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Record W3015249860 · doi:10.21037/atm.2020.03.160

Extubation strategies in neuro-intensive care unit patients and associations with outcomes: the ENIO multicentre international observational study

2020· article· en· W3015249860 on OpenAlexaff
Raphaël Cinotti, Paolo Pelosi, Marcus J. Schultz, Aikaterini Ioakeimidou, Pablo Alvarez, Rafael Badenes, Victoria Mc Credie, Abdurrahmaan Suei Elbuzidi, Muhammed Elhadi, Daniel Agustín Godoy, Mohan Gurjar, Matthias Hænggi, Callum Kaye, Julio Mijangos, Michaël Piagnerelli, Romain Piracchio, Syed Tariq Reza, Robert D. Stevens, Yoshitoyo Ueno, Karim Asehnoune

Bibliographic record

VenueAnnals of Translational Medicine · 2020
Typearticle
Languageen
FieldMedicine
TopicTracheal and airway disorders
Canadian institutionsUniversity of TorontoUniversity Health Network
Fundersnot available
KeywordsMedicineGlasgow Coma ScaleIntensive care unitObservational studyMechanical ventilationNeurointensive careEmergency medicineIntensive care medicinePopulationIntensive careCohortAnesthesiaInternal medicine

Abstract

fetched live from OpenAlex

BACKGROUND: Prolonged invasive ventilation is common in patients with severe brain injury. Information on optimal management of extubation and on the use of tracheostomy in these patients is scarce. International guidelines regarding the ventilator liberation and tracheostomy are currently lacking. METHODS: The aim of 'Extubation strategies in Neuro-Intensive care unit patients and associations with Outcomes' (ENIO) study is to describe current management of weaning from invasive ventilation, focusing on decisions on timing of tracheal extubation and tracheostomy in intensive care unit (ICU) patients with brain injury. We conducted a prospective, international, multi-centre observational study enrolling patients with various types of brain injury, including trauma, stroke, and subarachnoid haemorrhage, with an initial Glasgow Coma Score equal or less than 12, and a duration of invasive ventilation longer than 24 hours from ICU admission. ENIO is expected to include at least 1,500 patients worldwide. The primary endpoint of the ENIO study is extubation success in the 48 hours following endotracheal tube removal. The primary objective is to validate a score predictive of extubation success. To accomplish this, the study population will be randomly divided to a development cohort (2/3 of the included patients) and a validation cohort (the remaining 1/3). Secondary objectives are: to determine the incidence of extubation success rate according to various time-frames (within 96 hours, >96 hours after extubation); to validate (existing) prediction scores for successful extubation according to various time-frames and definitions (i.e., tracheostomy as extubation failure); and to describe the current practices of extubation and tracheostomy, and their associations. DISCUSSION: ENIO will be the largest prospective observational study of ventilator liberation and tracheostomy practices in patients with severe brain injury undergoing invasive mechanical ventilation, providing a validated predictive score of successful extubation. TRIAL REGISTRATION: The ENIO study is registered in the Clinical Trials database: NCT03400904.

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)0.004
metaresearch head score (Gemma)0.008
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 score0.004
Threshold uncertainty score0.020

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.008
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.191
GPT teacher head0.381
Teacher spread0.190 · 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

Citations18
Published2020
Admission routes1
Has abstractyes

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