Impact of Baseline and Week 2 and Week 4 Posttransplant CMV Cell-Mediated Immunity on Risk of CMV Infections and Mortality in Recipients of Allogeneic Hematopoietic Cell Transplant
Bibliographic record
Abstract
Abstract Background Cytomegalovirus (CMV) infection is a common opportunistic infection after allogeneic hematopoietic cell transplant (alloHCT). We explored whether a change in CMV cell-mediated immunity during the first month after transplant predicts the risk of development of CMV infection and all-cause mortality. Methods This follow-up analysis is based on data from the REACT study, a multicenter prospective observational study of recipients of alloHCT who were CMV-seropositive. Production of interferon γ following ex vivo stimulation with CMV antigens IE1 (immediate early 1) and pp65 (phosphoprotein 65) was assessed by CMV ELISPOT assay at baseline and 2 and 4 weeks after transplant. Clinically significant CMV infection (CS-CMVi) was defined as CMV viremia and/or disease necessitating antiviral therapy. We evaluated the impact of CMV CMI changes on the risk of CS-CMVi and post transplant mortality. Results The analysis included 226 recipients of alloHCT with CMV cell-mediated immunity data at baseline and 2 and/or 4 weeks after transplant. CS-CMVi occurred in 64 patients (28%). On Cox regression analyses, independent predictors of CS-CMVi included a negative Δ change from baseline to week 2 of pp65 spot counts (hazard ratio, 3.65 [95% CI, 1.65–8.04]; P = .001) to week 4 of IE1 spot counts (hazard ratio, 2.79 [95% CI, 1.46–5.35]; P = .002), anti-thymocyte globulin conditioning regimen, type of transplant, female sex, and corticosteroid use. Kaplan-Meir analysis showed a significant association of a negative IE1 change from baseline to week 4 and increased all-cause mortality after transplant (log rank test = 0.041). Conclusions A decrease in CMV-specific T-cell responses during the first month after transplant may predict CS-CMVi and is associated with all-cause mortality in recipients of alloHCT.
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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 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.001 | 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".