National health expenditure per capita is associated with CRT implantation practice: findings from the ESC CRT Survey II with 11 088 patients
Bibliographic record
Abstract
AIMS: Cardiac resynchronization therapy (CRT) reduces morbidity and mortality in selected patients with heart failure (HF) and electrical dyssynchrony. This treatment receives class IA recommendations in European Society of Cardiology (ESC) guidelines. However, despite these strong recommendations, CRT implantation practice varies greatly in Europe. The purpose of the sub-analysis of CRT Survey II data was to describe how countries' health per capita expenditure affects CRT implantation practice. METHODS AND RESULTS: Between 2015 and 2016, two ESC associations, European Heart Rhythm Association and Heart Failure Association, conducted the CRT Survey II, a survey of CRT implantations in 11 088 patients in 42 ESC member states. We analysed CRT patient selection and guideline adherence in those countries according to high or low health expenditure per capita. There were 21 high health expenditure countries (n = 6844 patients) and 21 (n = 3852) with low health expenditure. The countries with the lowest health expenditure were more likely to implant CRT in patients who had strong guideline recommendations for implantation, younger patients and those recently hospitalized for HF or with symptomatic HF (67% vs. 58%, P < 0.001). The ratio of CRT-Pacemaker (CRT-P) to CRT-Defibrillator (CRT-D) was similar in both spending groups, as was the percentage of CRT implantation in women. CONCLUSION: CRT Survey II has demonstrated a non-uniform delivery of healthcare. Countries with low health expenditure per capita appear to be reserving CRT therapy for younger patients, those with class IA indication and patients with more severe symptoms of heart failure.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".