IntroductionBone and joint infections (BJIs) are a major health concern causing remarkable morbidity and mortality. However, which antimicrobial treatment could be the best according to specific clinical scenarios and/or to the pharmacokinetic/pharmacodynamic (PK/PD) features remains an unmet clinical need. This multidisciplinary opinion article aims to develop evidence-based algorithms for empirical and targeted antibiotic therapy of patients affected by BJIs.Areas coveredA multidisciplinary team of four experts had several rounds of assessment for developing algorithms devoted to empirical and targeted antimicrobial therapy of BJIs. A literature search was performed on PubMed-MEDLINE (until April 2023) to provide evidence for supporting therapeutic choices. Four different clinical scenarios were structured according to specific infection types (i.e. vertebral osteomyelitis, prosthetic joint infections, infected non-unions and other chronic osteomyelitis, and infectious arthritis), need or not of surgical intervention or revision, isolation or not of clinically relevant bacterial pathogens from blood and/or tissue cultures, and PK/PD features of antibiotics.Expert opinionThe proposed therapeutic algorithms were based on a multifaceted approach considering the peculiar features of each antibiotic (spectrum of activity, PK/PD properties, bone penetration rate, and anti-biofilm activity), and could be hopefully helpful in improving clinical outcome of BJIs.

Pharmacokinetic and pharmacodynamic considerations for optimizing antimicrobial therapy used to treat bone and joint infections: an evidence-based algorithmic approach / Gatti, Milo; Tedeschi, Sara; Zamparini, Eleonora; Pea, Federico; Viale, Pierluigi. - In: EXPERT OPINION ON DRUG METABOLISM & TOXICOLOGY. - ISSN 1742-5255. - ELETTRONICO. - 19:8(2023), pp. 511-535. [10.1080/17425255.2023.2255525]

Pharmacokinetic and pharmacodynamic considerations for optimizing antimicrobial therapy used to treat bone and joint infections: an evidence-based algorithmic approach

Gatti, Milo;Tedeschi, Sara;Pea, Federico
;
Viale, Pierluigi
2023

Abstract

IntroductionBone and joint infections (BJIs) are a major health concern causing remarkable morbidity and mortality. However, which antimicrobial treatment could be the best according to specific clinical scenarios and/or to the pharmacokinetic/pharmacodynamic (PK/PD) features remains an unmet clinical need. This multidisciplinary opinion article aims to develop evidence-based algorithms for empirical and targeted antibiotic therapy of patients affected by BJIs.Areas coveredA multidisciplinary team of four experts had several rounds of assessment for developing algorithms devoted to empirical and targeted antimicrobial therapy of BJIs. A literature search was performed on PubMed-MEDLINE (until April 2023) to provide evidence for supporting therapeutic choices. Four different clinical scenarios were structured according to specific infection types (i.e. vertebral osteomyelitis, prosthetic joint infections, infected non-unions and other chronic osteomyelitis, and infectious arthritis), need or not of surgical intervention or revision, isolation or not of clinically relevant bacterial pathogens from blood and/or tissue cultures, and PK/PD features of antibiotics.Expert opinionThe proposed therapeutic algorithms were based on a multifaceted approach considering the peculiar features of each antibiotic (spectrum of activity, PK/PD properties, bone penetration rate, and anti-biofilm activity), and could be hopefully helpful in improving clinical outcome of BJIs.
2023
Pharmacokinetic and pharmacodynamic considerations for optimizing antimicrobial therapy used to treat bone and joint infections: an evidence-based algorithmic approach / Gatti, Milo; Tedeschi, Sara; Zamparini, Eleonora; Pea, Federico; Viale, Pierluigi. - In: EXPERT OPINION ON DRUG METABOLISM & TOXICOLOGY. - ISSN 1742-5255. - ELETTRONICO. - 19:8(2023), pp. 511-535. [10.1080/17425255.2023.2255525]
Gatti, Milo; Tedeschi, Sara; Zamparini, Eleonora; Pea, Federico; Viale, Pierluigi
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11585/943315
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