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Record W2606127074 · doi:10.1136/bmjopen-2016-013779

Prognostication in critically ill patients with severe traumatic brain injury: the TBI-Prognosis multicentre feasibility study

2017· article· en· W2606127074 on OpenAlexafffundabout
Alexis F. Turgeon, François Lauzier, Ryan Zarychanski, Dean Fergusson, Caroline Léger, Lauralyn McIntyre, Françis Bernard, Andrea Rigamonti, Karen E. A. Burns, Donald Griesdale, Robert S. Green, Damon C. Scales, Maureen O. Meade, Martin Savard, Michèle Shemilt, Jérôme Paquet, Jean‐Luc Gariépy, André Lavoie, Kesh Reddy, Draga Jichici, Giuseppe Pagliarello, David Zygun, Lynne Moore

Bibliographic record

VenueBMJ Open · 2017
Typearticle
Languageen
FieldMedicine
TopicTraumatic Brain Injury and Neurovascular Disturbances
Canadian institutionsUniversity of AlbertaSunnybrook HospitalUniversity of British ColumbiaDalhousie UniversityUniversity of TorontoSt. Michael's HospitalUniversity of ManitobaOttawa HospitalUniversity of OttawaUniversité de MontréalUniversité LavalMcMaster UniversityThe Quebec Population Health Research Network
FundersCanadian Institutes of Health ResearchFonds de Recherche du Québec - SantéGroupe canadien de recherche en soins intensifsCanadian Intensive Care FoundationIntensive Care Foundation
KeywordsMedicineTraumatic brain injuryCritically illIntensive care medicineNeurologyEmergency medicinePsychiatry

Abstract

fetched live from OpenAlex

OBJECTIVE: Severe traumatic brain injury is a significant cause of morbidity and mortality in young adults. Assessing long-term neurological outcome after such injury is difficult and often characterised by uncertainty. The objective of this feasibility study was to establish the feasibility of conducting a large, multicentre prospective study to develop a prognostic model of long-term neurological outcome in critically ill patients with severe traumatic brain injury. DESIGN: A prospective cohort study. SETTING: 9 Canadian intensive care units enrolled patients suffering from acute severe traumatic brain injury. Clinical, biological, radiological and electrophysiological data were systematically collected during the first week in the intensive care unit. Mortality and functional outcome (Glasgow Outcome Scale extended) were assessed on hospital discharge, and then 3, 6 and 12 months following injury. OUTCOMES: The compliance to protocolised test procedures was the primary outcome. Secondary outcomes were enrolment rate and compliance to follow-up. RESULTS: We successfully enrolled 50 patients over a 12-month period. Most patients were male (80%), with a median age of 45 years (IQR 29.0-60.0), a median Injury Severity Score of 38 (IQR 25-50) and a Glasgow Coma Scale of 6 (IQR 3-7). Mortality was 38% (19/50) and most deaths occurred following a decision to withdraw life-sustaining therapies (18/19). The main reasons for non-enrolment were the time window for inclusion being after regular working hours (35%, n=23) and oversight (24%, n=16). Compliance with protocolised test procedures ranged from 92% to 100% and enrolment rate was 43%. No patients were lost to follow-up at 6 months and 2 were at 12 months. CONCLUSIONS: In this multicentre prospective feasibility study, we achieved feasibility objectives pertaining to compliance to test, enrolment and follow-up. We conclude that the TBI-Prognosis prospective multicentre study in severe traumatic brain injury patients in Canada is feasible.

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)0.005
metaresearch head score (Gemma)0.010
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.029

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.010
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.098
GPT teacher head0.402
Teacher spread0.305 · 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 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

Citations22
Published2017
Admission routes3
Has abstractyes

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