C Abou-Diwan, R Hempton, J Clouet, D Diabate, J Aguanno
{"title":"B-033 Real World Assessment of the Impact of Infectious Disease Assays on Workflow Capabilities of Siemens Atellica IM Analyzers","authors":"C Abou-Diwan, R Hempton, J Clouet, D Diabate, J Aguanno","doi":"10.1093/clinchem/hvae106.397","DOIUrl":null,"url":null,"abstract":"Background Instrument immunoassay throughputs publicized in the industry are often theoretical, performed in relatively smaller scale, and/or in the best case generated only with fast assays, not representing the typical assay mix of routine activity. Infectious disease (ID) serology assays typically have long analytical times and have the potential to influence throughput capabilities and turnaround time (TAT) of other assays with shorter analytical times. The objective of this study is to utilize real world evidence across a large fleet of Atellica® IM 1300 and IM 1600 analyzers representing variously sized laboratories, using variations of ID assay mixes, to assess the impact on TAT on select STAT immunoassays. Methods Assay mix, test volumes and TAT data was mined from the Atellica® Smart Remote Services (SRS), a Siemens Healthineers proprietary remote connectivity platform over 3 distinct 14-day time windows. Real world data from >1800 Atellica IM and >8 million tests were queried per time window for the following ID assays: HIV, Hepatitis B, Hepatitis C, TORCH, Syphilis (long analytical time) and a selection of non-ID immunoassays: hs-troponin I (TNIH), Thyroid Stimulating Hormone (TSH3UL), total HCG (ThCG), and B-Type Natriuretic Peptide (BNP) (short analytical time). Median TAT for short assay was analyzed with 6 variations of ID assay mix (0%, <10%, <20%, <30%, <40%, <50%) in the run representing increasing percentages of assays requiring longer incubation times. TAT was represented as barcode to result and aspiration to result. Results The median TAT for TNIH remained consistent at 10.1 minutes across increasing % of ID assays (N=100961). The median TAT for TNIH for platforms not running ID assays (83237) remained consistent at 10.03 minutes. The median TAT for TSH remained consistent at 14.02 minutes across increasing % of ID assays (N=1183344). The median TAT for TSH for platforms not running ID assays (N=480219) remained consistent at 13.98 minutes. The median TAT for ThCG remained consistent at 10.28 minutes across increasing % of ID assays (N=24677). The median TAT for ThCG for platforms not running ID assays (N=79275) remained consistent at 10.27 minutes. The median TAT for BNP remained consistent at 10.1 minutes across increasing % of ID assays (N=42949). The median TAT for BNP for platforms not running ID assays (N=14990) remained consistent at 10.03 minutes. Conclusions Throughput and TAT on the Atellica IM Analyzer is relatively unaffected by mix of longer-incubation and shorter-incubation assays. The dual incubation rings allow more flexibility in the mix of incubation times with predictable and consistent TAT for all assays including STAT.","PeriodicalId":10690,"journal":{"name":"Clinical chemistry","volume":"57 1","pages":""},"PeriodicalIF":7.1000,"publicationDate":"2024-10-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Clinical chemistry","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1093/clinchem/hvae106.397","RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"MEDICAL LABORATORY TECHNOLOGY","Score":null,"Total":0}
引用次数: 0
Abstract
Background Instrument immunoassay throughputs publicized in the industry are often theoretical, performed in relatively smaller scale, and/or in the best case generated only with fast assays, not representing the typical assay mix of routine activity. Infectious disease (ID) serology assays typically have long analytical times and have the potential to influence throughput capabilities and turnaround time (TAT) of other assays with shorter analytical times. The objective of this study is to utilize real world evidence across a large fleet of Atellica® IM 1300 and IM 1600 analyzers representing variously sized laboratories, using variations of ID assay mixes, to assess the impact on TAT on select STAT immunoassays. Methods Assay mix, test volumes and TAT data was mined from the Atellica® Smart Remote Services (SRS), a Siemens Healthineers proprietary remote connectivity platform over 3 distinct 14-day time windows. Real world data from >1800 Atellica IM and >8 million tests were queried per time window for the following ID assays: HIV, Hepatitis B, Hepatitis C, TORCH, Syphilis (long analytical time) and a selection of non-ID immunoassays: hs-troponin I (TNIH), Thyroid Stimulating Hormone (TSH3UL), total HCG (ThCG), and B-Type Natriuretic Peptide (BNP) (short analytical time). Median TAT for short assay was analyzed with 6 variations of ID assay mix (0%, <10%, <20%, <30%, <40%, <50%) in the run representing increasing percentages of assays requiring longer incubation times. TAT was represented as barcode to result and aspiration to result. Results The median TAT for TNIH remained consistent at 10.1 minutes across increasing % of ID assays (N=100961). The median TAT for TNIH for platforms not running ID assays (83237) remained consistent at 10.03 minutes. The median TAT for TSH remained consistent at 14.02 minutes across increasing % of ID assays (N=1183344). The median TAT for TSH for platforms not running ID assays (N=480219) remained consistent at 13.98 minutes. The median TAT for ThCG remained consistent at 10.28 minutes across increasing % of ID assays (N=24677). The median TAT for ThCG for platforms not running ID assays (N=79275) remained consistent at 10.27 minutes. The median TAT for BNP remained consistent at 10.1 minutes across increasing % of ID assays (N=42949). The median TAT for BNP for platforms not running ID assays (N=14990) remained consistent at 10.03 minutes. Conclusions Throughput and TAT on the Atellica IM Analyzer is relatively unaffected by mix of longer-incubation and shorter-incubation assays. The dual incubation rings allow more flexibility in the mix of incubation times with predictable and consistent TAT for all assays including STAT.
背景 业界公布的仪器免疫测定通量往往是理论上的、在相对较小的范围内进行的,和/或在最好的情况下仅由快速测定产生,并不代表常规活动的典型测定组合。传染病(ID)血清学检测通常分析时间较长,有可能影响分析时间较短的其他检测的通量能力和周转时间(TAT)。本研究的目的是利用代表不同规模实验室的大量 Atellica® IM 1300 和 IM 1600 分析仪的实际证据,使用不同的 ID 化验组合,评估对特定 STAT 免疫测定 TAT 的影响。方法 从Atellica®智能远程服务(SRS)(西门子医疗专有的远程连接平台)中挖掘化验组合、化验量和TAT数据,历时3个不同的14天时间窗口。每个时间窗口查询了来自1800个Atellica IM和800万次检测的真实数据,涉及以下ID检测:HIV、乙肝、丙肝、TORCH、梅毒(分析时间长)和部分非ID免疫检测:hs-troponin I (TNIH)、促甲状腺激素 (TSH3UL)、总 HCG (ThCG) 和 B 型钠尿肽 (BNP)(分析时间短)。在运行中使用 6 种不同的 ID 混合测定(0%、<10%、<20%、<30%、<40%、<50%)分析短测定的中位 TAT,代表需要较长孵育时间的测定所占的比例不断增加。TAT 表示从条形码到结果和从抽吸到结果的时间。结果 TNIH 的中位 TAT 始终为 10.1 分钟,ID 检测的百分比不断增加(N=100961)。未运行 ID 检测的平台(83237)的 TNIH 中位 TAT 始终为 10.03 分钟。TSH的中位TAT在ID检测比例增加时(N=1183344)保持一致,为14.02分钟。未运行 ID 检测的平台(N=480219)TSH 的中位 TAT 始终为 13.98 分钟。ThCG的中位TAT在ID检测比例增加时(N=24677)保持一致,为10.28分钟。未运行 ID 检测的平台(N=79275)ThCG 的中位 TAT 始终为 10.27 分钟。在 ID 检测比例不断增加的情况下(N=42949),BNP 的中位 TAT 始终为 10.1 分钟。未运行 ID 检测的平台(N=14990)的 BNP 中位 TAT 始终为 10.03 分钟。结论 Atellica IM 分析仪的通量和 TAT 相对不受混合使用长孵育和短孵育测定的影响。双孵育环可以更灵活地混合孵育时间,包括 STAT 在内的所有检测的 TAT 均可预测且一致。
期刊介绍:
Clinical Chemistry is a peer-reviewed scientific journal that is the premier publication for the science and practice of clinical laboratory medicine. It was established in 1955 and is associated with the Association for Diagnostics & Laboratory Medicine (ADLM).
The journal focuses on laboratory diagnosis and management of patients, and has expanded to include other clinical laboratory disciplines such as genomics, hematology, microbiology, and toxicology. It also publishes articles relevant to clinical specialties including cardiology, endocrinology, gastroenterology, genetics, immunology, infectious diseases, maternal-fetal medicine, neurology, nutrition, oncology, and pediatrics.
In addition to original research, editorials, and reviews, Clinical Chemistry features recurring sections such as clinical case studies, perspectives, podcasts, and Q&A articles. It has the highest impact factor among journals of clinical chemistry, laboratory medicine, pathology, analytical chemistry, transfusion medicine, and clinical microbiology.
The journal is indexed in databases such as MEDLINE and Web of Science.