CMV-Specific Immunity and CMV Complications in Seropositive HCT Recipients Depend On Donor Serostatus.
Bibliographic record
Abstract
Abstract Abstract 2248 Poster Board II-225 Background: Anti-CMV T-cells are thought to control CMV. In seropositive recipients of grafts from seropositive donors (D+R+), both na•ve and memory/effector anti-CMV T-cells are transferred with the graft. In seropositive recipients of grafts from seronegative donors (D-R+), only na•ve anti-CMV T-cells are transferred with the graft. We hypothesized that counts of anti-CMV T-cells are higher in the D+R+ compared to the D-R+ group, and that this leads to a lower incidence of CMV complications like CMV disease or CMV reactivation treated with toxic antiviral drugs, and that this may be particularly obvious in the setting of T cell depletion. Patients and methods. We reviewed charts of 298 seropositive recipients for CMV reactivation (pp65 antigenemia or CMV DNAemia above institutional threshold for starting preemptive therapy), recurrent CMV reactivation (above the same threshold), CMV disease, and death due to any cause. In 76 of these patients, we determined the counts of anti-CMV effector T-cells (producing INFg upon 18 h stimulation with CMV lysate in case of CD4+ T-cells or pp65 overlapping peptides in case of CD8 T+-cells). Conditioning of all patients included rabbit-anti-human thymocyte globulin (Thymoglobulin). Median follow up of the 298 patients was 19.6 months (range, 0.3 – 120.6) Results. As shown in Table 1, the anti-CMV T cell, in particular, CD4+ T-cell counts were higher, and the cumulative incidences of CMV reactivation, recurrent CMV reactivation and CMV disease were lower in D+R+ compared to D-R+ patients. Conclusion. Compared to D+R+ patients, D-R+ have lower counts of anti-CMV T-cells. This appears to translate into a higher risk of CMV reactivation and CMV disease. New strategies to avoid CMV complications need to be explored for D-R+ patients, eg, donor vaccination pre-transplant or infusion of anti-CMV T-cells post-transplant. Disclosures: No relevant conflicts of interest to declare.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".