Symptom Recovery after Kidney Transplantation
Bibliographic record
Abstract
Background: We report physical and psychological symptom severity and frequency among incident kidney transplant (KT) recipients using Patient Reported Outcomes Measurement Information System (PROMIS) computer adaptive tests (CAT). Methods: Longitudinal convenience sample of incident (<30 days post-transplant) adult KT recipients, recruited 2021-2024. Participants completed PROMIS CATs at baseline, biweekly for 3 months, and monthly thereafter. PROMIS T are standardized to a mean of 50 and standard deviation (SD) of 10, corresponding to the U.S. general population mean. Scores > 60 or <= 40 indicate moderate-severe symptom severity or function impairment, respectively. Results: Of 133 participants, 84(63%) were male, 69(58%) were white, 43(35%) had diabetes, and mean(SD) age was 51(15) years. Median (interquartile range) time after transplant at enrolment was 5(3,8) days. At baseline, all domain T-scores were worse than the U.S. population mean and improved significantly by week 12. At week 12, domain T-scores neared the U.S. population mean (Table 1). Mean T-scores at week 24 were similar to week 12, except physical function and pain interference, which showed significant further improvement. At week 0, the proportion of patients scoring moderate-severe symptom severity or function impairment: fatigue 36%, sleep disturbance 32%, physical function 52%, pain interference 48%, anxiety 36%, and depression 18%. At week 12, the proportion of patients scoring moderate-severe symptom severity or function impairment: fatigue 7%, sleep disturbance 14%, physical function 12%, pain interference 10%, anxiety 11%, and depression 10%. All proportions were significantly lower at week 12 vs week 0, except for depression. Conclusion: A majority of KT recipients will experience moderate-severe symptom severity or function impairment immediately post-transplant. By week 12, most improve significantly and near levels seen in the U.S. general population. Findings highlight need for systematic symptom screening and support early after kidney transplant. Funding: Private Foundation Support, Government Support – Non-U.S.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".