Bibliographic record
Abstract
Patients with chronic obstructive pulmonary disease (COPD) are prone to acute respiratory exacerbations, which can develop suddenly or subacutely over the course of several days. Exacerbations have a detrimental effect on patients' health status and increase the burden on the healthcare system. Initial treatment is unsuccessful in 24-27% of patients, who have a relapse or a second exacerbation within 30 days of the initial event. No obvious benefit has been seen in recent clinical trials of anti-tumour necrosis factor therapy, anti-leukotriene therapy, intensive chest physiotherapy, or early inpatient pulmonary rehabilitation for treatment of exacerbations. By contrast, clinical trials of prevention rather than acute treatment have shown promising results. Long acting β agonist (LABA) or long acting anti-muscarinic (LAMA) bronchodilators and inhaled corticosteroid-LABA combinations prevent exacerbations in patients at risk, with relative risk reductions averaging 14-27% for each of these drugs relative to placebo. Triple therapy with inhaled corticosteroid-LABA plus LAMA may provide additional benefit, although study results to date are heterogeneous and more studies are needed. Pneumonia is an important complication of treatment with inhaled corticosteroid-LABA products, and the risk of pneumonia seems to be doubled in patients with COPD who use fluticasone. The addition of azithromycin to usual COPD therapy prevents exacerbations, although it may prolong the Q-T interval and increase the risk of death from cardiovascular disease in patients prone to arrhythmia. New potential drugs--including mitogen activated protein kinase inhibitors, phosphodiesterase 3 inhibitors, and monoclonal antibodies to the interleukin 1 receptor--offer additional hope for treatments that may prevent exacerbations in the future.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".