Quality assurance for antimicrobial susceptibility testing of in Latin American and Caribbean countries, 2013-2015.

OBJECTIVES

A antimicrobial susceptibility quality control comparison programme was re-established in Latin America and the Caribbean to ensure antimicrobial susceptibility data produced from the region are comparable nationally and internationally.

METHODS

Three panels, consisting of isolates comprising reference strains and other characterised isolates were sent to 11 participating laboratories between 2013 and 2015. Antimicrobial susceptibilities for these isolates were determined using agar dilution, Etest or disc diffusion methods. Modal minimum inhibitory concentrations (MICs) for each panel isolate/antibiotic combination were calculated. The guidelines of the Clinical and Laboratory Standards Institute were used for interpretations of antimicrobial susceptibility. The agreement of MICs with the modal MICs was determined for each of the participating laboratories as well as for each of the antibiotics tested.

RESULTS

Five of 11 laboratories that participated in at least one panel had an overall average agreement between participants' MIC results and modal MICs of >90%. For other laboratories, agreements ranged from 60.0% to 82.4%. The proportion of agreement between interpretations for all the antibiotics, except penicillin and tetracycline, was >90%. The percentages of agreement between MIC results and their modes for erythromycin, spectinomycin, cefixime and azithromycin were >90%. Tetracycline, ceftriaxone and ciprofloxacin agreement ranged from 84.5% to 89.1%, while penicillin had 78.8% agreement between MICs and modal MICs.

CONCLUSIONS

The participating laboratories had acceptable results, similar to other international quality assurance programmes. It is important to ensure continuation of the International Gonococcal Antimicrobial Susceptibility Quality Control Comparison Programme to ensure that participants can identify and correct any problems in antimicrobial susceptibility testing for as they arise and continue to generate reproducible and reliable data.