Trends in antimicrobial susceptibility patterns in healthcare-associated methicillin-resistant Staphylococcus aureus from bloodstream infections: A joinpoint regression analysis

To the Editor—Staphylococcus aureus ranks third among pathogens causing healthcare-associated bloodstream infections in Brazil, and >60% of reported isolates are methicillin resistant (ie, MRSA).1 The rise of healthcare-associated MRSA in Brazil occurred in the 1990s, mostly due to the extensive spread of the Brazilian epidemic clone (BEC).2 BEC harbored the staphylococcal chromosome cassette (SCC) mec type III and were typically resistant to several antimicrobials, such as trimethoprim/sulfametoxazole (TMP/SMX), quinolones, and clindamycin. For a long time (before the national registration of linezolid and daptomycin), glycopeptides remained as the sole therapeutic option for healthcare-associated MRSA (HA-MRSA) in Brazil.3 Recent studies report that BEC has been substituted for clones harboring SCCmec type II, with remarkable increasing susceptibility to TMP/SMX and modest increases in susceptibility to ciprofloxacin and clindamycin.4,5 Sporadic findings have indicated that TMX/SMX-susceptible, SCCmec type IV–harboring MRSA clones, which probably originated in the community, have spread within Brazilian hospitals.6,7 Susceptibility to TMP/SMX, ciprofloxacin, and clindamycin has been proposed as a proxy marker of the so-called community-associated MRSA (CA-MRSA) invading hospitals.8 Time series analysis, especially joinpoint regression techniques, which detect changes in time trends, have been rather infrequently applied to analyze long-term trends in antimicrobial resistance within healthcare settings. In a classic article, Deurenberg and Stobberingh10 describe the blurring of distinctions between CA- and HA-MRSA and argue for a pure molecular definition, based on SCCmec typing. Because strain typing is not widely available, especially in low-to-middle income countries, careful long-term follow-up of resistant profiles may provide a reasonable proxy for detecting ecological changes in MRSA infections.