The role of high frequency oscillatory ventilation in the management of children with severe traumatic brain injury and concomitant lung pathology
Bibliographic record
Abstract
OBJECTIVE: To report the use of high frequency oscillatory ventilation (HFOV) in two children with severe traumatic brain injury and concurrent lung pathology where conventional mechanical ventilation was ineffective. DESIGN: : Case report. SETTING: Regional intensive care unit in a pediatric teaching hospital. PATIENTS: Two severely head-injured children (both with postresuscitation Glasgow Coma Scores of 3), one of whom was age 11 yrs and developed an invasive fungal (rhizomucor) pneumonia, while the other age 5 yrs had bilateral lung contusions. Both were treated according to local head injury guidelines, which included conventional ventilation. Despite increasing conventional ventilatory support, CO2 removal became problematic in both cases, making the intracranial pressure control and consequent maintenance of adequate cerebral perfusion pressure difficult. In both patients, a dramatic reduction in intracranial pressure and improvement in cerebral perfusion pressure was observed soon after the use of HFOV. Additionally, inotropic support was weaned by 50% in both children after commencing HFOV. A significant increase in the mean arterial blood pressure occurred in one child with HFOV. INTERVENTION: Use of HFOV as an alternative to conventional mechanical ventilation. CONCLUSION: HFOV may have utility in the management of selected cases of severe brain trauma with concurrent lung pathology where conventional ventilation is ineffective.
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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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".