标准化的预分析代码(SPREC)聚集了热缺血(WIT),冷缺血(CIT),和固定时间(FIT)在一个精确的格式。尽管在欧洲体外诊断法规或美国国立卫生研究院广泛的分析前计划的支持下,其重要性日益提高,鲜为人知的是,它在生物样本手术标本中的经验发生。在几个步骤中,组织银行伯尔尼实现了一个完全翔实的SPREC代码,具有来自10,555CIT的见解,4,740WIT,和3,121FIT值。在根据精益六西格玛原则进行工艺优化时,我们确定了SPREC代码作为样本特征和可追溯过程参数的双重作用。通过这项分析前研究,我们概述了各种器官的真实数据,这些器官在WIT方面存在特定差异,CIT,和FIT值。此外,我们的FIT数据表明,由于周末延误,SPREC固定有可能适应混凝土石蜡包埋时间点,并将其类别扩展到72小时以上。此外,我们从工作负载中确定了分析前变量的依赖关系,白天,和诊所是可行的精益流程管理。因此,白天简化的生物作业工作流程对工作负载高峰具有显著的弹性,在重应力条件下,将天然组织处理(即CIT)的周转时间从74.6分钟减少到46.1分钟。总之,即使在过程优化下,也有手术特定的预分析在手术病理上受到限制,这可能会影响生物标志物从一个实体转移到另一个实体。除了样本特征之外,SPREC编码对于组织库和病理学研究所跟踪WIT非常有益,CIT,和适合过程优化和监测测量。
The standardized preanalytical code (
SPREC) aggregates warm ischemia (WIT), cold ischemia (CIT), and fixation times (FIT) in a precise format. Despite its growing importance underpinned by the European in vitro diagnostics regulation or broad preanalytical programs by the National Institutes of Health, little is known about its empirical occurrence in biobanked surgical specimen. In several steps, the Tissue Bank Bern achieved a fully informative
SPREC code with insights from 10,555 CIT, 4,740 WIT, and 3,121 FIT values. During process optimization according to LEAN six sigma principles, we identified a dual role of the
SPREC code as a sample characteristic and a traceable process parameter. With this preanalytical study, we outlined real-life data in a variety of organs with specific differences in WIT, CIT, and FIT values. Furthermore, our FIT data indicate the potential to adapt the
SPREC fixation toward concrete paraffin-embedding time points and to extend its categories beyond 72 h due to weekend delays. Additionally, we identified dependencies of preanalytical variables from workload, daytime, and clinics that were actionable with LEAN process management. Thus, streamlined biobanking workflows during the day were significantly resilient to workload peaks, diminishing the turnaround times of native tissue processing (i.e. CIT) from 74.6 to 46.1 min under heavily stressed conditions. In conclusion, there are surgery-specific preanalytics that are surgico-pathologically limited even under process optimization, which might affect biomarker transfer from one entity to another. Beyond sample characteristics,
SPREC coding is highly beneficial for tissue banks and Institutes of Pathology to track WIT, CIT, and FIT for process optimization and monitoring measurements.