Survival, ventricular arrhythmia, and implantable cardioverter‐defibrillator usefulness in toxic cardiomyopathy due to substance abuse
Bibliographic record
Abstract
BACKGROUND: Toxic dilated cardiomyopathy (T-DCM) due to substance abuse is now recognized as a potential cause of severe left ventricular dysfunction. The burden of ventricular arrhythmias (VA) and the role of a prophylactic implantable cardioverter-defibrillator (ICD) are not well documented in this population. We aim to assess the usefulness of ICD implantation in a T-DCM cohort. METHODS: Patients younger than 65 years with a left ventricular ejection fraction (LVEF) < 35% followed at a tertiary center heart failure (HF) clinic between January 2003 and August 2019 were screened for inclusion. The diagnosis of T-DCM was confirmed after excluding other etiologies, and substance abuse was established according to the DSM-5 criteria. The composite primary endpoints were arrhythmic syncope, sudden cardiac death (SCD), or death of unknown cause. The secondary endpoints were the occurrence of sustained VA and/or appropriate therapies in ICD carriers. RESULTS: Thirty-eight patients were identified, and an ICD was implanted in 19 (50%) of these patients, only one for secondary prevention. The primary outcome was similar between the two groups (ICD vs. non-ICD; p = 1.00). After a mean follow-up of 33 ± 36 months, only two VA episodes were reported in the ICD group. Three patients received inappropriate ICD therapies. One ICD implantation was complicated with cardiac tamponade. Twenty-three patients (61%) had an LVEF ≥35% at 12 months. CONCLUSION: VA are infrequent in the T-DCM population. The prophylactic ICD benefit was not observed in our cohort. The ideal timing for potential prophylactic ICD implantation in this population needs further studies.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".