Factors Affecting Hemodialysis Adequacy in Cohort of Iranian Patient with End Stage Renal Disease
Bibliographic record
Abstract
BACKGROUND: There are many factors that can affect dialysis adequacy; such as the type of vascular access, filter type, device used, and the dose, and rout of erythropoietin stimulation agents (ESA) used. The aim of this study was investigating factors affecting Hemodialysis adequacy in cohort of Iranian patient with end stage renal disease (ESRD). METHODS: This is a cross-sectional study conducted on 133 Hemodialysis patients referred to two dialysis units in Sistan-Baluchistan province in the cities of Zabol and Iranshahr, Iran. We have looked at, (the effects of the type of vascular access, the filter type, the device used, and the dose, route of delivery, and the type of ESA used) on Hemodialysis adequacy. Dialysis adequacy was calculated using kt/v formula, two-part information questionnaire including demographic data which also including access type, filter type, device used for hemodialysis (HD), type of Eprex injection, route of administration, blood groups and hemoglobin response to ESA were utilized. The data was analyzed using the SPSS v16 statistical software. Descriptive statistical methods, Mann-Whitney statistical test, and multiple regressions were used when applicable. RESULTS: The range of calculated dialysis adequacy is 0.28 to 2.39 (units of adequacy of dialysis). 76.7% of patients are being dialyzed via AVF and 23.3% of patients used central venous catheters (CVC). There was no statistical significant difference between dialysis adequacy, vascular access type, device used for HD (Fresenius and B. Braun), and the filter used for HD (p> 0.05). However, a significant difference was observed between the adequacy of dialysis and Eprex injection and patients' time of dialysis (p <0.05). CONCLUSION: Subcutaneous ESA (Eprex) injection and dialysis shift (being dialyzed in the morning) can have positive impact on dialysis adequacy. Patients should be educated on the facts that the type of device used for HD and the vascular access used has no significant effects on dialysis adequacy.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.000 |
| 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".