Effects of daily hemodialysis on heart rate variability: results from the Frequent Hemodialysis Network (FHN) Daily Trial
Bibliographic record
Abstract
BACKGROUND: End-stage renal disease is associated with reduced heart rate variability (HRV), components of which generally are associated with advanced age, diabetes mellitus and left ventricular hypertrophy. We hypothesized that daily in-center hemodialysis (HD) would increase HRV. METHODS: The Frequent Hemodialysis Network (FHN) Daily Trial randomized 245 patients to receive 12 months of six versus three times per week in-center HD. Two hundred and seven patients had baseline Holter recordings. HRV measures were calculated from 24-h Holter electrocardiograms at both baseline and 12 months in 131 patients and included low-frequency power (LF, a measure of sympathetic modulation), high-frequency power (HF, a measure of parasympathetic modulation) and standard deviation (SD) of the R-R interval (SDNN, a measure of beat-to-beat variation). RESULTS: Baseline to Month 12 change in LF was augmented by 50% [95% confidence interval (95% CI) 6.1-112%, P =0.022] and LF + HF was augmented by 40% (95% CI 3.3-88.4%, P = 0.03) in patients assigned to daily hemodialysis (DHD) compared with conventional HD. Changes in HF and SDNN were similar between the randomized groups. The effects of DHD on LF were attenuated by advanced age and diabetes mellitus (predefined subgroups). Changes in HF (r = -0.20, P = 0.02) and SDNN (r = -0.18, P = 0.04) were inversely associated with changes in left ventricular mass (LVM). CONCLUSIONS: DHD increased the LF component of HRV. Reduction of LVM by DHD was associated with increased vagal modulation of heart rate (HF) and with increased beat-to-beat heart rate variation (SDNN), suggesting an important functional correlate to the structural effects of DHD on the heart in uremia.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".