Rationale and Design of the EU-CERT-ICD Prospective Study: Comparative Effectiveness of Prophylactic ICD Implantation
Bibliographic record
Abstract
AIMS: The clinical effectiveness of primary prevention implantable cardioverter defibrillator (ICD) therapy is under debate. The EUropean Comparative Effectiveness Research to Assess the Use of Primary ProphylacTic Implantable Cardioverter Defibrillators (EU-CERT-ICD) aims to assess its current clinical value. METHODS AND RESULTS: The EU-CERT-ICD is a prospective investigator-initiated non-randomized, controlled, multicentre observational cohort study performed in 44 centres across 15 European Union countries. We will recruit 2250 patients with ischaemic or dilated cardiomyopathy and a guideline indication for primary prophylactic ICD implantation. This sample will include 1500 patients at their first ICD implantation and 750 patients who did not receive a primary prevention ICD despite having an indication for it (non-randomized control group). The primary endpoint is all-cause mortality; the co-primary endpoint in ICD patients is time to first appropriate shock. Secondary endpoints include sudden cardiac death, first inappropriate shock, any ICD shock, arrhythmogenic syncope, revision procedures, quality of life, and cost-effectiveness. At baseline (and prior to ICD implantation if applicable), all patients undergo 12-lead electrocardiogram (ECG) and Holter ECG analysis using multiple advanced methods for risk stratification as well as detailed documentation of clinical characteristics and laboratory values. Genetic biobanking is also organized. As of August 2018, baseline data of 2265 patients are complete. All subjects will be followed for up to 4.5 years. CONCLUSIONS: The EU-CERT-ICD study will provide a necessary update about clinical effectiveness of primary prophylactic ICD implantation. This study also aims for improved risk stratification and patient selection using clinical and ECG risk markers.
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 | 0.106 | 0.087 |
| Meta-epidemiology (narrow) | 0.005 | 0.003 |
| Meta-epidemiology (broad) | 0.005 | 0.003 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.002 | 0.006 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.005 | 0.003 |
| Research integrity | 0.006 | 0.004 |
| Insufficient payload (model declined to judge) | 0.013 | 0.005 |
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".