目的探讨盐酸沙格雷酯治疗2型糖尿病合并下肢动脉硬化闭塞症（ASO）患者的临床疗效。 方法笔者所在医院科室2011年2月至2012年2月期间采用盐酸沙格雷酯治疗了64例2型糖尿病合并ASO住院患者，用药方法为100 mg/次，3次/d，连续用药3个月。比较患者用药前后临床症状与体征、踝肱指数（ABI）、足背动脉血流量、凝血功能等指标的变化。 结果治疗后患者主观感觉下肢麻木、冷感、疼痛等症状均有不同程度的改善；间歇性跛行距离〔（620.26±16.76）m比（236.28±18.43）m〕、ABI〔0.86±0.04比0.50±0.08〕及足背动脉血流量〔（32.5±16.8）mL/min比（21.1±10.2）mL/min〕均较治疗前好转（P<0.05）；空腹血糖〔（6.18±1.23）mmol/L比（8.32±1.58）mmol/L〕、糖化血红蛋白〔（6.88±0.45）%比（7.26±0.26）%〕及低密度脂蛋白〔（3.02±0.26）mmol/L比（3.31±0.30）mmol/L〕也明显改善（P<0.05）；而治疗前后的凝血酶原时间、血小板计数、丙氨酸氨基转移酶、天门冬氨酸氨基转移酶、肌酐及尿素氮的差异均无统计学意义（P>0.05）。综合疗效显著24例，有效38例，无效2例，总有效率为96.9%。用药后有3例患者出现轻度胃部不适症状，余无任何不良反应及药物过敏发生。 结论盐酸沙格雷酯在2型糖尿病合并ASO患者的临床治疗中安全有效。
ObjectiveTo construct a prediction model of diabetics distal symmetric polyneuropathy (DSPN) based on neural network algorithm and the characteristic data of traditional Chinese medicine and Western medicine. MethodsFrom the inpatients with diabetes in the First Affiliated Hospital of Anhui University of Chinese Medicine from 2017 to 2022, 4 071 cases with complete data were selected. The early warning model of DSPN was established by using neural network, and 49 indicators including general epidemiological data, laboratory examination, signs and symptoms of traditional Chinese medicine were included to analyze the potential risk factors of DSPN, and the weight values of variable features were sorted. Validation was performed using ten-fold crossover, and the model was measured by accuracy, sensitivity, specificity, positive predictive value, negative predictive value, and AUC value. ResultsThe mean duration of diabetes in the DSPN group was about 4 years longer than that in the non-DSPN group (P<0.001). Compared with non-DSPN patients, DSPN patients had a significantly higher proportion of Chinese medicine symptoms and signs such as numbness of limb, limb pain, dizziness and palpitations, fatigue, thirst with desire to drink, dry mouth and throat, blurred vision, frequent urination, slow reaction, dull complexion, purple tongue, thready pulse and hesitant pulse (P<0.001). In this study, the DSPN neural network prediction model was established by integrating traditional Chinese and Western medicine feature data. The AUC of the model was 0.945 3, the accuracy was 87.68%, the sensitivity was 73.9%, the specificity was 92.7%, the positive predictive value was 78.7%, and the negative predictive value was 90.72%. ConclusionThe fusion of Chinese and Western medicine characteristic data has great clinical value for early diagnosis, and the established model has high accuracy and diagnostic efficacy, which can provide practical tools for DSPN screening and diagnosis in diabetic population.