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Record W2761476605 · doi:10.1136/bmjopen-2017-016355

Bypassing nearest hospital for more distant neuroscience care in head-injured adults with suspected traumatic brain injury: findings of the head injury transportation straight to neurosurgery (HITS-NS) pilot cluster randomised trial

2017· article· en· W2761476605 on OpenAlexaff
Fiona Lecky, Graham McClelland, Elspeth Pennington, Gordon Fuller, Steve Goodacre, Kyee Han, Andrew Curran, Damian Holliman, Nathan Chapman, Jennifer Freeman, Sonia Byers, Suzanne Mason, Hugh Potter, Tim Coats, Kevin Mackway‐Jones, Mary Anne Peters, Jane Shewan

Bibliographic record

VenueBMJ Open · 2017
Typearticle
Languageen
FieldMedicine
TopicTrauma and Emergency Care Studies
Canadian institutionsOccupational Cancer Research Centre
FundersHealth Technology Assessment ProgrammeUniversity of ManchesterJames Cook UniversityNational Institute for Health and Care Research
KeywordsMedicineNeurosurgeryTraumatic brain injuryRandomized controlled trialHead injuryCluster randomised controlled trialEmergency medicinePsychological interventionPoison controlPhysical therapyPsychiatryInternal medicine

Abstract

fetched live from OpenAlex

OBJECTIVE: Reconfiguration of trauma services, with direct transport of patients with traumatic brain injury (TBI) to specialist neuroscience centres (SNCs)-bypassing non-specialist acute hospitals (NSAHs), could improve outcomes. However, delays in stabilisation of airway, breathing and circulation (ABC) may worsen outcomes when compared with selective secondary transfer from nearest NSAH to SNC. We conducted a pilot cluster randomised controlled trial to determine the feasibility and plausibility of bypassing suspected patients with TBI -directly into SNCs-producing a measurable effect. SETTING: Two English Ambulance Services. PARTICIPANTS: 74 clusters (ambulance stations) were randomised within pairs after matching for important characteristics. Clusters enrolled head-injured adults-injured nearest to an NSAH-with internationally accepted TBI risk factors and stable ABC. We excluded participants attended by Helicopter Emergency Medical Services or who were injured more than 1 hour by road from nearest SNC. INTERVENTIONS: Intervention cluster participants were transported directly to an SNC bypassing nearest NSAH; control cluster participants were transported to nearest NSAH with selective secondary transfer to SNC. OUTCOMES: Trial recruitment rate (target n=700 per annum) and percentage with TBI on CT scan (target 80%) were the primary feasibility outcomes. 30-day mortality, 6-month Extended Glasgow Outcome Scale and quality of life were secondary outcomes. RESULTS: 56 ambulance station clusters recruited 293 patients in 12 months. The trial arms were similar in terms of age, conscious level and injury severity. Less than 25% of recruited patients had TBI on CT (n=70) with 7% (n=20) requiring neurosurgery. Complete case analysis showed similar 30-day mortality in the two trial arms (control=8.8 (2.7-14.0)% vs intervention=9.4(2.3-14.0)%). CONCLUSION: Bypassing patients with suspected TBI to SNCs gives an overtriage (false positive) ratio of 13:1 for neurosurgical intervention and 4:1 for TBI. A measurable effect from a full trial of early neuroscience care following bypass is therefore unlikely. TRIAL REGISTRATION NUMBER: ISRCTN68087745.

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)0.003
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Randomized trial · Consensus signal: Randomized trial
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.009
Threshold uncertainty score0.028

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.006
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0030.003
Bibliometrics0.0010.001
Science and technology studies0.0010.002
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0090.001

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 head0.066
GPT teacher head0.402
Teacher spread0.336 · 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 designRandomized trial
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

Citations24
Published2017
Admission routes1
Has abstractyes

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