基于六西格玛模式评价血脂项目的分析性能及其质量控制方案的设计

doi:10.3877/cma.j.issn.2095-5820.2025.04.002

目的

基于六西格玛（6σ）模式对血脂检测项目的分析性能进行评价，并为其制定个性化的室内质量控制（IQC）方案和精准的改进措施。

方法

以WS/T 403-2024《临床化学检验常用项目分析质量标准》作为血脂检测项目的质量目标，以2024年陕西省卫生健康委员会临床检验中心提供的第一次血脂室间质量评价数据评估正确度，以同期本实验室血脂检测项目的IQC数据评估精密度，基于上述3个指标评价血脂项目的σ水平，并在标准化的σ性能验证图上进行标示。同时，基于具有批长度的Westgard西格玛规则流程图和质量目标指数结果，为实验室血脂项目制定个性化的IQC方案和改进措施。

结果

总胆固醇（TC）、三酰甘油（TG）、高密度脂蛋白胆固醇（HDL-C）、低密度脂蛋白胆固醇（LDL-C）及载脂蛋白A（Apo-A）的分析性能均达到“良好”水平，载脂蛋白B（Apo-B）的分析性能达到“世界一流”水平。本研究建议对TC、TG、HDL-C、LDL-C和Apo-A推荐采取的IQC策略为 1_3s/2_2s/R_4s/4_1s多规则（N=4），分析批长度为200个样本。对Apo-B，建议采取的IQC策略为1_3s多规则（N=2），分析批长度为1000个样本。同时，血脂TC、TG、HDL-C、LDL-C和Apo-A 5项均在精密度方面存在不足，需要实施相应的措施来优先改进精密度。

结论

6σ模式在血脂项目的性能评价、质量控制方案设计和质量改进中具有重要的应用价值，能够有效提升实验室的检测能力。

关键词: 六西格玛, 血脂项目, 质量目标指数, 质量控制

Objective

To evaluate the analytical performance of lipid detection items using the Six Sigma model and to develop individualized internal quality control (IQC) strategies and precise improvement measures.

Methods

The WS/T 403-2024 Analytical Quality Standards for Common Clinical Chemistry Tests served as the quality goal for lipid testing. Accuracy was assessed using data from the first 2024 external quality assessment of lipid provided by the Shaanxi Provincial Clinical Laboratory Center, while precision was evaluated based on IQC data from our laboratory. The sigma metric for each lipid parameter was calculated based on these three indices and plotted on a standardized sigma performance chart. Furthermore, individualized IQC strategies and improvement measures were formulated using the Westgard Sigma Rules flowchart and by analyzing the quality goal index.

Results

The analytical performance of total cholesterol (TC), triglycerides (TG), high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), and apolipoprotein A (Apo-A) was rated as "Good", while that of apolipoprotein B (Apo-B) achieved "World Class" level. The recommended IQC strategy for TC, TG, HDL-C, LDL-C, and Apo-A were the 1_3s/2_2s/R_4s/4_1s multi-rule approach (N=4) with a batch length of 200 samples. For Apo-B, the recommended strategy was the 1_3s multi-rule (N=2) with a batch length of 1000 samples. Notably, precision deficiencies were observed in five lipid analytes, warranting prioritized improvement measures.

Conclusion

The Six Sigma model demonstrates significant utility in evaluating lipid analyte performance, designing IQC strategies, and implementing quality improvements, thereby enhancing laboratory testing capabilities.

Key words: Six Sigma, blood lipids, quality goal index, quality control

图1 血脂项目标准化的σ性能验证图

表1 血脂项目的σ水平

项目	TEa/%	Bias_合成/%	CV₁/%	CV₂/%	CV_合成/%	σ水平
TC	9	0.66	1.78	1.87	1.83	4.56
TG	14	0.23	2.87	3.08	2.98	4.62
HDL-C	20	0.01	3.95	4.16	4.06	4.92
LDL-C	20	0.57	4.11	4.41	4.26	4.56
Apo-A	25	0.07	5.68	5.88	5.78	4.31
Apo-B	25	0.57	2.31	2.18	2.25	10.86

表1 血脂项目的σ水平

项目	TEa/%	Bias_合成/%	CV₁/%	CV₂/%	CV_合成/%	σ水平
TC	9	0.66	1.78	1.87	1.83	4.56
TG	14	0.23	2.87	3.08	2.98	4.62
HDL-C	20	0.01	3.95	4.16	4.06	4.92
LDL-C	20	0.57	4.11	4.41	4.26	4.56
Apo-A	25	0.07	5.68	5.88	5.78	4.31
Apo-B	25	0.57	2.31	2.18	2.25	10.86

图2 具有批长度的Westgard西格玛规则

表2 血脂项目质量改进方案（σ值＜6）

项目	Bias_合成/%	CV_合成/%	QGI	改进措施
TC	0.66	1.83	0.24	精密度
TG	0.23	2.98	0.05	精密度
HDL-C	0.01	4.06	0.00	精密度
LDL-C	0.57	4.26	0.09	精密度
Apo-A	0.07	5.78	0.01	精密度

表2 血脂项目质量改进方案（σ值＜6）

项目	Bias_合成/%	CV_合成/%	QGI	改进措施
TC	0.66	1.83	0.24	精密度
TG	0.23	2.98	0.05	精密度
HDL-C	0.01	4.06	0.00	精密度
LDL-C	0.57	4.26	0.09	精密度
Apo-A	0.07	5.78	0.01	精密度

表3 实施改进措施后的各项目CV/%

项目	2024年6月		2024年7月		2024年8月
项目	CV₁	CV₂	CV₁	CV₂	CV₁	CV₂
TC	1.74	1.54	1.54	1.32	1.58	1.36
TG	2.53	2.64	2.45	2.57	2.32	2.21
HDL-C	3.67	3.41	3.35	3.21	3.12	3.21
LDL-C	4.01	4.22	3.56	3.42	3.65	3.45
Apo-A	4.96	5.11	4.54	4.65	4.34	4.21

表3 实施改进措施后的各项目CV/%

项目	2024年6月		2024年7月		2024年8月
项目	CV₁	CV₂	CV₁	CV₂	CV₁	CV₂
TC	1.74	1.54	1.54	1.32	1.58	1.36
TG	2.53	2.64	2.45	2.57	2.32	2.21
HDL-C	3.67	3.41	3.35	3.21	3.12	3.21
LDL-C	4.01	4.22	3.56	3.42	3.65	3.45
Apo-A	4.96	5.11	4.54	4.65	4.34	4.21

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Evaluating the analytical performance of blood lipid tests and designing quality control strategies using the Six Sigma model