Evaluation of the Risk of Malignant Arrhythmia Through Electrocardiography Parameters in Patients with Urinary Stone Disease
Bibliographic record
Abstract
Introduction: With a lifetime frequency of 10-15% and a recurrence rate of up to 50% within 10 years, urinary stone disease is a major cause of comorbidity. Recently, it has become widely recognized that urinary system stone disease is not only limited to kidney stone development but is also linked to cardiovascular disease and various other illnesses. Malignant arrhythmias (sudden cardiac death and ventricular arrhythmias) are consequences of coronary artery disease. Despite numerous studies demonstrating that urinary system stone disease is a risk factor for coronary artery disease, no electrocardiographic parameters have been evaluated in this patient group This prospective observational study aims to assess ventricular repolarization parameters using electrocardiography, which are risk indicators for malignant arrhythmias in patients with urinary stones disease. Materials and Methods The study included patients diagnosed with urinary stone disease and healthy volunteers. All patients underwent 12-lead electrocardiography. The electrocardiographys were evaluated for QTc interval, QTc dispersion, T peak-end interval, and Tp-e/QTc, and compared with the control group. Results: When comparing the QTc interval, QTc dispersion, T peak-end interval, and Tp-e/QTc parameters between the patient and control groups, no statistically significant differences were found. Conclusion: Contrary to existing knowledge, this study found that malignant arrhythmias in patients with urinary stone disease were not significantly different from the normal population.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".