Association of age with extubation failure in neurocritical intensive care unit patients––Insight from an international prospective study named ENIO
Bibliographic record
Abstract
OBJECTIVE: To assess the association of age with extubation failure in neurocritical care patients. DESIGN: Posthoc analysis of the 'Extubation strategies in Neuro-Intensive care unit patients and associations with Outcomes (ENIO) study', an international prospective observational study. SETTING: ENIO was conducted in 73 centers in 18 countries from 2018 to 2020. PATIENTS: Neurocritical care patients with a Glasgow Coma Scale score ≤ 12 and receiving ventilationfor at least 24 h were included. We categorized patients into four age groups based on age quartiles. MAIN RESULTS: This analysis included 1095 patients with a median age of 53 [35 to 65] years. Younger patients were more likely to be admitted with traumatic brain injury, whereas older patients more often had cerebral hemorrhage, ischemic stroke, central nervous infection, or brain malignancies. Extubation failure occurred in 209 (19 %) patients. In the unadjusted analysis, older patients had a higher risk of extubation failure (odds ratio (OR), 1.012 [95 %-confidence interval (CI) 1.004 to 1.021]; P = 0.006). However, after adjusting for confounding factors, the effect of age on extubation failure was no longer significant (OR, 1.008 [0.997 to 1.019]; P = 0.172). CONCLUSIONS: In this international cohort of intubated and ventilated neurocritical care patients, after adjusting for baseline covariates and for previously identified risk factors for extubation failure, age was not associated with extubation failure. Age may not be a factor to consider in extubation decisions for brain-injured patients. REGISTRATION: ENIO is registered at clinicaltrials.gov (study identifier NCT03400904).
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".