A longitudinal study on the effect of PM2.5 components on blood pressure in the hypertensive patients from 2011 to 2019.

Extensive research has established the link between PM2.5 exposure and blood pressure (BP) levels among normal individuals. However, the association between PM2.5 components and BP levels in hypertensive patients has not been fully explored. In this study, 12 971 hypertensive cases from Jinchang cohort (in Jinchang City, China) with nearly 9 years of follow-up were enrolled. Based on the linear mixed-effect model, the effects of fine particulate matter (PM2.5) and five major components [sulfate (SO42-), nitrate (NO3-), ammonium (NH4+), black carbon (BC) and organic matter (OM)]on BP [systolic blood pressure (SBP), diastolic blood pressure (DBP), mean arterial pressure (MAP) and pulse pressure (PP)]were evaluated by single-component model, component-joint model and component-residual model, respectively. A positive correlation was found between PM2.5 as well as its components (SO42-, NO3-, NH4+, BC and OM) exposure and BP levels. The effects of SO42-, BC and OM on BP were observed to be the most robust among the three models. Based on the results of interaction effects and stratified analysis, the effect of BC exposure on SBP, and the effect of PM2.5 and its five components on PP were greater in female than in males. Compared with elderly hypertensive patients, OM had more significant effects on SBP, DBP and MAP in young and (or) middle-aged hypertensive patients. During the heating season, the effect of PM2.5 and its components on BP was grater compared to the non-heating season. Meanwhile, PM2.5 and its components have a greater influence on BP in patients with hypertension combined with diabetes. Therefore, the findings suggested that both PM2.5 exposure and its components had a significant effect on BP in patients with hypertension. Women and young and middle-aged hypertensive patient were the sensitive population. The implementation of source control and reduction of PM2.5 emission (mainly for SO42-, BC and OM) may be of great significance to control BP level and could reduce the risk of cardiovascular disease in patients with hypertension.

Continuous Patient-Independent Estimation of Respiratory Rate and Blood Pressure Using Robust Spectro-Temporal Features Derived From Photoplethysmogram Only.

Objective: A patient-independent approach for continuous estimation of vital signs using robust spectro-temporal features derived from only photoplethysmogram (PPG) signal. Methods: In the pre-processing stage, we remove baseline shifts and artifacts of the PPG signal using Incremental Merge Segmentation with adaptive thresholding. From the cleaned PPG, we extract multiple parameters independent of individual patient PPG morphology for both Respiration Rate (RR) and Blood Pressure (BP). In addition, we derived a set of novel spectral and statistical features strongly correlated to BP. We proposed robust correlation-based feature selection methods for accurate RR estimates. For fewer computations and accurate measurements of BP, the most significant features are selected using correlation and mutual information measures in the feature engineering part. Finally, RR and BP are estimated using breath counting and a neural network regression model, respectively. Results: The proposed approach outperforms the current state-of-the-art in both RR and BP. The RR algorithm results in mean absolute errors (median, 25th-75th percentiles) of 0.4 (0.1-0.7) for CapnoBase dataset and 0.5(0.3-2.8) for BIDMC dataset without discarding any data window. Similarly, BP approach has been validated on a large dataset derived from MIMIC-II ([Formula: see text]1700 records) which has errors (mean absolute, standard deviation) of 5.0(6.3) and 3.0(4.0) for systolic and diastolic BP, respectively. The results meet the American Association for the Advancement of Medical Instrumentation (AAMI) and British Hypertension Society (BHS) Class A criteria. Conclusion: By using robust features and feature selection methods, we alleviated patient dependency to have reliable estimates of vitals.

Effect of blood pressure control on the risk of proteinuria during bevacizumab treatment in patients with colorectal cancer: a single-center retrospective cohort study.

PURPOSE: Pre-existing hypertension is reportedly a major risk factor for bevacizumab-induced proteinuria. However, few studies have focused on the effects of blood pressure (BP) control on proteinuria during bevacizumab treatment. We report a retrospective study of the association between poor BP control and the risk of developing proteinuria in patients with colorectal cancer (CRC). METHODS: Data for CRC patients who received bevacizumab between April 2015 and March 2022 were retrospectively collected. Patients were categorized into two groups based on average systolic blood pressure (SBP) during treatment: normal SBP (< 140 mmHg) and high SBP (≥ 140 mmHg). To evaluate the association between average SBP and grade ≥ 2 proteinuria, we used a 3 month landmark analysis and a Cox regression model. RESULTS: Of the 279 patients analyzed, 109 had high SBP and 170 had normal SBP. The cumulative incidence of grade ≥ 2 and severe proteinuria was significantly higher in the high compared to the normal SBP group (p < 0.001 and p = 0.028, respectively). Landmark analysis indicated significant differences in proteinuria between patients with and without high average SBP during the first 3 months of treatment (p = 0.002 and p = 0.015, respectively). Multivariate analysis showed that average SBP ≥ 140 mmHg was a significant independent risk factor for proteinuria (p = 0.008). CONCLUSION: Landmark analysis showed that BP status during the first 3 months of bevacizumab treatment influences the risk of subsequent proteinuria. Therefore, timely diagnosis and stricter BP control are recommended for at least the first 3 months to avoid severe proteinuria.

The promising role of Transcendental Meditation in the prevention and treatment of cardiometabolic diseases: A systematic review.

Psychological distress has a demonstrable impact on cardiovascular diseases (CVD) and risk factors. Transcendental Meditation (TM) has been shown to reduce stress and improve health and well-being. The current review aimed to synthesize the evidence on the effects of TM on cardiometabolic outcomes and identify gaps for future research. We searched PubMed/MEDLINE, EMBASE, SCOPUS, and Web of Science databases for relevant literature. Forty-five papers that reported studies of TM on cardiometabolic risk factors and diseases were included. Evidence shows that TM is effective in reducing blood pressure (BP). We found some evidence that TM can improve insulin resistance and may play a role in improving dyslipidemia, exercise tolerance, and myocardial blood flow, and in reducing carotid intima-media thickness and left ventricular mass. Studies show that long-term TM practice can reduce the risk of myocardial infarction, stroke, and CVD mortality. This review identified that certain studies have high participant drop-out rates, and fewer studies targeted comprehensive cardiometabolic outcomes beyond BP with longer follow-up periods. We found that most studies were conducted in specific populations, which may limit generalizability. In conclusion, TM has the potential to improve cardiometabolic health; however, research gaps highlight the need for larger phase III multicenter clinical trials with long-term follow-ups.

High-Detectivity All-Polymer Photodiode Empowers Smart Vitality Surveillance and Computational Imaging Rivaling Silicon Diodes.

Near-infrared (NIR) organic photodetectors (OPDs), particularly all-polymer-based ones, hold substantial commercial promise in the healthcare and imaging sectors. However, the process of optimizing their active layer composition to achieve highly competitive figures of merit lacks a clear direction and methodology. In this work, celebrity polymer acceptor PY-IT into a more NIR absorbing host system PBDB-T:PZF-V, to significantly enhance the photodetection competence, is introduced. The refined all-polymer ternary broadband photodetector demonstrates superior performance metrics, including experimentally measured noise current as low as 6 fA Hz-1/2, specific detectivity reaching 8 × 1012 Jones, linear dynamic range (LDR) of 145 dB, and swift response speed surpassing 200 kHz, striking a fair balance between sensitivity and response speed. Comprehensive morphological and photophysical characterizations elucidate the mechanisms behind the observed performance enhancements in this study, which include reduced trap density, enhanced charge transport, diminished charge recombination, and balanced electron/hole mobilities. Moreover, the practical deployment potential of the proof-of-concept device in self-powered mode is demonstrated through their application in a machine learning-based cuffless blood pressure (BP) estimation system and in high-resolution computational imaging across complex environments, where they are found to quantitatively rival commercial silicon diodes.

Renal function after ureteral reconstruction surgery in patients with solitary kidney.

Background: Ureteral strictures (US) could lead to impaired kidney function, which was alleviated by ureteral reconstruction surgery. However, solitary kidney (SK) patients with US were more complicated to treat. This study aimed to evaluate the impact of reconstruction surgery on renal function based on estimated glomerular filtration rate (eGFR) in patients with SK. Methods: We retrospectively enrolled patients who underwent reconstruction surgery between April 2014 to March 2022. eGFR was measured pre- and postoperatively. The 'static renal function' was defined as a change in eGFR of 20% or less at the last follow-up, and the 'worsening renal function group' was defined as a decrease of greater than 20%. Results: A total of 61 SK patients were involved. The success rate of ureteral reconstruction surgery was 90.16% (55/61). The median follow-up time was 20.8 months (range, 3.7-109.2 months). The median eGFR was 65.5 (range, 15.1-99.9) and 65.3 (range, 3.8-123.4) mL/min/1.73 m2 at the baseline and the last follow-up. No statistically significant difference in eGFR was observed between the preoperative baseline and last follow-up visits (P=0.58). However, in patients with baseline renal dysfunction [chronic kidney disease (CKD) stage 3-5], the eGFR significantly improved at the last follow-up compared to the baseline (P=0.02). Three patients developed a 'worsening renal function' (4.92%). Besides, the systolic blood pressures (SBP) at follow-up significantly reduced compared to the preoperative baseline (P=0.002). Conclusions: Ureteral reconstruction surgery is an effective treatment to preserve renal function, which also achieves a high success rate and is associated with the reduction of SBP for SK patients with US.

Mindfulness-based intervention for hypertension patients with depression and/or anxiety in the community: a randomized controlled trial.

OBJECTIVE: To evaluate mindfulness-based intervention for hypertension with depression and/or anxiety. METHODS: 10-week mindfulness-based intervention, including health education for hypertension, exclusively for the control group, was administered to the intervention group to assist sixty hypertension patients with depression/anxiety. Among them, the intervention group comprised 8 men and 22 women, with a mean age of 60.02 years and a mean duration of hypertension of 6.29 years. The control group consisted of 14 men and 16 women with a mean age of 57.68 years and a mean duration of hypertension of 6.32 years. The severity of depressive and/or anxiety symptoms was assessed using the 9-item Patient Health Questionnaire (PHQ-9) and the 7-item Generalized Anxiety Disorder scale (GAD-7), along with blood pressure (BP) measurements taken twice daily. The study utilized a self-made self-efficacy scale and awareness of physical and mental health to evaluate mental health and state. RESULTS: The depression PHQ-9 or GAD-7 scores reduced by 21.1% or 17.8% in the mindfulness-based intervention group, compared to the control (Z = -2.040, P = 0.041) post 10-week period, suggesting significant reduction in anxiety/stress. These results were consistent with a reduction in systolic BP of 12.24 mm Hg (t = 6.041, P = 0.000). The self-efficacy score of the mindfulness intervention group significantly improved compared to the control (t = 7.818, P < 0.001), while the awareness of physical and mental health in the mindfulness intervention group significantly improved compared to the control (χ2 = 5.781, P = 0.016). CONCLUSION: Mindfulness-based, short-term focused interventions provide modest relief for depression and/or anxiety and are effective in lowering blood pressure and improving self-efficacy scores. TRIAL REGISTRATION: Chinese Clinical Trial Registry, ChiCTR1900028258. Registered 16 December 2019, https://www.chictr.org.cn/showproj.html?proj=43627 .

Home blood pressure measurement self-reporting in real-life practices using the Hy-Result app: self-monitoring and digital pathway.

Background: Little real-life information is available on the clinical characteristics of information and communication technologies (ICTs) users, particularly in the context of hypertension and home blood pressure measurement (HBPM). This retrospective observational study describes HBPM practices obtained through the Hy-Result® system, a validated app designed to help patients perform HBPM and understand their results through an automatic interpretation of the readings using web interface. Methods: We analyzed 19,176 HBPM reports (sequence of 1 to 7 days of measurements; 3 in the morning, 3 in the evening) collected in real life circumstances from two groups of users: primary care (Prim) and hypertension center (Hosp). Results: Population: among the 19,176 reports, 63.2% declared receiving antihypertensive medication, having diabetes (15.2%), chronic kidney disease (9.7%) or history of stroke (7.6%). Treated users were older than normotensives [mean ± standard deviation (SD) age 64±12 vs. 58±14 years] with higher prevalence of comorbidities. Compliance with the HBPM schedule: the majority of reports (90.2%) totaled 15 systolic blood pressure (SBP) and diastolic blood pressure (DBP) readings or more, of which 96.1% were Hosp users and 89.3% Prim users, with a significant difference between both groups (P<0.001). The compliance rate for 7 days of measurement was higher in the Hosp group (57.6% vs. 30.5%; P<0.001). Blood pressure (BP) levels: in the 17,289 reports with a minimum of 15 readings, 42.7% had an average SBP and/or DBP above the recommended thresholds (below 135 and/or 85 mmHg), among whom, 36.8% were untreated subjects. Hosp users had better BP control than Prim (P<0.001). Users that are followed in the European Society of Hypertension (ESH) excellence center (Hosp) had better BP control than those in a Prim setting (P<0.001). HBPM oscillometric devices: in both groups, treated patients and untreated users, used the arm cuff devices more frequently than the wrist device. Conclusions: Our real-life study shows that 90% of the HBPM reports include the required minimum number of BP readings to allow the calculation of a reliable average among whom 40% have uncontrolled BP levels. The self-management Hy-Result web app demonstrates significant potential for inclusion in the patient care process and reinforces the patient's engagement to independently monitor and self-reported their BP. When the mean BP is not within the recommended range, the users were automatically prompted by text messages to seek medical advice by the software. Further research should determine the extent to which users adhere to text messages advice.

The association between sleep duration and cardiometabolic risk among children and adolescents in the United States (US): A NHANES study.

PURPOSE: This work aims to assess the association of sleep duration with cardiometabolic risk (adiposity, blood pressure, lipids, albuminuria and A1C) and to investigate lifestyle factors (physical activity, light exposure, caffeine consumption and sugar consumption) associated with sleep duration in children. METHODS: A nationally representative sample of 3907 children ages 6-17 years enrolled in NHANES from 2011 to 2014 was included in this cross-sectional study. Sleep duration was defined as the daily average time spent sleeping over 7 days as measured by a physical activity monitor (PAM). Participants without valid sleep data for ≥95% of the study were excluded. Regression models were adjusted for age, sex, race, body mass index (BMI) Z score, physical activity and light exposure. RESULTS: In adjusted regression models, longer sleep duration was associated with lower systolic blood pressure index (ß = -3.63 * 10-5, 95% CI -6.99 * 10-5, -2.78 * 10-6, p = 0.035) and BMI Z score (ß = -0.001, 95% CI -0.001, 0.000, p = 0.002). In logistic regression models, longer sleep duration was associated with lower odds of obesity (OR = 0.998, 95% CI 0.997, 0.999, p < 0.001) and overweight status (OR = 0.998, 95% CI 0.997, 0.999, p = 0.004). Greater light exposure (ß = 6.64 * 10-5, 95% CI 3.50 * 10-5, 9.69 * 10-5, p < 0.001) and physical activity (ß = 0.005, 95% CI 0.004, 0.006, p < 0.001) were associated with longer sleep. CONCLUSION: Longer sleep duration was associated with lower blood pressure and adiposity measures in children. Improving sleep quality by increasing physical activity and light exposure in childhood may decrease the lifetime risk of cardiometabolic disease.

PM2.5 associates with blood pressure: a Mendelian randomization analysis.

The relationship between fine particulate matter (PM2.5) and blood pressure (BP) is a controversial issue. We conducted a two-sample Mendelian randomization (MR) analysis and identified 58 genome-wide significant single-nucleotide polymorphisms associated with PM2.5 as instrument variables. Inverse-variance weighted (IVW) was used as the primary analysis approach. MR-Egger, weighted median, simple model, and weighted model methods were selected for quality control. We found a significant negative causal association of higher genetically predicted PM2.5 levels with lower systolic BP (SBP), while no causal relationship was identified between PM2.5 and diastolic BP (DBP). For each 1 standard deviation increase in genetically predicted PM2.5 levels, the beta value (95% CI) of SBP was -0.14 (-0.25, -0.03) for IVW (p=0.02), and -0.13 (-0.22, -0.04) for weighted median (p=0.005). Increased PM2.5 concentrations can lead to decreased SBP levels. Our findings provided novel insights into the controversial topic on the causal relationship between PM2.5 and BP.

Impacts of Supplementation with Silymarin on Cardiovascular Risk Factors: A Systematic Review and Dose-Response Meta-Analysis.

It has been suggested that silymarin (SIL) supplementation has positive effects on cardiovascular health and reduces the risk of cardiometabolic syndrome (CMS). This systematic review and dose-response meta-analysis assessed the impacts of SIL administration on cardiovascular risk factors. A systematic search of multiple databases was performed to identify eligible controlled trials published up to January 2023. The analysis used a random-effects model and included 33 trials with 1943 participants. It was revealed that SIL supplementation led to a notable reduction in serum levels of fasting blood glucose (FBG) (weighted mean difference (WMD): -21.68 mg/dL, 95% CI: -31.37, -11.99; p < 0.001), diastolic blood pressure (DBP) (WMD: -1.25 mmHg; 95% CI: -2.25, -0.26; p = 0.013), total cholesterol (TC) (WMD: -13.97 mg/dL, 95% CI: -23.09, -4.85; p = 0.003), triglycerides (TG) (WMD: -26.22 mg/dL, 95% CI: -40.32, -12.12; p < 0.001), fasting insulin (WMD: -3.76 mU/mL, 95% CI: -4.80, -2.72; p < 0.001), low-density lipoprotein (LDL) (WMD: -17.13 mg/dL, 95% CI: -25.63, -8.63; p < 0.001), and hemoglobin A1C (HbA1c) (WMD: -0.85%, 95% CI: -1.27, -0.43; p < 0.001) in the SIL-treated groups compared to their untreated counterparts. In addition, there were no substantial differences in body mass index (BMI), systolic blood pressure (SBP), C-reactive protein (CRP), body weight, and high-density lipoprotein (HDL) between the two groups. These outcomes suggest that SIL consumption reduces certain CMS risk factors and has favorable impacts on lipid and glycemic profiles with potential hypotensive effects. These findings should be supported by additional trials with larger sample sizes and longer durations.

Current insights and future perspectives of flavonoids: A promising antihypertensive approach.

Hypertension, or high blood pressure (BP), is a complex disease influenced by various risk factors. It is characterized by persistent elevation of BP levels, typically exceeding 140/90 mmHg. Endothelial dysfunction and reduced nitric oxide (NO) bioavailability play crucial roles in hypertension development. L-NG-nitro arginine methyl ester (L-NAME), an analog of L-arginine, inhibits endothelial NO synthase (eNOS) enzymes, leading to decreased NO production and increased BP. Animal models exposed to L-NAME manifest hypertension, making it a useful design for studying the hypertension condition. Natural products have gained interest as alternative approaches for managing hypertension. Flavonoids, abundant in fruits, vegetables, and other plant sources, have potential cardiovascular benefits, including antihypertensive effects. Flavonoids have been extensively studied in cell cultures, animal models, and, to lesser extent, in human trials to evaluate their effectiveness against L-NAME-induced hypertension. This comprehensive review summarizes the antihypertensive activity of specific flavonoids, including quercetin, luteolin, rutin, troxerutin, apigenin, and chrysin, in L-NAME-induced hypertension models. Flavonoids possess antioxidant properties that mitigate oxidative stress, a major contributor to endothelial dysfunction and hypertension. They enhance endothelial function by promoting NO bioavailability, vasodilation, and the preservation of vascular homeostasis. Flavonoids also modulate vasoactive factors involved in BP regulation, such as angiotensin-converting enzyme (ACE) and endothelin-1. Moreover, they exhibit anti-inflammatory effects, attenuating inflammation-mediated hypertension. This review provides compelling evidence for the antihypertensive potential of flavonoids against L-NAME-induced hypertension. Their multifaceted mechanisms of action suggest their ability to target multiple pathways involved in hypertension development. Nonetheless, the reviewed studies contribute to the evidence supporting the useful of flavonoids for hypertension prevention and treatment. In conclusion, flavonoids represent a promising class of natural compounds for combating hypertension. This comprehensive review serves as a valuable resource summarizing the current knowledge on the antihypertensive effects of specific flavonoids, facilitating further investigation and guiding the development of novel therapeutic strategies for hypertension management.

A continuous cuffless blood pressure measurement from optimal PPG characteristic features using machine learning algorithms.

Background and objective: Hypertension is a potentially dangerous health condition that can be detected by measuring blood pressure (BP). Blood pressure monitoring and measurement are essential for preventing and treating cardiovascular diseases. Cuff-based devices, on the other hand, are uncomfortable and prevent continuous BP measurement. Methods: In this study, a new non-invasive and cuff-less method for estimating Systolic Blood Pressure (SBP), Mean Arterial Pressure (MAP), and Diastolic Blood Pressure (DBP) has been proposed using characteristic features of photoplethysmogram (PPG) signals and nonlinear regression algorithms. PPG signals were collected from 219 participants, which were then subjected to preprocessing and feature extraction steps. Analyzing PPG and its derivative signals, a total of 46 time, frequency, and time-frequency domain features were extracted. In addition, the age and gender of each subject were also included as features. Further, correlation-based feature selection (CFS) and Relief F feature selection (ReliefF) techniques were used to select the relevant features and reduce the possibility of over-fitting the models. Finally, support vector regression (SVR), K-nearest neighbour regression (KNR), decision tree regression (DTR), and random forest regression (RFR) were established to develop the BP estimation model. Regression models were trained and evaluated on all features as well as selected features. The best regression models for SBP, MAP, and DBP estimations were selected separately. Results: The SVR model, along with the ReliefF-based feature selection algorithm, outperforms other algorithms in estimating the SBP, MAP, and DBP with the mean absolute error of 2.49, 1.62 and 1.43 mmHg, respectively. The proposed method meets the Advancement of Medical Instrumentation standard for BP estimations. Based on the British Hypertension Society standard, the results also fall within Grade A for SBP, MAP, and DBP. Conclusion: The findings show that the method can be used to estimate blood pressure non-invasively, without using a cuff or calibration, and only by utilizing the PPG signal characteristic features.

Hypotension prediction index for the prevention of hypotension during surgery and critical care: A narrative review.

Surgeons and anesthesia clinicians commonly face a hemodynamic disturbance known as intraoperative hypotension (IOH), which has been linked to more severe postoperative outcomes and increases mortality rates. Increased occurrence of IOH has been positively associated with mortality and incidence of myocardial infarction, stroke, and organ dysfunction hypertension. Hence, early detection and recognition of IOH is meaningful for perioperative management. Currently, when hypotension occurs, clinicians use vasopressor or fluid therapy to intervene as IOH develops but interventions should be taken before hypotension occurs; therefore, the Hypotension Prediction Index (HPI) method can be used to help clinicians further react to the IOH process. This literature review evaluates the HPI method, which can reliably predict hypotension several minutes before a hypotensive event and is beneficial for patients' outcomes.

Hemodynamic changes in progressive cerebral infarction: An observational study based on blood pressure monitoring.

Progressive cerebral infarction (PCI) is a common complication in patients with ischemic stroke that leads to poor prognosis. Blood pressure (BP) can indicate post-stroke hemodynamic changes which play a key role in the development of PCI. The authors aim to investigate the association between BP-derived hemodynamic parameters and PCI. Clinical data and BP recordings were collected from 80 patients with cerebral infarction, including 40 patients with PCI and 40 patients with non-progressive cerebral infarction (NPCI). Hemodynamic parameters were calculated from the BP recordings of the first 7 days after admission, including systolic and diastolic BP, mean arterial pressure, and pulse pressure (PP), with the mean values of each group calculated and compared between daytime and nighttime, and between different days. Hemodynamic parameters and circadian BP rhythm patterns  were compared between PCI and NPCI groups using t-test or non-parametric equivalent for continuous variables, Chi-squared test or Fisher's exact test for categorical variables, Cox proportional hazards regression analysis and binary logistic regression analysis for potential risk factors. In PCI and NPCI groups, significant decrease of daytime systolic BP appeared on the second and sixth days, respectively. Systolic BP and fibrinogen at admission, daytime systolic BP of the first day, nighttime systolic BP of the third day, PP, and the ratio of abnormal BP circadian rhythms were all higher in the PCI group. PCI and NPCI groups were significantly different in BP circadian rhythm pattern. PCI is associated with higher systolic BP, PP and more abnormal circadian rhythms of BP.

Noncontact remote sensing of abnormal blood pressure using a deep neural network: a novel approach for hypertension screening.

Background: As the global burden of hypertension continues to increase, early diagnosis and treatment play an increasingly important role in improving the prognosis of patients. In this study, we developed and evaluated a method for predicting abnormally high blood pressure (HBP) from infrared (upper body) remote thermograms using a deep learning (DL) model. Methods: The data used in this cross-sectional study were drawn from a coronavirus disease 2019 (COVID-19) pilot cohort study comprising data from 252 volunteers recruited from 22 July to 4 September 2020. Original video files were cropped at 5 frame intervals to 3,800 frames per slice. Blood pressure (BP) information was measured using a Welch Allyn 71WT monitor prior to infrared imaging, and an abnormal increase in BP was defined as a systolic blood pressure (SBP) ≥140 mmHg and/or diastolic blood pressure (DBP) ≥90 mmHg. The PanycNet DL model was developed using a deep neural network to predict abnormal BP based on infrared thermograms. Results: A total of 252 participants were included, of which 62.70% were male and 37.30% were female. The rate of abnormally high HBP was 29.20% of the total number. In the validation group (upper body), precision, recall, and area under the receiver operating characteristic curve (AUC) values were 0.930, 0.930, and 0.983 [95% confidence interval (CI): 0.904-1.000], respectively, and the head showed the strongest predictive ability with an AUC of 0.868 (95% CI: 0.603-0.994). Conclusions: This is the first technique that can perform screening for hypertension without contact using existing equipment and data. It is anticipated that this technique will be suitable for mass screening of the population for abnormal BP in public places and home BP monitoring.

Non-Invasive Blood Pressure Sensing via Machine Learning.

In this paper, a machine learning (ML) approach to estimate blood pressure (BP) using photoplethysmography (PPG) is presented. The final aim of this paper was to develop ML methods for estimating blood pressure (BP) in a non-invasive way that is suitable in a telemedicine health-care monitoring context. The training of regression models useful for estimating systolic blood pressure (SBP) and diastolic blood pressure (DBP) was conducted using new extracted features from PPG signals processed using the Maximal Overlap Discrete Wavelet Transform (MODWT). As a matter of fact, the interest was on the use of the most significant features obtained by the Minimum Redundancy Maximum Relevance (MRMR) selection algorithm to train eXtreme Gradient Boost (XGBoost) and Neural Network (NN) models. This aim was satisfactorily achieved by also comparing it with works in the literature; in fact, it was found that XGBoost models are more accurate than NN models in both systolic and diastolic blood pressure measurements, obtaining a Root Mean Square Error (RMSE) for SBP and DBP, respectively, of 5.67 mmHg and 3.95 mmHg. For SBP measurement, this result is an improvement compared to that reported in the literature. Furthermore, the trained XGBoost regression model fulfills the requirements of the Association for the Advancement of Medical Instrumentation (AAMI) as well as grade A of the British Hypertension Society (BHS) standard.

Estimating Blood Pressure during Exercise with a Cuffless Sphygmomanometer.

Accurately measuring blood pressure (BP) is essential for maintaining physiological health, which is commonly achieved using cuff-based sphygmomanometers. Several attempts have been made to develop cuffless sphygmomanometers. To increase their accuracy and long-term variability, machine learning methods can be applied for analyzing photoplethysmogram (PPG) signals. Here, we propose a method to estimate the BP during exercise using a cuffless device. The BP estimation process involved preprocessing signals, feature extraction, and machine learning techniques. To ensure the reliability of the signals extracted from the PPG, we employed the skewness signal quality index and the RReliefF algorithm for signal selection. Thereafter, the BP was estimated using the long short-term memory (LSTM)-based neural network. Seventeen young adult males participated in the experiments, undergoing a structured protocol composed of rest, exercise, and recovery for 20 min. Compared to the BP measured using a non-invasive voltage clamp-type continuous sphygmomanometer, that estimated by the proposed method exhibited a mean error of 0.32 ± 7.76 mmHg, which is equivalent to the accuracy of a cuff-based sphygmomanometer per regulatory standards. By enhancing patient comfort and improving healthcare outcomes, the proposed approach can revolutionize BP monitoring in various settings, including clinical, home, and sports environments.

Impact of frequent intradialytic hypotension on quality of life in patients undergoing hemodialysis.

BACKGROUND: Intradialytic hypotension (IDH) is frequently accompanied by symptoms of nausea, dizziness, fatigue, muscle spasm, and arrhythmia, which can adversely impact the daily lives of patients who undergo hemodialysis and may lead to decreased quality of life (QoL). This study employed the KDQOL™-36 scale to evaluate the impact of frequent IDH, based on the definition determined by predialysis blood pressure (BP) and nadir systolic blood pressure (SBP) thresholds, on the QoL of patients. METHODS: This is a single center retrospective cohort study involving 160 hemodialysis patients. We enrolled adult patients with uremia who received routine hemodialysis (4 h/time, 3 times/week) from October 1, 2019, to September 30, 2021. Frequent IDH was defined as an absolute nadir SBP < 90 mmHg occurring in no less than 30% of hemodialysis sessions when predialysis SBP < 159 mmHg (or < 100 mmHg when predialysis BP ≥ 160 mmHg).The differences between patients with and without frequent IDH were compared using the independent t test, Kruskal‒Wallis test, or chi-square test. The primary visit was at month 36, and the remaining visits were exploratory outcomes. RESULTS: Compared to patients with infrequent IDH at baseline, those with frequent IDH had significantly lower scores on the symptoms and discomfort of kidney disease dimension at all follow-up points (P < 0.05). The symptoms and discomfort of kidney disease dimension were worse in patients with frequent IDH. Those with frequent IDH had a significantly poorer QoL regarding the dimensions of symptoms and discomfort of kidney disease and the impact of kidney disease on life. CONCLUSIONS: The findings of the study suggest an association between frequent IDH and QoL dimensions of symptoms and discomfort of kidney disease and the impact of kidney disease on life dimension under the definition of frequent IDH.

Long-term exposure to PM2.5 and its components is associated with elevated blood pressure and hypertension prevalence: Evidence from rural adults.

INTRODUCTION: The toxicity of fine particulate matter (PM2.5) is determined by its components, while the evidence regarding associations of PM2.5 components with blood pressure (BP) is limited, especially in rural areas. OBJECTIVES: This study aimed to explore the associations of PM2.5 and its chemical components with systolic BP (SBP), diastolic BP (DBP), pulse pressure (PP), mean artery pressure (MAP) levels and hypertension prevalence, and to identify key components in Chinese rural areas. METHODS: 39,211 adults from the Henan Rural Cohort were included during 2015-2017. Different periods of PM2.5 and chemical components were estimated by hybrid satellite model. The single-pollutant, component-PM2.5 model, component-residual model and component-proportion model were applied to explore the associations of pollutants with BP levels and hypertension prevalence. Exposure-response (E-R) relationships, stratified analyses and sensitivity analyses were used to explore these associations further. RESULTS: 12,826 (32.71%) were identified with hypertension. For each 1 µg/m3 increase of pollutants, the adjusted odds ratio (OR) for hypertension prevalence was 1.03 for PM2.5 mass, 1.40 for BC, 1.16 for NH4+, 1.08 for NO3-, 1.17 for OM, 1.12 for SO42- and 1.25 for SOIL in the single-pollutant model. BC and SOIL were statistically significant in the component-PM2.5 model, component-residual model and component-proportion model. Similarly, associations of these pollutants with elevated BP levels were also found in aforementioned four models. These pollutants produced a stronger association with SBP than DBP, PP and MAP. Most of associations were non-linear in E-R relationships. The groups of older, the men, with lower per capita monthly income, lower educational level and higher BMI were more vulnerable to these pollutants in stratified analyses. The results remained stable in sensitivity analyses. CONCLUSION: Long-term exposure to PM2.5 and its components, especially BC and SOIL, was associated with elevated BP and hypertension prevalence in rural adults, and decreasing pollutants may provide additional benefits.