The association between physical activity time and neuropathy in longstanding type 1 diabetes: A cross-sectional analysis of the Canadian study of longevity in type 1 diabetes

AimPhysical activity (PA) is recommended to improve glycemic control in T1D; however, the effect of PA on distal symmetric polyneuropathy (DSPN) and cardiac autonomic function in longstanding T1D is unknown.MethodsData from 75 participants were collected as part of the Canadian Study of Longevity in T1D. Participants completed a physical exam, medical history, extensive complications phenotyping and reported their daily PA from the preceding 12-months. Pearson and Spearman correlations were used to assess PA time and complications variables. Linear regression was used to test associations between PA time, neurological and electrophysiological measures. Univariable regression was used to indicate the change in the given independent variables associated with a 30-min increase in PA per week.ResultsParticipants were 66 ± 8 years old with diabetes duration of 54 [52,58] years, HbA_1c was 7.3 ± 0.8, 65(89%) had DSPN. Weekly PA time was 156 ± 132 min, and 35(47%) reported ≧150 min/week. Participants with DSPN reported lower PA time compared to individuals without DSPN (141 ± 124 min/week vs. 258 ± 129 min/week; p = 0.015). PA time was associated with better cooling detection threshold (r = 0.24; p = 0.043), peroneal and sural amplitude (r = 0.36; p = 0.0017, r_s = 0.26; p = 0.024) and conduction velocity (r_s = 0.28; p = 0.015, r = 0.23; p = 0.050). Linear regression adjusting for age and HbA1c, showed that for each 30-min of PA there was a 0.09mv higher peroneal amplitude (p = 0.032) and 0.048 ms lower peroneal F-wave latency (p = 0.022).ConclusionIn longstanding T1D, PA time is associated with superior large nerve fibre function in the lower limbs and some better measures of small nerve fibre function.     

Mendelian randomization as a tool to gain insights into the mosaic causes of autoimmune diseases

Autoimmune diseases (ADs) are a broad range of disorders which are characterized by long-term inflammation and tissue damage arising from an immune response against one's own tissues. It is now widely accepted that the causes of ADs include environmental factors, genetic susceptibility and immune dysregulation. However, the exact etiology of ADs has not been fully elucidated to date. Because observational studies are plagued by confounding factors and reverse causality, no firm conclusions can be drawn about the etiology of ADs. Over the years, Mendelian randomization (MR) analysis has come into focus, offering unique perspectives and insights into the etiology of ADs and promising the discovery of potential therapeutic interventions. In MR analysis, genetic variation (alleles are randomly dispensed during meiosis, usually irrespective of environmental or lifestyle factors) is used instead of modifiable exposure to explore the link between exposure factors and disease or other outcomes. Therefore, MR analysis can provide a valuable method for exploring the causal relationship between different risk factors and ADs when its inherent assumptions and limitations are fully considered. This review summarized the recent findings of MR in major ADs, including systemic lupus erythematosus (SLE), rheumatoid arthritis (RA), multiple sclerosis (MS), and type 1 diabetes mellitus (T1DM), focused on the effects of different risk factors on ADs risks. In addition, we also discussed the opportunities and challenges of MR methods in ADs research.     

Trends of self-reported non-adherence among type 2 diabetes medication users in the United States across three years using the self-reported Medication Adherence Reasons Scale

Background & aimsTo determine the trends of self-reported non-adherence rates among adults taking Type 2 medicines (T2D) medicines between 2017 and 2019 and to identify the patterns for the frequently reported reasons for non-adherence in the United States.Methods & resultsData from the National Health and Wellness Survey, a self-administered, internet-based cross-sectional survey of US adults from 2017 to 2019 was used. Non-adherence was measured using the self-reported Medication Adherence Reasons Scale (MAR-Scale). Frequencies were used to identify the reasons for non-adherence for insulin and non-insulin therapies for T2D.Data were obtained from 2983 respondents in 2017, 5416 in 2018, and 5268 in 2019. Based on the MAR-Scale, the self-reported medication non-adherence rate was 25% in 2017, 21% in 2018, and 27% in 2019. The most common reason for non-adherence across all the three years was simple forgetfulness, yet patients reported the lowest mean number of days missing medication for that reason. Though less frequently reported, non-adherence lasted longer when patient did not know how to take their medicines, cost was a reason, or had concerns about the long term effects of the medicines.ConclusionsWith no significant improvement in adherence with T2D medicines over time, regardless of better awareness and extensive diabetes education, focus should be on individualized non-adherence reasons-based interventions.     

Effect of exercises according to the circadian rhythm in type 2 diabetes: Parallel-group,single-blind,crossover study

Background and aimTo evaluate the effectiveness of structured exercise appropriate the circadian rhythm in terms of blood sample test (BST), functionality and quality of life (QoL) in individuals with type 2 diabetes.Methods and resultsThis was a parallel-group, single-blind, crossover study. Thirty individuals with type 2 diabetes aged 35–65 years were enrolled in the study and allocated into 2 groups as the Morning Chronotype (MC) Group (n = 15) and the Evening Chronotype (EC) Group (n = 15) using Morningness-Eveningness Questionnaire which was used to determine the chronotypes. Participants were evaluated in terms of BST, functionality and QoL at the beginning of the study (T0), at 6 (T1), 12 (T2), and 18 (T3) weeks after the study started. A structured exercise program for 3 days a week over 6 weeks was applied in accordance with the chronotypes (T1-T2) and cross-controlled for the chronotypes (T2-T3). Significant differences were found in favor of the exercise given at the appropriate time for the chronotype in all parameters in both groups within groups (T0-T1-T2-T3) (p < 0.05). In the time1group interactions, exercise in accordance with the appropriate chronotype in both groups provided the highest statistical improvement in all parameters (p < 0.05).ConclusionIt was concluded that structured exercise performed at the appropriate time for chronotype improves HbA_1c, fasting blood glucose, HDL-LDL cholesterol, triglyceride, total cholesterol, functionality and quality of life in type 2 diabetes. This variation in blood values was observed to reflect the quantitative effects of exercise administered according to the circadian rhythm in individuals with type 2 diabetes.Trial registrationClinicalTrials.gov (NCT04427488). The protocol of the study was registered at ClinicalTrials.gov (NCT04427488).     

Evaluation of a deep learning model on coronary CT angiography for automatic stenosis detection

PurposeThe purpose of this study was to evaluate a deep-learning model (DLM) for classifying coronary arteries on coronary computed tomography -angiography (CCTA) using the Coronary Artery Disease-Reporting and Data System (CAD-RADS).Materials and methodsThe DLM was trained with 10,800 curved multiplanar reformatted (cMPR) CCTA images classified by an expert radiologist using the CAD-RADS. For each of the three main coronary arteries, nine cMPR images 40° apart acquired around each arterial circumference were then classified by the DLM using the highest probability. For the validation set composed of 159 arteries from 53 consecutive patients, the images were read by two senior and two junior readers; consensus of the two seniors was the reference standard. With the DLM, the majority vote for the nine images was used to classify each artery. Three groups (CAD-RADS 0, 1–2, or 3–4–5) and 2 groups CAD-RADS 0–1–2 or 3–4–5 (<50% vs. ≥50% stenosis) were used for comparisons with readers and consensus. Performance of the model and readers was compared to the consensus reading using the intraclass coefficient (ICC) and Cohen's kappa coefficient at the artery and patient levels.ResultsWith the three groups at the artery level, the ICC of the DLM was 0.82 (95% CI: 0.75–0.88) and not significantly different from those of 3/4 readers; accuracy was 81%. With the binary classification, Cohen kappa coefficient of the DLM was 0.85 (95% CI: 0.69–0.94) and not significantly different from that of 3/4 readers; accuracy was 96%. At the patient level, sensitivity and specificity were 93% and 97% respectively, and the negative predictive value was 97%.ConclusionThe DLM detected ≥50% stenoses with performances similar to those achieved by senior radiologists.     

Perivascular fat attenuation for predicting adverse cardiac events in stable patients undergoing invasive coronary angiography

BackgroundInflammation surrounding the coronary arteries can be non-invasively assessed using pericoronary adipose tissue attenuation (PCAT). While PCAT holds promise for further risk stratification of patients with low coronary artery disease (CAD) prevalence, its value in higher risk populations remains unknown.MethodsCORE320 enrolled patients referred for invasive coronary angiography with known or suspected CAD. Coronary computed tomography angiography (CCTA) images were collected for 381 patients for whom clinical outcomes were assessed 5 years after enrollment. Using semi-automated image analysis software, PCAT was obtained and normalized for the right coronary (RCA), left anterior descending (LAD), and left circumflex arteries (LCx). The association between PCAT and major adverse cardiovascular events (MACE) during follow up was assessed using Cox regression models.ResultsThirty-seven patients were excluded due to technical failure. For the remaining 344 patients, median age was 62 (interquartile range, 55–68) with 59% having ≥1 coronary artery stenosis of ≥50% by quantitative coronary angiography. Mean attenuation values for PCAT in RCA, LAD, and LCx were ?74.9, ?74.2, and ?71.2, respectively. Hazard ratios and 95% confidence intervals (CI) for normalized PCAT in the RCA, LAD, and LCx for MACE were 0.96 (CI: 0.75–1.22, p ?= ?0.71), 1.31 (95% CI: 0.96–1.78, p ?= ?0.09), and 0.98 (95% CI: 0.78–1.22, p ?= ?0.84), respectively. For death, stroke, or myocardial infarction only, hazard ratios were 0.68 (0.44–1.07), 0.85 (0.56–1.29), and 0.57 (0.41–0.80), respectively.ConclusionsIn patients referred for invasive coronary angiography with suspected CAD, PCAT did not predict MACE during long term follow up. Further studies are needed to understand the relationship of PCAT with CAD risk.     

Vestibular neuronitis in a vestibular schwannoma patient

This is a unique presentation of an acute vestibular syndrome (AVS) caused by vestibular neuronitis (VN) of a vestibular nerve (CNVIII) already affected by vestibular schwannoma (VS).A 48-year-old patient, formerly diagnosed with an intracanalicular VS, presented with AVS.The patient underwent clinical and neurotological examination including video Head Impulse Test and a 4-hour delayed-enhanced 3D-FLAIR MRI using intravenous gadolinium.Clinical and neurotological findings were consistent with VN of the CNVIII formerly diagnosed with VS. A 4-hour delayed-enhanced 3D-FLAIR MRI showed significant enhancement of the labyrinth also indicating VN of the same nerve affected by VS.Pragmatic corticosteroid therapy and vestibular exercises were applied resulting in satisfactory recovery of the patient.As vestibular symptoms are common in VS patients, investigating another cause of dizziness and vertigo in VS patients can be marginalized. Nevertheless, VS presenting as AVS is very unusual.VN should not be overlooked as a possible cause of acute vertigo in a patient previously diagnosed with VS.