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Record W2794734339 · doi:10.1089/neu.2017.5345

Adherence to Brain Trauma Foundation Guidelines for Management of Traumatic Brain Injury Patients and Its Effect on Outcomes: Systematic Review

2018· review· en· W2794734339 on OpenAlexaff
Yahya H. Khormi, Ibrahim M. Gosadi, Sandy Campbell, Ambikaipakan Senthilselvan, Cian O′Kelly, David Zygun

Bibliographic record

VenueJournal of Neurotrauma · 2018
Typereview
Languageen
FieldMedicine
TopicTrauma and Emergency Care Studies
Canadian institutionsUniversity of AlbertaHealth Sciences Centre
Fundersnot available
KeywordsTraumatic brain injuryMedicineBrain traumaProspective cohort studyTrauma centerCohortCohort studyIntensive care medicineEmergency medicinePhysical therapyInternal medicineRetrospective cohort studyPsychiatry

Abstract

fetched live from OpenAlex

Traumatic brain injury (TBI) management based on Brain Trauma Foundation (BTF) guidelines is widely accepted and thought to improve outcome. The objectives of this study are to provide an overview of adherence to BTF guidelines and to explore which factors influence adherence. We conducted a search of relevant electronic bibliographic databases. Twenty articles met inclusion/exclusion criteria out of 666 articles screened. All were cohort studies. Wide variation in adherence to BTF guidelines was observed with a median of 66.2% (range 0-100%). The lowest median adherence was observed with surgical management (14%), whereas the highest was observed with oxygenation (100%), steroid (97.8%), and blood pressure recommendation (92.3%). Variability was primarily explained by the variation in the strength of evidence of each recommendation. Treating patients with higher severity of injury as well as treatment in a Level I trauma center positively influenced adherence. Overall, adherence to BTF guidelines varies. Further research is required to strengthen the current evidence and to identify factors related to adherence to guidelines from a professional prospective.

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)0.002
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.317
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0060.001
Bibliometrics0.0010.000
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 head0.267
GPT teacher head0.483
Teacher spread0.216 · 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.

Study designSystematic review
Domainnot available
GenreReview

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

Citations31
Published2018
Admission routes1
Has abstractyes

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