GERIATRIC RENAL TRANSPLANT CO-MANAGEMENT: EVALUATION OF FRAIL OLDER ADULTS FOR TRANSPLANT ELIGIBILITY
Bibliographic record
Abstract
Abstract Older transplant patients have higher rates of adverse post-transplant outcomes. The Renal Transplant Co-Management (RCOM) program is a collaboration of surgeons, geriatricians, and social workers to medically and psychosocially optimize older renal transplant candidates by providing comprehensive geriatric-centered vulnerability assessments with corresponding medical and psychosocial interventions. The RCOM assessment aids the surgical team in deciding patient transplant eligibility, and greater clarity on its role may be clinically valuable. Fifty-five patients from a single metropolitan hospital were evaluated during the study period (1/1/22 to 6/16/22). Assessments included frailty (Clinical Frailty Scale/CFS), functional status (Karnofsky Score, Katz Index, Lawton-Brody Scale) and cognition (Montreal Cognitive Assessment/MoCA) – factors that the renal transplant team considers in listing a patient for surgery (i.e., listed/transplanted) or not (i.e., ineligible/removed from the list). Twenty patients (36.4%) were female. Mean age of ineligible/removed (n=10) and listed/transplanted (n=45) patients was 74.7 (4.8) and 72.5 (3.8), respectively, with no differences in age, gender, race, education, or health insurance between groups. Patients who were listed/transplanted had a higher Lawton-Brody instrumental activities of daily living (IADL) score than those not listed (p=0.025, t-test). CFS (p=0.118), Karnofsky (p=0.09), Katz (p=0.074), and MoCA (p=0.094) were similar but approached statistical significance despite a small sample size. Functional status as measured by IADL may be a significant factor considered in determining the transplant eligibility of older adults. Ongoing study and a larger sample size may provide greater clarity on the physical and cognitive functions that impact eligibility for transplant listing in frail older adults.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".