Mohammadnia Niekbachsh, Akyea Ralph K, Qureshi Nadeem, Bax Willem A, Cornel Jan H
Department of Internal Medicine, Northwest Clinics, Wilhelminalaan 12, 1815 JD, Alkmaar, The Netherlands.
Department of Cardiology, Northwest Clinics, Wilhelminalaan 12, 1815 JD, Alkmaar, The Netherlands.
Eur Heart J Digit Health. 2022 Oct 17;3(4):578-586. doi: 10.1093/ehjdh/ztac059. eCollection 2022 Dec.
Familial hypercholesterolaemia (FH) is a disorder of LDL cholesterol clearance, resulting in increased risk of cardiovascular disease. Recently, we developed a Dutch Lipid Clinic Network (DLCN) criteria-based algorithm to facilitate FH detection in electronic health records (EHRs). In this study, we investigated the sensitivity of this and other algorithms in a genetically confirmed FH population.
All patients with a healthcare insurance-related coded diagnosis of 'primary dyslipidaemia' between 2018 and 2020 were assessed for genetically confirmed FH. Data were extracted at the time of genetic confirmation of FH (T1) and during the first visit in 2018-2020 (T2). We assessed the sensitivity of algorithms on T1 and T2 for DLCN ≥ 6 and compared with other algorithms [familial hypercholesterolaemia case ascertainment tool (FAMCAT), Make Early Diagnoses to Prevent Early Death (MEDPED), and Simon Broome (SB)] using EHR-coded data and using all available data (i.e. including non-coded free text). 208 patients with genetically confirmed FH were included. The sensitivity (95% CI) on T1 and T2 with EHR-coded data for DLCN ≥ 6 was 19% (14-25%) and 22% (17-28%), respectively. When using all available data, the sensitivity for DLCN ≥ 6 was 26% (20-32%) on T1 and 28% (22-34%) on T2. For FAMCAT, the sensitivity with EHR-coded data on T1 was 74% (67-79%) and 32% (26-39%) on T2, whilst sensitivity with all available data was 81% on T1 (75-86%) and 45% (39-52%) on T2. For Make Early Diagnoses to Prevent Early Death MEDPED and SB, using all available data, the sensitivity on T1 was 31% (25-37%) and 17% (13-23%), respectively.
The FAMCAT algorithm had significantly better sensitivity than DLCN, MEDPED, and SB. FAMCAT has the best potential for FH case-finding using EHRs.
家族性高胆固醇血症（FH）是一种低密度脂蛋白胆固醇清除障碍疾病，会增加心血管疾病风险。最近，我们开发了一种基于荷兰脂质诊所网络（DLCN）标准的算法，以促进在电子健康记录（EHR）中检测FH。在本研究中，我们调查了该算法及其他算法在基因确诊的FH人群中的敏感性。
对2018年至2020年间所有医保编码诊断为“原发性血脂异常”的患者进行基因确诊FH评估。在FH基因确诊时（T1）以及2018 - 2020年首次就诊时（T2）提取数据。我们评估了T1和T2时DLCN≥6的算法敏感性，并使用EHR编码数据以及所有可用数据（即包括未编码的自由文本）与其他算法[家族性高胆固醇血症病例确定工具（FAMCAT）、早诊断早预防早死亡（MEDPED）和西蒙·布鲁姆（SB）]进行比较。纳入了208例基因确诊的FH患者。T1和T2时使用EHR编码数据且DLCN≥6的敏感性（95%CI）分别为19%（14 - 25%）和22%（17 - 28%）。使用所有可用数据时，T1和T2时DLCN≥6的敏感性分别为26%（20 - 32%）和28%（22 - 34%）。对于FAMCAT，T1时使用EHR编码数据的敏感性为74%（67 - 79%），T2时为32%（26 - 39%），而使用所有可用数据时，T1时敏感性为81%（75 - 86%），T2时为45%（39 - 52%）。对于MEDPED和SB，使用所有可用数据时，T1时敏感性分别为31%（25 - 37%）和17%（13 - 23%）。
FAMCAT算法的敏感性显著优于DLCN、MEDPED和SB。FAMCAT在使用EHR进行FH病例发现方面具有最佳潜力。
