Opinions of cardiologists on class II recommendations in current European Society of Cardiology 2018-2020 guidelines: YELLOW BOX
Bibliographic record
Abstract
Objectives: We planned our survey study to evaluate the opinion of cardiologists about the class II recommendations on levels of evidence in the current European Society of Cardiology Guidelines (ESC). Our aim is to determine which diagnosis or treatment option most prefer by cardiologist when guidelines do not make clear recommendations. Methods: The survey was conducted on September 2020 with the participation of cardiologists (n = 102). Our survey covers ESC's guidelines published in 2018-2020 on diagnosis and treatment strategies in coronary artery disease, diabetes, heart valve disease, arrhythmia, dyslipidemia and heart failure. Our survey consisting of 40 questions was shared with the cardiologists via e-mail. Results: Participants answered all of the survey questions. The majority of the participants (79.41%) did not consider the addition of a second long-term antithrombotic medication in addition to aspirin for secondary prevention in diabetes mellitus (DM) and coronary artery disease (CAD) patients who are not at high risk of bleeding. The lowest low density lipoprotein (LDL) value achieved by the participant physicians with treatment in their practices was < 40 mg/dl in 32 (31.37%) participants . One of the striking results of the survey was that 51.96% of the participants stated that it was not possible to measure the lipoprotein a (Lp(a)) level in the center where they were carrying out their practices, and 34.31% did not consider the Lp(a) level in the treatment of dyslipidemia in terms of directing the treatment. As for patients with asymptomatic Wolff-Parkinson-White (WPW) syndrome, 58.82% of the participants considered catheter ablation therapy. Conclusions: Although there were different opinions on some recommendations, the participants were mostly in agreement. We think that these survey results, which were mostly based on expert opinions, may contribute to the guidelines to be published in the future with the increase of survey studies on these issues.
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 | 0.012 | 0.039 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.002 | 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".