HealthSWEDE: costs with sublingual immunotherapy—a Swedish questionnaire study
Bibliographic record
Abstract
BACKGROUND: The aim of this cross-sectional survey was to compare the health-economic consequences for allergic rhinitis (AR) patients treated with sublingual Immunotherapy (SLIT) in terms of direct and indirect costs with a reference population of patients receiving standard of care pharmacological therapy. METHODS: Primary objective was to analyse the health-economic consequences of SLIT for grass pollen allergy in Sweden vs reference group waiting for subcutaneous immunotherapy (SCIT). A questionnaire was mailed to two groups of AR patients. RESULTS: The questionnaire was distributed to 548 patients, 307 with SLIT and 241 in reference group (waiting for SCIT). Response rate was 53.8%. Mean annual costs were higher for reference patients than SLIT group; € 3907 (SD 4268) vs € 2084 (SD 1623) p < 0.001. Mean annual direct cost was higher for SLIT-patients, € 1191 (SD 465) than for reference, € 751 (SD 589) p < 0.001. Mean annual indirect costs for combined absenteeism and presenteeism were lower for patients treated with SLIT, € 912 (SD 1530), than for reference, € 3346 (SD 4120) p < 0.001, with presenteeism as main driver. CONCLUSIONS: SLIT seems to be a cost-beneficial way to treat seasonal AR. This information might be used to guide future recommendations.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".