Association of abnormal electrocardiograph metrics with prolonged recovery time in incident hemodialysis patients
Bibliographic record
Abstract
BACKGROUND: Patients receiving intermittent hemodialysis have variable times of recovery to feeling better after dialysis. QT prolongation, a precursor to clinical and subclinical cardiovascular events, may contribute to delayed recovery time. We hypothesized that abnormal electrocardiographic parameters indicating perturbations in ventricular action are associated with longer recovery times thus impacting a patient-centered quality of life. METHODS: Among 242 incident in-center hemodialysis participants from the Predictors of Arrhythmic and Cardiovascular Risk in End Stage Renal Disease (PACE) study, corrected QT interval (QTc), QRST angle and heart rate variance were measured on non-dialysis days using a standard 5-min electrocardiograph recording. Left ventricular hypertrophy (LVH) was defined using the Cornell voltage product. Recovery time was ascertained during a phone interview with a standardized validated questionnaire. Associations between QTc, QRST angle, heart rate variance, and LVH and natural log-transformed recovery time were examined using linear regression adjusted for participant characteristics and electrolytes. RESULTS: Mean age was 55 (standard deviation 13) years, 55% were male, 72% were African American. Longer QTc interval was associated with increased recovery time (per 10 ms increase in QTc, recovery time increased by 6.2%; 95% confidence interval: 0.0-10.5). QRST angle, heart rate, heart rate variability and LVH were not significantly associated with recovery time. CONCLUSION: Longer QTc intervals are associated with longer recovery time independent of serum electrolytes. This supports a relationship between a patient's underlying arrhythmic status and time to recovery after hemodialysis. Future studies will determine if maneuvers to reduce QTc improves recovery time and quality of life of patients on hemodialysis.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".