Beyond the Usual Suspects: RSV Infection in Patients With Hematological Malignancies Compared to Influenza and SARS‐COV‐2—A Report From the EPICOVIDEHA/EPIRESEHA Registry
Bibliographic record
Abstract
hematological malignancy | neglected | opportunistic infection | real-world data | respiratory syncytial virusTo the Editor, Respiratory syncytial virus (RSV) is a major cause of acute respiratory infections and seasonal hospitalisations, particularly among immunocompromised adults [1].In patients with hematological malignancies, RSV can cause severe complications, including pneumonia, respiratory failure, and death, especially in those with lymphopenia, recent HSCT, or comorbidities [2].Although antivirals, monoclonal antibodies, and vaccines exist for other high-risk groups, their efficacy in this population remains uncertain [3].Screening and diagnostic protocols are inconsistent, treatments are often empiric, and hematological patients are largely excluded from clinical trials.Moreover, comparative data versus influenza and SARS-CoV-2 are limited, impeding the development of targeted, evidence-based prevention and management strategies for this vulnerable group [4].This study used the EPICOVIDEHA/EPIRESEHA registry [5] to describe RSV infection in adults with hematological malignancies Oliver A.
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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 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".