Microbiology of acute bacterial skin and skin-structure infections in Greece: A proposed clinical prediction score for the causative pathogen

Int J Antimicrob Agents. 2019 Dec;54(6):750-756. doi: 10.1016/j.ijantimicag.2019.08.020. Epub 2019 Aug 31.

Abstract

Although clinical definitions of acute bacterial skin and skin-structure infection (ABSSSI) are now well established, guidance of the prediction of likely pathogens based on evidence is missing. This was a large survey of the microbiology of ABSSSIs in Greece. During the period November 2014 to December 2016, all admissions for ABSSSI in 16 departments of internal medicine or surgery in Greece were screened to determine the likely bacterial aetiology. Samples were cultured on conventional media. Expression of the SA442, mecA/mecC and SCCmec-orfX junction genes was assessed. Following univariate and forward logistic regression analysis, clinical characteristics were used to develop scores to predict the likely pathogen with a target of 90% specificity. In total, 1027 patients were screened and 633 had positive microbiology. Monomicrobial infection by Gram-positive cocci occurred in 52.1% and by Gram-negative bacteria in 20.5%, and mixed infection by Gram-positive cocci and Gram-negative bacteria in 27.3%. The most common isolated pathogens were Staphylococcus aureus and coagulase-negative staphylococci. Resistance to methicillin was 57.3% (53.5-61.1%). Three predictive scores were developed: one for infection by methicillin-resistant S. aureus, incorporating recent hospitalisation, atrial fibrillation, residency in long-term care facility (LTCF) and stroke; one for mixed Gram-positive and Gram-negative infections, incorporating localisation of ABSSSI in lumbar area, fluoroquinolone intake in last 6 days, residency in LTCF and stroke; and another for Gram-negative infection, incorporating skin ulcer presentation, peptic ulcer and solid tumour malignancy. In conclusion, methicillin-resistant staphylococci are the main pathogens of ABSSSIs. The scores developed may help to predict the likely pathogen.

Keywords: ABSSSI; Causative pathogen; Methicillin resistance; Prediction score; Skin infection.

MeSH terms

  • Anti-Bacterial Agents / pharmacology
  • Bacteria / classification*
  • Drug Resistance, Bacterial
  • Female
  • Greece
  • Humans
  • Male
  • Skin Diseases, Bacterial / epidemiology
  • Skin Diseases, Bacterial / microbiology*
  • Soft Tissue Infections / epidemiology*
  • Soft Tissue Infections / microbiology*

Substances

  • Anti-Bacterial Agents