Effects of an alert system on implantable cardioverter defibrillator-related anxiety: rationale, design, and endpoints of the PANORAMIC multicentre trial
Bibliographic record
Abstract
AIMS: Implantable cardioverter defibrillators (ICD) can prevent sudden cardiac death by delivering high-energy shocks in patients at risk of life-threatening ventricular tachyarrhythmias. Patients may be anxious about receiving inappropriate shocks in case of device or lead system malfunction, or about failing to receive needed therapy for the same reason. New devices include programmable vibrating patient notifiers (PN), which, by warning patients of a possible device dysfunction, might lower device-related anxiety. PAtient NOtifier feature for Reduction of Anxiety: a Multicentre ICD study (PANORAMIC) is a multicentre, randomized, clinical trial designed to examine the effects of the awareness of an active vibrating alert system on device-related anxiety. METHODS: The trial will randomly assign 356 patients in a 1:1 design to a control group (PN OFF) vs. a treatment group (PN ON). Patients will be followed for 12 months, with visits scheduled at 6 and 12 months. During clinical follow-up visits, the ICD will be interrogated, and all patients will complete the Hospital Anxiety and Depression Scale and a device-related anxiety questionnaire. The sensitivity and specificity of PN, the effect of personality on anxiety, using the Type D scale (DS14), the number of delivered appropriate and inappropriate ICD therapies, changes in anxiety related to the delivery of appropriate or inappropriate shocks, crossovers from the assigned group, the number of hospitalizations, and the mortality rate will also be assessed. ClinicalTrials.gov Identifier: NCT00559559.
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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 | 0.014 | 0.017 |
| Meta-epidemiology (narrow) | 0.004 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.005 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.005 | 0.004 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".