Discrepancies between two lipid-lowering guidelines for CVD prevention in seemingly healthy individuals-case study Lebanon.
Bibliographic record
Abstract
BACKGROUND: In deciding on optimal interventions for cardiovascular disease (CVD) prevention, more than one set of guidelines are available. HYPOTHESIS: The aim of the study was to assess the agreement between the European Society of Cardiology (ESC) 2011 Guidelines for CVD Prevention and the Canadian Cardiovascular Society (CCS) 2009 Guidelines in recommending lipid lowering interventions in a seemingly healthy cohort of Lebanese persons. METHODS: A nationally representative cohort of Lebanon was identified according to the World Health Organization (WHO) Steps Criteria. From this cohort, a group of 283 adult individuals not known to have chronic illnesses was selected. Using the algorithms present in each guideline, lipid lowering recommendations for each individual were determined. Agreement between the two guideline recommendations was determined using the Kappa test. RESULTS: As per ESC, 3.9% of the participants required immediate drug therapy, 15.5% should be considered for drug therapy, and 80.1% required lifestyle intervention. As per the CCS, however, 19.4% required drug therapy. The overall level of agreement between the ESC and CCS for recommending lipid lowering was moderate (Kappa 0.77), and better in males (Kappa 0.82). In contrast, 37.5% of females recommended drug therapy as per the CCS guidelines would not be per the ESC guidelines (Kappa 0.63). CONCLUSIONS: Significant discrepancies exist in recommendations for lipid-lowering therapy between CCS and ESC guidelines when applied to Lebanese individuals, particularly for women. Local healthcare authorities and the WHO should attend to this issue in order to unify treatment approaches and limit disparities in care.
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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 | 0.007 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| 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".