A prospective multicenter observational study of cell-mediated immunity as a predictor for cytomegalovirus infection in kidney transplant recipients
Bibliographic record
Abstract
T cell immunity is essential for the control of cytomegalovirus (CMV) infection after transplantation. We evaluated a CMV-specific peptide-based enzyme-linked immunosorbent spot (ELISPOT) assay to determine whether assay results could predict subsequent CMV events. Adult kidney transplant recipients at 43 centers underwent ELISPOT testing to enumerate interferon gamma (IFN-γ) binding spot-forming units (sfu) after stimulation of cells with an overlapping peptide pool of CMV phosphoprotein 65 (pp65) and immediate early-1 (IE-1) protein at the end of antiviral prophylaxis (EOP) and various time points thereafter. The primary outcome was a CMV event in the first posttransplant year. In 583 kidney transplant recipients (260 seropositive donor [D+]/seronegative recipient [R−] and 277 R+), CMV events occurred in 44 of 368 eligible patients (11.8%) at a median of 227 days (range 92-360) posttransplant. A cutoff value of >40 sfu/2.5 × 10 5 cells for either IE-1 or pp65 was derived as a threshold for positivity, with a negative predictive value of >97% for CMV events. CMV events were significantly lower in assay positive vs assay negative patients (3.0% vs 19.5%, P < .0001 for pp65). Time to CMV event post-EOP was significantly greater in those with sfu >40 at EOP ( P < .0001). In this large, multicenter trial of kidney transplant recipients, we show that an assessment of CMV-specific immunity using a novel ELISPOT assay is able to predict protection from CMV infection.
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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 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".