Videolaringoscopios Pentax-AWS y Glidescope como alternativa al laringoscopio Macintosh en la dificultad de intubación prevista
Bibliographic record
Abstract
La dificultad y la imposibilidad para la intubación orotraqueal (IOT) suponen la principal causa de morbilidad y mortalidad de causa anestésica. \n \nLos videolaringoscopios (VL) se han desarrollado para reducir la dificultad de intubación laríngea, consiguiendo la visualización glótica sin necesidad de alinear los ejes oral, faríngeo y laríngeo. \n \nEl Pentax-AWS R (Pentax Corporation, Tokio, Japan) es un VL con canal y pala desechable, mientras que el GlidescopeR (Saturn Biomedical System INC., Burnaby, Canada) es un VL rígido sin canal. \n \nAmbos han demostrado ser más efectivos que la laringoscopia directa (LD) realizada con el laringoscopio de Macintosh en la vía aérea normal, sobre la vía aérea difícil simulada y en paciente bajo inmovilización cervical, pero no se ha comprobado en pacientes con dificultad de intubación (DI) prevista. \n \nDeterminar en un estudio prospectivo y aleatorizado la eficacia de estos VL, utilizados por anestesistas con experiencia en el manejo de la vía aérea difícil (VAD) prevista y comparar su eficacia con la LD realizada con el laringoscopio de Macintosh.
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 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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".