Heiling Bianka, Kneer Katharina, He Winnie, Lehmann Thomas, Müller Nicolle, Kloos Christof, Grimm Alexander, Axer Hubertus
Department of Neurology, Jena University Hospital, Friedrich Schiller University, 07747, Jena, Germany.
Clinician Scientist Program OrganAge, Jena University Hospital, 07747, Jena, Germany.
Sci Rep. 2024 Dec 16;14(1):30504. doi: 10.1038/s41598-024-82235-8.
Diabetic polyneuropathy (DPN) shares overlapping clinical and electrodiagnostic features with chronic inflammatory demyelinating polyneuropathy (CIDP), which complicates the differential diagnosis of CIDP in diabetic patients. 32 patients with diabetes mellitus and CIDP, 68 patients with CIDP without diabetes, 83 patients with DPN, and 28 diabetic patients without polyneuropathy were examined using clinical scores (Overall Neuropathy Limitation Scale (ONLS), Neuropathy Symptom Score, Neuropathy Deficit Score), nerve conduction studies, and nerve ultrasound (Ultrasound Pattern Sum Score (UPSS)). The ONLS was significantly higher in the CIDP patients with diabetes than in DPN (median [interquartile range]: 4.0 [3.0] vs. 0 [1.0], p < 0.001) as well as the UPSS (4.0 [6.0] vs. 0 [2.9], p < 0.001). Multiple binary logistic regression revealed UPSS and ONLS as statistically significant predictors to differentiate between CIDP with diabetes and DPN. Receiver operating characteristic curve analysis showed the ONLS with an area under the curve (AUC) of 0.918 (95% CI: 0.868-0.0.967, p < 0.001). The UPSS total score had an AUC of 0.826 (95% CI: 0.743-0.909, p < 0.001). An UPSS ≥ 2.5 had a sensitivity of 77.4% and a specificity of 68.7% to detect CIDP. An ONLS ≥ 1.5 had a sensitivity of 87.1% and a specificity of 81.9% to detect CIDP. ROC curve analysis of a composite score of ONLS and UPSS revealed an AUC of 0.959 (95% CI: 0.928-0.991, p < 0.001). CIDP is an important differential diagnosis in people with diabetes mellitus. This study reports that the UPSS is well suited to differentiate between DPN and CIDP.
糖尿病性多发性神经病(DPN)与慢性炎症性脱髓鞘性多发性神经病(CIDP)具有重叠的临床和电诊断特征,这使得糖尿病患者中CIDP的鉴别诊断变得复杂。对32例患有糖尿病和CIDP的患者、68例无糖尿病的CIDP患者、83例DPN患者以及28例无多发性神经病的糖尿病患者进行了检查,采用临床评分(总体神经病限制量表(ONLS)、神经病症状评分、神经病缺陷评分)、神经传导研究和神经超声(超声模式总分(UPSS))。糖尿病合并CIDP患者的ONLS显著高于DPN患者(中位数[四分位间距]:4.0[3.0]对0[1.0],p<0.001),UPSS也是如此(4.0[6.0]对0[2.9],p<0.001)。多元二元逻辑回归显示,UPSS和ONLS是区分糖尿病合并CIDP和DPN的统计学显著预测指标。受试者工作特征曲线分析显示,ONLS的曲线下面积(AUC)为0.918(95%CI:0.868 - 0.967,p<0.001)。UPSS总分的AUC为0.826(95%CI:0.743 - 0.909,p<0.001)。UPSS≥2.5检测CIDP的灵敏度为77.4%,特异度为68.7%。ONLS≥1.5检测CIDP的灵敏度为87.1%,特异度为81.9%。ONLS和UPSS综合评分的ROC曲线分析显示AUC为0.959(95%CI:0.928 - 0.991,p<0.001)。CIDP是糖尿病患者的重要鉴别诊断。本研究报告称,UPSS非常适合区分DPN和CIDP。