Automatic Digital Analysis of Chromogenic Media for Vancomycin-Resistant-Enterococcus Screens Using Copan WASPLab

Abstract

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.

FIG 1

Representative digital images of Colorex VRE chromogenic media and Oxoid VRE captured by the WASPLab. (A) Negative Colorex plate with no growth. (B) Positive Colorex plate containing VRE. (C) A zoomed-in image of clear breakthrough growth with no colorimetric reaction occurring on Colorex media. (D) Negative Oxoid agar. (E) Positive Oxoid agar. (F) A negative plate with breakthrough growth on Oxoid agar.

FIG 2

Examples of discrepant categories determined by a second manual reading. (A1) Automation-positive second manual positive showing a positive single colony that was identified as manual positive after a second observation. (A2) Magnification of inset in panel A1. (B1) Residual matrix creating a colorimetric reaction with the agar but containing growth. (B2) Magnification of inset in panel B1. (C1) A single colony containing colorimetric reaction but not falling within package insert definition of positive VRE. (C2) Magnification of inset in panel C1. (D1) An example of yeast breakthrough developing colors similar to those seen with positive VRE specimens. (D2) Magnification of inset in panel D1.

FIG 3

Cost analysis model of incorporation of CDM automation. The average technologist makes approximately $40.00 an hour with benefits included. In a previous study measuring the labor cost of VRE screening, a negative culture result required 9.6 min of hands-on time, equating to $6.40 of labor cost per negative specimen. Using the WASPLab, the hands-on time required for a negative specimen result is reduced to approximately 2 min, which reduces the cost to $1.33 in labor. In this study, 87,979 negative plates were analyzed. Comparing the two costs, using automation to process these specimens would result in a total savings of $446,053.53 and reductions in costs for the three sites of $46,284.03 (site 1, 14 months), $327,192.45 (site 2, 9 months), and $72,577.05 (site 3, 14 months). Adding the cost savings from batching 40 specimens per screen would increase the total savings to $460,333.53.