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Table 1 Examples of frequently occurring problems in the generation and reporting of clinical antimicrobial resistance data

From: Microbiology Investigation Criteria for Reporting Objectively (MICRO): a framework for the reporting and interpretation of clinical microbiology data

Issue Example
Failure to report key ‘bug-drug’ combinations For both CLSI and EUCAST methods, methicillin resistance in Staphylococcus aureus is determined in the laboratory using cefoxitin (or historically oxacillin) resistance as a proxy [19, 20]. The cefoxitin/oxacillin result is used to infer susceptibility for all beta-lactam drugs, except those with specific activity against methicillin-resistant S. aureus (MRSA, i.e. ceftaroline). Thus, consistent reporting of cefoxitin/oxacillin resistance is required for unambiguous comparison of MRSA proportions between studies.
Reporting of antimicrobials tested on a subset of isolates The issue of first- and second-line AST panels can lead to inconsistent reporting of resistance prevalence. In many instances, second-line agents (e.g. meropenem for Escherichia coli) are only tested on a subset of isolates (e.g. only those resistant to third-generation cephalosporins, such as ceftriaxone, or only in isolates from selected clinical specimens [19]) and reporting of incorrect overall resistance proportions can occur if inappropriate denominators are selected. For example, 100 E. coli isolates are tested against ceftriaxone and 10 (10%) are found to be resistant. These 10 isolates are tested subsequently against meropenem and 1 is resistant. This could be reported as 1/10 (10%) or 1/100 (1%) meropenem resistance. Neither of these percentages may be correct.
Multi-drug resistance definition and reporting With the exception of Mycobacterium tuberculosis (resistance to isoniazid and rifampicin), definitions of bacterial multi-drug resistance (MDR) have been poorly defined and applied. The definition of MDR often reflects local AST selection and antibiotic availability and thus rates are difficult to compare meaningfully [21]. MDR definitions for major bacterial pathogens have been proposed recently but overall consensus is lacking for many species [10, 21, 22].
Changes to published antimicrobial susceptibility breakpoints over time Changes in the definition of resistance can result in misleading time trends and difficulties in inter-study comparisons, if not explicitly dealt with during analysis. For example, the CLSI penicillin minimum inhibitory concentration (MIC) breakpoints for Streptococcus pneumoniae were updated in 2008, resulting in an increased proportion of non-meningitis isolates being reported as susceptible following the change [23].
Classification of infections by location Hospital-acquired infections (HAI) are frequently more drug resistant than community-acquired infections (CAI) caused by the same organism [24, 25]. Failure to classify organisms by timing or location of infection can lead to significant under- or over-estimation of AMR rates.
Selection of appropriate isolates to include in analysis Failure to account for screening specimens (e.g. swabs to determine extended spectrum beta-lactamase Enterobacteriaceae colonisation) and/or duplicate clinical isolates from discrete infection episodes can also result in significant overestimation of resistance [26].
Testing and reporting clinically inappropriate bug-drug combinations The inclusion of susceptibility data for drugs with limited in vivo activity for a given pathogen (e.g. gentamicin and Salmonella Typhi) may lead to clinical confusion and could result in poor treatment outcomes.