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Record W4412048112 · doi:10.1136/bmjopen-2024-094452

Effect of strategies to improve interhospital transports of critically ill patients on safety and costs: protocol for a systematic review and meta-analysis

2025· review· en· W4412048112 on OpenAlexafffund
Fabian Severino, Maria Cecília Bueno Jayme Gallani, Éric Mercier, Simon Ouellet, Jean-Sébastien Tremblay-Roy, Alexandra Lapierre, Christian Malo, Anick Boivin, Mélanie Berube

Bibliographic record

VenueBMJ Open · 2025
Typereview
Languageen
FieldMedicine
TopicTrauma and Emergency Care Studies
Canadian institutionsCentre Hospitalier Universitaire de SherbrookeUniversité de SherbrookeUniversité du Québec à RimouskiHôpital de l'Enfant-JésusUniversité du QuébecInstitut universitaire de cardiologie et de pneumologie de QuébecUniversité Laval
FundersCanadian Institutes of Health ResearchUniversité Laval
KeywordsMedicineCochrane LibraryCINAHLPsychological interventionMeta-analysisData extractionProtocol (science)MEDLINESystematic reviewRandomized controlled trialGrading (engineering)Publication biasIntensive care medicineAlternative medicineNursingSurgery

Abstract

fetched live from OpenAlex

Introduction Transporting critically ill patients between medical facilities can be hazardous and costly. Whether by road, fixed-wing aircraft or helicopter, many professional associations have proposed strategies to efficiently and safely transport patients at high risk of instability. Although these strategies have been assessed in some studies, no comprehensive synthesis of their benefits has been conducted to date. The aim of this study is to assess the effect of strategies to improve the safety and costs of interhospital transports for critically ill patients. Methods and analysis We will conduct a systematic review according to the Cochrane guidelines. The review will include randomised controlled trials (RCTs), cohort studies and case-control studies assessing the effect of interventions to improve interhospital transports of critically ill patients on safety and costs. We will search multiple electronic databases (PubMed, EMBASE, CINAHL, Web of Science, Cochrane Library) from inception to 6 months prior to the submission of the final manuscript. Screening by title and abstract, full-text screening, data extraction and quality assessment will be performed by two independent reviewers. We will assess the risk of bias with the Cochrane revised tool for RCTs and with the risk of bias in non-randomised studies of interventions tool. If possible, we will calculate pooled effect estimates and 95% CIs to assess the effect of the interventions. We will also assess heterogeneity using the I2 index and rate the certainty of evidence with the Grading of Recommendations Assessment, Development and Evaluation tool and trial sequential analysis. Ethics and dissemination Ethics approval is not required for this review. The results of this systematic review will be shared through publication in a peer-reviewed journal, conference presentations and our network of knowledge user collaborators. PROSPERO registration number International Prospective Register of Systematic Reviews (CRD42024595080).

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.066
metaresearch head score (Gemma)0.094
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Protocol · Consensus signal: Protocol
Teacher disagreement score0.066
Threshold uncertainty score0.347

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0660.094
Meta-epidemiology (narrow)0.0090.006
Meta-epidemiology (broad)0.0310.045
Bibliometrics0.0120.011
Science and technology studies0.0030.004
Scholarly communication0.0100.008
Open science0.0060.006
Research integrity0.0080.008
Insufficient payload (model declined to judge)0.0530.006

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.074
GPT teacher head0.491
Teacher spread0.417 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSystematic review
Domainnot available
GenreProtocol

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations1
Published2025
Admission routes2
Has abstractyes

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