Bluetooth-Enabled Implantable Cardiac Monitors and Two-Way Smartphone Communication for Patients With Hypertrophic Cardiomyopathy
Bibliographic record
Abstract
Background: Sudden cardiac death (SCD) risk stratification in hypertrophic cardiomyopathy (HCM) currently relies on arrhythmic burden quantification by 24 or 48-hour Holter monitoring. Whether this approach adequately captures arrhythmic burden, compared with longer-term continuous monitoring, is unclear. We sought to assess the long-term incidence of nonsustained ventricular tachycardia (NSVT) in HCM patients at low or moderate SCD risk, using implantable cardiac monitors (ICMs) paired with a novel Bluetooth-enabled 2-way communication platform. Methods: This prospective, single-arm, observational study enrolled 33 HCM patients. Patients were implanted with an Abbott (Chicago, IL) Confirm Rx ICM and monitored using a protocolized care pathway. Results: A total of 20 patients (60.6%) had ≥ 1 episode of NSVT recorded on the ICM, the majority of whom had previous Holter monitors that did not identify NSVT (60%, n = 12). A total of 71 episodes of NSVT were detected. Median time to first NSVT detection was 76.5 days (range: 0-553 days). A total of 19 patients underwent primary prevention implantable cardioverter defibrillator implantation during an average follow-up of 544 days (range: 42-925 days). A total of 172,112 automatic transmissions were received, and 65 (0.04%) required clinical follow-up. A total of 325 manual transmissions were received and managed. A total of 14 manual transmissions (4.3%) required follow-up, whereas 311 (95.7%) were managed solely with a text message. Conclusions: Surveillance and reporting systems utilizing 2-way communication enabled by novel ICMs are feasible and allow remote management of patients with HCM. Prolonged monitoring with ICMs identified more patients with nonsustained arrythmias than did standard Holter monitoring. In many cases, this information impacted both SCD risk stratification and patient management.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.000 | 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 teacher head, 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".