In patients with diabetes mellitus (DM), incident cardiovascular (CV) events are associated with poor long-term outcomes. Serum high-sensitivity troponin I (hs-TnI) is widely used to diagnose and predict outcomes in patients with acute coronary syndrome, however, few studies have investigated the accuracy of urine hs-TnI as a predictor for incident CV events in patients with DM. The enrolled participants included patients with DM. Fresh urine hs-TnI levels were measured. Medical records of enrolled patients were used to determine the number of incident CV events prospectively for 3 months. The study cohort comprised 378 participants. We observed significantly higher levels of urine hs-TnI in those with than without subsequent incident CV events. The multivariate logistic regression analysis using different models consistently showed that urine hs-TnI > 4.10 pg/mL was an independent factor predictive of incident CV events. The ROC-AUC analysis revealed that the optimal cutoff value for urine hs-TnI for predicting incident CV events was 1.55 pg/mL and the area was 0.611 (p = 0.027). A single measurement of urinary hs-TnI, collected easily and non-invasively, may be an acceptable biomarker for predicting subsequent incident CV events in patients with DM.

Background: Obesity-related cardiovascular risk, end points, and mortality are strongly related to arterial stiffening. Current therapeutic approaches for arterial stiffening are not focused on direct targeting within the vessel. Perivascular adipose tissue (PVAT) surrounding the artery has been shown to modulate vascular function and inflammation. Peroxisome proliferator-activated receptor γ (PPARγ) activation significantly decreases arterial stiffness and inflammation in diabetic patients with coronary artery disease. Thus, we hypothesized that PPARγ activation alters the PVAT microenvironment, thereby creating a favorable environment for the attenuation of arterial stiffening in obesity. Methods: Obese ob/ob mice were used to investigate the effect of PPARγ activation on the attenuation of arterial stiffening. Various cell types, including macrophages, fibroblasts, adipocytes, and vascular smooth muscle cells, were used to test the inhibitory effect of pioglitazone, a PPARγ agonist, on the expression of elastolytic enzymes. Results: PPARγ activation by pioglitazone effectively attenuated arterial stiffening in ob/ob mice. This beneficial effect was not associated with the repartitioning of fat from or changes in the browning of the PVAT depot but was strongly related to improvement of the PVAT microenvironment, as evidenced by reduction in the expression of pro-inflammatory and pro-oxidative factors. Pioglitazone treatment attenuated obesity-induced elastin fiber fragmentation and elastolytic activity and ameliorated the obesity-induced upregulation of cathepsin S and metalloproteinase 12, predominantly in the PVAT. In vitro, pioglitazone downregulated Ctss and Mmp12 in macrophages, fibroblasts, and adipocytes—cell types residing within the adventitia and PVAT. Ultimately, several PPARγ binding sites were found in Ctss and Mmp12 in Raw 264.7 and 3T3-L1 cells, suggesting a direct regulatory mechanism by which PPARγ activation repressed the expression of Ctss and Mmp-12 in macrophages and fibroblasts. Conclusions: PPARγ activation attenuated obesity-induced arterial stiffening and reduced the inflammatory and oxidative status of PVAT. The improvement of the PVAT microenvironment further contributed to the amelioration of elastin fiber fragmentation, elastolytic activity, and upregulated expression of Ctss and Mmp12. Our data highlight the PVAT microenvironment as an important target against arterial stiffening in obesity and provide a novel strategy for the potential clinical use of PPARγ agonists as a therapeutic against arterial stiffness through modulation of PVAT function.

Heart-sound auscultation is a rapid and fundamental technique used for examining the cardiovascular system. The main components of heart sounds are the first and second heart sounds. Discriminating these heart sounds under the presence of additional heart sounds and murmurs will be difficult. To recognize these signals efficiently, this study proposes a monitoring system with phonocardiogram and electrocardiogram. This system has two key points. The first is chip implementation, including capacitor coupled amplifier, transimpedance amplifier, high-pass sigma-delta modulator, and digital signal processing block. The chip in the system is fabricated in 0.18 μm standard complementary metal-oxide-semiconductor process. The second is a software application on smartphones for heart-related physiological signal recording, display, and identification. A wavelet-based QRS complex detection algorithm verified by MIT/BIH Arrhythmia Database is also proposed. The overall measured positive prediction, sensitivity, and error rate of the proposed algorithm are 99.90%, 99.82%, and 0.28%, respectively. During auscultation, doctors may refer to these physiological signals displayed on the smartphone and simultaneously listen to the heart sounds to diagnose the potential heart disease. By taking advantage of signal visualization and keeping the original diagnosis procedure, the uncertainty existing in heart sounds can be eliminated, and the training period to acquire auscultation skills can be reduced.

The detection of biosignals by using a comfortable material is important to improve human health. This paper presents a complete wearable system with smart clothing for the long-term monitoring of lead-I ECG and respiratory signals. The proposed system is divided into three parts, including biosignal-monitoring clothing, a biosignal acquisition device, and a software platform. The smart clothing integrates fabric-based ECG dry electrodes, conductive fiber traces, and a high-sensitivity capacitive respiration transducer to sense the biosignals. The challenge including the integration of ECG electrodes and the respiration transducer in the clothing system to provide the high-quality ECG and respiration signals for clinical use has been overcome in the proposed biosignal-monitoring clothing. The sensed signals on the smart clothing are collected in the biosignal-acquisition device through fabric-based traces and a specially designed clothing structure. Furthermore, the biosignals are processed using the biosignal-acquisition device and sent to the remote smart device through the Bluetooth module. The device according to the requirement of the front-end clothing system and the actual measurement accuracy is implemented and contributed onto the reduction in the effect of motion artifact. The software platform on the smart device provides real-time biosignal monitoring and health-information analysis. A highly efficient ECG QRS complex detection algorithm and respiratory-rate detection algorithm are also proposed. The ECG QRS complex detection algorithm is verified using the MIT/BIH Arrhythmia Database to demonstrate the achievement of high performance. The overall measured sensitivity, positive prediction, and error rate of the proposed algorithm are 99.86%, 99.93%, and 0.19%, respectively. The measured ECG signal of the clothing system is compared with the commercial silver/silver-chloride electrode by using the BIOPAC MP36 acquisition system. The result confirms the high quality of the signal, so the measured ECG signal can be used for medical applications. The function of the respiration transducer is verified by the BIOPAC SS11LA airflow transducer, and the overall accuracy of 19 test subjects is 98.74%. Using the proposed system, long-term health care in daily life can be achieved.

An electrocardiogram (ECG) test is usually performed through measurement with Ag/AgCl electrodes. However, this method has disadvantages, such as skin irritation, short shelf life, and conductance variation in gels over time, which limit the usability for long-term monitoring. One of the alternatives is adopting conductive fabric-based electrodes, but this method involves a problem in which a motion artifact (MA) becomes more severe because no gel and adhesive are available to provide a stable interface between the electrodes and the skin. To address this problem, this study presents a conductive fabric-based ECG monitoring system and an MA reduction algorithm. The system can simultaneously measure the ECG and the electrode-tissue impedance (ETI) with the proposed shirt. The MA reduction algorithm aims to reduce MA with ETI information. The MAs in Lead I, II, and III ECG measurement are generated by lifting arms, walking, and jogging. Results of the MA reduction are quantified by the correlation coefficient (CORR) and mean squared error (MSE). The quantitative analysis shows that the MA can be suppressed by the proposed algorithm. Moreover, compared with a reproduced existing approach, the proposed algorithm performs better in most cases.

Patients with atrial high-rate episodes (AHRE) are at higher risk of major adverse cardiovascular events (MACE). The cutoff threshold for AHRE duration for MACE, with/without history of atrial fibrillation (AF) or myocardial infarction (MI), is unknown. A total of 481 consecutive patients with/without history of AF or MI receiving dual-chamber pacemaker implantation were included. The primary outcome was a composite endpoint of MACE after AHRE ≥ 5 min, ≥ 6 h, and ≥ 24 h. AHRE was defined as > 175 bpm (MEDTRONIC) or > 200 bpm (BIOTRONIK) lasting ≥ 5 min. Cox regression analysis with time-dependent covariates was conducted. Patients’ mean age was 75.3 ± 10.7 years and 188 (39.1%) developed AHRE ≥ 5 min, 115 (23.9%) ≥ 6 h, and 83 (17.3%) ≥ 24 h. During follow-up (median 39.9 ± 29.8 months), 92 MACE occurred (IR 5.749%/year, 95% CI 3.88–5.85). AHRE ≥ 5 min (HR 5.252, 95% CI 2.575–10.715, P < 0.001) and ≥ 6 h (HR 2.548, 95% CI 1.284–5.058, P = 0.007) was independently associated with MACE, but not AHRE ≥ 24 h. Patients with history of MI (IR 17.80%/year) had higher MACE incidence than those without (IR 3.77%/year, p = 0.001). Significant differences were found between MACE patients with/without history of AF in AHRE ≥ 5 min but not AHRE ≥ 6 h or ≥ 24 h. Patients with dual-chamber pacemakers who develop AHRE have increased risk of MACE, particularly after history of AF or MI.