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Record W4389051478 · doi:10.1186/s13054-023-04718-w

An international RAND/UCLA expert panel to determine the optimal diagnosis and management of burn inhalation injury

2023· article· en· W4389051478 on OpenAlexaff
Helena Milton-Jones, Sabri Soussi, Emmanuel Charbonney, Walton N. Charles, Heather Cleland, Ken Dunn, Dashiell Gantner, Julian Giles, Marc G. Jeschke, Nicole Lee, Matthieu Legrand, Joanne Lloyd, Ignacio Martín‐Loeches, Olivier Pantet, Mark Samaan, Odhran Shelley, Alice Sisson, Kaisa Spragg, Fiona Wood, Jeremy Yarrow, Marcela P. Vizcaychipi, Andrew J Williams, Jorge Leon-Villapalos, Declan Collins, Isabel Jones, Suveer Singh

Bibliographic record

VenueCritical Care · 2023
Typearticle
Languageen
FieldMedicine
TopicBurn Injury Management and Outcomes
Canadian institutionsSunnybrook Health Science CentreUniversité de MontréalToronto Western HospitalCentre Hospitalier de l’Université de MontréalUniversity of TorontoUniversity Health Network
FundersRoyal College of AnaesthetistsNational Institute for Health and Care Research
KeywordsMedicineDelphi methodIntensive care medicineAirway managementIntubationEmergency medicineAnesthesia

Abstract

fetched live from OpenAlex

BACKGROUND: Burn inhalation injury (BII) is a major cause of burn-related mortality and morbidity. Despite published practice guidelines, no consensus exists for the best strategies regarding diagnosis and management of BII. A modified DELPHI study using the RAND/UCLA (University of California, Los Angeles) Appropriateness Method (RAM) systematically analysed the opinions of an expert panel. Expert opinion was combined with available evidence to determine what constitutes appropriate and inappropriate judgement in the diagnosis and management of BII. METHODS: A 15-person multidisciplinary panel comprised anaesthetists, intensivists and plastic surgeons involved in the clinical management of major burn patients adopted a modified Delphi approach using the RAM method. They rated the appropriateness of statements describing diagnostic and management options for BII on a Likert scale. A modified final survey comprising 140 statements was completed, subdivided into history and physical examination (20), investigations (39), airway management (5), systemic toxicity (23), invasive mechanical ventilation (29) and pharmacotherapy (24). Median appropriateness ratings and the disagreement index (DI) were calculated to classify statements as appropriate, uncertain, or inappropriate. RESULTS: Of 140 statements, 74 were rated as appropriate, 40 as uncertain and 26 as inappropriate. Initial intubation with ≥ 8.0 mm endotracheal tubes, lung protective ventilatory strategies, initial bronchoscopic lavage, serial bronchoscopic lavage for severe BII, nebulised heparin and salbutamol administration for moderate-severe BII and N-acetylcysteine for moderate BII were rated appropriate. Non-protective ventilatory strategies, high-frequency oscillatory ventilation, high-frequency percussive ventilation, prophylactic systemic antibiotics and corticosteroids were rated inappropriate. Experts disagreed (DI ≥ 1) on six statements, classified uncertain: the use of flexible fiberoptic bronchoscopy to guide fluid requirements (DI = 1.52), intubation with endotracheal tubes of internal diameter < 8.0 mm (DI = 1.19), use of airway pressure release ventilation modality (DI = 1.19) and nebulised 5000IU heparin, N-acetylcysteine and salbutamol for mild BII (DI = 1.52, 1.70, 1.36, respectively). CONCLUSIONS: Burns experts mostly agreed on appropriate and inappropriate diagnostic and management criteria of BII as in published guidance. Uncertainty exists as to the optimal diagnosis and management of differing grades of severity of BII. Future research should investigate the accuracy of bronchoscopic grading of BII, the value of bronchial lavage in differing severity groups and the effectiveness of nebulised therapies in different severities of BII.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.635
Threshold uncertainty score0.247

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.068
GPT teacher head0.383
Teacher spread0.315 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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

Citations25
Published2023
Admission routes1
Has abstractyes

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