Effects of hemodialysis on ventricular activation time in children with end‐stage renal disease
Bibliographic record
Abstract
Patients with end-stage renal disease are affected by cardiovascular complications, including disturbances of the heart intraventricular conduction. Body surface potential mapping is a non-invasive electrocardiographic detection method of initial disturbances in heart activation propagation. A goal of the study was to analyze the effects of single hemodialysis (HD) session on ventricular activation time (VAT) maps obtained from hemodialyzed children. The study group consisted of 13 hemodialyzed children (age: 6-18 years). The control group is composed of 26 healthy subjects. In each HD patient, 12-lead electrocardiogram and echocardiography examinations were performed. Isochrone heart maps, reflecting body surface distribution of VAT isolines, were recorded from an 87-electrode HPM-7100 system for body surface potential mapping, before (group B) and after HD session (group A). The distribution of isochrones and VAT values, as recorded in the HD patients, differed significantly from the reference VAT map for controls. The highest VAT maximal value was noted in group B (Me: 110 vs. 62 ms in the control group; P < 0.001), becoming significantly lower after HD session (Me: 98 ms for group A vs. 110 ms for group B; P < 0.001). Ventricular activation time maps, recorded before HD session, showed significant VAT delays with isochrone arrangement specific for the left bundle branch block. After HD session, VAT maps presented significant changes, suggesting a normalization process. Ventricular activation time maps in children with end-stage renal disease exhibited disturbances of intraventricular conduction within the left bundle branch block, undetectable on standard electrocardiogram. A single HD session resulted in VAT map improvement related to overall HD treatment duration.
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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 | 0.000 | 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 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".