Forstenpointner Julia, Moeller Paul, Sendel Manon, Reimer Maren, Hüllemann Philipp, Baron Ralf
Division of Neurological Pain Research and Therapy, Department of Neurology, University Hospital Schleswig-Holstein, Kiel 24105, Germany.
J Pain Res. 2019 Jul 23;12:2223-2230. doi: 10.2147/JPR.S206223. eCollection 2019.
Fabry disease belongs to lysosomal storage disorders and can be successfully treated today. On the contrary, the correct diagnostic classification of its symptoms can be challenging and most patients suffer from pain for years, until they are diagnosed correctly. The aim of this project was to characterize patients with unclassified extremity pain and to present a simple algorithm for a retrospective stratification approach.
The FabryScan includes a bedside-test and a questionnaire, consisting of 10 symptom-orientated and anamnestic questions. For the stratification of patients according to the likelihood for Fabry disease two different approaches were conducted. First, a prospective subgrouping based on the previously invented FabryScan evaluation system was conducted. The second retrospective approach consisted of a factor analysis and a subsequent two-way cluster analysis. Further on, 4 patients diagnosed with Fabry disease were stratified according to both approaches.
In total, 183 completed datasets were included in the statistical analysis. The first approach prospectively classified patients into 3 subgroups (n=40 [likely], n=96 [possible], n=47 [unlikely]) according to the FabryScan evaluation system. The second approach retrospectively stratified patients into 3 subgroups (n=47 [cluster 1], n=95 [cluster 2], n=41 [cluster 3]). Finally, the Fabry patients were sorted to the subgroups, indicative for the highest possibility of Fabry disease in both stratification approaches A and B.
Both stratification approaches sorted patients with confirmed Fabry disease to the subgroups, indicative for the highest likelihood for Fabry. These results indicate validity of the initially selected FabryScan outcome parameters.
法布里病属于溶酶体贮积症,如今可得到有效治疗。相反,对其症状进行正确的诊断分类可能具有挑战性,大多数患者会遭受数年疼痛,直至得到正确诊断。本项目的目的是对未分类的肢体疼痛患者进行特征描述,并提出一种用于回顾性分层方法的简单算法。
法布里病扫描包括一项床旁检测和一份问卷,问卷由10个以症状为导向的回忆性问题组成。为根据法布里病的可能性对患者进行分层,采用了两种不同方法。首先,基于先前发明的法布里病扫描评估系统进行前瞻性亚组划分。第二种回顾性方法包括因子分析和随后的双向聚类分析。此外,根据这两种方法对4例诊断为法布里病的患者进行了分层。
统计分析共纳入183个完整数据集。第一种方法根据法布里病扫描评估系统将患者前瞻性地分为3个亚组(n = 40[可能],n = 96[有可能],n = 47[不太可能])。第二种方法将患者回顾性地分为3个亚组(n = 47[聚类1],n = 95[聚类2],n = 41[聚类3])。最后,将法布里病患者归入这两个分层方法(A和B)中表明法布里病可能性最高的亚组。
两种分层方法均将确诊为法布里病的患者归入表明法布里病可能性最高的亚组。这些结果表明最初选择的法布里病扫描结果参数具有有效性。