Soleimani Neda, Azadi Amir, Esmaeili Mohammad Javad, Ghodsi Fatemeh, Ghahramani Reza, Hafezi Azadeh, Hosseyni Tayebeh, Arabzadeh Arezoo, Khajeh Samira, Farhadi Mahsa, Mohammadzadeh Sahand
Department of Pathology, Shiraz Medical School, Shiraz University of Medical Sciences, Shiraz, Iran.
Department of Pathology, Shiraz Transplant Center, Abu Ali Sina Hospital, Shiraz University of Medical Sciences, Shiraz, Iran.
J Anal Methods Chem. 2021 May 13;2021:9955990. doi: 10.1155/2021/9955990. eCollection 2021.
Although the automation of instruments has reduced the variability of results and errors of analysis, in some laboratories, repeating a test to confirm its accuracy is still performed for critical and noncritical results. However, the importance of repeat testing is not well established yet, and there are no clear criteria for repeating a test.
In this cross-sectional study, all repeated tests for 26 biochemical analytes (i.e., albumin, alkaline phosphatase (ALP), alanine aminotransferase (ALT), amylase, aspartate aminotransferase (AST), bilirubin total (BT), bilirubin direct (BD), blood urea nitrogen (BUN), calcium, chloride (Cl), cholesterol total (CholT), creatine kinase (CK), creatinine (Cr), glucose, gamma-glutamyl transferase (GGT), high-density lipoprotein-cholesterol (HDL-c), iron, lactate dehydrogenase (LDH), LDL-c, lipase, magnesium (Mg), phosphorus (Ph), protein total (ProtT), total iron binding capacity (TIBC), triglyceride (TG), and uric acid) were assessed in both critical and noncritical ranges over two consecutive months (routine subjective test repeats in the first month and rule-based repeats in the second month). To determine the usefulness of test repeats, differences between the initial and verified results were compared with the allowable bias, and repeat testing was considered necessary if it exceeded the allowable bias range. All causes of repeat testing, including linearity flags, delta checks, clinically significant values, and critical values, were also documented. All data, including the cause of repeats, initial and verified results, time, and costs in the two consecutive months, were transferred to Microsoft Excel for analysis. For comparison of data between the months, Student's -test was used.
A total of 7714 repeat tests were performed over two consecutive months. Although a significant decline (38%) was found in repeated tests in the second month ( < 0.001), there was no significant change in the percentage of unnecessary repeats (77% in the first month and 74% in the second month). In both consecutive months, AST and ALT were the most commonly repeated tests, and delta check was the most common cause of repeat testing. Mg, ALP, AST, and lipase showed the highest rates of necessary repeats, respectively (the least stable tests), while albumin, LDL, and CholT tests showed the highest rates of unnecessary repeats, respectively (the most stable tests). The total cost and delay in turnaround time (TAT) due to repeated testing decreased by 32% and 36%, respectively.
Although repeat testing has been shown to be unnecessary in most cases, having a strict policy for repeat testing appears to be more valuable than avoiding it completely. Each laboratory is advised to establish its own protocol for repeat testing based on its own practice.
尽管仪器自动化减少了结果的变异性和分析误差,但在一些实验室中,对于关键和非关键结果仍会重复进行检测以确认其准确性。然而,重复检测的重要性尚未得到充分确立,且对于重复检测也没有明确的标准。
在这项横断面研究中,对26种生化分析物(即白蛋白、碱性磷酸酶(ALP)、丙氨酸氨基转移酶(ALT)、淀粉酶、天冬氨酸氨基转移酶(AST)、总胆红素(BT)、直接胆红素(BD)、血尿素氮(BUN)、钙、氯(Cl)、总胆固醇(CholT)、肌酸激酶(CK)、肌酐(Cr)、葡萄糖、γ-谷氨酰转移酶(GGT)、高密度脂蛋白胆固醇(HDL-c)、铁、乳酸脱氢酶(LDH)、低密度脂蛋白胆固醇(LDL-c)、脂肪酶、镁(Mg)、磷(Ph)、总蛋白(ProtT)、总铁结合力(TIBC)、甘油三酯(TG)和尿酸)的所有重复检测在连续两个月内的关键和非关键范围内进行评估(第一个月为常规主观检测重复,第二个月为基于规则的重复)。为了确定检测重复的有用性,将初始结果与验证结果之间的差异与允许偏差进行比较,如果超过允许偏差范围,则认为重复检测是必要的。还记录了重复检测的所有原因,包括线性标记、增量检查、临床显著值和关键值。所有数据,包括重复原因、初始和验证结果、时间以及连续两个月的成本,都转移到Microsoft Excel中进行分析。为了比较两个月之间的数据,使用了学生t检验。
连续两个月共进行了7714次重复检测。尽管第二个月的重复检测显著下降(38%)(P<0.001),但不必要重复的百分比没有显著变化(第一个月为77%,第二个月为74%)。在连续两个月中,AST和ALT是最常重复检测的项目,增量检查是重复检测最常见的原因。Mg、ALP、AST和脂肪酶分别显示出最高的必要重复率(最不稳定的检测项目),而白蛋白、LDL和CholT检测分别显示出最高的不必要重复率(最稳定的检测项目)。由于重复检测导致的总成本和周转时间(TAT)延迟分别下降了32%和36%。
尽管在大多数情况下重复检测已被证明是不必要的,但制定严格的重复检测政策似乎比完全避免重复检测更有价值。建议每个实验室根据自身实践建立自己的重复检测方案。