Rapid Device‐Detected Nonsustained Ventricular Tachycardia in the Risk Stratification of Hypertrophic Cardiomyopathy
Bibliographic record
Abstract
BACKGROUND: Nonsustained ventricular tachycardia (NSVT) detected by ambulatory Holter (Holter NSVT) is a major risk factor for sudden cardiac death in hypertrophic cardiomyopathy (HCM). We hypothesized that the prognostic utility of Holter NSVT in HCM would improve with prolonged monitoring and a higher heart rate cut-off for detection. METHODS: We enrolled 60 patients (44 ± 14 years) with HCM, who had a prophylactic implantable cardioverter defibrillator (ICD). Positive Holter NSVT (prior to implant) was defined as ≥3 beats at ≥120 beats per minute (bpm). We assessed the prevalence of rapid NSVT (RNSVT) detected by their ICD within 12 months of its implant, defined as 4-16 beats at ≥150-200 bpm. The primary outcome was appropriate ICD therapy (antitachycardia pacing and shocks) for sustained ventricular arrhythmia (VA). RESULTS: Holter NSVT was detected in 34 patients. RNSVT occurred in 21 (35%) patients of whom five did not have Holter NSVT. Over a median follow-up of 61 (interquartile range 29, 129) months after ICD implant, nine patients had VA. RNSVT, but not Holter NSVT, was significantly associated with VA (hazard ratio 6.2, 95% confidence interval [1.3-30], P = 0.01) by multivariable Cox regression analysis that included conventional risk factors. Receiver operating characteristic analysis for RNSVT (area under curve 0.80, P = 0.005) showed that the occurrence of ≥2 episodes of RNSVT discriminated patients for VA optimally (sensitivity 78%, specificity 84%, positive predictive value 47%, negative predictive value 96%). CONCLUSIONS: In this pilot study, RNSVT detected by continuous monitoring independently predicted VA in HCM and offered superior discrimination of VA risk compared to conventional risk factors, including Holter NSVT. Future studies are needed to validate these findings in a larger, unselected HCM cohort.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".