Heart rate variability (HRV) in kidney failure: measurement and consequences of reduced HRV
Bibliographic record
Abstract
A common cause of death in end-stage renal disease (ESRD) patients on dialysis is sudden cardiac death (SCD). Compared to the general population, the percentage of cardiovascular deaths that are attributed to SCD is higher in patients treated by dialysis. While coronary artery disease (CAD) is the predominant cause of SCD in dialysis patients, reduced heart rate variability (HRV) may play a role in the higher risk of SCD among other risk factors. HRV refers to beat-to-beat alterations in heart rate as measured by periodic variation in the R-R interval. HRV provides a non-invasive method for investigating autonomic input into the heart. It quantifies the amount by which the R-R interval or heart rate changes from one cardiac cycle to the next. The autonomic nervous system transmits impulses from the central nervous system to peripheral organs and is responsible for controlling the heart rate, blood pressure and respiratory activity. In normal individuals, without cardiac disease, the heart rate has a high degree of beat-to-beat variability. HRV fluctuates with respiration: it increases with inspiration and decreases with expiration and is primarily mediated by parasympathetic activity. HRV has been used to evaluate and quantify the cardiac risk associated with a variety of conditions including cardiac disorders, stroke, multiple sclerosis and diabetes. In this narrative review, we will examine the association between HRV and SCD. This report explains the measurement of HRV and the consequences of reduced HRV in the general population and dialysis patients. Lastly, this review will outline the possible use of HRV as a clinical predictor for SCD in the dialysis population. The current understanding of SCD based on HRV findings among the ESRD population support the use of more aggressive treatment of CAD; greater use of angiotensin converting enzyme inhibitor (ACE-i)/angiotensin receptor blockers (ARBs) and beta-blockers and more frequent and/or nocturnal haemodialysis to improve the survival of a patient with kidney failure.
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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".