Individual risk assessment and information technology to optimise screening frequency for diabetic retinopathy
Individual risk assessment and information technology to optimise screening frequency for diabetic retinopathy
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DOI：
10.1007/s00125-011-2257-7
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发表时间：
2011-10-01
期刊：
影响因子：
8.2
通讯作者：
Stefansson, E.
中科院分区：
文献类型：
--
作者：
Aspelund, T.;Porisdottir, O.;Stefansson, E.
本研究的目的是通过使用信息技术和个体化风险评估来确定筛查间隔时间，以减少糖尿病眼部筛查的频率，同时保持安全性。基于糖尿病视网膜病变危险因素的流行病学数据，创建了一种数学算法。通过网站，该算法接收临床数据，包括糖尿病的类型和持续时间，HbA（1c）或平均血糖，血压以及视网膜病变的存在和等级。这些数据用于计算每个人随着时间的推移视力恶化的视网膜病变的风险。定义风险范围，算法为筛选间隔内具有发展威胁视力的视网膜病变（STR）标准化风险的每例患者推荐筛选间隔。我们设定了风险界限，以便在固定的年度筛查或我们的个性化筛查系统中，相同数量的患者在筛查间隔内发生STR。丹麦奥胡斯大学医院眼科的糖尿病视网膜病变数据库用于经验性检验算法的有效性。已有5，199名患者20年的临床数据，这允许以前瞻性的方式测试该算法。在丹麦糖尿病数据库中，该算法建议筛查间隔为6至60个月，平均为29个月。这比固定的年度筛查少59%。这相当于每100名患者每年41次就诊。基于流行病学数据的信息技术可能有助于个性化确定糖尿病眼病的筛查间隔。经验测试表明，这种方法可能比传统的年度筛查更便宜，同时不会影响安全性。该算法确定个人风险，并根据每个人的风险状况单独确定筛查间隔。该算法有可能通过减少世界上不断增加的糖尿病患者的筛查次数来节省医疗资源和患者的工作时间。
The aim of this study was to reduce the frequency of diabetic eye-screening visits, while maintaining safety, by using information technology and individualised risk assessment to determine screening intervals.A mathematical algorithm was created based on epidemiological data on risk factors for diabetic retinopathy. Through a website, the algorithm receives clinical data, including type and duration of diabetes, HbA(1c) or mean blood glucose, blood pressure and the presence and grade of retinopathy. These data are used to calculate risk for sight-threatening retinopathy for each individual's worse eye over time. A risk margin is defined and the algorithm recommends the screening interval for each patient with standardised risk of developing sight-threatening retinopathy (STR) within the screening interval. We set the risk margin so that the same number of patients develop STR within the screening interval with either fixed annual screening or our individualised screening system. The database for diabetic retinopathy at the Department of Ophthalmology, Aarhus University Hospital, Denmark, was used to empirically test the efficacy of the algorithm. Clinical data exist for 5,199 patients for 20 years and this allows testing of the algorithm in a prospective manner.In the Danish diabetes database, the algorithm recommends screening intervals ranging from 6 to 60 months with a mean of 29 months. This is 59% fewer visits than with fixed annual screening. This amounts to 41 annual visits per 100 patients.Information technology based on epidemiological data may facilitate individualised determination of screening intervals for diabetic eye disease. Empirical testing suggests that this approach may be less expensive than conventional annual screening, while not compromising safety. The algorithm determines individual risk and the screening interval is individually determined based on each person's risk profile. The algorithm has potential to save on healthcare resources and patients' working hours by reducing the number of screening visits for an ever increasing number of diabetic patients in the world.