Clinical characteristics and outcome associated with pandemic (2009) H1N1 influenza infection in patients with hematologic malignancies: a retrospective cohort study
Bibliographic record
Abstract
Pandemic H1N1 (pH1N1) influenza has been associated with a worldwide outbreak of febrile respiratory illness. Although impaired immunity, such as that caused by hematologic malignancy, has been identified as a risk factor for severe infection with this virus, the course of this infection has not been adequately characterized in patients with underlying hematologic malignancy in comparison with immune competent controls. We report our experience with severe pH1N1 infection in patients with hematologic cancers and compare this group to non-immunosuppressed patients. Data were retrospectively collected on all patients admitted to our institution with confirmed pH1N1 infection. Clinical characteristics, treatments and outcomes were compared between patients with hematologic malignancies and non-immunocompromised controls. Fifteen patients with hematologic malignancy and 49 controls were identified. The control group had higher baseline rates of asthma (p = 0.01) and smoking (p = 0.05) at baseline. Clinical features of infection in the two groups were similar, except for a higher prevalence of abnormalities on chest imaging in the group with malignancy (p = 0.05). No statistically significant difference in mortality was observed between the groups. Mean duration of hospitalization (22.1 days vs. 9.2 days, p = 0.04) and duration of antiviral treatment (9.9 days vs. 6.7 days, p < 0.05) were greater in the hematologic malignancy group. Hospitalized patients with hematologic malignancies with pH1N1 infection had greater durations of hospitalization and treatment than non-immunocompromised controls, possibly reflecting decreased clearance of the virus as a consequence of impaired immunity.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.000 |
| 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".