[Naochang Tongtiao acupuncture based on brain-gut axis for acute ischemic stroke and its effect on levels of IL-17, hs-CRP and TMAO].

OBJECTIVE: To compare the clinical therapeutic effect on acute ischemic stroke between Naochang Tongtiao acupuncture (acupuncture for brain-gut homology) and conventional acupuncture, and to explore the possible mechanism. METHODS: A total of 64 patients with acute ischemic stroke were randomized into an observation group and a control group, 32 cases in each one. Basic western medical therapy was adopted in both groups. In the observation group, Naochang Tongtiao acupuncture was applied at anterior oblique line of vertex-temporal, Zhongwan (CV 12), Guanyuan (CV 4), Tianshu (ST 25), Zusanli (ST 36), Shangjuxu (ST 37) and Xiajuxu (ST 39). In the control group, conventional acupuncture was applied. The treatment was given once a day, 6 days a week for 3 weeks in both groups. Before and after treatment, National Institution of Health stroke scale (NIHSS) score, serum levels of interleukin-17 (IL-17) and hypersensitive C reactive protein (hs-CRP), and plasma level of trimethylamine oxide (TMAO) were compared in the two groups. RESULTS: After treatment, NIHSS scores, serum levels of IL-17 and hs-CRP, and plasma levels of TMAO were decreased compared before treatment in both groups (P<0.01), and those in the observation group were lower than the control group (P<0.05). CONCLUSION: Naochang Tongtiao acupuncture can improve the nerve function in patients with acute ischemic stroke, its therapeutic effect is superior to conventional acupuncture, the mechanism may relate to the regulation on inflammatory reaction and the level of intestinal flora metabolite.

Prediction of the trans-stenotic pressure gradient with arteriography-derived hemodynamic features in patients with idiopathic intracranial hypertension.

The pathogenesis of idiopathic intracranial hypertension (IIH) is attributed to segmental stenosis of the venous sinus. The current treatment paradigm requires a trans-stenotic pressure gradient of ≥8 mmHg or ≥6 mmHg threshold. This study aimed to develop a machine learning screening method to identify patients with IIH using hemodynamic features. A total of 204 venous manometry instances (n = 142, training and validation; n = 62, test) from 135 patients were included. Radiomic features extracted from five arteriography perfusion parameter maps were selected using least absolute shrinkage and selection operator and then entered into support vector machine (SVM) classifiers. The Thr8-23-SVM classifier was created with 23 radiomic features to predict if the pressure gradient was ≥8 mmHg. On an independent test dataset, prediction sensitivity, specificity, accuracy, and AUC were 0.972, 0.846, 0.919, and 0.980, respectively (95% confidence interval: 0.980-1.000). For the 6 mmHg threshold, thr6-28-SVM incorporated 28 features, and its sensitivity, specificity, accuracy, and AUC were 0.923, 0.956, 0.935, and 0.969, respectively (95% confidence interval: 0.927-1.000). The trans-stenotic pressure gradient result was associated with perfusion pattern changes, and SVM classifiers trained with arteriography perfusion map-derived radiomic features could predict the 8 mmHg and 6 mmHg dichotomized trans-stenotic pressure gradients with favorable accuracy.