Inducible clindamycin resistance among clinical isolates of Staphylococcus aureus - Kanwal Deep Singh Lyall; Veenu Gupta; Deepinder Chhina (Wolters Kluwer Medknow Publications, 2013)
Introduction: The resistance to antimicrobial agents among staphylococci is an increasing problem. This has led to renewed interest in the usage of macrolide-lincosamide-streptogramin B (MLSB) antibiotics to treat Staphylococcus aureus infections. Clinical failure has been reported due to multiple mechanisms that confer resistance to MLSB antibiotics. The present study was aimed to detect inducible clindamycin resistance among S. aureus isolates and to study the relationship between clindamycin and methicillin resistance. Materials and Methods: During a period of 1 year, a total of 593 S. aureus isolates from various clinical specimens were included in the study. Antimicrobial susceptibility test was done by Kirby-Bauer's disc diffusion method as per Clinical and Laboratory Standards Institute (CLSI) guidelines. For detection of inducible clindamycin resistance, D test using erythromycin and clindamycin as per CLSI guidelines was performed, and three different phenotypes were interpreted as methicillin-sensitive (MS) phenotype (D test negative), inducible MLSB (iMLSB) phenotype (D test positive), and constitutive MLSB phenotype. Results: Of the total 593 S. aureus isolates, majority were obtained from pus (31.1%) followed by blood and body fluids (27.3%). All the isolates were sensitive to vancomycin, teicoplanin, and linezolid. Out of 306 (51.7%) erythromycin resistant isolates, 280 (91.5%) were methicillin-resistant S. aureus (MRSA) and 26 (8.5%) were methicillin-sensitive S. aureus (MSSA). iMLSB phenotype in 33.3%, MS phenotype in 44.8%, and constitutive MLSB phenotype was observed in 21.9% of isolates. Inducible clindamycin resistance was almost equal among MRSA and MSSA isolates. Conclusion: D test should be included as a mandatory method in routine disc diffusion testing to detect inducible clindamycin resistance in staphylococci for the optimum treatment of patients.