OBJECTIVEChronic diabetic peripheral neuropathic pain (DPNP) is difficult to treat, with treatment regimens often inadequate at controlling pain and limited by side effects and drug tolerance. Secondary parameters, such as quality of sleep and mood, may also be important for successful DPNP management. The objectives of this study were to compare the analgesic efficacy of pregabalin, amitriptyline, and duloxetine, and their effect on polysomnographic sleep, daytime functioning, and quality of life in patients with DPNP.RESEARCH DESIGN AND METHODSThis was a double-blind, randomized, parallel group investigation of type 1 and 2 diabetic subjects with DPNP. Each treatment group had a single-blind, 8-day, placebo run-in followed by 14 days of lower-dose and 14 days of higher-dose medication. At the end of each dose titration period, subjective pain, sleep, and daytime functioning were assessed during a 2-day residential period.RESULTSAll medications reduced pain when compared with placebo, but no one treatment was superior to any other. For sleep, pregabalin improved sleep continuity (P < 0.001), whereas duloxetine increased wake and reduced total sleep time (P < 0.01 and P < 0.001). Despite negative effects on sleep, duloxetine enhanced central nervous system arousal and performance on sensory motor tasks. There were no significant safety findings; however, there was a significantly higher number of adverse events in the pregabalin treatment group.CONCLUSIONSThere was no significant difference in analgesic efficacy between amitriptyline, duloxetine, and pregabalin. However, there were significant differences in the secondary parameters, which may be of relevance when deciding the optimal treatment for DPNP.
Background-Hypoglycemia is associated with increased cardiovascular mortality, but the reason for this association is poorly understood. We tested the hypothesis that the myocardial blood flow reserve (MBFR) is decreased during hypoglycemia using myocardial contrast echocardiography in patients with type 1 diabetes mellitus (DM) and in healthy control subjects. Methods and Results-Twenty-eight volunteers with DM and 19 control subjects underwent hyperinsulinemic clamps with maintained sequential hyperinsulinemic euglycemia (plasma glucose, 90 mg/dL [5.0 mmol/L]) followed by hyperinsulinemic hypoglycemia (plasma glucose, 50 mg/dL [2.8 mmol/L]) for 60 minutes each. Low-power real-time myocardial contrast echocardiography was performed with flash impulse imaging using low-dose dipyridamole stress at baseline and during hyperinsulinemic euglycemia and hyperinsulinemic hypoglycemia. In control subjects, MBFR increased during hyperinsulinemic euglycemia by 0.57 U (22%) above baseline (B coefficient, 0.57; 95% confidence interval, 0.38 to 0.75; PϽ0.0001) and decreased during hyperinsulinemic hypoglycemia by 0.36 U (14%) below baseline values (B coefficient, Ϫ0.36; 95% confidence interval, Ϫ0.50 to Ϫ0.23; PϽ0.0001). Although MBFR was lower in patients with DM at baseline by 0.37 U (14%; B coefficient, Ϫ0.37; 95% confidence interval, Ϫ0.55 to Ϫ0.19; Pϭ0.0002) compared with control subjects at baseline, the subsequent changes in MBFR during hyperinsulinemic euglycemia and hyperinsulinemic hypoglycemia in DM patients were similar to that observed in control subjects. Finally, the presence of microvascular complications in the patients with DM was associated with a reduction in MBFR of 0.52 U (24%; B coefficient, Ϫ0.52; 95% confidence interval, Ϫ0.70 to Ϫ0.34; PϽ0.0001). Conclusions-Hypoglycemia decreases MBFR in both healthy humans and patients with DM. This finding may explain the association between hypoglycemia and increased cardiovascular mortality in susceptible individuals. (Circulation. 2011;124:1548-1556.)Key Words: diabetes mellitus Ⅲ echocardiography Ⅲ hypoglycemia Ⅲ insulin Ⅲ regional blood flow S everal studies have shown that hypoglycemia is associated with an increase in cardiovascular mortality (CVM). [1][2][3][4][5][6] This association has been demonstrated in people with and without established coronary artery disease. [1][2][3] Importantly, patients with acute coronary syndromes appear to have worse short-and long-term outcomes if they experience hypoglycemia in the acute phase of their presentation. [2][3][4] For example, in patients with diabetes mellitus (DM) and acute coronary syndromes, hypoglycemia within 48 hours of their admission was associated with a 2-fold increase in all-cause mortality over a 2-year follow-up. 2 Similarly, Pinto et al 3 showed that patients with ST-segment-elevation myocardial infarction and an admission blood glucose Ͻ4.5 mmol/L had a 3-fold increased rate of adverse outcomes (defined as 30-day mortality and myocardial infarction). Furthermore, in the same study, patients w...
The exact mechanism for capillary occlusion in diabetic retinopathy is still unclear, but increased leukocyteendothelial cell adhesion has been implicated. We examined the possibility that posttranslational modification of surface O-glycans by increased activity of core 2 transferase (UDP-Glc:Gal1-3GalNAc␣R-N-acetylglucoaminyltransferase) is responsible for increased adhesion of leukocytes to vascular endothelium in diabetes. The mean activity of core 2 transferase in polymorphonuclear leukocytes isolated from type 1 and type 2 diabetic patients was higher compared with agematched control subjects (1,638 ± 91 [n = 42] vs. 249 ± 35 pmol · h -1 · mg -1 protein [n = 24], P = 0.00013; 1,459 ± 194 [n = 58] vs. 334 ± 86 [n = 11], P = 0.01). As a group, diabetic patients with retinopathy had significantly higher mean activity of core 2 transferase compared with individuals with no retinopathy. There was a significant association between enzyme activity and severity of retinopathy in type 1 and type 2 diabetic patients. There was a strong correlation between activity of core 2 transferase and extent of leukocyte adhesion to cultured retinal capillary endothelial cells for diabetic patients but not for age-matched control subjects. Results from transfection experiments using human myelocytic cell line (U937) demonstrated a direct relationship between increased activity of core 2 transferase and increased binding to cultured endothelial cells. There was no relationship between activity of core 2 transferase and HbA 1c (P = 0.8314), serum advanced glycation end product levels (P = 0.4159), age of the patient (P = 0.7896), and duration of diabetes (P = 0.3307). On the basis that branched O-glycans formed by the action of core 2 transferase participate in leukocyte adhesion, the present data suggest the involvement of this enzyme in increased leukocyteendothelial cell adhesion and the pathogenesis of capillary occlusion in diabetic retinopathy. Diabetes
Background: A risk assessment tool has been developed for automated estimation of level of neuropathy based on the clinical characteristics of patients. The smart tool is based on risk factors for diabetic neuropathy, which utilizes vibration perception threshold (VPT) and a set of clinical variables as potential predictors. Methods: Significant risk factors included age, height, weight, urine albumin-to-creatinine ratio, glycated hemoglobin, total cholesterol, and duration of diabetes. The continuous-scale VPT was recorded using a neurothesiometer and classified into three categories based on the clinical thresholds in volts (V): low risk (0-20.99 V), medium risk (21-30.99 V), and high risk (≥31 V). Results: The initial study had shown that by just using patient data ( n = 5088) an accuracy of 54% was achievable. Having established the effectiveness of the “classical” method, a special Neural Network based on a Proportional Odds Model was developed, which provided the highest level of prediction accuracy (>70%) using the simulated patient data ( n = 4158). Conclusion: In the absence of any assessment devices or trained personnel, it is possible to establish with reasonable accuracy a diagnosis of diabetic neuropathy by means of the clinical parameters of the patient alone.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.