Optimal blood pressure control with fewer antihypertensive medications: Achieved mostly in low-risk hypertensive patients.

Recent studies indicate that intensive blood pressure (BP) targets can be reached with less than two medications. This cross-sectional study, involving 4991 individuals from the Majiapu community, assessed the correlation between BP control and the burden of antihypertensive drugs. Participants on medication were categorized into controlled (BP < 140/90 mm Hg) and uncontrolled (BP ≥ 140/90 mm Hg) groups, with the former further divided into optimal (BP < 130/80 mm Hg) and good control (BP < 140/90 but >130/80 mm Hg) subgroups. Multivariate logistic regression analyzed factors affecting hypertension control across these BP categories. The study found that, 54% of participants had hypertension. Of those treated (62.5%), 55.7% achieved BP control, including 23.15% maintaining BP below 130/80 mm Hg. The average number of antihypertensive medications was 1.61 for the controlled group (with an average BP of 126.6/76 mm Hg) and 1.75 for the uncontrolled group (with an average BP of 150.6/84.0 mm Hg). Additionally, the average number of antihypertensive medications was 1.66 in the good control group and 1.55 in the optimal control group. The uncontrolled group had a higher mean systematic coronary risk estimation (SCORE) of 5.59, against 3.97 and 2.5 in the good and optimal control groups, respectively. Key factors linked to poor BP control included age over 65, male sex, obesity, and former smoking, whereas lipid-lowering medication use was associated with better control. In conclusions, patients needing fewer antihypertensive drugs to achieve stricter targets may have a lower risk profile. Notably, only a small proportion of treated patients are low-risk individuals who can easily achieve BP levels below 130/80 mm Hg.

Validation of the RBP-9801 oscillometric blood pressure monitor in the general population according to the association for the Advancement of Medical Instrumentation/European Society of Hypertension/ International Organization for Standardization Universal Standard.

The aim of this study was to evaluate the accuracy of the single upper-arm cuff oscillometric blood pressure (BP) monitor RBP-9801 developed for office and home BP measurement in the general population according to the Association for the Advancement of Medical Instrumentation/European Society of Hypertension/International Organization for Standardization (AAMI/ESH/ISO) Universal Standard (ISO 81060-2:2018). Subjects were recruited to fulfil the age, gender, BP and cuff distribution criteria of the AAMI/ESH/ISO Universal Standard in general population using the same arm sequential BP measurement method. A total of 105 subjects were recruited and 85 were analyzed. For validation criterion 1, the mean ± SD of the differences between the test device and reference BP readings was 2.3 ± 6.4/3.1 ± 5.8 mmHg (systolic/diastolic). For criterion 2, the SD of the mean BP differences between the test device and reference BP per subject was 5.24/5.03 mmHg (systolic/diastolic). The conclusion is that the RBP-9801 oscillometric device for office and home BP measurement fulfilled all the requirements of the AAMI/ESH/ISO Universal Standard (ISO 81060-2:2018) in the general population and can be recommended for clinic and self-use at home.

Validation of the Raycome model M2 ambulatory blood pressure monitor in the general population according to the Association for the Advancement of Medical Instrumentation/European Society of Hypertension/International Organization for Standardization Universal Standard (ISO 81060-2:2018).

OBJECTIVE: The aim of this study was to evaluate the accuracy of the Raycome model M2 oscillometric upper-arm blood pressure (BP) monitor developed for ambulatory BP measurement in the general population according to the Association for the Advancement of Medical Instrumentation/European Society of Hypertension/International Organization for Standardization (AAMI/ESH/ISO) Universal Standard (ISO 81060-2:2018) at rest and during dynamic exercise. METHOD: Subjects were recruited to fulfill the age, gender, BP and cuff distribution criteria of the AAMI/ESH/ISO Universal Standard in the general population using the same arm sequential BP measurement method. Three cuffs of the test device were used for arm circumference 18-22 cm (small), 22-32 cm (medium) and 32-42 cm (large). RESULTS: For the general validation study, 106 subjects were recruited and 85 were analyzed. For validation criterion 1, the mean ±â€…SD of the differences between the test device and reference BP readings was 0.5 ±â€…6.2/-0.2 ±â€…5.1 mmHg (systolic/diastolic). For criterion 2, the SD of the mean BP differences between the test device and reference BP per subject was 5.23/4.50 mmHg (systolic/diastolic). In the ambulatory validation study ( N  = 35), the mean difference was 0.4 ±â€…5.9/-1.1 ±â€…5.8 mmHg. The Raycome model M2 performed well against the standard in both the general and ambulatory validations and the Bland-Altman plots did not show any systematic variation in the error. CONCLUSION: These data show that the Raycome model M2 monitor meets the requirements of the AAMI/ESH/ISO Universal Standard (ISO 81060-2:2018) and in the ambulatory setting, indicating its suitability for measuring BP in the general population.

The association of triglyceride-glucose index and related parameters with hypertension and cardiovascular risk: a cross-sectional study.

The objective of this study was to investigate the association between triglyceride-glucose index (TyG) and related parameters (TyG-BMI, TyG-WC, TyG-WHR, and TyG-WHtR) with hypertension and cardiovascular risk. Additionally, the study aimed to compare the performance of these parameters in identifying patients with hypertension and high cardiovascular risk and determine appropriate indicators for the prediction of cardiovascular risk. Residents from a community in Beijing, China, who underwent health examinations at a regional hospital between December 2011 and August 2012, were recruited. Logistic regression analysis was used to explore the association between each parameter with hypertension and cardiovascular disease (CVD). The receiver operating characteristic curve was used to compare the predictive ability of each parameter in identifying people with hypertension or high cardiovascular risk. A total of 16,834 participants were included. After adjusting for confounders, the highest quartile groups of TyG and related parameters showed a significantly increased risk of hypertension compared to the lowest quartile groups. Among the parameters, TyG-WC exhibited the highest diagnostic efficacy for hypertension [area under the curve (AUC): 0.665, 95% CI: 0.656-0.673] followed by TyG-WHtR, TyG-BMI, TyG-WHR, and TyG index. Similarly, the highest quartile groups of each parameter demonstrated significantly increased risks of high cardiovascular risk compared to the lowest quartile groups. TyG-WHR performed best in distinguishing participants with high cardiovascular risk (AUC: 0.718, 95% CI: 0.710-0.726) followed by TyG-WC, TyG-WHtR, TyG-BMI, and TyG index. In conclusion, TyG-related parameters had independent associations with hypertension and cardiovascular risk. TyG-WHR exhibited the highest efficacy in distinguishing participants with high cardiovascular risk, which might contribute to the primary prevention of CVD.

A Fast Anti-Jamming Algorithm Based on Imitation Learning for WSN.

Wireless sensor networks (WSNs), integral components underpinning the infrastructure of the internet of things (IoT), confront escalating threats originating from attempts at malicious jamming. Nevertheless, the limited nature of the hardware resources in distributed, low-cost WSNs, such as those for computing power and storage, poses a challenge when implementing complex and intelligent anti-jamming algorithms like deep reinforcement learning (DRL). Hence, in this paper a rapid anti-jamming method is proposed based on imitation learning in order to address this issue. First, on-network nodes obtain expert anti-jamming trajectories using heuristic algorithms, taking historical experiences into account. Second, an RNN neural network that can be used for anti-jamming decision making is trained by mimicking these expert trajectories. Finally, the late-access network nodes receive anti-jamming network parameters from the existing nodes, allowing them to obtain a policy network directly applicable to anti-jamming decision making and thus avoiding redundant learning. Experimental results demonstrate that, compared with traditional Q-learning and random frequency-hopping (RFH) algorithms, the imitation learning-based algorithm empowers late-access network nodes to swiftly acquire anti-jamming strategies that perform on par with expert strategies.

Anti-Jamming Communication Using Imitation Learning.

The communication reliability of wireless communication systems is threatened by malicious jammers. Aiming at the problem of reliable communication under malicious jamming, a large number of schemes have been proposed to mitigate the effects of malicious jamming by avoiding the blocking interference of jammers. However, the existing anti-jamming schemes, such as fixed strategy, Reinforcement learning (RL), and deep Q network (DQN) have limited use of historical data, and most of them only pay attention to the current state changes and cannot gain experience from historical samples. In view of this, this manuscript proposes anti-jamming communication using imitation learning. Specifically, this manuscript addresses the problem of anti-jamming decisions for wireless communication in scenarios with malicious jamming and proposes an algorithm that consists of three steps: First, the heuristic-based Expert Trajectory Generation Algorithm is proposed as the expert strategy, which enables us to obtain the expert trajectory from historical samples. The trajectory mentioned in this algorithm represents the sequence of actions undertaken by the expert in various situations. Then obtaining a user strategy by imitating the expert strategy using an imitation learning neural network. Finally, adopting a functional user strategy for efficient and sequential anti-jamming decisions. Simulation results indicate that the proposed method outperforms the RL-based anti-jamming method and DQN-based anti-jamming method regarding solving continuous-state spectrum anti-jamming problems without causing "curse of dimensionality" and providing greater robustness against channel fading and noise as well as when the jamming pattern changes.

Effect of weight loss on blood pressure changes in overweight patients: A systematic review and meta-analysis.

To determine quantitative differences between weight loss and changes in clinic blood pressure (BP) and ambulatory BP in patients with obesity or overweight, the authors performed a meta-analysis. PubMed, Embase, and Scopus databases were searched up to June 2022. Studies that compared clinic or ambulatory BP with weight loss were included. A random effect model was applied to pool the differences between clinic BP and ambulatory BP. Thirty-five studies, for a total of 3219 patients were included in this meta-analysis. The clinic systolic blood pressure (SBP) and diastolic blood pressure (DBP) were significantly reduced by 5.79 mmHg (95% CI, 3.54-8.05) and 3.36 mmHg (95% CI, 1.93-4.75) after a mean body mass index (BMI) reduction of 2.27 kg/m2 , and the SBP and DBP were significantly reduced by 6.65 mmHg (95% CI, 5.16-8.14) and 3.63 mmHg (95% CI, 2.03-5.24) after a mean BMI reduction of 4.12 kg/m2 . The BP reductions were much larger in patients with a BMI decrease ≥3 kg/m2 than in patients with less BMI decrease, both for clinic SBP [8.54 mmHg (95% CI, 4.62-12.47)] versus [3.83 mmHg (95% CI, 1.22-6.45)] and clinic DBP [3.45 mmHg (95% CI, 1.59-5.30)] versus [3.15 mmHg (95% CI, 1.21-5.10)]. The significant reduction of the clinic and ambulatory BP followed the weight loss, and this phenomenon could be more notable after medical intervention and a larger weight loss.