Impact of Frequent Nocturnal Hemodialysis on Myocardial Mechanics and Cardiomyocyte Gene Expression
Bibliographic record
Abstract
BACKGROUND: Regression of left ventricular mass with nocturnal hemodialysis has been observed. The influence of nocturnal hemodialysis on myocardial mechanics and cardiomyocyte gene expression is unknown. METHODS AND RESULTS: Forty-two patients (30 male:12 female; age, 44 ± 12 years [mean ± SD]) with end-stage renal disease were followed for 3.1 ± 1.8 years before and after conversion to nocturnal hemodialysis and were compared with 29 normal subjects (18 male:11 female; age, 48 ± 13 years). Myocardial mechanics were assessed by 2-dimensional velocity vector imaging. Uremic plasma (10%) was added to cultures of neonatal Sprague-Dawley rat ventricular myocytes. Total RNA was isolated from cell cultures and subjected to differential gene expression profiling with specific interest in genes affecting apoptosis and fibrosis. Left ventricular mass index and left atrial volume index decreased from 122.6 ± 42.6 to 98.5 ± 34.9 g/m(2) (P<0.001) and 25.9 ± 9.1 to 22.5 ± 9.6 cm(3)/m(2) (P=0.005), respectively. Left ventricular apical circumferential strain and basal rotation improved after conversion to nocturnal hemodialysis and approximated normal values. Nocturnal hemodialysis increased sessional dialysis dose and lowered parathyroid hormone levels (from 51 ± 67 to 24 ± 37 pmol/L, P<0.05) and phosphate. Under conventional hemodialysis conditions, there was an upregulation of genes leading to apoptosis and fibrosis in cardiomyocytes. The change in left ventricle rotation was associated with the change in parathyroid hormone values (r=0.37, P=0.02) and to the change in left ventricle mass (r=0.31, P=0.046). CONCLUSIONS: Frequent hemodialysis is associated with improvement in myocardial mechanics and cardiac gene expression profile, which warrants prognostic validation.
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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 | 0.000 |
| 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".