136-81: Validation of a novel single lead heart rhythm monitor
Bibliographic record
Abstract
CardioSTAT TM is a new “patch-like” single lead heart rhythm monitor. Recording is made through 2 electrodes positioned in a lead 1- like configuration. In a previous study, we validated atrial fibrillation detection compared to 12-lead ECG. In this study, we sought to compare its performance to a standard 24h Holter for arrhythmia detection. Method/Results: Patients undergoing 24h Holter for control or suspicion of atrial fibrillation (AF) were included in the study. Recording of the standard holter was performed simultaneously with recording with CardioSTAT. The CardioSTAT can monitor up to one week in a continuous manner, however for the purpose of this study, only 24h recordings were performed. Analysis of the data was performed by an electrophysiology technician and interpreted in a blinded fashion by a cardiologist. Eighty-four monitoring were compared. AF was diagnosed in 30 patients and atrial flutter in 4 patients. Agreement between CardioSTAT and standard Holter was 95% for AF detection with kappa = 0.9 and 95 % for atrial flutter detection with kappa = 0.47. No significant difference in premature atrial and ventricular beat counts, (PAC 303 ± 1105 vs. 358 ± 1155, and PVC 733 ± 2338 vs. 651 ± 2154 for Holter vs CardioSTAT respectively), in mean, minimal and maximal heart rate (69 ± 11 vs. 6811; 48 ± 18 vs. 49 ± 13; 117 ± 31 vs 115 ± 29), longest RR interval (1.82 ± 0.5 vs. 1.82 ± 0.5 seconds) and AF burden (15% vs. 15%). Noise was recorded in 4.8% of Holter and 7.9% of CardioSTAT (p = 0.03). Concerning noise detection, modification of the device installation was performed after the first 43 patients. When analysing only patients 44 to 84, noise detection was 4.1 vs 4.45 (CardioSTAT vs Holter), p = ns Conclusion: Preliminary results for validation of a novel heart monitor device show excellent correlation with the standard Holter for detection of atrial fibrillation. Added value of CardioSTAT included the possibility of longer monitoring duration (up to 7 days), less cumbersome installation (2 electrodes and no wires) and water resistance (patient can shower with the device).
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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) | 0.000 | 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) | 0.000 | 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".