A Primed Neutrophil Subset Predicts the Risk of Bloodstream Infections in Allogeneic Hematopoietic Stem-Cell Transplant Patients: A Prospective Study
Bibliographic record
Abstract
BACKGROUND: Bloodstream infections (BSIs) are the most common infectious complication in patients who receive allogeneic hematopoietic stem-cell transplants (allo-HSCTs). Polymorphonuclear neutrophils (PMNs) are quantified to monitor the susceptibility to BSIs; however, their degree of activation is not. We previously identified a population of primed PMNs (pPMNs) with distinct markers of activation representing approximately 10% of PMNs in circulation. In this study, we investigate whether susceptibility to BSIs is related to the proportion of pPMNs rather than strictly PMN counts. METHODS: In this prospective observational study, we used flow cytometry to assess pPMNs in blood and oral rinse samples collected from patients receiving an allo-HSCT over the course of their treatment. We used the proportion of pPMNs in the blood on day 5 post-transplant to categorize patients into a high- or a low-pPMN group (>10% or <10% pPMNs). These groups were then used as a predictor of BSIs. RESULTS: A total of 76 patients were enrolled in the study with 36 in the high-pPMN group and 40 in the low-pPMN group. Patients in the low-pPMN group had lower expression of PMN activation and recruitment markers and displayed a delay in PMN repopulation of the oral cavity after the transplant. These patients were more susceptible to BSIs compared with patients in the high-pPMN group with an odds ratio of 6.5 (95% confidence interval, 2.110-25.07; P = .002). CONCLUSIONS: In patients who receive an allo-HSCT, having <10% pPMNs early in the post-transplant phase can be an independent predictor of BSI in allo-HSCT patients.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".