Center Variation and the Effect of Center and Provider Characteristics on Clinical Outcomes in Kidney Transplantation: A Systematic Review of the Evidence
Bibliographic record
Abstract
BACKGROUND: Kidney transplantation is the best treatment option for patients with end-stage renal disease. While patient-level factors affecting survival are established, the presence of variation in the management of transplant recipients remains unknown. OBJECTIVE: The objective of this study was to examine center variation in kidney transplantation and identify center and provider characteristics that may be associated with clinical outcomes. DESIGN: This is a systematic review. DATA SOURCES: Ovid Medline, Embase, and Cochrane library from inception to June 2016 were used. STUDY ELIGIBILITY: Any study examining the association between center or provider characteristics and graft or patient survival, quality of life, or functional status were included. RESULTS: We identified 6327 records and 24 studies met eligibility. Most studies used data registries. Characteristics evaluated include center volume (n = 17), provider volume (n = 2), provider experience (n = 1), center type (n = 2), and location of follow-up (n = 1). Outcomes assessed included graft survival (n = 24) and patient survival (n = 9). Significant center variation was described in 12 of 15 and 5 of 7 studies for graft and patient survival. There was a significant and positive association between center volume and graft and patient survival in 8 and 2 studies, respectively. Provider experience and volume were significantly associated with less allograft loss and provider volume with lower risk of death. There was no association between graft survival and location of follow-up or center type. LIMITATIONS: There was substantial heterogeneity in the variables assessed and methodology used to analyze associations. CONCLUSION: This systematic review found center variation in kidney transplantation. Future studies in the current era are necessary to better evaluate this important topic.
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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 | 0.012 | 0.065 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.011 |
| Bibliometrics | 0.011 | 0.015 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 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".