Short Daily Dialysis (SDHD) Efficacy : Pilot Multicentric Study with Nine Patients from Madrid
Bibliographic record
Abstract
Interest in quotidian (daily) hemodialysis (HD) seems to be growing. Clinical data consistently showed improved quality of life, better control of blood pressure, less need for medications including erythropoietin (EPO) and better nutrition. We evaluate the SDHD efficacy in 9 patients in conventional HD (3 weekly sesions/4 hours), mean age 57,78 years range (33–75), 6 males and 3 females who needed increased dialysis efficiency by different medical indications: 5 cases with hypertensive miocardiopathy and severe LVH, 2 of them with EFLV 26% and 27%. 2 cases with ischemic cardiopathy symptoms, one of them with anger and restless dysnea with a non resvascularizable coronary lesion, and other with cardiac insufficiency episodes requiring hospitalization once a month. 1 patient with big body surface area and elevated phosphorus levels although without control, with conventional three times/week HD. 1 patient indication was made by 12 years on HD with multiple vascular accesses failed needing a Tessio cathéter being into infradialysis regimen for his malnutrition status.The schedule in all of them was 6 days per week sessions between 2.15 hrs till 3 hours depending of body surface area to obtain a weekly kt/v nearest to 4. HD session were realized in the Hospital (4 pts) or in satellite unit (5 pts) due to the characteristics of the patients. The time remaining in this schedule was between 5 months to 2 years and 9 months. All the patients showed clinical improvement, subjective and objective, since the first weeks of starting SDHD. Sleep symptoms were the first to improve. All patients showing good coping with this HD alternative. Blood pressure levels were controlled without need for antihypertensive drugs, although the dry weight increased significantly in all cases. Albumin serum levels increased as nutrition parameter, controlling also the osteodystrophy and phosphorus. In a patient the EFLV was normalized from 6 months (26%–50%) improving in other. Two patients could be included in Tx waiting list. Again, anemia improved and decreasing EPO was required. No vascular access (autologous AVF) malfunction was detected in relation to daily procedure. Conclusion: Our pilot experience shows a clinical and biochemical improvement in the patients and quality of life as well. Prospective studies to demonstrate the financial benefits of these modalities are needed.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".