Krouwer Jan S, Cembrowski George S
Krouwer Consulting, Sherborn, Massachusetts 01770, USA.
J Diabetes Sci Technol. 2010 Jan 1;4(1):75-83. doi: 10.1177/193229681000400110.
Glucose performance is reviewed in the context of total error, which includes error from all sources, not just analytical. Many standards require less than 100% of results to be within specific tolerance limits. Analytical error represents the difference between tested glucose and reference method glucose. Medical errors include analytical errors whose magnitude is great enough to likely result in patient harm. The 95% requirements of International Organization for Standardization 15197 and others make little sense, as up to 5% of results can be medically unacceptable. The current American Diabetes Association standard lacks a specification for user error. Error grids can meaningfully specify allowable glucose error. Infrequently, glucose meters do not provide a glucose result; such an occurrence can be devastating when associated with a life-threatening event. Nonreporting failures are ignored by standards. Estimates of analytical error can be classified into the four following categories: imprecision, random patient interferences, protocol-independent bias, and protocol-dependent bias. Methods to estimate total error are parametric, nonparametric, modeling, or direct. The Westgard method underestimates total error by failing to account for random patient interferences. Lawton's method is a more complete model. Bland-Altman, mountain plots, and error grids are direct methods and are easier to use as they do not require modeling. Three types of protocols can be used to estimate glucose errors: method comparison, special studies and risk management, and monitoring performance of meters in the field. Current standards for glucose meter performance are inadequate. The level of performance required in regulatory standards should be based on clinical needs but can only deal with currently achievable performance. Clinical standards state what is needed, whether it can be achieved or not. Rational regulatory decisions about glucose monitors should be based on robust statistical analyses of performance.
在总误差的背景下对葡萄糖检测性能进行了综述，总误差包括来自所有来源的误差，而不仅仅是分析误差。许多标准要求不到100%的结果在特定的公差范围内。分析误差表示检测的葡萄糖与参考方法测定的葡萄糖之间的差异。医学误差包括那些大小足以可能导致患者伤害的分析误差。国际标准化组织15197等标准的95%要求没什么意义，因为高达5%的结果在医学上可能是不可接受的。当前美国糖尿病协会的标准缺乏对用户误差的规范。误差网格可以有意义地规定允许的葡萄糖误差。偶尔，血糖仪无法提供葡萄糖检测结果；当这种情况与危及生命的事件相关联时，可能是毁灭性的。标准忽略了未报告故障。分析误差的估计可分为以下四类：不精密度、随机患者干扰、与方案无关的偏差和与方案有关的偏差。估计总误差的方法有参数法、非参数法、建模法或直接法。韦斯特加德方法由于未考虑随机患者干扰而低估了总误差。劳顿方法是一个更完整的模型。布兰德-奥特曼法、山峰图和误差网格是直接法，使用起来更方便，因为它们不需要建模。可以使用三种类型的方案来估计葡萄糖误差：方法比较、专项研究和风险管理以及现场血糖仪性能监测。当前血糖仪性能标准不充分。监管标准中要求的性能水平应基于临床需求，但只能处理当前可实现的性能。临床标准说明了需要什么，无论能否实现。关于葡萄糖监测仪的合理监管决策应基于对性能的可靠统计分析。
