Oscillation After Inhalation: High Frequency Oscillatory Ventilation in Burn Patients With the Acute Respiratory Distress Syndrome and Co-Existing Smoke Inhalation Injury
Bibliographic record
Abstract
The purpose of this study was to evaluate the effectiveness of, and complications associated with High Frequency Oscillatory Ventilation (HFOV) in burn patients with the Acute Respiratory Distress Syndrome (ARDS) who have had a smoke inhalation injury, and to compare with those without an inhalation injury. Burn patients with progressive oxygenation failure from ARDS while on conventional mechanical ventilation were placed on HFOV as a "rescue" ventilation modality. There were 19 patients with burn + inhalation injury and 30 patients with burn only. Burned patients with ARDS but without inhalation injury had significant temporal improvement in the oxygenation index from 27 +/- 8 on conventional mechanical ventilation to 17 +/- 6 within 48 hours of initiating HFOV. However, burned patients with ARDS and smoke inhalation injury did not achieve significant or even eventual improvements in oxygenation index with HFOV. There was also a trend towards higher rates of early HFOV failure and severe hypercapnia while on HFOV among the patients with inhalation injury. Delivery of nebulized bronchodilators, heparin and n-acetyl cysteine, normally mainstays of smoke inhalation therapy, was impossible during HFOV. The presence of a smoke inhalation injury appears to impair the response to HFOV when this ventilation modality is instituted for ARDS-related oxygenation failure. Severe hypercapnia tended to be more frequent during HFOV among patients with smoke inhalation. These findings, combined with the difficulties in delivery of nebulized medications during HFOV suggest that HFOV may not be the optimal "rescue" ventilation modality in cases of ARDS if there has been an inhalation injury.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".