Main Obstacles of Pre-kidney Transplant Work-Up: A Quality Assessment/Process Improvement Program
Bibliographic record
Abstract
Background: Failure to complete a comprehensive pre-kidney transplant workup results in increased dialysis exposure and poorer post-transplant survivals. Failure also puts stress on transplant centers’ resources, as referrals continue to come, patients who are in ‘pending activation limbo’ are either neglected or detract from new patients’ evaluation. Candidates are worked-up by our transplant program after referral rather than by the dialysis programs where candidates are universally referred to transplant centres after finalizing workup. We are aiming to assess metrics of quality at our program focusing on variability in the time taken for completion of pre-transplant workup among different coordinators, processes, and populations. Methods: This is a single center retrospective study evaluating the duration and obstacles of pre-kidney transplant workup of all in limbo candidates who were evaluated at our program prior to January 1, 2021. Data will be compared with candidates’ workup during a later period, when a more regular chart review was adopted by our newer coordinator to expedite workup. Results: 112 candidate’s files were reviewed by January 1, 2021. 54 (48.2%) candidates were in limbo [Age 54.5±10.7 years, female (44.4%), Caucasian (74.1%)], 38 files were closed due to patients’ wishes or nonadherence and 20 others had expired. By March 1, 2024, 47 (87%) in limbo candidates received a transplant decision while 7 patients stayed in workup. Median time from assessment to transplant decision was 23.3 (14.3-37.1) months, while time from chart review to transplant decision was 7.7 (3-16) months. Patients who are still in workup live further away from our center, were assessed once (P 0.035), and have a longer median workup to date 44.6 (42.4-55.7) months. The median time to transplant decision of candidates with more frequent pre-transplant assessments compared with those with less frequent assessments was shorter (20.2 vs 27.1 months, P 0.037). Finally, at the time of transplant decision, 38 (81%) patients were on dialysis (24 on dialysis > 24 months, 9 (24%) on dialysis < 1 year). Conclusion: Regular chart review and frequent assessments of pre-transplant candidates result in shorter workup and dialysis vintage.
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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 | 0.008 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".