Influenza in patients with hematological malignancies: Experience at two comprehensive cancer centers
Bibliographic record
Abstract
The burden of influenza infections in patients with hematological malignancies (HMs) is not well defined. We describe the clinical presentation and associated outcomes of influenza at two comprehensive cancer centers (center 1 in the United States and center 2 in Mexico). Clinical and laboratory data on patients with HMs and influenza infection diagnosed from April 2009 to May 2014 at the two centers were reviewed retrospectively. A total of 190 patients were included, the majority were male (63%) with a median age of 49 years (range, 1-88 years), and had active or refractory HMs (76%). Compared to center 1, patients in center 2 were significantly sicker (active cancer, decreased albumin levels, elevated creatinine levels, or hypoxia at influenza diagnosis) and experienced higher lower respiratory tract infection (LRI) rate (42% vs 7%; P < 0.001). In multivariable logistic regression analysis (odds ratio, 95% confidence interval), leukemia, (3.09, 1.23-7.70), decreased albumin level (3.78, 1.55-9.20), hypoxia at diagnosis (14.98, 3.30-67.90), respiratory co-infection (5.87, 1.65-20.86), and corticosteroid use (2.71, 1.03-7.15) were significantly associated with LRI; and elevated creatinine level (3.33, 1.05-10.56), hypoxia at diagnosis (5.87, 1.12-30.77), and respiratory co-infection (6.30, 1.55-25.67) were significantly associated with 60 day mortality in both centers. HM patients with influenza are at high risk for serious complications such as LRI and death, especially if they are immunosuppressed. Patients with respiratory symptoms should seek prompt medical care during influenza season.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| 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".