Static and Dynamic Pressure-Volume Curves Reflect Different Aspects of Respiratory System Mechanics in Experimental Acute Respiratory Distress Syndrome
Bibliographic record
Abstract
There is an increasing body of evidence that obstructive sleep apnea (OSA) affects systemic blood pressure and quality of life. The evidence linking OSA with other types of cardiovascular morbidity and mortality is not as strong. We review the current literature on the health impact, diagnosis, and treatment of OSA and provide a framework for evaluating levels of evidence in each of these areas, with the focus on high quality studies. Clinical prediction rules and unattended portable monitoring devices, such as digital oximeters, are inexpensive and have clinically useful likelihood ratios, sensitivity, and specificity, so they can be considered clinically useful in the evaluation of individuals suspected of having OSA. This approach has the potential to change the probability of disease in some patients to a level at which polysomnography is unnecessary. Recent randomized, placebo-controlled trials have indicated that treating OSA with continuous positive airway pressure im- proves quality of life, driving simulator performance, blood pressure, and sleepiness. The evidence in support of mandibular advancement is less strong, and surgical measures should be viewed as an option only after continuous positive airway pressure and mandibular advancement have been considered, given the paucity of evidence to support surgery. The quality of research done on the prognosis, diagnosis, and treatment of OSA has improved substantially in recent years. However, there remains a need for additional studies that evaluate ambulatory monitors and for larger randomized controlled trials of therapy with longer patient follow-up to verify the range of benefits that OSA patients can expect from the various treatment modalities.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".