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Oral Biofilm Analysis of Palatal Expanders by Fluorescence In-Situ Hybridization and Confocal Laser Scanning Microscopy
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Antimicrobial Resistance Patterns and Microbial Epidemiology of Oral and Maxillofacial Space Infections: A Systematic

Yanlan Lai1, Lingling Ye2, Chaohui Wu3

  • 1Department of Pharmacy, School and Hospital of Stomatology, Fujian Medical University, Fuzhou, China.

Microbial Drug Resistance (Larchmont, N.Y.)
|April 21, 2026
PubMed

Insights

Oral and maxillofacial space infections (OMSIs) are serious bacterial conditions. Streptococcus is the most common bacteria, with MRSA also prevalent. Resistance patterns vary, highlighting the need for targeted antimicrobial therapy.

Area of Science:

  • Oral and Maxillofacial Surgery
  • Infectious Diseases
  • Microbiology
  • Pharmacology

Background:

  • Oral and maxillofacial space infections (OMSIs) are polymicrobial and potentially life-threatening.
  • Effective management hinges on timely and appropriate antimicrobial therapy.
  • Understanding current microbial epidemiology and resistance is crucial.

Purpose of the Study:

  • To systematically review and meta-analyze studies on OMSIs.
  • To evaluate the microbial epidemiology and antimicrobial resistance patterns in OMSIs.
  • To identify factors influencing these patterns.

Main Methods:

  • Systematic review and meta-analysis of 53 studies.
  • Inclusion of 12,408 cases of OMSIs.
  • Analysis of pathogen prevalence and antimicrobial susceptibility data.

Main Results:

  • *Streptococcus* was the predominant pathogen (45.51%), followed by *Prevotella* and *Porphyromonas*.
  • Methicillin-resistant *Staphylococcus aureus* (MRSA) comprised 19.18% of *S. aureus* isolates.
  • Diabetic patients showed higher *Klebsiella* prevalence (27.09%).
  • Lowest resistance observed for levofloxacin (11.03%) and cephalosporins (16.83%).
  • Highest resistance noted for gentamicin (39.66%) and erythromycin (39.35%).
  • Infection source, diabetic status, and diagnostic methods influenced patterns.

Conclusions:

  • Microbial landscape and resistance in OMSIs are multifactorial.
  • Local surveillance data combined with influencing factors can guide empirical therapy.
  • Further well-designed studies are needed to optimize antimicrobial use amidst rising resistance.
Keywords:
antimicrobial resistancemeta-analysismicrobial epidemiologyoral and maxillofacial space infectionssystematic review

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