OBJECTIVES: Methicillin-resistant Staphylococcus aureus is a common cause of ventilator-associated pneumonia and can be identified by the mecA gene that confers resistance. The objective was to develop a polymerase chain reaction assay for mecA using mini-bronchoalveolar lavage to allow rapid diagnosis of ventilator associated pneumonia attributable to methicillin-resistant Staphylococcus aureus. DESIGN: Real-time quantitative polymerase chain reaction was developed using serial dilution of plasmids containing known amounts of mecA gene fragments. Specificity of molecular identification was based on the presence of the mecA gene and S. aureus-specific femA-SA gene, with absence of Staphylococcus epidermidis specific femA-SE. SETTING AND PATIENTS: To validate the polymerase chain reaction, we compared it to mini-bronchoalveolar lavage quantitative cultures in 100 mechanically ventilated patients with suspected pneumonia. We derived a threshold value for defining a positive polymerase chain reaction based on a priori criteria of 100% sensitivity. We then tested the polymerase chain reaction using this threshold value on a separate cohort of 50 patients. MAIN RESULTS: Polymerase chain reaction was able to detect mecA down to a copy number of three, with a high degree of correlation (r=.999). The area under the receiver-operating characteristic curve for polymerase chain reaction was 0.98 (95% confidence interval, 0.93-0.99). Using a cut-point of >or=421 for the polymerase chain reaction resulted in sensitivity of 100%, specificity of 87% (95% confidence interval 81%-94%), positive predictive value of 39% (95% confidence interval, 29%-49%), negative predictive value of 100%, and an overall correct classification rate of 89%. Applying the polymerase chain reaction with a cut-point of >or=421 to the second cohort resulted in a sensitivity of 100% and a specificity of 80%. CONCLUSIONS: Quantitative polymerase chain reaction of mecA combined with femA-SA and femA-SE detection was able to rapidly and accurately diagnose methicillin-resistant S. aureus.
OBJECTIVES: Methicillin-resistant Staphylococcus aureus is a common cause of ventilator-associated pneumonia and can be identified by the mecA gene that confers resistance. The objective was to develop a polymerase chain reaction assay for mecA using mini-bronchoalveolar lavage to allow rapid diagnosis of ventilator associated pneumonia attributable to methicillin-resistant Staphylococcus aureus. DESIGN: Real-time quantitative polymerase chain reaction was developed using serial dilution of plasmids containing known amounts of mecA gene fragments. Specificity of molecular identification was based on the presence of the mecA gene and S. aureus-specific femA-SA gene, with absence of Staphylococcus epidermidis specific femA-SE. SETTING AND PATIENTS: To validate the polymerase chain reaction, we compared it to mini-bronchoalveolar lavage quantitative cultures in 100 mechanically ventilated patients with suspected pneumonia. We derived a threshold value for defining a positive polymerase chain reaction based on a priori criteria of 100% sensitivity. We then tested the polymerase chain reaction using this threshold value on a separate cohort of 50 patients. MAIN RESULTS: Polymerase chain reaction was able to detect mecA down to a copy number of three, with a high degree of correlation (r=.999). The area under the receiver-operating characteristic curve for polymerase chain reaction was 0.98 (95% confidence interval, 0.93-0.99). Using a cut-point of >or=421 for the polymerase chain reaction resulted in sensitivity of 100%, specificity of 87% (95% confidence interval 81%-94%), positive predictive value of 39% (95% confidence interval, 29%-49%), negative predictive value of 100%, and an overall correct classification rate of 89%. Applying the polymerase chain reaction with a cut-point of >or=421 to the second cohort resulted in a sensitivity of 100% and a specificity of 80%. CONCLUSIONS: Quantitative polymerase chain reaction of mecA combined with femA-SA and femA-SE detection was able to rapidly and accurately diagnose methicillin-resistant S. aureus.
Authors: Naomi J Gadsby; Clark D Russell; Martin P McHugh; Harriet Mark; Andrew Conway Morris; Ian F Laurenson; Adam T Hill; Kate E Templeton Journal: Clin Infect Dis Date: 2016-01-07 Impact factor: 9.079