International approaches to the prescription of long-term oxygen therapy
Bibliographic record
Abstract
While there is broad agreement about who should receive long-term oxygen therapy (LTOT), there is little information available on how clinicians should decide on the oxygen prescription itself, at rest, during sleep and during exercise. The authors describe the results of an international survey that was undertaken to compare how respirologists prescribed oxygen. A questionnaire was sent to 100 respirologists in each of seven countries. The questionnaire identified whether resting flow rates were derived in a standard manner or by individualized patient testing. Test targets were ascertained for rest, exercise and sleep, as was the percentage of time that each test target had to reach for the test to be accepted. The majority of respondents individualized the oxygen prescription at rest (81%). Resting arterial oxygen saturation (Sa,O2) was most commonly targeted at 90-91%. The approach to night prescription varied (p<0.001). Respirologists in Canada and the USA increased the resting Sa,O2 by 1-2 L x min(-1) during sleep, while those in Spain used the resting (awake) flow for the night prescription (62%). Respirologists in the Netherlands, France, and Italy individualized the night prescription more frequently. Although oxygen during exercise was individualized in most countries (74%), significant differences remained among countries (p<0.001). The majority of respirologists (62%) aimed to achieve an Sa,O2 of 90-91% during exercise, while 70% of all respirologists tried to achieve the desired Sa,O2 for 90% of the test. There were substantial differences among countries as to how the oxygen prescription was written. This survey highlights the need for multicentre studies that improve the effectiveness of long-term oxygen therapy utilization.
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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 | 0.012 | 0.022 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".