A 5-Year Prospective Multicenter Evaluation of Influenza Infection in Transplant Recipients
Bibliographic record
Abstract
Background: Seasonal influenza infection may cause significant morbidity and mortality in transplant recipients. The purpose of this study was to assess the epidemiology of symptomatic influenza infection posttransplant and determine risk factors for severe disease. Methods: Twenty centers in the United States, Canada, and Spain prospectively enrolled solid organ transplant (SOT) or hematopoietic stem cell transplant (HSCT) recipients with microbiologically confirmed influenza over 5 consecutive years (2010-2015). Demographics, microbiology data, and outcomes were collected. Serial nasopharyngeal swabs were collected at diagnosis and upto 28 days, and quantitative polymerase chain reaction for influenza A was performed. Results: We enrolled 616 patients with confirmed influenza (477 SOT; 139 HSCT). Pneumonia at presentation was in 134 of 606 (22.1%) patients. Antiviral therapy was given to 94.1% for a median of 5 days (range, 1-42 days); 66.5% patients were hospitalized and 11.0% required intensive care unit (ICU) care. The receipt of vaccine in the same influenza season was associated with a decrease in disease severity as determined by the presence of pneumonia (odds ratio [OR], 0.34 [95% confidence interval {CI}, .21-.55], P < .001) and ICU admission (OR, 0.49 [95% CI, .26-.90], P = .023). Similarly, early antiviral treatment (within 48 hours) was associated with improved outcomes. In patients with influenza A, pneumonia, ICU admission, and not being immunized were also associated with higher viral loads at presentation (P = .018, P = .008, and P = .024, respectively). Conclusions: Annual influenza vaccination and early antiviral therapy are associated with a significant reduction in influenza-associated morbidity, and should be emphasized as strategies to improve outcomes of transplant recipients.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".