Predictive Factors of Cloxacillin Susceptibility in Primary Bacterial Spinal Infection.

infection spine spondylodiscitis

Journal

Global spine journal
ISSN: 2192-5682
Titre abrégé: Global Spine J
Pays: England
ID NLM: 101596156

Informations de publication

Date de publication:
06 May 2024
Historique:
medline: 6 5 2024
pubmed: 6 5 2024
entrez: 6 5 2024
Statut: aheadofprint

Résumé

Prognostic study. The objective of this study is to identify predictive factors for cloxacillin susceptibility in spinal infections. A retrospective analysis was conducted using data from January 1, 1997, to December 31, 2021. The study included patients presenting with back pain and either a positive bacterial culture from the spine or radiological evidence of spinal infection (spondylodiscitis and/or epidural abscess) along with positive bacterial blood culture. Among 171 patients (127 males, 44 females), 53.2% had This study identified predictive factors for spinal infection by gram-positive bacteria with cloxacillin resistance and gram-negative bacteria. Patients with lower globulin levels (<33.5 g/L), recent hospitalization within 90 days, or residency in an old age home upon admission should avoid standalone cloxacillin therapy and consider antibiotics with gram-negative coverage. Higher RDW (>16.1%) and CCI scores were associated with increased 1-year all-cause mortality. These findings contribute to treatment decision-making and improving patient outcomes in spinal infections.

Identifiants

pubmed: 38710111
doi: 10.1177/21925682241251814
doi:

Types de publication

Journal Article

Langues

eng

Pagination

21925682241251814

Déclaration de conflit d'intérêts

Declaration of Conflicting InterestsThe author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Auteurs

Chris Yuk Kwan Tang (CYK)

Department of Orthopaedics and Traumatology, The University of Hong Kong, Hong Kong, China.

Pak Leung Ho (PL)

Department of Microbiology and Carol Yu Centre for Infection, University of Hong Kong, Hong Kong, China.

Classifications MeSH