How reliable are single day electrocardiogram measurements to detect excessive supraventricular ectopic activity?
Bibliographic record
Abstract
Abstract Background Excessive Supraventricular Activity (ESVEA) is widely recognized as a significant risk marker for incident atrial fibrillation, but the diagnostic reliability of ESVEA measured by 24-hour electrocardiogram (ECG) is unknown. Objectives To study the variability of ESVEA over 14 days using mobile cardiac telemetry (MCT). Methods We included US patients aged 17-100 years with ≥14 full days of ambulatory full-disclosure ECG using an MCT device during 2017, without atrial fibrillation during any of the recording days. ESVEA was defined as the presence of ≥720 premature atrial complexes and/or a ≥20 beat long supraventricular tachycardia, and calculated for each recording day. Results The study population consisted of 9,899 patients (median age 70 (interquartile range 59-77) years, 57% female). ESVEA was very common: 45% (n= 4,453) had ESVEA on at least one day. Of the patients with ESVEA, it occurred on one day only in 28% and on all registered days in 18%. The median number of ESVEA positive days was 4 (IQR 1-12). On the first monitoring day, 20% were ESVEA positive, resulting in a sensitivity of 44.64% and a negative predictive value of 68.84% of a single day measurement of ESVEA. Conclusions ESVEA occurs in almost half of an MCT population, but less than half of the patients with any occurrence of ESVEA are detected on the first monitored day. Reliable diagnosis of supraventricular ectopy requires longer monitoring durations.
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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 | 0.006 | 0.038 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".