Cox Daniel J, Gonder-Frederick Linda, Ritterband Lee, Clarke William, Kovatchev Boris P
Department of Psychiatry and Neurobehavioral Sciences, University of Virginia Health System, Charlottesville, Virginia 22908, USA.
Diabetes Care. 2007 Jun;30(6):1370-3. doi: 10.2337/dc06-1386. Epub 2007 Mar 15.
Prevention of severe hypoglycemia (SH) is premised partially on the ability to accurately anticipate its occurrence. This study prospectively tests methods for predicting SH using blood glucose meter readings.
One hundred adults with type 1 diabetes were followed for 6 months, and 79 insulin-using adults with type 2 diabetes were followed for 4 months. During this time, subjects' routine self-monitored blood glucose (SMBG) readings were stored on and retrieved from memory meters, and participants were queried biweekly about occurrence of SH. Respective demographics for the two groups were age 40.7 and 50.2 years, duration of diabetes 20.0 and 12.2 years, A1C 7.6 and 8.8%, and male sex 43 and 39%, respectively.
Relative risk for SH, quantified by the ratio of an individual's low blood glucose index (LBGI) based on the previous 150 SMBG readings to the LBGI based on recent SMBG readings, increased significantly in the 24 h before SH episodes in individuals with type 1 and type 2 diabetes (t = 10.3, P < 0.0001, and t = 4.2, P < 0.001, respectively). A sliding algorithm detected 58% of imminent (within 24 h) SH episodes in the type 1 diabetic group and 60% of those in the type 2 diabetic group when three SMBG readings were available in the 24 h before an episode. Detection increased to 63 and 75%, respectively, if five SMBG readings were available in the 24 h before an episode.
SH often follows a specific blood glucose fluctuation pattern that is identifiable from SMBG. Thus, partial prediction of imminent SH is possible, providing a potential tool to trigger self-regulatory prevention of significant hypoglycemia.
预防严重低血糖（SH）部分基于准确预测其发生的能力。本研究前瞻性地测试了使用血糖仪读数预测SH的方法。
对100名1型糖尿病成年人随访6个月，对79名使用胰岛素的2型糖尿病成年人随访4个月。在此期间，受试者的常规自我监测血糖（SMBG）读数存储在记忆血糖仪中并从中检索，每两周询问参与者SH的发生情况。两组各自的人口统计学数据分别为年龄40.7岁和50.2岁，糖尿病病程20.0年和12.2年，糖化血红蛋白（A1C）7.6%和8.8%，男性分别为43%和39%。
通过个体基于前150次SMBG读数的低血糖指数（LBGI）与基于近期SMBG读数的LBGI之比量化的SH相对风险，在1型和2型糖尿病患者SH发作前24小时显著增加（t分别为10.3，P<0.0001和t为4.2，P<0.001）。当发作前24小时有三次SMBG读数时，滑动算法在1型糖尿病组中检测到58%的即将发生（24小时内）的SH发作，在2型糖尿病组中检测到60%。如果发作前24小时有五次SMBG读数，检测率分别提高到63%和75%。
SH通常遵循一种可从SMBG中识别的特定血糖波动模式。因此，对即将发生的SH进行部分预测是可能的，这为触发自我调节预防严重低血糖提供了一种潜在工具。
