Department of Pathology, UC San Diego Health, San Diego, California, USA.
Division of Biostatistics and Bioinformatics, Herbert Wertheim School of Public Health and Human Longevity Science, UC San Diego, San Diego, California, USA.
Microbiol Spectr. 2022 Oct 26;10(5):e0144222. doi: 10.1128/spectrum.01442-22. Epub 2022 Aug 16.
Urine cultures are among the highest-volume tests in clinical microbiology laboratories and usually require considerable manual labor to perform. We evaluated the APAS Independence automated plate reader system and compared it to our manual standard of care (SOC) for processing urine cultures. The APAS device provides automated image interpretation of urine culture plate growth and sorts those images that require further evaluation. We examined 1,519 specimens over a 4-month period and compared the APAS growth interpretations to our SOC. We found that 72 of the 1,519 total specimens (4.74%) had growth discrepancies, where these specimens were interpreted differently by the APAS and the technologist, which required additional evaluation of plate images on the APAS system. Overall, there were 56 discrepancies in pathogen identification, which were present in 3.69% of the cultures. An additional pathogen was uncovered in a majority of these discrepancies; 12 (21.4%) identified an additional pathogen for the SOC, and 40 (71.4%) identified an additional pathogen for the APAS workflow. We found 214 (2.69%) antimicrobial susceptibility test (AST) discrepancies; 136 (1.71%) minor errors (mEs), 41 (0.52%) major errors (MEs), and 36 (0.45%) very major errors (VMEs). Many of the MEs and VMEs occurred in only a small subset of 13 organisms, suggesting that the specimen may have had different strains of the same pathogens with differing AST results. Given the significant labor required to perform urine cultures, the APAS Independence system has the potential to reduce manual labor while maintaining the identity and AST results of urinary pathogens. Urine cultures are among the highest-volume tests performed in clinical microbiology facilities and require considerable manual labor to perform. We compared the results of our manual SOC workflow with that of the APAS Independence system, which provides automated image interpretation and sorting of urine culture plates based on growth. We examined 1,519 urine cultures processed using both workflows and found that only 4.74% had growth pattern discrepancies and 3.69% pathogen identification discrepancies. There was substantial agreement in AST results between workflows, with only 2.69% having discrepancies. Only 1.71% of the ASTs had mEs, 0.52% had MEs, and 0.45% had VMEs, with most of the MEs and VMEs belonging to a small subset of organisms. The APAS system significantly decreased manual urine culture processing, while providing similar results to the SOC. As such, incorporating such automation into laboratory workflows has the potential to significantly improve efficiency.
尿液培养是临床微生物实验室中检测量最大的项目之一，通常需要大量的人工劳动来完成。我们评估了 APAS Independence 自动化平板读取器系统，并将其与我们的手动标准操作程序 (SOC) 进行了比较，用于处理尿液培养。APAS 设备提供尿液培养板生长的自动图像解释，并对需要进一步评估的图像进行分类。我们在 4 个月的时间内检查了 1519 个标本，并将 APAS 的生长解释与我们的 SOC 进行了比较。我们发现，在 1519 个总标本中有 72 个（4.74%）存在生长差异，这些标本的 APAS 和技术人员的解释不同，这需要在 APAS 系统上对平板图像进行额外的评估。总的来说，在培养物中发现了 56 个病原体鉴定差异，占培养物的 3.69%。在这些差异中，大多数都发现了额外的病原体；12 个（21.4%）为 SOC 确定了额外的病原体，40 个（71.4%）为 APAS 工作流程确定了额外的病原体。我们发现了 214 个（2.69%）抗菌药物敏感性试验（AST）差异；136 个（1.71%）次要误差（mEs），41 个（0.52%）主要误差（MEs）和 36 个（0.45%）非常大的误差（VMEs）。许多 MEs 和 VMEs 仅发生在少数 13 种生物中的一小部分，这表明标本可能具有不同的同一病原体的不同菌株，具有不同的 AST 结果。鉴于尿液培养需要大量的人工劳动，APAS Independence 系统具有减少人工劳动的潜力，同时保持尿源性病原体的身份和 AST 结果。 尿液培养是临床微生物学实验室中检测量最大的项目之一，需要大量的人工劳动来完成。我们将我们的手动 SOC 工作流程的结果与 APAS Independence 系统进行了比较，该系统提供基于生长的尿液培养平板的自动图像解释和分类。我们检查了使用两种工作流程处理的 1519 个尿液培养物，发现只有 4.74%的培养物存在生长模式差异，3.69%的培养物存在病原体鉴定差异。工作流程之间的 AST 结果具有高度一致性，只有 2.69%存在差异。只有 1.71%的 AST 有 mEs，0.52%有 MEs，0.45%有 VMEs，大多数 MEs 和 VMEs 属于一小部分生物体。APAS 系统显著减少了手动尿液培养处理，同时提供了与 SOC 相似的结果。因此，将这种自动化纳入实验室工作流程有可能显著提高效率。
