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1.
J Clin Microbiol ; 54(10): 2464-9, 2016 10.
Artigo em Inglês | MEDLINE | ID: mdl-27413193

RESUMO

Vancomycin-resistant enterococci (VRE) are an important cause of health care-acquired infections (HAIs). Studies have shown that active surveillance of high-risk patients for VRE colonization can aid in reducing HAIs; however, these screens generate a significant cost to the laboratory and health care system. Digital imaging capable of differentiating negative and "nonnegative" chromogenic agar can reduce the labor cost of these screens and potentially improve patient care. In this study, we evaluated the performance of the WASPLab Chromogenic Detection Module (CDM) (Copan, Brescia, Italy) software to analyze VRE chromogenic agar and compared the results to technologist plate reading. Specimens collected at 3 laboratories were cultured using the WASPLab CDM and plated to each site's standard-of-care chromogenic media, which included Colorex VRE (BioMed Diagnostics, White City, OR) or Oxoid VRE (Oxoid, Basingstoke, United Kingdom). Digital images were scored using the CDM software after 24 or 40 h of growth, and all manual reading was performed using digital images on a high-definition (HD) monitor. In total, 104,730 specimens were enrolled and automation agreed with manual analysis for 90.1% of all specimens tested, with sensitivity and specificity of 100% and 89.5%, respectively. Automation results were discordant for 10,348 specimens, and all discordant images were reviewed by a laboratory supervisor or director. After a second review, 499 specimens were identified as representing missed positive cultures falsely called negative by the technologist, 1,616 were identified as containing borderline color results (negative result but with no package insert color visible), and 8,234 specimens were identified as containing colorimetric pigmentation due to residual matrix from the specimen or yeast (Candida). Overall, the CDM was accurate at identifying negative VRE plates, which comprised 84% (87,973) of the specimens in this study.


Assuntos
Automação Laboratorial/métodos , Técnicas Bacteriológicas/métodos , Compostos Cromogênicos/metabolismo , Meios de Cultura/química , Infecções por Bactérias Gram-Positivas/diagnóstico , Programas de Rastreamento/métodos , Enterococos Resistentes à Vancomicina/isolamento & purificação , Erros de Diagnóstico , Infecções por Bactérias Gram-Positivas/microbiologia , Humanos , Processamento de Imagem Assistida por Computador/métodos , Imagem Óptica/métodos , Sensibilidade e Especificidade
2.
J Clin Microbiol ; 54(3): 620-4, 2016 Mar.
Artigo em Inglês | MEDLINE | ID: mdl-26719443

RESUMO

Recently, systems have been developed to create total laboratory automation for clinical microbiology. These systems allow for the automation of specimen processing, specimen incubation, and imaging of bacterial growth. In this study, we used the WASPLab to validate software that discriminates and segregates positive and negative chromogenic methicillin-resistant Staphylococcus aureus (MRSA) plates by recognition of pigmented colonies. A total of 57,690 swabs submitted for MRSA screening were enrolled in the study. Four sites enrolled specimens following their standard of care. Chromogenic agar used at these sites included MRSASelect (Bio-Rad Laboratories, Redmond, WA), chromID MRSA (bioMérieux, Marcy l'Etoile, France), and CHROMagar MRSA (BD Diagnostics, Sparks, MD). Specimens were plated and incubated using the WASPLab. The digital camera took images at 0 and 16 to 24 h and the WASPLab software determined the presence of positive colonies based on a hue, saturation, and value (HSV) score. If the HSV score fell within a defined threshold, the plate was called positive. The performance of the digital analysis was compared to manual reading. Overall, the digital software had a sensitivity of 100% and a specificity of 90.7% with the specificity ranging between 90.0 and 96.0 across all sites. The results were similar using the three different agars with a sensitivity of 100% and specificity ranging between 90.7 and 92.4%. These data demonstrate that automated digital analysis can be used to accurately sort positive from negative chromogenic agar cultures regardless of the pigmentation produced.


Assuntos
Automação Laboratorial/métodos , Técnicas Bacteriológicas/métodos , Compostos Cromogênicos/metabolismo , Meios de Cultura/química , Processamento de Imagem Assistida por Computador/métodos , Staphylococcus aureus Resistente à Meticilina/isolamento & purificação , Infecções Estafilocócicas/diagnóstico , Humanos , Sensibilidade e Especificidade , Software
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