The EKiTE network (epidemiology in kidney transplantation - a European validated database): an initiative epidemiological and translational European collaborative research
Bibliographic record
Abstract
BACKGROUND: Kidney transplantation is considered to be the treatment of choice for people with end-stage renal disease (ESRD). However, due to the shortage of available organs and the increase in the ESRD prevalence in Europe, it is essential to improve transplantation outcomes by studying the related prognostic factors. Today, there is no European registry collecting data to perform such clinical epidemiology studies. MAIN BODY: Entitled EKiTE, for European cohort for Kidney Transplantation Epidemiology, this prospective and multicentric cohort includes patients from Spanish (Barcelona), Belgian (Leuven), Norwegian (Oslo) and French (Paris Necker, Lyon, Nantes, Nancy, Montpellier, Nice and Paris Saint Louis) transplantation centers and currently contains 13,394 adult recipients of kidney (only) transplantation from 2005 and updated annually. A large set of parameters collected from transplantation until graft failure or death with numbers of post-transplantation outcomes. The long-term follow-up and the collected data enable a wide range of possible survival and longitudinal analyses. CONCLUSION: EKiTE is a multicentric cohort aiming to better assess the natural history of the ESRD in European kidney transplant recipients and perform benchmarking of clinical practices. The data are available for clinical epidemiology studies and open for external investigators upon request to the scientific council. Short-term perspectives are to extend EKITE network to other European countries and collect additional parameters in respect of the common thesaurus.
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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 | 0.006 | 0.000 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".