A population-based study of the burden of severe asthma in Alberta, Canada
Bibliographic record
Abstract
RATIONALE A comprehensive understanding of the burden of illness and management strategies for severe asthma (SA), especially by disease control, is lacking in Canada.OBJECTIVES The objectives of this study were to describe treatments, exacerbation outcomes and healthcare resource utilization (HCRU) for patients with controlled and uncontrolled SA in Alberta, Canada.METHODS A retrospective cohort of SA patients 12+ years (April 1, 2011 to March 31, 2020) was identified from administrative health data, based on medication dispensed for controlling asthma symptoms, stratified by disease control at index. Treatment patterns were analyzed for incident SA patients. Annualized exacerbation incidence rate ratios (IRR) were estimated throughout follow-up and stratified by disease control at index. Asthma-specific HCRU and direct costs were calculated.RESULTS The study cohort included 74,134 patients (12.4% of eligible asthma patients) of whom 71,099 (95.5%) were classified as controlled and 3,035 (4.1%) as uncontrolled at index. Inhaled corticosteroid + long-acting beta agonist (ICS + LABA) was the most frequent first-line therapy among incident SA patients (n = 53,084), received by 42.7% of patients. A minority received >2 lines of therapy; few received triple therapy. The uncontrolled (at index) versus controlled (at index) cohort had a 5.5 times higher exacerbation rate (IRR: 5.5, 95% CI: 5.1–5.8; p < 0.001), higher HCRU, and higher associated annual costs (mean [SD]: $3,799 [$6,668] uncontrolled vs $1,339 [$2,515] controlled).CONCLUSIONS SA, whether controlled or uncontrolled at index, was associated with ongoing exacerbations and HCRU despite treatment intensification that identified patients as having SA. Some treatment patterns appeared misaligned with guidelines, suggesting potential need for better recognition of asthma severity and escalating therapies.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.006 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".