Critical Appraisal of the Clinical Practice Guidelines for the Management of Dyslipidaemias: Lipid Modification to Reduce Cardiovascular Risk: European Society of Cardiology (ESC) and European Atherosclerosis Society (ESC/EAS) 2019 Guidelines
Bibliographic record
Abstract
Abstract Objective The aim of the study was to assess the quality of the recently published European clinical practice guidelines for the management of dyslipidaemias, utilizing the refined Appraisal of Guidelines for Research & Evaluation tool. Method The 2019 European Society of Cardiology and European Atherosclerosis Society Guidelines for the management of dyslipidaemias: lipid modification to reduce cardiovascular risk was appraised and scored for methodological rigour and transparency by 5 independent appraisers using a validated tool. Key findings The guideline scored highest in the domains that evaluated editorial independence (100%) and clarity of presentation (98.6%) and lowest in the domains that addressed stakeholder involvement (55.56%) and rigour of development (63%). Overall the quality of the guideline was high, and all reviewers recommended its use in practice. Conclusion The guideline’s overall quality was judged to be high, and all appraisers recommended its use in practice without modifications.
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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 | 0.326 | 0.666 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.005 | 0.007 |
| Bibliometrics | 0.018 | 0.011 |
| Science and technology studies | 0.004 | 0.005 |
| Scholarly communication | 0.009 | 0.004 |
| Open science | 0.006 | 0.004 |
| Research integrity | 0.007 | 0.009 |
| Insufficient payload (model declined to judge) | 0.003 | 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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".