Barriers Limiting Equity in Access to Pretransplant Evaluation Among Predialysis Patients: A Cohort Study
Bibliographic record
Abstract
Background. Kidney transplantation is the optimal treatment for end-stage renal disease; however, referral for pretransplant evaluation remains inconsistent. We aimed to compare patients deemed eligible for pretransplant evaluation with those whose eligibility status was undetermined. Methods. We conducted a single-center retrospective cohort study of patients aged ≤80 y, followed-up in a chronic kidney disease (CKD) clinic as of June 2021. We compared demographic, clinical characteristics, and survival prognosis scores between these groups. Results. Of the 572 patients followed in the clinic, 395 were aged ≤80 y. Among them, 203 had progressive disease, defined as CKD stage V or CKD stage IV with an estimated glomerular filtration rate (eGFR) projected to fall below 15 mL/min/1.73 m 2 within 5 y. These 203 patients were classified by the CKD clinic medical team as follows: 46 (23%) were considered eligible for pretransplant evaluation, 78 (38%) were deemed unsuitable, and 79 (39%) had an undetermined status. There were no significant differences in sex, body mass index, ethnicity, or distance from the transplant center between eligible and undetermined patients. However, undetermined patients were older (66 ± 11 versus 58 ± 13 y, P < 0.01), had a higher eGFR (15 ± 5 versus 12 ± 4 mL/min/1.73 m 2 , P < 0.01), a greater number of cardiovascular and metabolic comorbidities (2.4 ± 1.6 versus 1.6 ± 1.3, P < 0.01), and a higher 3-y mortality risk score (5.9 ± 3.7 versus 3.2 ± 3.0, P < 0.01). Nonetheless, 43 (54%) of 79 undetermined patients were in the acceptable prognosis risk category for kidney transplantation, with a predicted 3-y dialysis mortality of ≤30%. Conclusions. A substantial proportion of patients theoretically eligible for pretransplant evaluation had an undetermined referral status. Our findings suggest that several of these patients share similar age, comorbidity profiles, and survival prospects with those already deemed eligible for pretransplant evaluation.
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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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 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".