Immune Sensitization and Mortality in Wait-Listed Kidney Transplant Candidates
Bibliographic record
Abstract
Cardiovascular mortality is the leading cause of death in ESRD. Whereas innate and adaptive immunity have established roles in cardiovascular disease, the role of humoral immunity is unknown. We conducted a retrospective cohort study in first-time adult kidney transplant candidates (N=161,308) using data from the Scientific Registry of Transplant Recipients and the Centers for Medicare and Medicaid Services to evaluate whether anti-human leukocyte antigen antibodies, measured as panel reactive antibodies (PRAs), are related to mortality in ESRD. Relationships between time-varying PRAs and all-cause or cardiovascular mortality were assessed using Cox proportional hazards models. The analysis was repeated in subcohorts of candidates at lower risk for significant comorbidities, activated on the waiting list after 2007, or unsensitized at activation. Competing risks analyses were also conducted. Fully adjusted models showed increased hazard ratios (HRs [95% confidence intervals]) for all-cause mortality (HR, 1.02 [95% CI, 0.99 to 1.06]; HR, 1.11 [95% CI,1.07 to 1.16]; and HR,1.21 [95% CI,1.15 to 1.27]) and cardiovascular mortality (HR, 1.05 [95% CI,1.00 to 1.10]; HR,1.11 [95% CI,1.05 to 1.18]; and HR,1.21 [95% CI,1.12 to 1.31]) in PRA 1%-19%, PRA 20%-79%, and PRA 80%-100% categories compared with PRA 0%, respectively. Associations between PRA and the study outcomes were accentuated in competing risks models and in lower-risk patients and persisted in other subcohorts. Our findings suggest that PRA is an independent predictor of mortality in wait-listed kidney transplant candidates. The mechanisms by which PRA confers an incremental mortality risk in sensitized patients, and the role of transplantation in modifying this risk, warrant further study.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".