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Standard versus biofilm antimicrobial susceptibility testing to guide antibiotic therapy in cystic fibrosis

2012· review· en· W4236832845 on OpenAlexaff
Valerie Waters, Félix Ratjen

Bibliographic record

VenueCochrane Database of Systematic Reviews · 2012
Typereview
Languageen
Field
Topic
Canadian institutionsSickKids FoundationHospital for Sick Children
Fundersnot available
KeywordsMedicineCystic fibrosisPseudomonas aeruginosaAntimicrobialAntibioticsClinical trialInternal medicineRandomized controlled trialIntensive care medicineMicrobiologyBiologyBacteria

Abstract

fetched live from OpenAlex

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 cystic fibrosis patients 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. 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: 02 August 2012. 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 individuals 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 authors contacted the trial investigators to obtain further information. MAIN RESULTS: The search identified one multicentre, randomized, double-blind controlled clinical trial eligible for inclusion in the review (39 participants). This trial 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. The mean (standard deviation) change in density in log(10) colony forming units per gram was -2.94 (2.83) in the biofilm group and -3.27 (3.09) in the control group, for a mean difference of 0.28 (95% confidence interval -1.98 to 2.54) (P = 0.8). The data did not provide evidence that biofilm susceptibility testing was superior to conventional susceptibility testing. 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. Future randomized clinical trials on this topic may shed further light on this question.

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 imitation

Not 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.

metaresearch head score (Codex)0.027
metaresearch head score (Gemma)0.102
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.027
Threshold uncertainty score0.145

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0270.102
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0070.005
Bibliometrics0.0060.005
Science and technology studies0.0000.002
Scholarly communication0.0040.004
Open science0.0020.001
Research integrity0.0040.002
Insufficient payload (model declined to judge)0.0060.001

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.

Opus teacher head0.199
GPT teacher head0.408
Teacher spread0.209 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSystematic review
Domainnot available
GenreReview

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".

Quick stats

Citations19
Published2012
Admission routes1
Has abstractyes

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