Associations of serum and dialysate electrolytes with QT interval and prolongation in incident hemodialysis: the Predictors of Arrhythmic and Cardiovascular Risk in End-Stage Renal Disease (PACE) study
Bibliographic record
Abstract
BACKGROUND: Prolonged QT interval in hemodialysis patients may be associated with sudden cardiac death, however, few studies examined the longitudinal associations of modifiable factors such as serum and dialysate concentrations of calcium, potassium, and magnesium with corrected QT (QTc) prolongation in incident hemodialysis patients. METHODS: In 330 in-center hemodialysis participants from the PACE study who were followed up for one year, we examined the associations of predialysis serum electrolytes (total calcium [Ca], corrected Ca [cCa], ionized Ca [iCa], potassium [K], magnesium [Mg]), dialysate (dCa and dK), and serum-to-dialysate gradient measures with QTc interval and prolongation (≥460 ms in women and ≥ 450 ms in men). RESULTS: At the first study visit, 47% had QTc prolongation. Lower iCa and K were associated with longer QTc interval independent of potential confounders (QTc difference = 8.55[95% CI: 2.13, 14.97] ms for iCa; QTc difference = 9.89[1.58, 18.20] ms for K). Lower iCa was also associated with a higher risk of QTc prolongation. At 1 year of follow-up, 31% had persistent QTc prolongation. In longitudinal analyses, the associations of iCa and K with QTc interval remained significant, and lower K was associated with a higher risk of QTc prolongation while the association of iCa with QTc prolongation was borderline statistically significant. Serum Mg, dCa or dK, and respective gradients were not associated with QTc interval or prolongation. CONCLUSION: Prolonged QTc is very common in incident hemodialysis participants and persists over follow-up. Ionized Ca and K are consistently inversely associated with QTc prolongation, which suggests closer monitoring for a low calcium or potassium level to mitigate risk.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".