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Record W2883987324 · doi:10.1213/xaa.0000000000000838

The Role of ECMO in the “At-Risk” Tracheal Extubation: A Case Report

2018· article· en· W2883987324 on OpenAlexaff
Sarah Phipps, Jason G. Meisner, David E. Watton, Gemma Malpas, Orlando Hung

Bibliographic record

VenueA&A Practice · 2018
Typearticle
Languageen
FieldMedicine
TopicAirway Management and Intubation Techniques
Canadian institutionsDalhousie University
Fundersnot available
KeywordsMedicineExtracorporeal membrane oxygenationContext (archaeology)AirwayAirway managementAnesthesiaIntensive care medicineIntubationOxygenation

Abstract

fetched live from OpenAlex

Tracheal extubation requires careful planning and preparation. We present the extubation of a patient with severe ankylosing spondylitis after cervical spine surgery. We discuss the use of extracorporeal membrane oxygenation (ECMO) in this "at-risk" extubation, where our ability to oxygenate was uncertain and reintubation was predicted to be difficult. To our knowledge, ECMO has not previously been used in this context. We suggest preparing ECMO for rescue oxygenation when all other fundamental oxygenation techniques are predicted to be difficult or impossible. ECMO could be included in airway management and extubation guidelines.

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)0.001
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: Case report · Consensus signal: Case report
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.012
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.006
Meta-epidemiology (narrow)0.0030.001
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0030.002
Science and technology studies0.0050.002
Scholarly communication0.0030.004
Open science0.0020.003
Research integrity0.0120.006
Insufficient payload (model declined to judge)0.0020.001

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 head0.016
GPT teacher head0.336
Teacher spread0.320 · 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 designCase report
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

Citations1
Published2018
Admission routes1
Has abstractyes

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