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Record W4393376199 · doi:10.1097/ccm.0000000000006283

Evaluating the Sum of Eye and Motor Components of the Glasgow Coma Score As a Predictor of Extubation Failure in Patients With Acute Brain Injury

2024· article· en· W4393376199 on OpenAlexaff
Shaurya Taran, Bastien Perrot, Federico Angriman, Raphaël Cinotti

Bibliographic record

VenueCritical Care Medicine · 2024
Typearticle
Languageen
FieldMedicine
TopicTraumatic Brain Injury and Neurovascular Disturbances
Canadian institutionsHealth Sciences CentreSunnybrook Health Science CentreUniversity of Toronto
Fundersnot available
KeywordsMedicineGlasgow Coma ScaleComa (optics)AnesthesiaOdds ratioMechanical ventilationOddsLogistic regressionInternal medicine

Abstract

fetched live from OpenAlex

OBJECTIVES: To evaluate the association between the pre-extubation sum of eye and motor components of the Glasgow Coma Score (GCS-EM) and odds of extubation failure in patients with acute brain injury being liberated from mechanical ventilation. DESIGN: Secondary analysis of a prospective, multicenter observational study ( ClinicalTrials.gov identifier NCT03400904). SETTING: Sixty-three hospital sites worldwide, with patient recruitment from January 2018 to November 2020. PATIENTS: One thousand one hundred fifty-two critically ill patients with acute brain injury, with a median age of 54 years, of whom 783 (68.0%) were male, 559 (48.5%) had traumatic brain injury, and 905 (78.6%) had a GCS-EM greater than 8 before extubation (scores range from 2 to 10). INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: GCS-EM was computed in intubated patients on the day of extubation. The main outcome was extubation failure, defined as unplanned reintubation within 5 days of extubation. Analyses used multilevel logistic regression with adjustment for patient characteristics and a random intercept for hospital site. In the primary analysis, GCS-EM was not associated with extubation failure (odds ratio, 1.07 per additional point; 95% CI, 0.87-1.31). Findings were consistent in sensitivity analyses that: 1) used different adjustment covariates, 2) included a verbal estimate to derive an overall GCS, 3) accounted for missing data, 4) considered a 2-day time interval to define extubation failure, 5) accounted for competing risks, and 6) used a propensity score-based model. There was no association between GCS-EM and extubation outcome in subgroups defined by brain injury diagnosis or age. CONCLUSIONS: In this large, contemporary, multicenter cohort of patients with acute brain injury, we found no association between the GCS-EM and odds of extubation failure. However, few patients had a pre-extubation GCS-EM less than or equal to 8, and the possibility of a true prognostic association in patients with low scores is not excluded.

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)0.015
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 score0.003
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.015
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.030
GPT teacher head0.335
Teacher spread0.306 · 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

Citations4
Published2024
Admission routes1
Has abstractyes

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