Standard versus biofilm antimicrobial susceptibility testing to guide antibiotic therapy in cystic fibrosis
Bibliographic record
Abstract
BACKGROUND: The antibiotics used to treat pulmonary infections in people with cystic fibrosis are typically chosen based on the results of antimicrobial susceptibility testing performed on bacteria traditionally grown in a planktonic mode (grown in a liquid). However, there is considerable evidence to suggest that Pseudomonas aeruginosa actually grows in a biofilm (or slime layer) in the airways of people with cystic fibrosis with chronic pulmonary infections. Therefore, choosing antibiotics based on biofilm rather than conventional antimicrobial susceptibility testing could potentially improve response to treatment of Pseudomonas aeruginosa in people with cystic fibrosis. This is an update of a previously published Cochrane Review. OBJECTIVES: To compare biofilm antimicrobial susceptibility testing-driven therapy to conventional antimicrobial susceptibility testing-driven therapy in the treatment of Pseudomonas aeruginosa infection in people with cystic fibrosis. SEARCH METHODS: We searched the Cochrane Cystic Fibrosis Trials Register, compiled from electronic database searches and handsearching of journals and conference abstract books. We also searched a registry of ongoing trials and the reference lists of relevant articles and reviews.Most recent search: 19 November 2014. SELECTION CRITERIA: Randomized controlled trials of antibiotic therapy based on biofilm antimicrobial susceptibility testing compared to antibiotic therapy based on conventional antimicrobial susceptibility testing in the treatment of Pseudomonas aeruginosa pulmonary infection in people with cystic fibrosis. DATA COLLECTION AND ANALYSIS: Both authors independently selected trials, assessed their risk of bias and extracted data from eligible trials. Additionally, the review authors contacted the trial investigators to obtain further information. MAIN RESULTS: The searches identified two multicentre, randomized, double-blind controlled clinical trials eligible for inclusion in the review with a total of 78 participants; one trial was done in people who were clinically stable, the other in people experiencing pulmonary exacerbations. These trials prospectively assessed whether the use of biofilm antimicrobial susceptibility testing improved microbiological and clinical outcomes in participants with cystic fibrosis who were infected with Pseudomonas aeruginosa. The primary outcome was the change in sputum Pseudomonas aeruginosa density from the beginning to the end of antibiotic therapy.Although the intervention was shown to be safe, the data from these two trials did not provide evidence that biofilm susceptibility testing was superior to conventional susceptibility testing either in terms of microbiological or lung function outcomes. One of the trials also measured risk and time to subsequent exacerbation as well as quality of life measures and did not demonstrate any difference between groups in these outcomes. Both trials had an overall low risk of bias. AUTHORS' CONCLUSIONS: The current evidence is insufficient to recommend choosing antibiotics based on biofilm antimicrobial susceptibility testing rather than conventional antimicrobial susceptibility testing in the treatment of Pseudomonas aeruginosa pulmonary infections in people with cystic fibrosis. Biofilm antimicrobial susceptibility testing may be more appropriate in the development of newer, more effective formulations of drugs which can then be tested in 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 | 0.028 | 0.114 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.006 |
| Bibliometrics | 0.007 | 0.005 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.005 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 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".