Cardiac autonomic function and vascular profile in subclinical hypothyroidism: Increased beat-to-beat QT variability
Bibliographic record
Abstract
Background: Patients with subclinical hypothyroidism (SH) may have higher incidence of coronary heart disease and autonomic dysfunction. Design of the Study: Prospective case control study. Aim and Objectives: To evaluate beat-to-beat QT variability and vascular stiffness in patients with SH compared to normal controls. Materials and Methods: We compared linear and nonlinear measures of cardiac repolarization liability using beat-to-beat QT intervals derived from the surface electrocardiogram during supine posture and vascular indices including pulse wave velocity and ankle-brachial index (ABI) during supine posture between female patients with SH and age- and sex-matched normal controls. Spectral analysis was done at very low frequency (LF) (0.003–0.04 Hz), Low frequency (LF) (0.04–0.15 Hz), and high frequency (HF) (0.15–0.4 Hz). The HF represents vagal regulation (parasympathetic) and LF represents both parasympathetic and sympathetic regulation. Results: We recruited 58 women with a mean age of 31.83 ± 8.9 years and 49 controls with mean age of 32.4 ± 9.9 years (P = NS). QT variability index (QTvi) was higher in cases compared to controls (P = 0.01). The ratio of LF/HF of R-R interval which is an index of sympathovagal tone was significantly more in cases compared to controls (P = 0.02). The difference in the left minus the right ABI was significant between cases and controls (P = 0.03). Conclusions: The cases had lower parasympathetic activity as compared to controls, and there was a predominance of sympathetic activity in cases. QTvi may be an important noninvasive tool in this group of patients to study the risk of cardiovascular mortality.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.002 | 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".