Can Intensive Hemodialysis Prevent Loss of Functionality in the Elderly ESRD Patient?
Bibliographic record
Abstract
Initiation of dialysis may be accompanied by decline in physical and cognitive function and independence, especially in the elderly ESRD patient. Here, we postulate the underlying factors, which may contribute to this observation in the elderly dialysis population, such as increased risk of dialysis-induced hypotension and associated cerebral and cardiac events, as well as malnutrition, infections, sleep abnormalities, and psychological complications of dialysis initiation. We describe an elderly dialysis patient who did well on nocturnal home hemodialysis (HD), and we hypothesize how intensive HD (i.e., nocturnal HD and/or short daily HD) may reduce the incidence of these dialysis complications and may therefore be considered as an option to attempt to preserve functional status and quality of life, especially early after the transition from predialysis to dialysis. Before general adoption of this strategy, further studies on the etiology of functional loss at the time of dialysis initiation, as well as on the potential advantageous effects of intensive HD in the elderly ESRD patient as compared with conventional HD, peritoneal dialysis and kidney transplantation, are required.
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 | 0.000 | 0.002 |
| 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".