Electrocardiographic Parameters Indicating Worse Evolution in Patients with Acquired Long QT Syndrome and Torsades de Pointes
Bibliographic record
Abstract
BACKGROUND: Acquired long QT syndrome (a-LQTS) is associated with life-threatening ventricular arrhythmias, mainly torsades de pointes (TdP). ECG parameters predicting evolving into ventricular fibrillation (VF) are ill defined. AIMS: To determine ECG parameters preceding and during TdP associated with higher risk of developing VF. METHODS: We analyzed 151 episodes of TdP, recorded in 28 patients with a-LQTS (mean QTc 638 ms ± 57). RESULTS: All 28 patients had prolonged QT interval, (mean QTc 638 ms ± 57) ranging from 502 ms to 858 ms correcting by Bazett's formula. The mean TdP heart rate was 218 bpm ± 38 (mean cycle length of TdP 274 ± 47 ms). We classified TdPs episodes into "slower"-TdP (s-TdP) < 220 bpm (range from 145-220 bpm) observed in 81 (53.6%) episodes and "faster"-TdP (f-TdP) ≥ 220 bpm (ranged from 221-281 bpm) observed in 70 (46.4%) episodes. Among 151 episodes of TdP, 21 (13.9%) were unstable (converted into VF). Out of 81 episodes of "slower"-TdP only 2 (2.5%) episodes converted into VF. The mean coupling interval (CI) of the PVC initiating TdP was 510 ms ± 118, the pause-RR interval was 1147 ms ± 335, the prematurity index (PI) of PVC that initiated TdP was 0.45 ± 0.13. The mean cycle length variability of TdP (VRV-TdP) was 30.79 ms ± 19.7. U wave was observed in 86 episodes (56.9%), among that in 69 episodes, the U/T wave ratio was > 1. Macro T wave alternans was observed in 4 patients. The QT interval was not different in patients with VF(+) and VF(-) episodes, 633 ± 60 and 639 ± 57, respectively. CONCLUSIONS: Some electrocardiographic parameters can be helpful in determining the risk of TdP evolving into VF. The slower ventricular rate (< 220 bpm), the higher rate instability (VRV > 30 ms) and the short episodes < 20 beats could predict benign evolution.
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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 | 0.000 | 0.002 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".