004). Heteroplasmy in the displacement loop and coding regions were significantly higher for PAD than non-PAD subjects after adjustment for age, sex, race, and diabetes mellitus (P=0.037 and 0.004, respectively). Low mitochondrial damage, defined by both low mitochondrial DNA copy number and low microheteroplasmy, was associated with better walking performance. Conclusions People with PAD have higher "low frequency" heteroplasmy in gastrocnemius muscle compared with people without PAD. Among people with PAD, those who had evidence of least mitochondrial damage, had better walking performance than those with more mitochondrial damage. Registration URL http//www.clinicaltrials.gov. Unique identifier NCT02246660.Background The prognostic impact of benzodiazepines has been unclear in patients with heart failure (HF). Methods and Results This was a historical observational cohort study. A total of 826 patients who had been hospitalized for HF and were being treated for insomnia with either benzodiazepines or Z-drugs (zolpidem, zopiclone, or eszopiclone), were enrolled and divided on the basis of their hypnotics benzodiazepine group (n=488 [59.1%]) and Z group (n=338 [40.9%]). We compared the patient characteristics and postdischarge prognosis between the groups. The primary end points were rehospitalization for HF and cardiac death. The benzodiazepine group was older (age, 72.0 versus 69.0 years; P=0.010), had a higher prevalence of depression (17.4% versus 8.9%; P less then 0.001), and showed a higher use of loop diuretics (77.9% versus 67.8%; P=0.001). In the laboratory data, the benzodiazepine group demonstrated lower levels of hemoglobin (12.3 versus 13.0 g/dL; P=0.001), sodium (139.0 versus 140.0 mEq/L; P=0.018), and albumin (3.7 versus 3.9 g/dL; P=0.003). Kaplan-Meier analysis showed that both end points were higher in the benzodiazepine group (rehospitalization for HF, log-rank P=0.001; cardiac death, log-rank P=0.043). Multiple Cox proportional hazard analysis revealed that the use of benzodiazepines was an independent predictor of rehospitalization for HF (hazard ratio, 1.530; 95% CI, 1.025-2.284; P=0.038). Furthermore, rehospitalization for HF was higher in the benzodiazepine group after propensity score matching (log-rank P=0.036). Conclusions Benzodiazepine is associated with higher risk of rehospitalization for HF compared with Z-drugs in patients with HF.Background Severe, symptomatic aortic stenosis (AS) is associated with poor prognoses.  https://www.selleckchem.com/products/nf-kb-activator-1.html  However, early detection of AS is difficult because of the long asymptomatic period experienced by many patients, during which screening tools are ineffective. The aim of this study was to develop and validate a deep learning-based algorithm, combining a multilayer perceptron and convolutional neural network, for detecting significant AS using ECGs. Methods and Results This retrospective cohort study included adult patients who had undergone both ECG and echocardiography. A deep learning-based algorithm was developed using 39 371 ECGs. Internal validation of the algorithm was performed with 6453 ECGs from one hospital, and external validation was performed with 10 865 ECGs from another hospital. The end point was significant AS (beyond moderate). We used demographic information, features, and 500-Hz, 12-lead ECG raw data as predictive variables. In addition, we identified which region had the most significant effect on the decision-making of the algorithm using a sensitivity map. During internal and external validation, the areas under the receiver operating characteristic curve of the deep learning-based algorithm using 12-lead ECG for detecting significant AS were 0.884 (95% CI, 0.880-0.887) and 0.861 (95% CI, 0.858-0.863), respectively; those using a single-lead ECG signal were 0.845 (95% CI, 0.841-0.848) and 0.821 (95% CI, 0.816-0.825), respectively. The sensitivity map showed the algorithm focused on the T wave of the precordial lead to determine the presence of significant AS. Conclusions The deep learning-based algorithm demonstrated high accuracy for significant AS detection using both 12-lead and single-lead ECGs.Background Heart rate variability (HRV) is associated with vascular risk factors for dementia, but whether HRV is associated with specific domains of cognitive performance is unclear. Methods and Results In the Multi-Ethnic Study of Atherosclerosis (N=3018; mean age 59.3±9.2 years), we assessed the relationship of 10-second HRV to scores on tests of global cognitive performance (Cognitive Abilities Screening Instrument), processing speed (Digit Symbol Coding), and working memory (Digit Span). HRV was computed as the SD of normal-normal intervals (SDNN) and root mean square of successive differences (RMSSD) at Exam 1 (2000-2002) and Exam 5 (2010-2012). Cognitive tests were administered at Exam 5. We report regression coefficients (β [95% CI]) representing cognitive test score change per 2-fold increase in HRV. After adjustment for age, race/ethnicity, sex, education, apolipoprotein E genotype, and cardiovascular risk factors and incident disease, higher Exam 1 (β=0.37 [0.06, 0.67]) and Exam 5 (β=0.31 [0.04, 0.59]) SDNN were associated with better Cognitive Abilities Screening Instrument performance. Higher Exam 1 (β=0.80 [0.17, 1.43]) and Exam 5 (β=0.63 [0.06, 1.20]) SDNN, and Exam 5 RMSSD (β=0.54 [0.01, 1.08]) were associated with better Digit Symbol Coding performance. Finally, higher Exam 5 SDNN was associated with better Digit Span performance (β=0.17 [0.01, 0.33]). Associations were attenuated after adjustment for resting heart rate. Conclusions Higher HRV is generally associated with better cognitive performance in this multi-ethnic cohort of aging adults, and further study of the relationship of autonomic function to cognition is warranted.Availability of reliable prognostic biomarkers also able to monitor preventive/therapeutic interventions in patients with Mild Cognitive Impairment (MCI) is crucial. Cerebral Brain Derived Neurotrophic Factor (BDNF) alterations were evidenced in Alzheimer's disease, but the value of blood BDNF in MCI is unclear, especially because of the incomplete/incorrect management of the numerous confounding factors unrelated to the disease. The present study, applying a multidisciplinary methodological approach, aimed to clarify whether blood BDNF can really mirror the cognitive symptoms of MCI, thus supporting the evaluation of clinical protocols' effectiveness as well as the definition of the conversion rate to dementia. Healthy elderly subjects (HE) and MCI patients were assessed for socio-demographic, neuropsychological, pharmacological and lifestyle data, and plasma BDNF was measured (baseline); then, in the MCI cohort, the biomarker was tested in a comprehensive cognitive stimulation intervention (CS) as well as in a 2-year follow-up period.