An online international survey study into the incidence and potential reasons of therapy non-adherence in catecholaminergic polymorphic ventricular tachycardia: preliminary results
Bibliographic record
Abstract
Abstract Background Since the first description of catecholaminergic polymorphic ventricular tachycardia (CPVT), a rare inherited cardiac arrhythmia, effective medical therapy to prevent the arrhythmic events – syncope, sudden cardiac arrest, sudden cardiac death – have been described. However, a significant proportion of patients experience breakthrough events despite optimal medical therapy, which are regularly associated with therapy non-adherence. Purpose To investigate the incidence of and potential reasons for therapy non-adherence in a large cohort of patients with CPVT. Methods An online survey was created in Dutch, English, and French and shared with CPVT patients at the outpatient clinic, through peer-recruitment, and on social media from November 1, 2022 onwards. Self-reported non-adherence was measured using the validated Medication Adherence Rating Scale (MARS, contains five 5-Point Likert scale questions, non-adherence was defined as a score <22). The Beliefs about Medication Questionnaire (BMQ, eleven 5-Point Likert scale statements regarding concern and necessity of CPVT medication and eight 5-Point Likert scale questions regarding overuse and harm of medication in general) and Illness Perception Questionnaire (IPQ, statements rated with a scale from 0 to 10) were used to explore associations between patient beliefs and non-adherence. Results After three months, 85 patients had completed the survey, of whom 77 (91%) used medication (32 [42%] used a beta-blocker, 5 [6%] flecainide, and 40 [52%] beta-blocker and flecainide dual therapy). Of the patients using medication, current median age was 37 (interquartile range [IQR]: 26-55) years, 56 (73%) were female, and 15 (20%) suffered from syncope, aborted cardiac arrest or appropriate ICD shock after diagnosis. Ten (13%) of the patients were non-adherent. Clinical characteristics of non-adherent patients did not differ from adherent patients (Table). Non-adherent patients reported a significantly higher agreement with statements regarding concern about CPVT-related medication (17.5 [15.2-20.8] vs. 14.0 [12.0-18.0], p=0.039), specifically the statement about unpleasant adverse effects (4.0 [3.2-4.8] vs. 3.0 [2.0-4.0], p=0.008, Figure). The IPQ statements did not differ between non-adherent and adherent patients (Figure). Conclusion Preliminary data of this survey study shows that the rate of self-reported non-adherence is significant and is associated with concern regarding CPVT-related medication. This knowledge could assist in improving patient education aimed at therapy adherence. In addition, this preliminary data show that it is feasible and useful to study non-adherence in a CPVT population using online surveys.TableFigure
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".