The Role of Primary Care in Asthma Control and Severity
Bibliographic record
Abstract
Background: Asthma is a common chronic inflammatory disease of the airways affecting 3 millionCanadians. Primary Care Providers (PCPs) are integral to care coordination, enhanced through thedevelopment of a strong patient-PCP relationship with Continuity of Care (COC). A recent CIHI studynoted that 40% of Albertans do not have a COC model for primary care.Objectives: We aim to evaluate how primary care for adults with asthma impacts different measures ofcontrol.Methods: Prospective population-based recruitment of adults through various community venuesacross Alberta. Those who had self-reported asthma and were willing to participate completed a surveywhich included demographics, comorbidities, medication use (including biologics, allergy medications,steroids), Asthma Control Questionnaire (ACQ-5), Asthma Control Test (ACT), Quality of Life (QoL)measured through the mini-Asthma Quality of Life Questionnaire (mini-AQLQ) and health care utilization(including Emergency Department (ED) visits, hospitalizations and ICU stays for asthma).Results: Of the 1685 individuals approached, 61 (3.6%) reported having asthma, of which 47 lived inAlberta. Most (41, 87%) had a PCP, with 30 (64%) visiting their PCP at least twice a year. Uncontrolledasthma was noted in 21 (45%) with either the ACQ-5 or ACT. The mini-AQLQ indicated 5 (11%) withreduced QoL. Mean lifetime hospitalizations, lifetime Emergency Department (ED) visits, and ICU staysrelated to asthma were 1.52, 4.55 and 0.25 respectively. Further, mean hospitalizations and ED visits inthe past 12 months related to asthma were 0.05 and 0.30 respectively.Conclusions: Asthma control was poor in 21 (45%) surveyed individuals, suggesting sub-optimal asthmamanagement in Alberta. Knowledge of Primary Care Networks (PCNs) was low, while ED and hospitalusage was high.
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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 | 0.003 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 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".