Cardiovascular Risk Reduction in the Workplace With CAMMPUS (Cardiovascular Assessment and Medication Management by Pharmacists at the UBC Site)
Bibliographic record
Abstract
BACKGROUND: Cardiovascular (CV) disease is a leading cause of death despite being largely preventable. Employers increasingly offer preventive health programs in the workplace, and pharmacists are well suited to provide these programs. OBJECTIVE: To evaluate the impact of a pharmacist-led service on CV risk in University of British Columbia (UBC) employees. METHODS: This was a prospective observational pre-and-post design study, with participants as their own controls. Employees >18 years of age in the UBC health plan with a Framingham Risk Score (FRS) ≥10% or ≥1 medication-modifiable CV risk factor were included. Participants received a baseline assessment, individualized consultation for 12 months, and a final assessment by a pharmacist at the UBC Pharmacists Clinic. The primary end point was FRS reduction. RESULTS: Baseline assessment of 512 participants between September 2015 and October 2016 yielded 207 (40%) participants, of whom 178 (86%) completed the 12-month intervention. Participants were 54% female and 55% Caucasian, with an average age of 51 (SD = 9.1) years. FRS at baseline was <10 in 45.8%, 10 to 19.9 in 37.9%, and ≥20 in 16.4% of participants. Over 12 months, significant reductions in average FRS (from 11.7 [SD = 7.7] to 10.7 [SD = 7.3]; P = 0.0017) and other parameters were observed. Significant improvements in quality of life (EQ5D change of 0.031 [95% CI = 0.001, 0.062] P = 0.023) and medication adherence (MMAS-8 change of 0.42 [ P = 0.019]) were also noted. CONCLUSIONS AND RELEVANCE: UBC employees had improvements in health markers, self-reported quality of life, and medication adherence after receiving a 12-month pharmacist-led intervention. Pharmacists are encouraged to provide CV risk reduction services in workplaces.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".