Similar Outcomes for Canadian Renal Transplant Recipients Followed Up in Transplant Centers and Satellite Clinics
Bibliographic record
Abstract
BACKGROUND: A significant proportion of long-term care for renal transplant recipients (RTRs) in Canada is provided by community nephrologists in satellite clinics (SCs). The outcomes of RTRs followed up in SCs have not been formally compared with those followed up in transplant centers (TCs). METHODS: This multicenter retrospective study from 13 TCs and SCs across Canada compared patient and graft outcomes in RTRs with a functioning graft more than or equal to 18 months. Data were abstracted at 6 to 18 months posttransplantation, and at last visit (if >18 months). Patients were stratified in a 1:1 ratio between TCs and SCs, and by a 3:1 ratio between cyclosporine A and tacrolimus. The primary outcome was change (Δ) in Modification of Diet in Renal Disease estimated glomerular filtration rate (eGFR) from 6 to 18 months posttransplantation (ΔeGFRM18-6). Secondary outcomes included the prevalence of hyperlipidemia, diabetes, and hypertension. RESULTS: A total of 264 RTRs followed at TCs and SCs demonstrated broad similarity in baseline recipient and donor characteristics. ΔeGFRM18-6 were similar for TCs versus SCs and better for tacrolimus versus cyclosporine A (P=0.022). There was no difference in lipid levels between TCs and SCs during 6 to 18 months, although low-density lipoprotein cholesterol was lower in SCs versus TCs at most recent visit (2.6 vs. 2.3 mmol/L; P=0.003). Fasting blood glucose levels were similar in TCs and SCs. Comparable target blood pressure levels were achieved, and the prevalence of hypertension was similar for both TCs and SCs at all time points. CONCLUSION: Short-term graft and patient outcomes are similar in TC and SC RTRs, supporting the feasibility of follow-up patient care outside major TCs.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".