alabama.
Patrick RossUniversity of Southern California Keck School of Medicine and Department of Anesthesiology and Critical Care, Children's Hospital Los Angeles, Los Angeles, California.
Robinder G KhemaniUniversity of Southern California Keck School of Medicine and Department of Anesthesiology and Critical Care, Children's Hospital Los Angeles, Los Angeles, California.
L Nelson Sanchez-PintoNorthwestern University Feinberg School of Medicine, Ann and Robert H. Lurie Children's Hospital of Chicago, Chicago, Illinois.
Children's Hospital of Los Angeles · USRiley Hospital for Children · USChildren's of Alabama · USNorthwestern University · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundTimely ventilator liberation can prevent morbidities associated with invasive mechanical ventilation in the pediatric ICU (PICU). There currently exists no standard benchmark for duration of invasive mechanical ventilation in the PICU. This study sought to develop and validate a multi-center prediction model of invasive mechanical ventilation duration to determine a standardized duration of invasive mechanical ventilation ratio.

methodsThis was a retrospective cohort study using registry data from 157 institutions in the Virtual Pediatric Systems database. The study population included encounters in the PICU between 2012-2021 involving endotracheal intubation and invasive mechanical ventilation in the first day of PICU admission who received invasive mechanical ventilation for > 24 h. Subjects were stratified into a training cohort (2012-2017) and 2 validation cohorts (2018-2019/2020-2021). Four models to predict the duration of invasive mechanical ventilation were trained using data from the first 24 h, validated, and compared.

resultsThe study included 112,353 unique encounters. All models had observed-to-expected (O/E) ratios close to one but low mean squared error and R

conclusionsWe derived and validated a model to predict the duration of invasive mechanical ventilation that performed well in aggregated predictions at the PICU and the cohort level. This model could be beneficial in quality improvement and institutional benchmarking initiatives for use at the PICU level and for tracking of performance over time.

Indexed as

Intensive Care Units, PediatricRespiration, ArtificialChildHospitalizationHumansLength of StayRetrospective Studiesmachine learningmechanical ventilationpediatric critical carepediatricsquality improvement

Identifiers

PMID37137712
PMCPMC10676255
OpenAlexW4367839926

What OpenQuestion holds

Textmetadata
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.