Are patients suffering from stable angina receiving optimal medical treatment?
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
There is good evidence for the use of antiplatelet, beta-blocker and lipid-lowering drugs in the treatment of ischaemic heart disease, but few data on how these medications are used in treating stable angina pectoris. We examined prescription profiles for a sample of patients aged > or =65 years with stable angina, to compare the profiles to local guidelines and to explore the determinants of these profiles, in a cross-sectional study. We identified 11 141 individuals from the Quebec provincial out-patient pharmaceutical database for the period 1 June 1996 to 31 May 1997, and examined the percentage of these patients with and without associated co-morbidities receiving antiplatelet, beta-blocker and lipid-lowering medications. We used hierarchical modelling to examine the role of patient and physician characteristics in explaining the variation in the use of these medications. Calcium-channel blockers were the class of anti-ischaemic drugs most prescribed (63%). Beta-blockers were prescribed in 52.1% of patients. Antiplatelet and lipid-lowering drugs were prescribed to 56.8% and 32.6%, respectively. Increasing age and female gender made patients less likely to be prescribed these treatments. General practitioners were less likely than cardiologists to prescribe beta-blockers and lipid-lowering drugs (OR 0.79, CI 95% 0.68-0.91 and OR 0.77, CI 95% 0.66-0.91, respectively). There is a general under-use of antiplatelet, beta-blocker and lipid-lowering medications in the treatment of stable angina pectoris patients, possibly leading to adverse patient outcomes.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.000 |
| 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 | 0.000 |
| 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 it