Long‐term clinical outcomes of nocturnal hemodialysis patients compared with conventional hemodialysis patients post‐renal transplantation
Bibliographic record
Abstract
Nocturnal home hemodialysis (NHD) is a novel dialysis strategy associated with multiple advantages over conventional hemodialysis (CHD). Short- and long-term clinical outcomes of NHD patients after kidney transplantation are unknown. We hypothesized that the incidence of delayed graft function (DGF), patient and graft survival, and post-transplant estimated glomerular filtration rate (eGFR) is better among CHD-transplanted individuals than among those having received NHD. Of 231 NHD patients, 36 underwent renal transplantation between 1994 and 2006 and were matched to 68 transplanted CHD patients with a maximum follow-up of 11.7 yr. The incidence of DGF was not different between the two groups [NHD: 15/35 (42.9%) vs. CHD: 25/68 (36.8%) p = 0.43]. In modeling eGFR pre-transplant weight, donor age and recipient race were most predictive. Dialysis modality prior to transplantation influenced neither the level of eGFR post-transplantation (p = 0.34), nor the rate of eGFR decline. Patient survival was comparable between NHD and CHD groups (log-rank p = 0.91). Based on this analysis, it appeared that the incidence of DGF was similar between NHD- and CHD-transplanted patients and that pre-transplant modality did not impact on the level or rate of deterioration of post-transplant eGFR.
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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 | 0.003 |
| 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 | 0.001 | 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".