Polonsky William H, Jelsovsky Zhihong, Panzera Susanne, Parkin Christopher G, Wagner Robin S
University of California San Diego, San Diego, California, USA.
Diabetes Technol Ther. 2009 May;11(5):283-91. doi: 10.1089/dia.2008.0087.
The purpose of this study was to determine if primary care physicians could utilize data collection tools to accurately identify glycemic abnormalities in structured, episodic self-monitoring of blood glucose (SMBG) data from patients with non-insulin-treated type 2 diabetes and whether use of these SMBG data would influence their therapeutic decisions.
Twenty-three case studies demonstrating several glycemic states (normoglycemia, elevated fasting glucose, elevated postprandial glucose, all elevated glucose, and hypoglycemia) were presented to 61 primary care physicians who evaluated the cases based upon A1C data, alone and then in combination with SMBG data. SMBG data were presented in five formats. Participants were to identify the specific glucose pattern, determine the necessity for therapy change, and select specific therapeutic changes. Participant assessments were compared with assessments made by a panel of diabetes care specialists.
Most (78%) participants identified the same primary blood glucose feature identified by the diabetes specialists; 93.8% agreed with the diabetes care specialists regarding the need for therapy modification. The majority (77%) of participants changed the way they would manage the case after evaluating case studies with SMBG data made available to them. Eighty-six percent of participants considered the SMBG data to be of equal value or more valuable than an A1C test result; 71% of participants strongly agreed that they are now more likely to recommend structured, episodic SMBG to their non-insulin-treated type 2 diabetes mellitus patients.
Primary care physicians can correctly identify glycemic abnormalities in SMBG data obtained through structured, episodic SMBG. Additional studies are needed to determine the clinical impact of similar testing regimens in primary care practice settings.
本研究的目的是确定基层医疗医生能否利用数据收集工具，通过对非胰岛素治疗的2型糖尿病患者的结构化、间歇性自我血糖监测（SMBG）数据准确识别血糖异常，以及这些SMBG数据的使用是否会影响他们的治疗决策。
向61名基层医疗医生展示了23个体现几种血糖状态（正常血糖、空腹血糖升高、餐后血糖升高、所有血糖均升高及低血糖）的病例研究，这些医生先仅根据糖化血红蛋白（A1C）数据评估病例，然后结合SMBG数据进行评估。SMBG数据以五种格式呈现。参与者需识别特定的血糖模式，确定是否有必要改变治疗方案，并选择具体的治疗改变措施。将参与者的评估结果与一组糖尿病护理专家的评估结果进行比较。
大多数（78%）参与者识别出了糖尿病专家所确定的主要血糖特征；93.8%的人在是否需要调整治疗方案上与糖尿病护理专家意见一致。大多数（77%）参与者在评估了提供给他们的带有SMBG数据的病例研究后，改变了他们处理病例的方式。86%的参与者认为SMBG数据与A1C检测结果具有同等价值或更有价值；71%的参与者强烈同意他们现在更有可能向非胰岛素治疗的2型糖尿病患者推荐结构化、间歇性的SMBG。
基层医疗医生能够通过结构化、间歇性的SMBG正确识别所获SMBG数据中的血糖异常。需要进一步研究以确定类似检测方案在基层医疗实践环境中的临床影响。
