Home Oxygen in Chronic Obstructive Pulmonary Disease
Bibliographic record
Abstract
Abstract Two landmark trials conducted more than 35 years ago provided scientific evidence that, under very specific circumstances, long-term oxygen therapy (LTOT) may prolong life. These two trials enrolled 290 patients with chronic obstructive pulmonary disease and severe daytime hypoxemia documented by direct arterial blood gas measurement. From that time, LTOT became a standard of care, and the indications for oxygen therapy expanded to include nocturnal oxygen therapy for isolated nocturnal oxygen desaturation, ambulatory oxygen to correct exercise-induced desaturation, and short-burst oxygen to relieve dyspnea. In most cases, the rationale for broadening the indications for oxygen therapy is that, if hypoxemia exists, correcting it by increasing the FiO2 should help. However, with the exception of LTOT in severely hypoxemic patients with chronic obstructive pulmonary disease, randomized controlled trials of oxygen therapy have failed to demonstrate clinically significant benefits. Also, adherence to LTOT is usually suboptimal. Important areas for future research include improving understanding of the mechanisms of action of supplemental oxygen, the clinical and biochemical predictors of responsiveness to LTOT, the methods for measuring and enhancing adherence to LTOT, and the cost-effectiveness of oxygen therapy. A standardization of terminology to describe the use of supplemental oxygen at home is provided.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".