Determinants of Cardiac Autonomic Dysfunction in ESRD
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVES: Cardiovascular events are common in patients with ESRD. Whether sympathetic overactivity or vagal withdrawal contribute to cardiovascular events is unclear. We determined the general prevalence and clinical correlates of heart rate variability in patients on hemodialysis. DESIGN, SETTING, PARTICIPANTS, & MEASUREMENTS: We collected baseline information on demographics, clinical conditions, laboratory values, medications, physical performance, left ventricular mass (LVM), and 24-hour Holter monitoring on 239 subjects enrolled in the Frequent Hemodialysis Network Daily Trial. RESULTS: The mean R-R interval was 812 ± 217 ms. The SD of R-R intervals was 79.1 ± 40.3 ms. Spectral power analyses showed low-frequency (sympathetic modulation of heart rate) and high-frequency power (HF; vagal modulation of heart rate) to be 106.0 (interquartile range, 48.0 to 204 ms(2)) and 42.4 ms(2) (interquartile range, 29.4 to 56.3 ms(2)), respectively. LVM was inversely correlated with log HF (-0.02 [-0.0035; -0.0043]) and the R-R interval (-1.00 [-1.96; -0.032]). Physical performance was associated with mean R-R intervals (1.98 [0.09; 3.87]) and SD of R-R intervals (0.58 [0.049; 1.10]). After adjustment for age, race, ESRD vintage, diabetes, and physical performance, the relationship between log HF and LVM (per 10 g) remained significant (-0.025 [-0.042; -0.0085]). CONCLUSIONS: Holter findings in patients on hemodialysis are characterized by sympathetic overactivity and vagal withdrawal and are associated with higher LVM and impaired physical performance. Understanding the spectrum of autonomic heart rate modulation and its determinants could help to guide preventive and therapeutic strategies.
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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 | 0.003 |
| 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) | 0.001 | 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".