Agreement between patients' self‐report and physicians' prescriptions on cardiovascular drug exposure: the PGRx database experience
Bibliographic record
Abstract
PURPOSE: Patients' self-reported drug exposure is subjected to memory errors and different sources of bias. Utilization of prescription records is impaired with non-compliance and over-the-counter (OTC) drug utilization. This study compared patients' self-report (PS) to physician's prescriptions of cardiovascular drugs (CVDs). METHODS: The PGRx database is constituted by networks of specialized centers that recruited cases of 15 different diseases including myocardial infarction (MI) cases, and a network of general practitioners recruiting a pool of potential referents. For MI cases and referents, data on all drug utilization within the 2 years preceding the index date were obtained from PS and from physician's report of their prescriptions (PP). Patients' reports were obtained using a structured telephone interview complemented with an interview guide containing names of diseases and pictures of drug packages. Comparisons were made on exposure to each class of CVDs, for different time-windows, 2 months, 3-12 months and 13-24 months prior to the index date. RESULTS: The concordance between physician and patient report was assessed on 2702 patient-physician pairs. Agreement was excellent overall (kappa = 0.83, 95% confidence interval (CI): 0.81-0.85). Prevalences of exposure were very close between PS and PP for all classes of prescription CVDs. CONCLUSION: Using a standardized and systematic collection of information on drug exposure directly from patients appeared to provide similar information to using physician prescription records over a 2-year recall period.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".