Background Type 2 diabetic kidney disease is the most common cause of chronic kidney diseases (CKD) and end-stage renal diseases (ESRD). Although kidney biopsy is considered as the ‘gold standard’ for diabetic kidney disease (DKD) diagnosis, it is an invasive procedure, and the diagnosis can be influenced by sampling bias and personal judgement. It is desirable to establish a non-invasive procedure that can complement kidney biopsy in diagnosis and tracking the DKD progress. Methods In this cross-sectional study, we collected 252 urine samples, including 134 uncomplicated diabetes, 65 DKD, 40 CKD without diabetes and 13 follow-up diabetic samples, and analyzed the urine proteomes with liquid chromatography coupled with tandem mass spectrometry (LC–MS/MS). We built logistic regression models to distinguish uncomplicated diabetes, DKD and other CKDs. Results We quantified 559 ± 202 gene products (GPs) (Mean ± SD) on a single sample and 2946 GPs in total. Based on logistic regression models, DKD patients could be differentiated from the uncomplicated diabetic patients with 2 urinary proteins (AUC = 0.928), and the stage 3 (DKD3) and stage 4 (DKD4) DKD patients with 3 urinary proteins (AUC = 0.949). These results were validated in an independent dataset. Finally, a 4-protein classifier identified putative pre-DKD3 patients, who showed DKD3 proteomic features but were not diagnosed by clinical standards. Follow-up studies on 11 patients indicated that 2 putative pre-DKD patients have progressed to DKD3. Conclusions Our study demonstrated the potential for urinary proteomics as a noninvasive method for DKD diagnosis and identifying high-risk patients for progression monitoring.
Background We assessed the efficacy and safety of the Xiaoketongbi Formula (XF) vs. pregabalin in patients with painful diabetic neuropathy (PDN). Methods Patients with PDN (n = 68) were included in a single‐center, randomized, single‐blind, double‐dummy, parallel controlled clinical trial. The primary outcome was the change in the Brief Pain Inventory for Diabetic Peripheral Neuropathy (BPI‐DPN). Secondary outcomes evaluated included the reduction of BPI‐DPN >50%, changes in the numeric rating scale‐11 (NRS‐11) score for pain, Daily Sleep Interference Diary (DSID), Patient Global Impression of Change (PGIC), nerve conduction velocity (NCV), and adverse events. Results After 10 weeks of treatment, the BPI‐DPN score reduced from 42.44 ± 17.56 to 26.47 ± 22.22 and from 52.03 ± 14.30 to 37.85 ± 17.23 in the XF and pregabalin group ( P s < 0.001), respectively. The difference in the absolute change in BPI‐DPN score between both groups was −1.79 (95% CI: −9.09, 5.50; p = 0.625). In the XF and pregabalin groups, 44.1% (15/34) and 20.6% (7/34) of patients reported a BPI‐DPN reduction >50% ( p = 0.038), respectively. There were no significant differences between groups in NRS‐11 and DSID ( P s > 0.05). A significantly greater number of patients in the XF group felt “significantly improved” or “improved” than in the pregabalin group (35.3% (12/34) vs. 11.8% (4/34), p = 0.045). The absolute change in motor nerve conduction velocity of the right median nerve was significantly different between both groups (XF group 0.7 ± 2.3 vs. pregabalin group −2.2 ± 4.1, p = 0.004). No serious adverse events were reported in either group. Conclusions XF is equivalent to pregabalin in reducing pain symptoms and improves the quality of life in patients with PDN. In addition, XF has the potential to improve nerve function by increasing NCV.
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