Exploring the Distribution of Prescription for Sulfonylureas in Patients with Type 2 Diabetes According to Cardiovascular Risk Factors Within a Canadian Primary Care Setting.
Bibliographic record
Abstract
BACKGROUND: A growing body of evidence generated from observational studies and meta-analyses has begun to illustrate the potential adverse cardiovascular (CV) risk profile associated with sulfonylurea (SU) use. Specifically, the use of an SU has been demonstrated to be associated with increased mortality and a higher risk of stroke with more CV events associated with SU use having been reported in subgroups of patients with a history of CV disease, elderly and a higher body mass index. OBJECTIVE: The objective of the current study was to explore the distribution of established atherosclerotic CV disease and CV risk factors amongst patients with diabetes on an SU using a Canadian primary care dataset for the 2013 calendar year. METHODS: The Canadian Primary Care Sentinel Surveillance Network (CPCSSN), which is a multi-disease surveillance system based on primary care electronic medical record data, was utilized for this research study. Patients with a diagnosis of diabetes and exposure to an SU were identified. Distribution/prevalence of CV risk profile amongst this sub-cohort was explored. RESULTS: In analyzing the CPCSSN database for the 2013 calendar year, 6150 patients were identified as having diabetes, at least one visit with their family doctor, and on an SU. For this sub-cohort, demographic data was as follows: age [mean (SD)] 65.4(12.8) years-old; 56.4% male and mean BMI 31.3(10.0). Established atherosclerotic CV disease was observed in 16.8% of the patients with the following distribution: 13.2% had ischemic heart disease/myocardial infarction or coronary artery disease; 2.4% had stroke; and 2.3% had peripheral vascular disease. Regarding the aggregation of CV risk factors, a large proportion (65%) of patients without established atherosclerotic CV disease presented with 2 or more CV risk factors including: hypertension (62%), dyslipidemia (33%), active smoking (13%), and obesity (43%). Almost half of the cohort (45%) were males older than 55 years of age or females older than 60 years of age with at least one of the following risk factors: dyslipidemia, hypertension or current smoking, but without established cardiovascular disease. A large proportion of patients (19.5%) had a diagnosis of cardiac-specific issues including ischemic heart disease/myocardial infarction/coronary artery disease, heart failure (not due to ischemic heart disease/myocardial infarction/coronary artery disease), or arrhythmia. Almost 82% of patients had either established atherosclerotic CV disease or 2 or more CV risk factors without established atherosclerotic CV disease. CONCLUSION: This study illustrated that in this dataset of Canadian patients with diabetes in a primary care setting, a substantial proportion of patients treated with an SU in 2013 had established CV disease and/or an aggregation of multiple CV risk factors. In light of recent data reporting on an association between SU utilization and CV events and increased mortality, pharmacovigilance programs should actively monitor SU utilization in patients with diabetes and a high risk CV profile in real world clinical settings.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.003 | 0.009 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.002 | 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".