Influenza and tuberculosis co‐infection: A systematic review
Bibliographic record
Abstract
INTRODUCTION: There are limited data on risk of severe disease or outcomes in patients with influenza and pulmonary tuberculosis (PTB) co-infection compared to those with single infection. METHODS: We conducted a systematic review of published literature on the interaction of influenza viruses and PTB. Studies were eligible for inclusion if they presented data on prevalence, disease association, presentation or severity of laboratory-confirmed influenza among clinically diagnosed or laboratory-confirmed PTB cases. We searched eight databases from inception until December 2018. Summary characteristics of each study were extracted, and a narrative summary was presented. Cohort or case-control studies were assessed for potential bias using the Newcastle-Ottawa scale. RESULTS: We assessed 5154 abstracts, reviewed 146 manuscripts and included 19 studies fulfilling selection criteria (13 human and six animal). Of seven studies reporting on the possible effect of the underlying PTB disease in patients with influenza, three of four analytical studies reported no association with disease severity of influenza infection in those with PTB, whilst one study reported PTB as a risk factor for influenza-associated hospitalization. An association between influenza infection and PTB disease was found in three of five analytical studies; whereas the two other studies reported a high frequency of PTB disease progression and complications among patients with seasonal influenza co-infection. CONCLUSION: Human analytical studies of an association between co-infection and severe influenza- or PTB-associated disease or increased prevalence of influenza co-infection in individuals' hospitalized for PTB were not conclusive. Data are limited from large, high-quality, analytical epidemiological studies with laboratory-confirmed endpoints.
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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.001 |
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".