Pre‐transplant cognitive screening is a poor predictor of post‐transplant cognitive status
Bibliographic record
Abstract
INTRODUCTION: Transplant centers hesitate to transplant patients with cognitive impairment. It is unclear if pre-kidney transplant (KT) cognitive screening can predict post-KT cognitive function. METHODS: We evaluated pre- to post-KT cognitive function with the Montreal Cognitive Assessment (MoCA) in a cohort of 108 patients. We used an adjusted logistic regression model to assess pre- to post-KT changes in cognitive status (continuous variable) and a linear mixed model to assess changes in MoCA scores (categorical variable) pre- to post- KT. RESULTS: The average pre- and post-KT MoCA scores were 25.3 ± 3.0 and 26.4 ± 2.8, respectively. Final pre-KT score did not predict post-KT cognitive status (OR = 1.08; 95% CI: .92-1.26; P = .35). 32% of the patients with a final pre-KT score ≥26 had at least one post-KT score < 26. Conversely, 61% of the patients with a final pre-KT score < 26 had at least one post KT score ≥26. In the linear mixed model analysis, the final pre-KT score was associated with a small, clinically insignificant (β = .34; 95% CI: .19-.49; P < .001) effect on the post-KT score. CONCLUSION: A low pre-KT MoCA score is not a strong independent predictor of post-KT cognitive function and should not preclude patients from receiving a KT.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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) | 0.001 | 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".