Characteristics of patients and implantable defibrillators associated with failure to sense device alert systems
Bibliographic record
Abstract
AIMS: In the era of increasing implantable cardioverter defibrillator (ICD) complexity, the ICD patient alert is deemed to be an important feature in the early detection of ICD system malfunction and is either an audible or a vibratory alert. We sought to evaluate the patient's ability to detect these ICD alerts in the device clinic setting as a surrogate endpoint of clinical utility. METHODS AND RESULTS: From 1 November 2006 to 31 March 2008, 563 patients with an ICD equipped with either an audible patient alert (APA, Medtronic and Guidant; n = 485) or a vibratory monitoring alert ([VMA, St Jude Medical; n = 78) had their alarm demonstrated in the quiet clinic setting. The ability to recognize the alert was analysed and then stratified by gender, age, manufacturer, type of alert, and pocket location. The average patient age was 63.3 (± 13.6) years and 82.8% of patients were male. Implantable cardioverter defibrillator manufacturers were Medtronic (n = 464), Boston Scientific (n = 21), and SJM (n = 78). The APA was heard in 86.0% of patients. This was less likely in patients who were older, male, and where the device was placed in the submuscular position. Every patient with a VMA sensed their alert. CONCLUSION: In the current ICD alert technology, the ability to sense the ICD alert in the device clinic appears to be higher for the VMA than for the APA. In particular, older patients and male patients are less likely to sense the APA.
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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 | 0.006 |
| 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".