Результати опитування «Оцінювання етацизину для гострого та хронічного лікування фібриляції передсердь у реальній практиці: українське національне опитування (ETERNITY)»
Bibliographic record
Abstract
The aim of the study: based on a survey of physicians, the study aims to identify the real clinical practices regarding the use of class IC antiarrhythmic drugs in Ukraine, particularly ethacizine, for restoring sinus rhythm in paroxysmal and persistent forms of atrial fibrillation, employing a methodology similar to the “pill-in-the-pocket” approach. Materials and methods. Data were analysed from 100 anonymous voluntary questionnaires. We used snowball sampling to collect the responses. Participants had the option to skip questions, and calculations were based on the number of respondents who answered each question. Results. More than half of the respondents actively prescribe class IC antiarrhythmic drugs (AADs), with ethacizine being the most commonly prescribed (56.8 % of respondents). Notably, 61.4 % of respondents had never prescribed flecainide, 34.3 % had never prescribed propafenone, and 18.6 % had never prescribed ethacizine. The primary indication for prescribing class IC AADs was atrial fibrillation (AF) (43.3 %), followed by the combination of ventricular and supraventricular rhythm disturbances (34.4 %). Only 13.8 % of respondents initiate therapy with class IC AADs exclusively in inpatient settings, while 31.9 % primarily did so in outpatient settings with ECG monitoring. More than half of the respondents reported experience restoring sinus rhythm (SR) in AF with ethacizine using a regimen similar to “pill-in-the-pocket”; over a quarter of these cases were decisions made by patients already on ethacizine for SR maintenance. More than a quarter of respondents had experience using ethacizine for the “acute treatment” of AF in single doses higher than the standard 100 mg (125 mg – 6.8 %; 150 mg – 20.3 %). At the same time, 31.9 % of respondents prescribed ethacizine for SR restoration in AF as discrete regimens, prescribing low doses at shorter intervals (1–3 hours). Conclusions. The survey results indicate that class IC AADs, especially ethacizine, are actively prescribed in real clinical practice not only for arrhythmia prevention, including AF, but also for SR restoration. This underscores the need for high-quality clinical studies to assess the efficacy and safety of such treatment strategies for ethacizine, which remains less studied within class IC AADs.
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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 | 0.005 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.022 | 0.006 |
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".