Utility of a Simplified Lidocaine and Potassium Infusion in Diagnosing Long QT Syndrome among Patients with Borderline QTc Interval Prolongation
Bibliographic record
Abstract
BACKGROUND: Congenital long QT syndrome (LQTS) is caused by mutations in the cardiac Na+ or K+ channels that result in a prolonged QTc interval and increased QT dispersion. Na+ channel blockers and K+ can reverse the repolarization abnormalities in the Na+ channel variant (LQT3) and K+ channel variant (LQT1, LQT2), respectively. The phenotype of LQTS can be difficult to recognize, especially when the QTc interval is mildly prolonged. Additional noninvasive testing methods are needed to enhance the diagnosis of LQTS. This study compared the response of the QTc interval and QT dispersion to a sequential lidocaine/K+ infusion in LQTS patients with borderline QTc interval prolongation and control patients as a means of diagnosing LQTS. METHODS: In this study, eight LQTS patients with borderline QTc, defined as QTc < 470 ms, and 10 healthy controls received sequential lidocaine/K+ infusion. RESULTS: At baseline, LQTS patients had a longer QTc (446 +/- 29 vs 416 +/- 28 ms, P < 0.05) but similar QT dispersion (43 +/- 14 vs 29 +/- 10 ms) compared to controls. After lidocaine administration, baseline QTc and QT dispersion did not change in either LQTS or controls. One LQTS patient had a 54 ms (12%) reduction in his QTc but no change in QT dispersion. Following K+ infusion, baseline QTc and QT dispersion decreased by 9% (P < 0.005) and 45% (P < 0.005), respectively in LQTS. No effect was seen in control patients, where QTc and QT dispersion shortened by 1% (5 +/- 14 ms) and 20% (6 +/- 7 ms), respectively, compared to baseline. The combined lidocaine/K+ infusion had a sensitivity, specificity, and accuracy of 88%, 100%, and 94%, respectively, in diagnosing LQTS. CONCLUSIONS: A simplified sequential lidocaine/K+ challenge is accurate in diagnosing LQTS among patients with borderline QTc prolongation.
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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) | 0.001 | 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".