Background:The effect of remote monitoring (RM) in atrial arrhythmia detection, stroke reduction, and anticoagulation therapy remains unknown, particularly for patients with implantable or wearable cardiac devices.Methods and Results:We performed a systematic review and meta-analysis to evaluate the role of RM in atrial arrhythmia detection, stroke reduction and anticoagulation therapeutic intervention. Online databases were queried to include randomized controlled trials comparing detection of atrial arrhythmia and stroke risk between patients undergoing RM and those receiving in-office (IO) follow-up. Outcomes and complications of RM-guided anticoagulation therapy and conventional therapy in patients with atrial fibrillation were also reviewed. A total of 16 studies were included. Compared with patients receiving IO follow-up, patients undergoing RM had a significantly higher detection rate of atrial arrhythmia (risk ratio [RR], 1.363; 95% confidence interval [CI], 1.147–1.619), and a lower risk of stroke (RR, 0.539; 95% CI, 0.301–0.936). The higher rate of atrial arrhythmia was only noted in patients with wearable devices (RR, 4.070; 95% CI, 2.408–6.877), and the lower risk of stroke was only noted in patients with cardiovascular implantable electronic devices (CIED) (RR, 0.513; 95% CI, 0.265–0.996).Conclusions:RM is effective for atrial arrhythmia detection in patients using wearable devices and for reducing the risk of stroke in patients with CIED.

Heart failure (HF) is a syndrome encompassing several important etiologies that lead to the imbalance between oxygen demand and supply. Despite the usage of guideline-directed medical therapy for HF has shown better outcomes, novel therapeutic strategies are desirable, especially for patients with preserved or mildly reduced left ventricular ejection fraction. In this regard, understanding the molecular basis for cardiomyopathies is expected to fill in the knowledge gap and generate new therapies to improve prognosis for HF. This review discusses an evolutionary mechanism designed to regulate cardiac contraction and relaxation through the most often genetically determined cardiomyopathies associated with HF. In addition, both the myosin inhibitor and myosin activator are promising new treatments for cardiomyopathies. A comprehensive review from genetic mutations to the molecular basis of direct sarcomere modulators will help shed light on future studies for a better characterization of HF etiologies and potential therapeutic targets.

Recent advancements in flexible patches offer stretchability and adaptability to body contours. However, most require skin contact, causing potential discomfort for long-term health monitoring. We present a non-contact electromagnetic induction-based patch sensor that integrates a passive LC tank, inductance-to-digital converter ASIC, and wireless module into a flexible substrate, characterizing compact of 9 cm × 5 cm and lightweight of 6 g. The proposed patch sensor employs biomedical eddy current sensing to establish magnetic coupling between the sensor coil's magnetic field and the counteracting magnetic fields generated by the biomedical target's eddy currents. This enables the measurement of resonance frequency variations in response to pulsatile signals across multiple physiological sites, including the heart, lungs, carotid, radial, and femoral arteries, without direct skin contact. The sensor demonstrates high applicability across various fabric materials and thicknesses, effectively detecting heart rate (HR) through fabric layers up to 5.35 mm thick when positioned at the chest. The accuracy of HR and respiratory rate (RR) measurements across all tested physiological sites achieved mean absolute errors (MAE) within ± 5 beats per minute (bpm) and ± 3 respirations per minute (rpm), respectively. Furthermore, the sensor can effectively respond to real-time physiological state changes, as demonstrated by cold pressor test-induced HR variations and different breathing modes, highlighting its practicality in real-life scenarios. In conclusion, the proposed patch sensor provides an all-in-one flexible, non-contact solution capable of multi-site physiological monitoring, offering high accuracy, comfort, and adaptability for wearable health monitoring.

Accurate blood pressure measurement (BPM) is essential for managing hypertension, but previous studies have not systematically compared different monitoring methods across varying BP levels. To address this gap, a comprehensive analysis using network meta-analysis (NMA) and meta-regression was done to evaluate their agreement and clinical implications. To compare BP values obtained using different BPM methods using office BPM (OBPM) as the reference. Studies published in MEDLINE and Scopus up to October 2024. Studies aimed to compare the values between BPM methods in participants older than 18 years. Risk of bias was assessed on the basis of the internal validity of the study overall and the quality of the BPM methods. The mean differences between BPMs were calculated using NMA and meta-regression. Sixty-five studies encompassing 40 022 participants were analyzed. Compared with research office systolic BPM, the pooled mean differences from corresponding systolic BPs were 2.69 mm Hg (95% CI, -0.13 to 5.51 mm Hg) higher for convenient OBPM, 4.57 mm Hg (CI, 2.54 to 6.60 mm Hg) lower for automated OBPM, 4.59 mm Hg (CI, 2.83 to 6.34 mm Hg) lower for home BPM, 4.22 mm Hg (CI, 2.62 to 5.82 mm Hg) lower for daytime ambulatory BPM (ABPM), 18.14 mm Hg (CI, 16.21 to 20.06 mm Hg) lower for nighttime ABPM, and 8.63 mm Hg (CI, 6.97 to 10.28 mm Hg) lower for 24-hour ABPM. Differences varied by reference research OBPM levels: Higher reference BP levels are associated with larger differences between research office and other BPM methods. Heterogeneity due to the inclusion of studies with different research designs. Our analysis found differences among BPM methods that varied from the recommendations of current hypertension guidelines. Furthermore, discrepancies were more pronounced at elevated BP levels. Ministry of Health and Welfare, Taiwan. (PROSPERO: CRD42021246448).