Clinical use of high‐efficiency hemodialysis treatments: Long‐term assessment
Bibliographic record
Abstract
Significant technological changes in blood flow rate, dialyzer membrane permeability, bicarbonate dialysate, and ultrafiltration-controlled delivery systems permitted the implementation of 3 modifications to conventional hemodialysis as follows: high-efficiency hemodialysis (HEHD), high-flux hemodialysis (HFHD), and double-high-flux hemodiafiltration (HDF). The impact of these techniques on the quantity of the treatment administered and treatment time were assessed. One hundred and eighty-three patients were enrolled over 6 years. Monthly Kt/Vurea and dialysis treatment time were compared among the treatment techniques. In vivo extracorporeal clearances were measured for the dialyzers used. In vivo kinetically derived effective dialyzer clearances were calculated from Kt/V. Patient survival and standardized mortality ratio (SMR) were determined for each treatment modality. Treatment time averaged 192+/-28, 176+/-29, and 159+/-32 min, Kt/Vurea averaged 1.33+/-.34, 1.29+/-.30, 1.41+/-.32, and in vivo delivered urea clearance averaged 222+/-51, 272+/-34, and 333+/-43 mL/min for HEHD, HFHD, and HDF, respectively. These results were achieved even in patients with body weights in excess of 80 kgs. Net ultrafiltration rate during the treatment reached 20-30 mL/min, without clinical untoward effects. Blood flow rate ranged between 450-650 mL/min in all patients. Kaplan-Meier Survival analysis yielded a significant difference when high-efficiency treatments were compared with USRDS outcomes. Standardized mortality ratio analysis showed significance for only HDF vs. USRDS. High-efficiency treatments can provide the same quantity of treatment in a shorter period of time without affecting mortality. The increased spectrum of solutes removal provided by HFHD and HDF may be a further advantage of these treatments.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| 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 teacher head, 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".