Psoriasis associates with increased risk for kidney transplant rejection
Bibliographic record
Abstract
BACKGROUND AND HYPOTHESIS: Psoriasis is a common immune-mediated skin disorder with additional manifestations due to systemic inflammation. Patients with psoriasis have an increased risk of end-stage renal disease (ESRD) requiring either dialysis or renal transplant; however, the relationship between psoriasis and renal allograft failure has not been established. METHODS: We conducted a retrospective cohort study using the United States Renal Data System to analyze the association between psoriasis and graft failure (occurring more than 2 weeks after the transplant). We compared transplant failure rates in ESRD patients with a psoriasis diagnosis prior to the initial transplant versus transplanted ESRD patients without a psoriasis diagnosis. From 2004 to 2019, a total of 151 272 renal transplant patients aged 18-100 and meeting exclusion and inclusion criteria were identified; in this cohort, 1105 ESRD patients had International Classification of Diseases (ICD)-9 and -10 claim codes for psoriasis prior to their renal transplant. RESULTS: Logistic regression modeling was used to examine possible confounders of psoriasis on graft failure. Kaplan-Meier estimates indicated that renal transplant patients with psoriasis had reduced graft survival over time compared with those without psoriasis. In addition, Cox proportional hazard analysis, controlling for demographics and clinical risk factors, showed a significantly increased hazard ratio for renal allograft failure for patients with a diagnosis of psoriasis. CONCLUSIONS: The systemic inflammation and immune-mediated pathophysiology underlying psoriasis could underlie the association between psoriasis and the increased risk of renal transplant failure.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".