Evaluation of Cardiovascular Risk Factor Control Among People with Diabetes in the Community Pharmacy Setting—A Descriptive Observational Study
Bibliographic record
Abstract
Background: In some countries, community pharmacists provide advanced services to people with diabetes that improve glycaemic control and cardiovascular risk. This study aims to describe the cardiovascular risk profile of people with diabetes attending community pharmacy in Ireland. Methods: Data collection for this descriptive, observational, cross-sectional study took place in 10 pharmacies, in four Irish counties between July 2018 and October 2019. Participants were aged ≥18 years, with type 1 or type 2 diabetes, attending a participating pharmacy and were dispensed oral diabetes medicines, insulin, or devices for monitoring glycaemic control. Participants were asked about their demographics, medical history, and cardiovascular risk factors. Current medications were identified from dispensing software. Results: Data were available for 106 participants; 70 (66.0%) were male and 36 (34.0%) were female. The median age was 66.0 [56.5: 72.0] years. Of these, 90 (84.9%) had type 2 diabetes. Hypertension and dyslipidaemia were reported by 60 (56.6%) and 59 (55.7%) participants, respectively. Twenty-one participants (19.8%) were current smokers, 31 (29.2%) followed no specific diet, and 44 (41.5%) did not undertake exercise. Oral diabetes medication was prescribed to 85 (80.2%) and insulin was prescribed to 29 (27.4%) participants. Where an antihypertensive was prescribed, 21 participants (19.8%) achieved the systolic blood pressure on-treatment goal of ≤130 mmHg and 34 (32.1%) achieved the diastolic blood pressure on-treatment goal of <80 mmHg. Conclusions: Study participants demonstrated a high rate of characteristics associated with increased cardiovascular risk, including non-achievement of target blood pressure, smoking, and lack of exercise. A community pharmacist-led intervention aimed at potentially improving cardiovascular risk factors in people with diabetes warrants further study in an Irish setting.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".