Neuraminidase inhibitors for the treatment of influenza infection in people with cystic fibrosis
Bibliographic record
Abstract
BACKGROUND: Cystic fibrosis is the most common, life-threatening, recessively inherited disease of Caucasian populations. It is a multisystem disorder caused by a mutation in the gene encoding the cystic fibrosis transmembrane conductance regulator protein which is important in producing sweat, digestive juices and mucus.The impaired or absent function of this protein results in the production of viscous mucus within the lungs and an environment that is susceptible to chronic airway obstruction and pulmonary colonization by a range of pathogenic bacteria. Morbidity and mortality of cystic fibrosis is related to chronic pulmonary sepsis and its complications by these bacteria.Influenza can worsen the course of the disease in cystic fibrosis by increasing the risk of pneumonia and secondary respiratory complications. Antiviral agents form an important part of influenza management and include the neuraminidase inhibitors zanamivir and oseltamivir. These inhibitors can limit the infection and prevent the spread of the virus. OBJECTIVES: To assess the effects of neuraminidase inhibitors for the treatment of influenza infection in people with cystic fibrosis. SEARCH METHODS: We searched the Cochrane Cystic Fibrosis and Genetic Disorders Group Trials Register comprising references identified from comprehensive electronic database searches and handsearches of relevant journals and abstract books of conference proceedings.Most recent search: 08 July 2013. SELECTION CRITERIA: Randomised controlled trials and quasi-randomised controlled trials comparing neuraminidase inhibitors with placebo or other antiviral drugs. DATA COLLECTION AND ANALYSIS: Two review authors had planned to independently screen studies, extract data and assess risk of bias using standard Cochrane Collaboration methodologies. No studies were identified for inclusion. MAIN RESULTS: No relevant studies were retrieved after a comprehensive search of the literature. AUTHORS' CONCLUSIONS: We were unable to identify any randomised controlled trials or quasi-randomised controlled trials on the efficacy of neuraminidase inhibitors for the treatment of influenza infection in people with cystic fibrosis. The absence of high level evidence for the effectiveness of these interventions emphasises the need for well-designed, adequately powered, randomised controlled clinical trials.
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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 | 0.006 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.005 | 0.004 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 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 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".