UK Renal Registry 16th Annual Report: Chapter 4 Demography of Patients Waitlisted for Renal Transplantation in the UK: National and Centre-specific Analyses
Bibliographic record
Abstract
INTRODUCTION: For suitable patients, renal transplantation is considered the optimal modality of renal replacement therapy, with availability of donor organs limiting the number of transplants undertaken. The 2006 kidney allocation policy was developed to ensure equity of allocation to patients on the transplant waiting list, whilst still achieving a good donor/recipient match. This study aims to describe the characteristics of the kidney transplant waiting list and variations in median waiting times. METHODS: Demographics and clinical characteristics of all patients listed for a kidney only transplant in the UK on 1st January 2011 were examined. Renal unit variations were explored. Patients listed between January 2006 and December 2009 were included in analysis of waiting times to transplant. RESULTS: At the beginning of 2011, there were 6,699 patients registered active for kidney only transplant in UK; a prevalence rate of 107 pmp. The median age of prevalent listed patients was 53 years, with 8% aged 70 or above. Of the patients listed, 84% had started renal replacement therapy (RRT), 59% were male, 28% were from ethnic minorities, 50% had blood group type O, 28% were defined as difficult to HLA match and 23% were highly sensitised (calculated HLA antibody reaction frequency 85%). Median waiting time to transplant was 38 months. Waiting time was shorter for White patients (36 months) compared to Asian or Black patients (46 months), and was doubled in highly sensitised compared to un-sensitised patients. CONCLUSIONS: Intercentre variation was observed in the rate of wait-listing and in the proportion of listed patients across different ethnic groups, age, blood groups and level of sensitisation. This may reflect differences in baseline population characteristics as well as individual centre practice patterns. Median waiting times differ significantly across blood groups, degree of sensitisation and ethnic group.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.009 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.013 | 0.003 |
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".