Bibliographic record
Abstract
High frequency oscillatory ventilation (HFOV) is an unconventional form of mechanical ventilation which has been used for the past two decades in the neonatal intensive care unit for respiratory distress syndrome. Recognition of HFOV's lung protective properties combined with sound physiologic evidence of its ability to open and recruit the lung, have led to translation of HFOV to the adult ICU, for patients with the Acute Respiratory Distress Syndrome (ARDS). Initially HFOV was employed as a rescue therapy for severe ARDS cases with end-stage oxygenation failure. More recently, however, HFOV has been successfully employed as a ventilation approach earlier and earlier in the course of ARDS among diverse patient populations including burn patients. Currently, very little has been reported on the use of HFOV after inhalation injury, aside from one animal experiment,1 a pediatric case report,2 and data (unpublished) from 19 adult burn and inhalation injury patients treated with HFOV at our institution.3 Therefore, at the present time (and for the purposes of this discussion), HFOV must primarily be viewed within the context of its use as a rescue ventilation strategy in ARDS, to which smoke inhalation injury patients are obviously prone. Consideration of HFOV after smoke inhalation outside the scenario of severe ARDS, for example, as a mode of ventilation for early acute lung injury (ALI), or immediately after injury, may be somewhat premature. Nevertheless, there are distinct and potentially fruitful research questions surrounding HFOV and its role among thermally injured patients with smoke inhalation, which will be explored in this section.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".