Case Report Central Hypoventilation: A Case Study of Issues Associated with Travel Medicine and Respiratory Infection
Bibliographic record
Abstract
Copyright © 2015 Kam Lun Hon et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Aim. We presented the case of a child with central hypoventilation syndrome (CHS) to highlight issues that need to be considered in planning long-haul flight and problems that may arise during the flight. Case. The pediatric intensive care unit (PICU) received a child with central hypoventilation syndrome (Ondine’s curse) on nocturnal ventilatory support who travelled to Hong Kong on a make-a-wish journey. He was diagnosed with central hypoventilation and had been well managed in Canada. During a long-haul aviation travel, he developed respiratory symptoms anddesaturations.The child arrived inHongKong andhis respiratory symptoms persisted. He was taken to a PICU for management. The child remained well and investigations revealed no pathogen to account for his respiratory infection. He went on with his make-a-wish journey. Conclusions. Various issues of travel medicine such as equipment, airline arrangement, in-flight ventilatory support, travel insurance, and respiratory infection are explored anddiscussed. This case illustrates that long-haul air travel is possible for childrenwith respiratory compromise if anticipatory preparation is timely arranged. 1.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.006 | 0.002 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.007 | 0.006 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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.
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".