Longer daily oxygen use associates with more adverse events, symptoms, and worse health status in long-term oxygen therapy
Bibliographic record
Abstract
Introduction Use of long-term oxygen therapy (LTOT) for more than 15 h per day does not reduce mortality or hospitalizations, but may increase the risk of adverse events. We evaluated the relationship between daily oxygen use duration and adverse events, symptoms, and health status in patients on LTOT. Methods This was a cross-sectional survey study of a random sample ( N = 650) of adults with ongoing LTOT in Sweden. Oxygen use (h/day) was reported, and associations were analyzed with adverse events, symptom severities (revised Edmonton Symptom Assessment System), sleep duration and quality, and health status (COPD assessment test [CAT]). Results In total, surveys from 204 patients were analyzed; 60% female, mean age 75.3 (SD 8.7) years. Swedevox baseline characteristics were similar between sampled respondents and non-respondents. Patients reporting 24 h of daily oxygen use (53.4%) also reported a higher number of total adverse events, higher ratings of dyspnea, depression and anxiety, and worse health status, compared to those reporting fewer hours of oxygen use. A longer daily duration of oxygen use also associated with a higher number of experienced adverse events, higher ratings of dyspnea and anxiety, and worse rated health status in crude and adjusted linear regression models. No associations were seen between oxygen use duration and sleep quality or duration. Conclusion More adverse events, a higher severity of some symptoms, and worse health status are seen among patients with a longer daily duration of oxygen use. Further research is needed to establish evidence of causality.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".