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Introduction: Friedreich ataxia (FRDA) is an autosomal recessive neurodegenerative disorder causing gait and limb ataxia, dysarthria, impaired vibratory sense, with cardiomyopathy being the predominant cause of death. There is no approved therapy, which results in the use of symptomatic treatments, and in the chronic support of physiotherapy. Dimethyl fumarate (DMF) is a fumaric acid ester used for the treatment of psoriasis and Multiple Sclerosis (MS).It induces Nrf2 in vitro and in vivo, and it increases frataxin in FRDA patient lymphoblasts, in mouse models, and in MS treated patients.Methods: aim of our study is to investigate if DMF can increase the expression of the FXN gene and frataxin protein and ameliorate in-vivo detectable measures of mitochondrial dysfunction in FRDA. The study is composed of a screening visit and two sequential phases of identical length of 12 weeks each: a core phase and an extension phase. During the first phase (core), patients will be randomly assigned to either DMF or placebo in a 1:1 ratio. During the first week, patients will receive a total daily dose of 240 mg of DMF or placebo, from the second week of treatment, the dose will be increased to two 120 mg tablets BID for a total daily dose of 480 mg. During the second phase (extension), all patients will be treated with DMF.EudraCT number 2021-006274-23.Endpoints: Primary endpoint will be a change in FXN gene expression level after 12 weeks of treatment. Secondary Endpoints will be: frataxin protein level, cardiopulmonary exercise test outputs, echocardiographic measures, Nrf2 pathway and mitochondrial biogenesis gene expression, safety, clinical scales, and quality of life scales.Conclusions: this is the first study aimed at exploring the ability of DMF, an already available treatment for MS and psoriasis, to correct the biological deficits of FRDA and potentially improve mitochondrial respiration in-vivo.

Sarcoidosis is a systemic disease characterized by noncaseating granulomatous inflammation with tremendous clinical heterogeneity and uncertain pathobiology and lacking in clinically useful biomarkers. The Genomic Research in Alpha-1 Antitrypsin Deficiency and Sarcoidosis (GRADS) study is an observational cohort study designed to explore the role of the lung microbiome and genome in these two diseases. This article describes the design and rationale for the GRADS study sarcoidosis protocol. The study addresses the hypothesis that distinct patterns in the lung microbiome are characteristic of sarcoidosis phenotypes and are reflected in changes in systemic inflammatory responses as measured by peripheral blood changes in gene transcription. The goal is to enroll 400 participants, with a minimum of 35 in each of 9 clinical phenotype subgroups prioritized by their clinical relevance to understanding of the pathobiology and clinical heterogeneity of sarcoidosis. Participants with a confirmed diagnosis of sarcoidosis undergo a baseline visit with self-administered questionnaires, chest computed tomography, pulmonary function tests, and blood and urine testing. A research or clinical bronchoscopy with a research bronchoalveolar lavage will be performed to obtain samples for genomic and microbiome analyses. Comparisons will be made by blood genomic analysis and with clinical phenotypic variables. A 6-month follow-up visit is planned to assess each participant's clinical course. By the use of an integrative approach to the analysis of the microbiome and genome in selected clinical phenotypes, the GRADS study is powerfully positioned to inform and direct studies on the pathobiology of sarcoidosis, identify diagnostic or prognostic biomarkers, and provide novel molecular phenotypes that could lead to improved personalized approaches to therapy for sarcoidosis.

To investigate the relationship between the incidence of atrial fibrillation (AF) recurrence and the levels of the systemic immune-inflammatory index (SII, platelet × neutrophil/lymphocyte ratio) in patients with AF and diabetes mellitus (DM) undergoing after radiofrequency catheter ablation (RFCA). Preoperative SII levels were determined in AF patients with DM undergoing RFCA. Restricted cubic splines were used to determine the correlation between SII and the risk of AF recurrence. Multivariate-adjusted logistic regression models were constructed to determine the relationship between SII levels and AF recurrence. The predictive value of the clinical model and combined with the SII index was estimated by the area under the receiver-operating characteristic curve, net reclassification improvement (NRI), and integrated discrimination improvement (IDI). A total of 204 patients with AF and DM who underwent RFCA in our hospital were included. Seventy-seven patients had AF recurred during a mean follow-up of 20 months. Restricted cubic spline analysis showed that when SII ≥ 444.77 × 10 /L, there was a positive correlation with the incidence of AF recurrence. In addition, adding the SII to the predictive model for AF recurrence after RFCA in patients with DM and AF could contribute to an increase in C-statistics (0.798 vs. 0.749, p = .034). After SII was incorporated into the clinical model, the comprehensive discrimination and net reclassification tended to improve (IDI and NRI > 0, p < .05). SII was independently and positively associated with recurrence after the first catheter ablation in patients with DM and AF.

Background The increase in protocol complexity and the resulting rise in the effort required by investigative sites to implement protocols have been well documented, but existing measures of site burden only offer an incomplete view of the burden experienced by site personnel. The introduction of Decentralized Clinical Trials—trials supported by remote and virtual technologies and services—is expected to impact the burden imposed on sites, but this impact has not yet been systematically measured. Methods The Tufts Center for the Study of Drug Development conducted an online survey among clinical research sites worldwide and gathered 355 responses assessing the burden associated with distinct activities and procedures related to the implementation of clinical trial protocols using traditional and decentralized approaches. Results A high percentage of investigative sites (50.5%) have had no experience with DCT solutions and only a small percentage (6.6%) have participated in fully decentralized clinical trials. Overall, half of respondents view DCT solutions as more burdensome than traditional clinical trials. In general, activities related to operational and managerial aspects of trial implementation were viewed as less burdensome when done remotely, while clinical procedures or elements that require study team–patient interactions were viewed as more burdensome when using DCT approaches versus in-person or traditional methods.

Background The prevalence of type 2 diabetes (T2D) continues to rise in the United States and worldwide. Cognitive behavioral therapy (CBT) has been shown to improve glycemic control in patients with T2D, but broad implementation has been limited by inherent access and resource constraints. Digital therapeutics have the potential to overcome these obstacles. Hypothesis To describe the rationale and design of a trial evaluating the efficacy and safety of a digital therapeutic providing CBT to improve glycemic control in adults with T2D. Methods This randomized, controlled, multicenter, Phase 3 trial evaluates the hypothesis that BT‐001, an investigational digital therapeutic intended to help patients with T2D improve their glycemic control, on top of standard of care therapy, will lower hemoglobin A1c (HbA1c) compared to a control app across a broad range of patients in a real‐world setting. The study is designed to provide evidence to support FDA review of this device as a digital therapeutic. The intervention is provided within the digital application (app) and includes no person‐to‐person coaching. The primary endpoint is the difference in HbA1c change from baseline to 90 days for BT‐001‐allocated subjects compared with those assigned to the control app. Safety assessment includes adverse events and adverse device effects. The study incorporates pragmatic features including entirely remote conduct with at‐home visits for physical measures and blood sample collection. Conclusions This randomized, controlled trial evaluates a cognitive behavioral intervention delivered via smartphone app which has the potential to provide a scalable treatment option for patients with T2D.

Background The use of transcatheter aortic valve implantation (TAVI) for treating aortic stenosis (AS) has increased exponentially in recent years. Despite the availability of clinical practice guidelines for the management of valvular heart disease, disparities in quality of care (QoC) for TAVI patients remain widespread across Europe. Tailored QoC measures will help to reduce resource utilization and improve patient outcomes without compromising patient safety. Using a clear set of QoC measures, the BENCHMARK registry aims to document the progress that can be achieved if such tailored QoC measures are implemented. Methods The BENCHMARK registry (BENCHMARK) is a non‐interventional, multicenter registry in patients with severe symptomatic AS undergoing TAVI with a 1‐ and 12‐months follow‐up. BENCHMARK will be conducted at 30 centers across Europe and will enroll a total of 2400 consecutive TAVI patients. Patients suffering from severe symptomatic AS who undergo TAVI with a balloon‐expandable transcatheter aortic valve will be included. The registry will comprise four phases: (1) a retrospective baseline evaluation phase; (2) an education phase; (3) an implementation phase; and (4) a prospective effect documentation phase (prospective phase). The registry's primary objectives are to reduce the length of hospital stay and accelerate the post‐procedural patient recovery pathway, but without compromising safety. The study started in April 2021 and has an estimated completion date of May 2023. Discussion BENCHMARK will establish QoC measures to reduce resource utilization, intensive care unit bed occupancy, and overall length of hospitalization with uncompromised patient safety post‐TAVI (ClinicalTrials.gov Identifier: NCT04579445). Highlights The BENCHMARK registry is a non‐interventional, multicenter international registry. A total of 2400 patients with severe AS will be enrolled at 30 European centers. The registry is designed to be partly retrospective and partly prospective. The BENCHMARK registry will help to improve TAVI QoC standards across Europe.

The Reevaluation of Systemic Early Neuromuscular Blockade (ROSE) trial is a multicenter, randomized trial designed to assess the efficacy and safety of early neuromuscular blockade in patients with moderate to severe acute respiratory distress syndrome. This document provides background for interpretation of the trial results, and highlights unique design approaches that may inform future trials of acute illness. We describe the process by which ROSE was chosen as the inaugural trial of the multidisciplinary Prevention and Early Treatment of Acute Lung Injury Network, provide the trial methodology using the Consolidated Standards of Reporting Trials framework, and discuss key design challenges and their resolution. Four key design issues proved challenging-feasibility, choice of sedation depth in the control group, impact of emphasizing early treatment on enrollment criteria and protocol execution, and choice of positive end-expiratory pressure strategy. We used literature, an iterative consensus model, and internal surveys of current practice to inform design choice. ROSE will provide definitive, Consolidated Standards of Reporting Trials adherent data on early neuromuscular blockade for future patients with acute respiratory distress syndrome. Our multidisciplinary approach to trial design may be of use to other trials of acute illness. Clinical trial registered with www.clinicaltrials.gov (NCT02509078).

Background Heart failure with preserved ejection fraction (HFpEF) is associated with high hospitalization and mortality rates, representing a significant healthcare burden. This study aims to utilize various information including echocardiogram and phonocardiogram to construct and validate a nomogram, assisting in clinical decision‐making. Methods This study analyzed 204 patients (68 HFpEF and 136 non‐HFpEF) from the First Affiliated Hospital of Chongqing Medical University. A total of 49 features were integrated and used, including phonocardiogram, echocardiogram features, and clinical parameters. The least absolute shrinkage and selection operator (LASSO) regression was used to select the optimal matching factors, and a stepwise logistic regression was employed to determine independent risk factors and develop a nomogram. Model performance was evaluated by the area under receiver operating characteristic (ROC) curve (AUC), calibration curve, decision curve analysis (DCA), and clinical impact curve (CIC). Results The nomogram was constructed using five significant indicators, including NT‐proBNP (OR = 4.689, p = 0.015), E/e′ (OR = 1.219, p = 0.032), LAVI (OR = 1.088, p < 0.01), D/S (OR = 0.014, p < 0.01), and QM1 (OR = 1.058, p < 0.01), and showed a better AUC of 0.945 (95% CI = 0.908–0.982) in the training set and 0.933 (95% CI = 0.873–0.992) in the testing set compared to conventional nomogram without phonocardiogram features. The calibration curve and Hosmer–Lemeshow test demonstrated no statistical significance in the training and testing sets (p = 0.814 and p = 0.736), indicating the nomogram was well‐calibrated. The DCA and CIC results confirmed favorable clinical usefulness. Conclusion The nomogram, integrating phonocardiogram and echocardiogram features, enhances HFpEF diagnostic efficiency, offering a valuable tool for clinical decision‐making. A total of 204 patients and 49 features were collected. After splitting the population into training and test sets according to a ratio of 7:3, the LASSO and logistic regression was used to select the final five factors for a nomogram. The AUC for the nomogram model is 0.945, while the AUC for the echocardiographic parameters combined with NT‐proBNP in the diagnostic model (E/e′ + LAVI + NT‐proBNP) is 0.887. In conclusion, combining phonocardiogram, echocardiogram features, and clinical parameters can effectively improve the diagnostic efficiency of HFpEF.

The purpose of this study was to develop and validate a machine learning (ML) based prediction model for the risk of heart failure (HF) in patients with prediabetes or diabetes. We used 3527 subjects aged 40 years and older with a prior diagnosis of prediabetes or diabetes from the National Health and Nutrition Examination Survey (NHANES) from 2007 to 2018. The search for independent risk variables linked to HF was conducted using univariate and multivariable logistic regression analysis. The 3527 subjects were randomly divided into training set and validation set in a 7:3 ratio. Five ML models were built on the training set using five ML algorithms, including random forest (RF), and then validated on the validation set. Receiver operating characteristic (ROC) curves, calibration curves, and decision curve analysis and Bootstrap resampling method were used to measure the predictive performance of the five ML models. Multivariate logistic regression analysis showed that age, poverty-to-income ratio, myocardial infarction condition, coronary heart disease condition, chest pain condition, and glucose-lowering medication use were independent predictors of HF. By comparing the performance of the five ML models, the RF model (AUC = 0.978) was the best prediction model. The risk of HF in middle-aged and elderly patients with prediabetes or diabetes can be accurately predicted using ML models. The best prediction performance is presented by RF model, which can assist doctors in making clinical decisions.

Background Radiofrequency ablation has been applied for the treatment of hypertrophic obstructive cardiomyopathy (HOCM). The two known procedures are percutaneous intramyocardial septal radiofrequency ablation (PIMSRA) and endocardial radiofrequency septal ablation (ERSA). Methods This study presents a retrospective analysis of the PIMSRA and ERSA procedures in patients with drug‐refractory HOCM. A total of 28 patients participated in the study, with 12 receiving PIMSRA and 16 receiving ERSA. The objective of our study was to compare the short‐term effects of these two radiofrequency ablation procedures. Results At the 30‐day follow‐up, the PIMSRA group demonstrated a greater reduction in left ventricular outflow tract peak gradient at rest compared to the ERSA group (22.25 [16.72] mmHg versus 47.75 [21.94] mmHg) (p < .01). The values for the PIMSRA group decreased from 99.33 (32.00) mmHg to 22.25 (16.72) mmHg (p < .01), while the ERSA group decreased from 97.75 (30.24) mmHg to 47.75 (21.94) mmHg (p < .01). Only the PIMSRA group exhibited a decrease in mitral regurgitation (MR). The area of MR decreased from 10.13 (4.12) mm2 to 3.65 (2.80) mm2 in the PIMSRA group (p < .01). Additionally, the PIMSRA group experienced reductions in left atrial diameter (LAD) and left ventricular ejection fraction (LVEF)%. The values for LAD changed from 43.58 (7.53) mm to 37.08 (6.92) mm (p = .03), and the values for LVEF% decreased from 65.75 (6.12) pg/mL to 60.83 (4.06) pg/mL (p = .03). Conclusion In terms of the two types of radiofrequency ablation methods used in HOCM, it has been observed that PIMSRA demonstrates a more favorable early treatment effect compared to ERSA.