Combination antimicrobial susceptibility testing for acute exacerbations in chronic infection of Pseudomonas aeruginosa in cystic fibrosis
Notice bibliographique
Résumé
BACKGROUND: Antibiotic therapy for acute pulmonary exacerbations in people with cystic fibrosis is usually chosen based on the results of antimicrobial susceptibility testing of individual drugs. Combination antimicrobial susceptibility testing assesses the efficacy of drug combinations including two or three antibiotics in vitro and can often demonstrate antimicrobial efficacy against bacterial isolates even when individual antibiotics have little or no effect. Therefore, choosing antibiotics based on combination antimicrobial susceptibility testing could potentially improve response to treatment in people with cystic fibrosis with acute exacerbations. This is an updated version of a previously published review. OBJECTIVES: To compare antibiotic therapy based on conventional antimicrobial susceptibility testing to antibiotic therapy based on combination antimicrobial susceptibility testing in the treatment of acute pulmonary exacerbations in people with cystic fibrosis and chronic infection with Pseudomonas aeruginosa. SEARCH METHODS: We searched the Cochrane Cystic Fibrosis and Genetic Disorders Group Cystic Fibrosis Trials Register which comprises of references identified from comprehensive electronic database searches and handsearches of relevant journals and abstract books of conference proceedings. Date of latest search: 19 December 2016.We also searched ongoing trials registries. Date of latest search: 08 March 2017. SELECTION CRITERIA: Randomised and quasi-randomised controlled studies of antibiotic therapy based on conventional antimicrobial susceptibility testing compared to antibiotic therapy based on combination antimicrobial susceptibility testing in the treatment of acute pulmonary exacerbations in cystic fibrosis due to chronic infection with Pseudomonas aeruginosa. DATA COLLECTION AND ANALYSIS: Both authors independently selected studies, assessed their quality and extracted data from eligible studies. Additionally, the authors contacted the study investigators to obtain further information. MAIN RESULTS: The search identified one multicentre study eligible for inclusion in the review. This study prospectively assessed whether the use of multiple combination bactericidal antibiotic testing improved clinical outcomes in participants with acute pulmonary exacerbations of cystic fibrosis who were infected with multiresistant bacteria. A total of 132 participants were randomised in the study. The study investigators provided data specific to the 82 participants who were only infected with Pseudomonas aeruginosa for their primary outcome of time until next pulmonary exacerbation. For participants specifically infected with only Pseudomonas aeruginosa, the hazard ratio of a subsequent exacerbation was 0.82, favouring the control group (95% confidence interval 0.44 to 1.51) (P = 0.52). No further data for any of this review's outcomes specific to participants infected with Pseudomonas aeruginosa were available. The risk of bias for the included study was deemed to be low. The quality of the evidence was moderate for the only outcome providing data solely for individuals with infection due to Pseudomonas aeruginosa. For other outcomes, we were unable to judge the quality of the evidence as no data were available for the relevant subset of participants. AUTHORS' CONCLUSIONS: The current evidence, limited to one study, shows that there is insufficient evidence to determine effect of choosing antibiotics based on combination antimicrobial susceptibility testing compared to choosing antibiotics based on conventional antimicrobial susceptibility testing in the treatment of acute pulmonary exacerbations in people with cystic fibrosis with chronic Pseudomonas aeruginosa infection. A large international and multicentre study is needed to further investigate this issue.The only study included in the review was published in 2005, and we have not identified any further relevant studies up to March 2017. We therefore do not plan to update this review until new studies are published.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,011 | 0,044 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,008 | 0,005 |
| Bibliométrie | 0,007 | 0,006 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,002 | 0,002 |
| Science ouverte | 0,002 | 0,001 |
| Intégrité de la recherche | 0,003 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,009 | 0,001 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».