Patient perspectives on the use of oral corticosteroids in asthma
Bibliographic record
Abstract
OBJECTIVE: Oral corticosteroids (OCS) are used to treat uncontrolled asthma, either as short rescue courses of treatment for severe disease exacerbations, or as long-term maintenance therapy in addition to other controller medications. Although the adverse events (AEs) associated with OCS are well understood by healthcare professionals (HCPs), the patient's perspective may be underappreciated. This review discusses the patient perspective on OCS use. DATA SOURCES: A PubMed literature review was performed. STUDY SELECTION: Articles were selected to include those primarily containing data on patient perspectives on OCS use in asthma or other airway diseases, including qualitative and quantitative studies. Articles including only clinical data and those primarily focused on another indication were excluded. Additional articles meeting the criteria were permitted based on author knowledge and the bibliographies of systematic reviews on other topics. RESULTS: A total of 6066 articles were identified from the PubMed search; 111 were assessed more closely for eligibility. Fourteen articles were eventually selected by the reviewers for inclusion and confirmed by all authors. Several key themes were identified: (1) Key AEs were prominently reported by patients (including weight gain, skin thinning, known osteoporosis/osteopenia, and sleep/mood disturbances); (2) Impact of OCS on day-to-day lives; (3) Patient perceptions of OCS; (4) Effect of perceptions on treatment adherence. CONCLUSION: HCPs should consider the impact that OCS have on their patients' wellbeing, including short courses. It is essential for HCPs to discuss the short and long-term risks of OCS with patients prior to initiation of treatment and consider alternatives for patients on long-term OCS.
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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 | 0.040 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 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".