In‐hospital incidence of and risk factors for influenza‐associated respiratory failure
Bibliographic record
Abstract
BACKGROUND: Respiratory failure (RF) is the most important complication of influenza virus infection. Its definition and incidence are heterogeneous in the literature. METHODS: This systematic review and meta-analysis aim to determine the incidence of and risk factors for RF in patients hospitalized with influenza. Electronic databases were searched for articles on RF in patients hospitalized for influenza infection up to December 2021 regardless of their geographical location. Observational and experimental studies were considered for inclusion, excluding case series. The Newcastle-Ottawa and Johanna Briggs scales were used for quality assessment. A random-effects meta-analysis was performed, followed by subgroup analyses according to, among others, presence/absence of pneumonia, RF definition, serotype and time period. PRISMA guidelines were followed for this review. RESULTS: Thirty-six studies were finally included in the meta-analysis. Overall, RF incidence was 24% (range 5%-85%, 95% confidence interval [95CI] 19%-31%). Significantly higher incidences of RF were found in patients with pneumonia (42%, 95CI 28%-57%, p = .006), when RF was defined as hypoxemia (58%, 95CI 31%-81%, p < .001), and during the 2009 pandemic (25%, 95CI 16%-36%) and postpandemic period (23%, 95CI 15%-34%, p = .01). No differences were found between human influenza serotypes. Assessment of risk factors associated with the development of RF was not possible due to their inconsistent and heterogeneous reporting. CONCLUSION: Respiratory failure is frequent in hospitalized influenza patients, especially in patients with pneumonia and since the 2009 pandemic, although its definition and reporting widely vary in the literature. This complicates its characterization and comparison between cohorts and with other respiratory viruses.
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 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 | 0.012 | 0.084 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| 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".