Evidence map›Paper›PMID 40591921›Full record

ReviewAmerican journal of respiratory and critical care medicine2025

Trial Analysis and Interpretation in Critical Care Using the Evidential (Likelihood) Approach: Rationale and Practical Considerations.

Fernando G Zampieri, Peter M B Cahusac, Israel S Maia, Nadir Yehya, Nuala J Meyer, Fan Li, Michael O Harhay

Abstract readReview
PubMed Full text at PMC Publisher
In one paragraph

Review in American journal of respiratory and critical care medicine, 2025. 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
–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

1 citing paper in PubMed.

  1. Bayesian statistics: a primer for perioperative medicine clinicians.Perioperative medicine (London, England) · 2026
    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

7 authors.

Fernando G ZampieriDepartment of Critical Care Medicine, University of Alberta, Edmonton, Alberta, Canada.ORCID 0000-0001-9315-6386
Peter M B CahusacDepartment of Pharmacology and Biostatistics, College of Medicine, Alfaisal University, Riyadh, Saudi Arabia.
Israel S MaiaResearch Institute, Hospital do Coracao, Sao Paulo, Brazil.
Nadir YehyaDepartment of Anesthesiology and Critical Care Medicine, Children's Hospital of Philadelphia and University of Pennsylvania, Philadelphia, Pennsylvania.
Nuala J MeyerPulmonary, Allergy, and Critical Care Medicine Division, Department of Medicine, and.
Fan LiDepartment of Biostatistics, School of Public Health, Yale University, New Haven, Connecticut; and.
Michael O HarhayLeonard Davis Institute of Health Economics and.ORCID 0000-0002-0553-674X

Funding

Linking Endotypes and Outcomes in Pediatric Acute Respiratory Distress SyndromeR01HL148054 · NHLBI · CHILDREN'S HOSP OF PHILADELPHIA · PI YEHYA, NADIR · 2019 to 2023
$4.1M
Advancing the design, analysis, and interpretation of acute respiratory distress syndrome trials using modern statistical toolsR01HL168202 · NHLBI · UNIVERSITY OF PENNSYLVANIA · PI Michael Oscar Harhay, Fan Li · 2023 to 2026
$2.9M
NHLBI NIH HHS R01 HL148054NHLBI NIH HHS R01 HL168202NHLBI NIH HHS R01-HL168202
6 · The paper itself

Abstract

Selecting the optimal methodological framework for evidence synthesis presents a fundamental challenge in contemporary clinical research. In critical care, in which many interventions yield inconclusive results under traditional

Indexed as

Critical CareResearch DesignBayes TheoremData Interpretation, StatisticalHumansLikelihood FunctionsRespiration, ArtificialBayesianclinical trialslikelihood

Identifiers

PMID40591921
PMCPMC12432443

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.