Internal quality assurance in diagnostic microbiology: A simple approach for insightful data

Abstract

Given the importance of microbiology results on patient care, high quality standards are expected. Internal quality assurance (IQA) could mitigate the limitations of internal quality control, competency assessment and external quality assurance, adding a longitudinal insight, including pre- and post-analytical steps. Here, we implemented an IQA program in our clinical microbiology facilities with blind resubmission of routine samples during 22 months. One-hundred-and-twenty-one out of 123 (98.4%) serological analyses and 112 out of 122 (91.8%) molecular analyses were concordant. Among the discordances in molecular biology analyses, 6 results were low positive samples that turned out negative, likely due to stochastic repartition of nucleic acids. Moreover, one identified retranscription error led us to implement automated results transmission from the Applied Biosystems instruments to the laboratory information system (LIS). Regarding Gram stain microscopy, 560 out of 745 (75.2%) of compared parameters were concordant. As many as 67 out of 84 (79.8%) pairs of culture results were similar, including 16 sterile pairs, 27 having identical identification or description and semi-quantification and 24 only showing variations in semi-quantification with identical description or identification of colonies. Seventeen pairs had diverging identification or description of colonies. Culture was twice only done for one member of the pairs. Regarding antibiotic susceptibility testing, a major discrepancy was observed in 5 out of 48 results (10.4%). In conclusion, serological tests were highly reproducible. Molecular diagnosis also revealed to be robust except when the amounts of nucleic acids present in the sample were close to the limits of detection. Conventional microbiology was less robust with major discrepancies reaching 39.5% of the samples for microscopy. Similarly, culture and antibiotic susceptibility testing were prone to discrepancies. This work was ground for reconsidering multiples aspects of our practices and demonstrates the importance of IQA to complete the other quality management procedures.

Fig 1. Molecular biology results pairs reparation.

Straight line represents the line of identity, expressing perfect match. Pointed lines delaminate a ± 3.3 Ct tolerance margin. Represented are low positive versus negative results (n = 5, diamonds); moderate positive versus negative results (n = 1, square), quantitative discrepancies with over one log₁₀ difference in copies/ml (straight triangles, n = 3), quantitative discrepancy with difference over 3.3Ct but less than one log10 (reversed triangle, n = 1); agreeing positive results (rounds, n = 20). 92 negative agreeing results are not represented on this figure. Note that these results here include two negative pairs and one positive pair of tests that were not quantitatively reported in copies/ml but only reported in Ct number by the laboratory.

Fig 2. AST agreement, per antibiotics.

Counts of concordant pairs of AST results are in green, minor discrepancies (sensitive versus intermediate or intermediate versus resistant) are in yellow and major discrepancies (sensitive versus resistant) are in red. Only antibiotics tested more than 10 times are represented. Complete results are available in S2 Table. AMC = amoxicillin-clavulanic acid; AMK = amikacin; AMP = ampicillin; AMX = amoxicillin; CAZ = ceftazidime; CIP = ciprofloxacin; CLI = clindamycin; CLR = clarithromycin; CRO = ceftriaxone; CXM = cefuroxime; ERY = erythromycin; ETP = ertapenem; FEP = cefepime; FOF = fosfomycin; GEN = gentamicin; IPM = imipenem; LVX = levofloxacin; MEM = meropenem; NIT = nitrofurantoin; PEN = penicillin; SXT = trimethoprim-sulfamethoxazole; TEC = teicoplanin; TET = tetracycline; TOB = tobramycin; TZP = piperacillin-tazobactam; VAN = vancomycin.