Évaluation de l’application des lignes directrices de dyslipidémie de la Société canadienne de cardiologie publiées en 2021 quant au dosage de la lipoprotéine (a) au CHUS en 2021
Bibliographic record
Abstract
Introduction: On March 26, 2021, the Canadian Cardiovascular Society (CCS) updated its dyslipidemia guidelines, recommending lipoprotein (a) measurement once in a patient’s lifetime, with the aim of enabling better cardiovascular risk assessment. It would therefore be interesting to determine the impact of this new recommendation on lipoprotein (a) prescription habits of physicians in Canada. Methods: A single-center observational study was performed at the “Centre hospitalier universitaire de Sherbrooke (CHUS)”, and all patients with lipoprotein (a) measurements ordered from June 2020 to December 2021 were included. An interrupted time series analysis and a segmented linear regression were used in analyzing the data. To properly validate assumptions, a logarithmic transformation was applied to the number of lipoprotein (a) measurements ordered per week. The primary endpoint was based on the slope change following March 26, 2021, regarding the number of lipoprotein (a) measurements ordered every week. Results: A total of 624 patients met our inclusion criteria. We observed an upward prepublication slope of 1.01 (95% CI: 0.99-1.02) and an upward slope of 1.03 (95% CI: 1.01-1.05) after publication. The slope difference between these two periods was statistically significant (p = 0.0014). Conclusion: The 2021 CCS’ updated guidelines on the management of dyslipidemia have influenced lipoprotein (a) prescription habits of physicians at the CHUS in 2021.
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.
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 | 0.025 | 0.042 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".