Chronic Peritoneal Dialysis in the Elderly: A Review
Bibliographic record
Abstract
During the past few decades, the pattern of end-stage renal disease has changed significantly with the emerging predominance of elderly patients. Because this heterogeneous population is characterized by a physiological decline in function of all organs, the nephrologist must contemplate the special needs of individual patients when they develop end-stage renal disease. Before the initiation of dialysis, these patients must be given detailed information to help them select the particular mode that will maximize their quality of life. According to available data, peritoneal dialysis offers some advantages for elderly patients, such as hemodynamic stability, steady-state metabolic control, good control of hypertension, independence from hospital, and avoidance of repeated vascular access. Early referral promotes the establishment of peritoneal access and minimizes the consequences of uremia, subsequent morbidity, and frequent hospitalization. Elderly patients are compliant and highly motivated to cooperate with their treatment. They have no higher modality-related complications than younger patients and their quality of life is satisfactory. Although most have comorbid conditions that interfere with self-performance of dialysis, such as impaired vision and reduced physical and mental activity, they can perform peritoneal dialysis successfully if they have a high level of family support. Patients who do not have family support may have successful peritoneal dialysis if they have access to a network of medical and social support, that is, private home nurses, rehabilitation and chronic care dialysis units, or nursing homes.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".