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Andras Bikov,1,2 Peter Lange,3,4 Julie A Anderson,5 Robert D Brook,6 Peter MA Calverley,7 Bartolome R Celli,8 Nicholas J Cowans,9 Courtney Crim,10 Ian J Dixon,9 Fernando J Martinez,11 David E Newby,12 Julie C Yates,10 Jørgen Vestbo1,2 1Manchester University NHS Foundation Trust, Manchester Academic Health Science Centre, Manchester, UK; 2Division of Infection, Immunity & Respiratory Medicine, University of Manchester, Manchester, UK; 3Medical Department, Herlev and Gentofte Hospital, Herlev, Denmark; 4Section of Epidemiology, Department of Public Health, University of Copenhagen, Copenhagen, Denmark; 5Research & Development, GlaxoSmithKline, Middlesex, UK; 6University of Michigan Health System, Ann Arbor, MI, USA; 7University of Liverpool, Department of Medicine, Clinical Sciences Centre, University Hospital Aintree, Liverpool, UK; 8Pulmonary and Critical Care Division, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, USA; 9Statistics & Programming, Veramed Ltd., Twickenham, UK; 10Research & Development, GlaxoSmithKline, Research Triangle Park, NC, USA; 11Division of Pulmonary and Critical Care Medicine, Weill Cornell Medicine, New York, NY, USA; 12British Heart Foundation Centre for Cardiovascular Science, University of Edinburgh, Edinburgh, UKCorrespondence: Andras Bikov 2nd Floor ERC Building, Wythenshawe Hospital, Southmoor Road, Manchester M23 9LT, UKTel +36203141599Fax +441612915730Email andras.bikov@gmail.comPurpose: Chronic obstructive pulmonary disease (COPD) is one of the leading causes of death worldwide. Impaired lung function is associated with heightened risk for death, cardiovascular events, and COPD exacerbations. However, it is unclear if forced expiratory volume in one second (FEV1) and forced vital capacity (FVC) differ in predictive value.Patients and Methods: Data from 16,485 participants in the Study to Understand Mortality and Morbidity (SUMMIT) in COPD were analyzed. Patients were grouped into quintiles for each lung function parameter (FEV1 %predicted, FVC %predicted, FEV1/FVC). The four highest quintiles (Q2–Q5) were compared to the lowest (Q1) to assess their relationship with all-cause mortality, cardiovascular events, and moderate-to-severe and severe exacerbations. Cox-regression was used, adjusted for age, sex, ethnicity, body-mass index, smoking status, previous exacerbations, cardiovascular disease, treatment, and modified Medical Research Council dyspnea score.Results: Compared to Q1 (< 53.5% FEV1 predicted), increasing FEV1 quintiles (Q2 53.5– 457.5% predicted, Q3 57.5– 461.6% predicted, Q4 61.6– 465.8% predicted, and Q5 ≥ 65.8%) were all associated with significantly decreased all-cause mortality (20% (4– 34%), 28% (13– 40%), 23% (7– 36%), and 30% (15– 42%) risk reduction, respectively). In contrast, a significant risk reduction (21% (4– 35%)) was seen only between Q1 and Q5 quintiles of FVC. Neither FEV1 nor FVC was associated with cardiovascular risk. Increased FEV1 and FEV1/FVC quintiles were also associated with the reduction of moderate-to-severe and severe exacerbations while, surprisingly, the highest FVC quintile was related to the heightened exacerbation risk (28% (8– 52%) risk increase).Conclusion: Our results suggest that FEV1 is a stronger predictor for all-cause mortality than FVC in moderate COPD patients with heightened cardiovascular risk and that subjects with moderate COPD have very different risks.Keywords: airflow limitation, cardiovascular risk, exacerbation, lung function, lung volumes, death rate

Blood pressure (BP) is affected by many environmental factors including ambient temperature, altitude, latitude, noise, and air pollutants. Given their pervasiveness, it is plausible that such factors may also have an impact on hypertension prevalence and control rates. Health care providers should be aware that the environment can play a significant role in altering BP. Although not among the established modifiable risk factors (eg, obesity) for hypertension, reducing exposures when pertinent should be considered to prevent or control hypertension. The authors provide a concise review of the evidence linking diverse environmental factors with BP and suggest an approach for incorporating this knowledge into clinical practice. The authors propose using the term environmental hypertensionology to refer to the study of the effects of environmental factors on BP in clinical and research settings. [ABSTRACT FROM AUTHOR]

Arm size can affect the accuracy of blood pressure (BP) measurement, and "undercuffing" of large upper arms is likely to be a growing problem. Therefore, the authors investigated the relationship between upper arm and wrist readings. Upper arm and wrist circumferences and BP were measured in 261 consecutive patients. Upper arm auscultation and wrist BP was measured in triplicate, rotating measurements every 30 seconds between sites. Upper arm BP was 131.9+/-20.6/71.6+/-12.6 mm Hg in an obese population (body mass index, 30.6+/-6.6 kg/m(2)) with mean upper arm size of 30.7+/-5.1 cm. Wrist BP was higher (2.6+/-9.2 mm Hg and 4.9+/-6.6 mm Hg, respectively, P<.001); however, there was moderate concordance for the Seventh Report of the Joint National Committee on Prevention, Detection, Evaluation, and Treatment of High Blood Pressure (JNC 7) strata (kappa value=0.27-0.71), and the difference was >or=5 mm Hg in 72% of the patients. The authors conclude that there was poor concordance between arm and wrist BP measurement and found no evidence that "hidden undercuffing" was associated with obesity; therefore, they do not support routine use of wrist BP measurements. [ABSTRACT FROM AUTHOR]

Background: The public health relevance of daily Air Quality Index (AQI) activity guidelines for the general adult public in the United States to prevent atherosclerotic cardiovascular disease (ASCVD) events is questionable., Objectives: The purpose of the study was to explore the utility of a policy tailoring activity guidance to calculated ASCVD risk rather than uniform recommendations to the general adult public as currently provided., Methods: We calculated the number needed to treat (NNT) to prevent one ASCVD event per day by following activity recommendations across 10-year ASCVD risk scores (1% to 20%). Second, we modeled the benefits of tailoring recommendations to ASCVD risk., Results: The NNT decreased as ASCVD risk and/or AQI levels increased. At AQIs up to 151 (68% of days with AQIs above moderate in the United States), the NNTs remained untenably high (>2.7-55.3 million) across ASCVD risk. Under unhealthy conditions (AQIs 151-200), 28% of elevated AQIs, NNTs <1 million could be achieved by current guidance (15% exposure reduction), but only among the highest-risk individuals (ASCVD 18% to 20%) on the most polluted days (AQIs 192-200). Tailoring guidance to ASCVD risk could yield NNTs <1 million at risk thresholds of 7.5% and 10% if activity restrictions were more stringent (35% to 50% exposure reductions) during unhealthy conditions., Conclusions: ASCVD risk has a major influence on the NNT to prevent cardiovascular events by following AQI guidance. It may be possible for a future policy to improve the utility of AQI activity guidance for the general adult public by tailoring activity recommendations to ASCVD risk., Competing Interests: This study was supported by grant funding from the National Institutes of Environmental Health (1R35ES031702-01A1). The authors have reported that they have no relationships relevant to the contents of this paper to disclose., (© 2024 The Authors.)

Background: High blood pressure (BP) increases recurrent stroke risk., Methods and Results: We assessed hypertension prevalence, treatment, control, medication adherence, and predictors of uncontrolled BP 90 days after ischemic or hemorrhagic stroke among 561 Mexican American and non-Hispanic White (NHW) survivors of stroke from the BASIC (Brain Attack Surveillance in Corpus Christi) cohort from 2011 to 2014. Uncontrolled BP was defined as average BP ≥140/90 mm Hg at 90 days poststroke. Hypertension was uncontrolled BP or antihypertensive medication prescribed or hypertension history. Treatment was antihypertensive use. Adherence was missing zero antihypertensive doses per week. We investigated predictors of uncontrolled BP using logistic regression adjusting for patient factors. Median (interquartile range) age was 68 (59-78) years, 64% were Mexican American, and 90% of strokes were ischemic. Overall, 94.3% of survivors of stroke had hypertension (95.6% Mexican American versus 92.0% non-Hispanic White; P =0.09). Of these, 87.9% were treated (87.3% Mexican American versus 89.1% non-Hispanic White; P =0.54). Among the total population, 38.3% (95% CI, 34.4%-42.4%) had uncontrolled BP. Among those with uncontrolled BP prescribed an antihypertensive, 84.5% reported treatment adherence (95% CI, 78.8%-89.3%). Uncontrolled BP 90 days poststroke was less likely in patients with stroke who had a primary care physician (adjusted odds ratio [aOR], 0.45 [95% CI, 0.24-0.83]; P =0.01), greater stroke severity (aOR per-1-point-higher National Institutes of Health Stroke Scale score, 0.96 [95% CI, 0.93-0.99]; P =0.02), or more depressive symptoms (aOR per-1-point-higher Personal Health Questionnaire Depression Scale-8 score, 0.95 [95% CI, 0.92-0.99] among those with a history of hypertension at baseline; P =0.009)., Conclusions: Greater than one third of survivors of stroke have uncontrolled BP at 90 days poststroke in this population-based study. Interventions are needed to improve BP control after stroke.

Background: Exposure to fine particulate matter (<2.5 um, particulate matter with an aerodynamic diameter <2.5 microns [PM 2.5 ]) has been implicated in atherogenesis. Limited data in animal studies suggest that PM 2.5 exposure leads to myocardial fibrosis and increased incidence of heart failure (HF). Whether PM 2.5 is associated with adverse outcomes in patients with preexisting HF has not been widely studied., Methods and Results: In this retrospective cohort study, Medicare patients hospitalized with first HF between 2013 and 2020 were identified from the Medicare Provider Analysis and Review Part A 100% files. Patients were linked with integrated estimates of ambient PM 2.5 obtained at 1×1 km using the zip code of participants' residence. The study outcomes were all-cause death, HF, and all-cause readmissions burden. A total of 2 599 525 patients were included in this study, with 6 321 731 person-years of follow-up. Mean PM 2.5 was 7.3±1.7 μg/m 3 . Each interquartile range of PM 2.5 was associated with 0.9% increased hazard of all-cause death, 4.5% increased hazard of first HF readmission, 3.1% increased risk of HF hospitalization burden, and 5.2% increase in all-cause readmission burden, after adjusting for 11 sociodemographic and medical factors. Subgroup analyses showed that the effects were more pronounced at levels <7 μg/m 3 and in patients aged <75 years, Asians, and those residing in rural areas., Conclusions: Ambient air pollution is associated with higher risk of adverse events in Medicare beneficiaries with established HF. These associations persist below the National Air Quality Standards (12 μg/m 3 ), supporting that no threshold effect exists for health effects of air pollution exposure.

Importance: Reducing exposure to fine particulate matter (<2.5 μm [PM2.5]) air pollution improves cardiopulmonary morbidity and mortality. However, the public health relevance of air quality index (AQI) activity guidelines under present-day environmental conditions in the US has not been critically assessed., Objective: To evaluate the public health relevance of following PM2.5 AQI activity guidance in preventing serious atherosclerotic cardiovascular disease (ASCVD) and pulmonary events among adults in the US., Design, Setting, and Participants: This cross-sectional modeling study involved the general adult population and sensitive individuals as designated by the US Environmental Protection Agency (EPA), including adults with preexisting ASCVD or lung disease (asthma or chronic obstructive pulmonary disease). The study was conducted between August 1, 2023, and January 31, 2024., Exposures: Daily AQI strata for PM2.5 and the corresponding activity recommendations., Main Outcomes and Measures: The main outcome was the number needed to treat (NNT) per day by following activity guidance across daily AQI strata to prevent 1 serious ASCVD or pulmonary event among relevant populations. To calculate PM2.5-induced excess disease event rates per day, estimated baseline disease-specific daily event rates for each group were multiplied by the increase in risks due to PM2.5 levels at each AQI stratum. The number of events prevented per day was calculated by multiplying each excess disease event rate by the percentage in exposure reduction plausibly incurred by following population-specific activity guidance at each AQI level. The NNT is the reciprocal of the number of events prevented., Results: The NNT to prevent ASCVD events was high for the general population and for patients with ASCVD across all AQI strata. The range of values was comparatively lower to prevent pulmonary events among adults with lung disease. During most days (96%) when activity recommendations were promulgated due to elevated PM2.5 (AQI, 101-200), the NNT to prevent a serious disease event remained very high for the general population (>18 million), patients with ASCVD (approximately 1.6-5 million), and adults with lung disease (approximately 66 000-202 000)., Conclusions and Relevance: These findings suggest that existing PM2.5 AQI activity recommendations are of questionable public health relevance in present-day conditions and merit consideration for updating to improve their potential effectiveness.

Competing Interests: Disclosures None.

Competing Interests: Disclosures R.D. Brook is a consultant for Alnylam Pharmaceuticals. The other authors report no conflicts.

Background: Increased particulate matter <2.5 μm (PM 2.5 ) air pollution is associated with adverse cardiovascular outcomes. However, its impact on patients with prior coronary artery bypass grafting (CABG) is unknown., Objectives: The purpose of this study was to evaluate the association between major adverse cardiovascular events (MACE) (defined as myocardial infarction, stroke, or cardiovascular death) and air pollution after CABG., Methods: We linked 26,403 U.S. veterans who underwent CABG (2010-2019) nationally with average annual ambient PM 2.5 estimates using residential address. Over a 5-year median follow-up period, we identified MACE and fit a multivariable Cox proportional hazard model to determine the risk of MACE as per PM 2.5 exposure. We also estimated the absolute potential reduction in PM 2.5 attributable MACE simulating a hypothetical PM 2.5 lowered to the revised World Health Organization standard of 5 μg/m 3 ., Results: The observed median PM 2.5 exposure was 7.9 μg/m 3 (IQR: 7.0-8.9 μg/m 3 ; 95% of patients were exposed to PM 2.5 above 5 μg/m 3 ). Increased PM 2.5 exposure was associated with a higher 10-year MACE rate (first tertile 38% vs third tertile 45%; P  < 0.001). Adjusting for demographic, racial, and clinical characteristics, a 10 μg/m 3 increase in PM 2.5 resulted in 27% relative risk for MACE (HR: 1.27, 95% CI: 1.10-1.46; P  < 0.001). Currently, 10% of total MACE is attributable to PM 2.5 exposure. Reducing maximum PM 2.5 to 5 μg/m 3 could result in a 7% absolute reduction in 10-year MACE rates., Conclusions: In this large nationwide CABG cohort, ambient PM 2.5 air pollution was strongly associated with adverse 10-year cardiovascular outcomes. Reducing levels to World Health Organization-recommended standards would result in a substantial risk reduction at the population level., Competing Interests: The authors have reported that they have no relationships relevant to the contents of this paper to disclose.

Background: The Reducing Air Pollution in Detroit Intervention Study (RAPIDS) was designed to evaluate cardiovascular health benefits and personal fine particulate matter (particulate matter < 2.5 μm in diameter, PM 2.5 ) exposure reductions via portable air filtration units (PAFs) among older adults in Detroit, Michigan. This double-blind randomized crossover intervention study has shown that, compared to sham, air filtration for 3 days decreased 3-day average brachial systolic blood pressure by 3.2 mmHg. The results also showed that commercially available HEPA-type and true HEPA PAFs mitigated median indoor PM 2.5 concentrations by 58% and 65%, respectively. However, to our knowledge, no health intervention study in which a significant positive health effect was observed has also evaluated how outdoor and indoor PM 2.5 sources impacted the subjects. With that in mind, detailed characterization of outdoor and indoor PM 2.5 samples collected during this study and a source apportionment analysis of those samples using a positive matrix factorization model were completed. The aims of this most recent work were to characterize the indoor and outdoor sources of the PM 2.5 this community was exposed to and to assess how effectively commercially available HEPA-type and true HEPA PAFs were able to reduce indoor and outdoor PM 2.5 source contributions. Methods: Approximately 24 h daily indoor and outdoor PM 2.5 samples were collected on Teflon and Quartz filters from the apartments of 40 study subjects during each 3-day intervention period. These filters were analyzed for mass, carbon, and trace elements. Environmental Protection Agency Positive Matrix Factorization (PMF) 5.0 was utilized to determine major emission sources that contributed to the outdoor and indoor PM 2.5 levels during this study. Results: The major sources of outdoor PM 2.5 were secondary aerosols (28%), traffic/urban dust (24%), iron/steel industries (15%), sewage/municipal incineration (10%), and oil combustion/refinery (6%). The major sources of indoor PM 2.5 were organic compounds (45%), traffic + sewage/municipal incineration (14%), secondary aerosols (13%), smoking (7%), and urban dust (2%). Infiltration of outdoor PM 2.5 for sham, HEPA-type, and true HEPA air filtration was 79 ± 24%, 61 ± 32%, and 51 ± 34%, respectively. Conclusions: The results from our study showed that intervention with PAFs was able to significantly decrease indoor PM 2.5 derived from outdoor and indoor PM 2.5 sources. The PAFs were also able to significantly reduce the infiltration of outdoor PM 2.5 . The results of this study provide insights into what types of major PM 2.5 sources this community is exposed to and what degree of air quality and systolic blood pressure improvements are possible through the use of commercially available PAFs in a real-world setting.

Fine particulate matter (PM 2.5 ) air pollution is a leading contributor to the global burden of cardiovascular disease (CVD). One important underlying mechanism is an increase in blood pressure (BP). A growing number of studies have reported a beneficial effect of portable air cleaners (PACs) on systolic and diastolic BP; SBP and DBP. We conducted an updated systematic review and meta-analysis of studies using true versus sham mode filtration reporting the effects on BP. Of 214 articles identified up to February 5, 2023, seventeen (from China, USA, Canada, South Korea and Denmark) enrolling approximately 880 participants (484 female) met the inclusion criteria for meta-analyses. Aside from studies conducted in China, research on PACs and BP has been conducted in relatively low pollution settings. Mean indoor PM 2.5 concentrations during the active and sham mode purification were 15.9 and 41.2 µg/m 3 , respectively. The mean efficiency of PACs against indoor PM 2.5 was 59.8 % (ranging from 23 % to 82 %). True mode filtration was associated with a pooled mean difference of - 2.35 mmHg (95 % confidence interval [CI]: - 4.5, - 0.2) and - 0.81 mmHg (95 % CI: - 1.86, 0.24) in SBP and DBP, respectively. After removing the studies with high risk of bias, the magnitude of the pooled benefits on SBP and DBP increased to - 3.62 mmHg (95 % CI: - 6.69, - 0.56) and - 1.35 mmHg (95 % CI: - 2.29, - 0.41), respectively. However, there are several barriers to the use of PACs, specifically in low- and middle-income countries (LMICs), such as the initial purchase cost and filter replacements. There may be several avenues to help overcome these economic burdens and improve cost effectiveness, such as implementing government or other subsidized programs to distribute PACs targeting vulnerable and higher-risk individuals. We propose that environmental health researchers and healthcare providers should be better trained to educate the public regarding the use of PACs to reduce the impacts of PM 2.5 on cardiometabolic diseases globally., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. It should be noted that Ryan W. Allen has conducted studies using PACs purchased at a discounted rate from Woongjin-Coway., (Copyright © 2023 The Authors. Published by Elsevier Inc. All rights reserved.)

Traffic noise and air pollution are 2 major environmental health risk factors in urbanized societies that often occur together. Despite cooccurrence in urban settings, noise and air pollution have generally been studied independently, with many studies reporting a consistent effect on blood pressure for individual exposures. In the present reviews, we will discuss the epidemiology of air pollution and noise effects on arterial hypertension and cardiovascular disease (part I) and the underlying pathophysiology (part II). Both environmental stressors have been found to cause endothelial dysfunction, oxidative stress, vascular inflammation, circadian dysfunction, and activation of the autonomic nervous system, thereby facilitating the development of hypertension. We also discuss the effects of interventions, current gaps in knowledge, and future research tasks. From a societal and policy perspective, the health effects of both air pollution and traffic noise are observed well below the current guideline recommendations. To this end, an important goal for the future is to increase the acceptance of environmental risk factors as important modifiable cardiovascular risk factors, given their substantial impact on the burden of cardiovascular disease., Competing Interests: Disclosures None.

Traffic noise and air pollution are environmental stressors found to increase risk for cardiovascular events. The burden of disease attributable to environmental stressors and cardiovascular disease globally is substantial, with a need to better understand the contribution of specific risk factors that may underlie these effects. Epidemiological observations and experimental evidence from animal models and human controlled exposure studies suggest an essential role for common mediating pathways. These include sympathovagal imbalance, endothelial dysfunction, vascular inflammation, increased circulating cytokines, activation of central stress responses, including hypothalamic and limbic pathways, and circadian disruption. Evidence also suggests that cessation of air pollution or noise through directed interventions alleviates increases in blood pressure and intermediate surrogate pathways, supporting a causal link. In the second part of this review, we discuss the current understanding of mechanisms underlying and current gaps in knowledge and opportunities for new research., Competing Interests: Disclosures None.

As the world's population becomes increasingly urbanized, there is growing concern about the impact of urban environments on cardiovascular health. Urban residents are exposed to a variety of adverse environmental exposures throughout their lives, including air pollution, built environment, and lack of green space, which may contribute to the development of early cardiovascular disease and related risk factors. While epidemiological studies have examined the role of a few environmental factors with early cardiovascular disease, the relationship with the broader environment remains poorly defined. In this article, we provide a brief overview of studies that have examined the impact of the environment including the built physical environment, discuss current challenges in the field, and suggest potential directions for future research. Additionally, we highlight the clinical implications of these findings and propose multilevel interventions to promote cardiovascular health among children and young adults., Competing Interests: Disclosures None.

Conjunctival melanoma is an uncommon and malignant tumor of the ocular surface with the propensity for metastasis and death. Despite the grim outlook, the factors predicting poor prognosis are slowly being uncovered given the rarity of the disease. Here, we present a rare and surprising case of a long standing, extensive, and invasive conjunctival melanoma that, despite multiple factors predicting a poor prognosis, had no systemic metastatic disease. We hope that by reviewing in depth the various factors that may explain our patient's unusual course of illness we can add to our growing understanding of conjunctival melanoma., Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (©2023PublishedbyElsevierInc.)

Background: Fine particulate matter (PM 2.5 ) promotes atherosclerosis progression and plaque vulnerability. Consequently, patients with a high atherosclerotic burden may be at especially increased risk when exposed to air pollution., Objectives: The purpose of this study was to examine the relationship between chronic ambient PM 2.5 exposure and adverse outcomes after percutaneous coronary interventions (PCI)., Methods: Baseline clinical and procedural data from U.S. veterans undergoing elective PCI (2005-2018) were linked to annual ambient PM 2.5 exposure. The association between PM 2.5 exposure and major adverse cardiovascular events (MACEs) (myocardial infarction, stroke, or all-cause mortality) was determined using time-varying Cox regression models. Using flexible parametric models, we also evaluated the average life months lost for specific PM 2.5 levels over the 15-year period., Results: In the 73,425 veterans that underwent an elective PCI, the mean annual PM 2.5 exposure was 8.4 ± 1.8 μg/m 3 (median follow-up 6.75 years). The incidence of MACE was 28%, 48%, and 65% at 5, 10, and 15 years, respectively. In adjusted models, each 1-μg/m 3 increase in PM 2.5 exposure was associated with an 8.7% (95% CI: 8.4%-8.9%; P  < 0.001) increase in MACE. Compared to patients exposed to 5 μg/m 3 , those exposed to 10 μg/m 3 lost 1.1, 3.8, and 7.6 months of life at 5, 10, and 15 years of exposure, respectively., Conclusions: Veterans undergoing elective PCI are at increased risk of MACE and significant life years lost with long-term exposure to fine particulate matter pollution, even at the current low levels in the United States. These findings emphasize the need for improved air quality standards and patient interventions to better protect vulnerable populations., Competing Interests: This work was partly funded by the 10.13039/100006545National Institute on Minority Health and Health Disparities Award #P50MD017351. The authors have reported that they have no relationships relevant to the contents of this article to disclose., (© 2023 The Authors.)

Particulate-filtering respirators (PFRs) have been recommended as a practical personal-level intervention to protect individuals from the health effects of particulate matter exposure. However, the cardiovascular benefits of PFRs including improvements in key surrogate endpoints remain unclear. We performed a systematic review and meta-analysis of randomized studies (wearing versus not wearing PFRs) reporting the effects on blood pressure (BP) and heart rate variability (HRV). The search was performed on January 3, 2022 to identify published papers until this date. We queried three English databases, including PubMed, Web of Science Core Collection and Scopus. Of 527 articles identified, eight trials enrolling 312 participants (mean age ± standard deviation: 36 ± 19.8; 132 female) met our inclusion criteria for analyses. Study participants wore PFRs from 2 to 48 h during intervention periods. Wearing PFRs was associated with a non-significant pooled mean difference of -0.78 mmHg (95% confidence interval [CI]: -2.06, 0.50) and -0.49 mmHg (95%CI: -1.37, 0.38) in systolic and diastolic BP (SBP and DBP). There was a marginally significant reduction of mean arterial pressure (MAP) by nearly 1.1 mmHg (95%CI: -2.13, 0.01). The use of PFRs was associated with a significant increase of 38.92 ms 2 (95%CI: 1.07, 76.77) in pooled mean high frequency (power in the high frequency band (0.15-0.4 Hz)) and a reduction in the low (power in the low frequency band (0.04-0.15Hz))-to-high frequency ratio [-0.14 (95%CI: -0.27, 0.00)]. Other HRV indices were not significantly changed. Our meta-analysis demonstrates modest or non-significant improvements in BP and many HRV parameters from wearing PFRs over brief periods. However, these findings are limited by the small number of trials as well as variations in experimental designs and durations. Given the mounting global public health threat posed by air pollution, larger-scale trials are warranted to elucidate more conclusively the potential health benefits of PFRs., (Copyright © 2022. Published by Elsevier Ltd.)

Emotions play an essential role in human relationships, and many real-time applications rely on interpreting the speaker's emotion from their words. Speech emotion recognition (SER) modules aid human-computer interface (HCI) applications, but they are challenging to implement because of the lack of balanced data for training and clarity about which features are sufficient for categorization. This research discusses the impact of the classification approach, identifying the most appropriate combination of features and data augmentation on speech emotion detection accuracy. Selection of the correct combination of handcrafted features with the classifier plays an integral part in reducing computation complexity. The suggested classification model, a 1D convolutional neural network (1D CNN), outperforms traditional machine learning approaches in classification. Unlike most earlier studies, which examined emotions primarily through a single language lens, our analysis looks at numerous language data sets. With the most discriminating features and data augmentation, our technique achieves 97.09%, 96.44%, and 83.33% accuracy for the BAVED, ANAD, and SAVEE data sets, respectively., Competing Interests: The authors declare that there are no conflicts of interest regarding the publication of this paper., (Copyright © 2022 Abeer Ali Alnuaim et al.)

Human-computer interaction (HCI) has seen a paradigm shift from textual or display-based control toward more intuitive control modalities such as voice, gesture, and mimicry. Particularly, speech has a great deal of information, conveying information about the speaker's inner condition and his/her aim and desire. While word analysis enables the speaker's request to be understood, other speech features disclose the speaker's mood, purpose, and motive. As a result, emotion recognition from speech has become critical in current human-computer interaction systems. Moreover, the findings of the several professions involved in emotion recognition are difficult to combine. Many sound analysis methods have been developed in the past. However, it was not possible to provide an emotional analysis of people in a live speech. Today, the development of artificial intelligence and the high performance of deep learning methods bring studies on live data to the fore. This study aims to detect emotions in the human voice using artificial intelligence methods. One of the most important requirements of artificial intelligence works is data. The Ryerson Audio-Visual Database of Emotional Speech and Song (RAVDESS) open-source dataset was used in the study. The RAVDESS dataset contains more than 2000 data recorded as speeches and songs by 24 actors. Data were collected for eight different moods from the actors. It was aimed at detecting eight different emotion classes, including neutral, calm, happy, sad, angry, fearful, disgusted, and surprised moods. The multilayer perceptron (MLP) classifier, a widely used supervised learning algorithm, was preferred for classification. The proposed model's performance was compared with that of similar studies, and the results were evaluated. An overall accuracy of 81% was obtained for classifying eight different emotions by using the proposed model on the RAVDESS dataset., Competing Interests: The authors declare that there are no conflicts of interest regarding the publication of this paper., (Copyright © 2022 Abeer Ali Alnuaim et al.)

Sign language is the native language of deaf people, which they use in their daily life, and it facilitates the communication process between deaf people. The problem faced by deaf people is targeted using sign language technique. Sign language refers to the use of the arms and hands to communicate, particularly among those who are deaf. This varies depending on the person and the location from which they come. As a result, there is no standardization about the sign language to be used; for example, American, British, Chinese, and Arab sign languages are all distinct. Here, in this study we trained a model, which will be able to classify the Arabic sign language, which consists of 32 Arabic alphabet sign classes. In images, sign language is detected through the pose of the hand. In this study, we proposed a framework, which consists of two CNN models, and each of them is individually trained on the training set. The final predictions of the two models were ensembled to achieve higher results. The dataset used in this study is released in 2019 and is called as ArSL2018. It is launched at the Prince Mohammad Bin Fahd University, Al Khobar, Saudi Arabia. The main contribution in this study is resizing the images to 64 ∗ 64 pixels, converting from grayscale images to three-channel images, and then applying the median filter to the images, which acts as lowpass filtering in order to smooth the images and reduce noise and to make the model more robust to avoid overfitting. Then, the preprocessed image is fed into two different models, which are ResNet50 and MobileNetV2. ResNet50 and MobileNetV2 architectures were implemented together. The results we achieved on the test set for the whole data are with an accuracy of about 97% after applying many preprocessing techniques and different hyperparameters for each model, and also different data augmentation techniques., Competing Interests: The authors declare that they have no conflicts of interest., (Copyright © 2022 Abeer Alnuaim et al.)

The field of image processing is distinguished by the variety of functions it offers and the wide range of applications it has in biomedical imaging. It becomes a difficult and time-consuming process for radiologists to do the manual identification and categorization of the tumour. It is a complex and time-consuming procedure conducted by radiologists or clinical professionals to remove the contaminated tumour region from magnetic resonance (MR) pictures. It is the goal of this study to improve the performance and reduce the complexity of the image segmentation process by investigating FCM predicted image segmentation procedures in order to reduce the intricacy of the process. Furthermore, relevant characteristics are collected from each segmented tissue and aligned as input to the classifiers for autonomous identification and relegation of encephalon cancers in order to increase the accuracy and quality rate of the neural network classifier. An evaluation, validation, and presentation of the experimental performance of the suggested approach have been completed. A unique APSO (accelerated particle swarm optimization) based artificial neural network model (ANNM) for the relegation of benign and malignant tumours is presented in this study effort, which allows for the automated identification and categorization of brain tumours. Using APSO training to improve the suggested ANNM model parameters would give a unique method to alleviate the stressful work of radiologists performing manual identification of encephalon cancers from MR images. The use of an APSO-based ANNM (artificial neural network model) model for automated brain tumour classification has been presented in order to demonstrate the resilience of the classification model. It has been suggested to utilise the improved enhanced fuzzy c means (IEnFCM) method for image segmentation, while the GLCM (gray level co-occurrence matrix) feature extraction approach has been employed for feature extraction from magnetic resonance imaging (MR pictures)., Competing Interests: The authors of this manuscript declared that they do not have any conflicts of interest., (Copyright © 2022 K. R. Pradeep et al.)

A difficult challenge in the realm of biomedical engineering is the detection of physiological changes occurring inside the human body, which is a difficult undertaking. At the moment, these irregularities are graded manually, which is very difficult, time-consuming, and tiresome due to the many complexities associated with the methods involved in their identification. In order to identify illnesses at an early stage, the use of computer-assisted diagnostics has acquired increased attention as a result of the requirement of a disease detection system. The major goal of this proposed work is to build a computer-aided design (CAD) system to help in the early identification of glaucoma as well as the screening and treatment of the disease. The fundus camera is the most affordable image analysis modality available, and it meets the financial needs of the general public. The extraction of structural characteristics from the segmented optic disc and the segmented optic cup may be used to characterize glaucoma and determine its severity. For this study, the primary goal is to estimate the potential of the image analysis model for the early identification and diagnosis of glaucoma, as well as for the evaluation of ocular disorders. The suggested CAD system would aid the ophthalmologist in the diagnosis of ocular illnesses by providing a second opinion as a judgment made by human specialists in a controlled environment. An ensemble-based deep learning model for the identification and diagnosis of glaucoma is in its early stages now. This method's initial module is an ensemble-based deep learning model for glaucoma diagnosis, which is the first of its kind ever developed. It was decided to use three pretrained convolutional neural networks for the categorization of glaucoma. These networks included the residual network (ResNet), the visual geometry group network (VGGNet), and the GoogLeNet. It was necessary to use five different data sets in order to determine how well the proposed algorithm performed. These data sets included the DRISHTI-GS, the Optic Nerve Segmentation Database (DRIONS-DB), and the High-Resolution Fundus (HRF). Accuracy of 91.11% for the PSGIMSR data set and the sensitivity of 85.55% and specificity of 95.20% for the suggested ensemble architecture on the PSGIMSR data set were achieved. Similarly, accuracy rates of 95.63%, 98.67%, 95.64%, and 88.96% were achieved using the DRIONS-DB, HRF, DRISHTI-GS, and combined data sets, respectively., Competing Interests: The authors declare that they have no conflicts of interest., (Copyright © 2022 Shubham Joshi et al.)

In experimental analysis and computer-aided design sustain scheme, segmentation of cell liver and hepatic lesions by an automated method is a significant step for studying the biomarkers characteristics in experimental analysis and computer-aided design sustain scheme. Patient to patient, the change in lesion type is dependent on the size, imaging equipment (such as the setting dissimilarity approach), and timing of the lesion, all of which are different. With practical approaches, it is difficult to determine the stages of liver cancer based on the segmentation of lesion patterns. Based on the training accuracy rate, the present algorithm confronts a number of obstacles in some domains. The suggested work proposes a system for automatically detecting liver tumours and lesions in magnetic resonance imaging of the abdomen pictures by using 3D affine invariant and shape parameterization approaches, as well as the results of this study. This point-to-point parameterization addresses the frequent issues associated with concave surfaces by establishing a standard model level for the organ's surface throughout the modelling process. Initially, the geodesic active contour analysis approach is used to separate the liver area from the rest of the body. The proposal is as follows: It is possible to minimise the error rate during the training operations, which are carried out using Cascaded Fully Convolutional Neural Networks (CFCNs) using the input of the segmented tumour area. Liver segmentation may help to reduce the error rate during the training procedures. The stage analysis of the data sets, which are comprised of training and testing pictures, is used to get the findings and validate their validity. The accuracy attained by the Cascaded Fully Convolutional Neural Network (CFCN) for the liver tumour analysis is 94.21 percent, with a calculation time of less than 90 seconds per volume for the liver tumour analysis. The results of the trials show that the total accuracy rate of the training and testing procedure is 93.85 percent in the various volumes of 3DIRCAD datasets tested., Competing Interests: The authors declare that they have no conflicts of interest., (Copyright © 2022 Piyush Kumar Shukla et al.)

Despite the reported association between diurnal variations in ambulatory blood pressure (BP) and elevated cardiovascular disease risk, little is known regarding the effects of isometric resistance training (IRT), a practical BP-lowering intervention, on ambulatory BP and morning BP surge (MBPS). Thus, we investigated whether (i) IRT causes reductions in ambulatory BP and MBPS, in young normotensives, and (ii) if there are any sex differences in these changes. Twenty normotensive individuals (mean 24-h SBP = 121 ± 7, DBP = 67 ± 6 mmHg) undertook 10-weeks of bilateral-leg IRT (4 × 2-min/2-min rest, at 20% maximum voluntary contraction (MVC) 3 days/week). Ambulatory BP and MBPS (mean systolic BP (SBP) 2 h after waking minus the lowest sleeping 1 h mean SBP) was measures pre- and post-training. There were significant reductions in 24-h ambulatory SBP in men (- 4 ± 2 mmHg, P = 0.0001) and women (- 4 ± 2 mmHg, P = 0.0001) following IRT. Significant reductions were also observed in MBPS (- 6 ± 8 mmHg, p = 0.044; - 6 ± 7 mmHg, P = 0.019), yet there were no significant differences between men and women in these changes, and 24-h ambulatory diastolic BP remained unchanged. Furthermore, a significant correlation was identified between the magnitude of the change in MBPS and the magnitude of changes in the mean 2-h SBP after waking for both men and women (men, r = 0.89, P = 0.001; women, r = 0.74, P = 0.014). These findings add further support to the idea that IRT, as practical lifestyle intervention, is effective in significantly lowering ambulatory SBP and MBPS and might reduce the incidence of adverse cardiovascular events that often occur in the morning., (© 2022. The Author(s).)

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Background: Assisted reproductive technology (ART) insurance mandates promote more selective utilization of ART clinic resources including intracytoplasmic sperm injection (ICSI). Our objective was to examine whether ICSI utilization differs by state insurance mandates for ART coverage and assess if such a difference is associated with male factor, preimplantation genetic testing (PGT), and/or live birth rates., Methods: In this retrospective analysis of the Centers for Disease Control (CDC) data from 2018, ART clinics in ART-mandated states (n = 8, AR, CT, HI, IL, MD, MA, NJ, RI) were compared individually to one another and with non-mandated states in aggregate (n = 42) for use of ICSI, male factor, PGT, and live birth rates. ANOVA was used to evaluate differences between ART-mandated states and non-mandated states. Individual ART-mandated states were compared using Welch t-tests. Statistical significance was determined by Bonferroni Correction., Results: There were significant differences in ICSI rates (%, mean ± SD) between MA (53.3 ± 21.3) and HI (90.7 ± 19.6), p = 0.028; IL (86.5 ± 18.7) and MA, p = 0.002; IL and MD (57.2 ± 30.8), p = 0.039; IL and NJ (62.0 ± 26.8), p = 0.007; between non-mandated states in aggregate (79.9 ± 19.9) and MA, p = 0.006, and NJ (62.0 ± 26.8), p = 0.02. Male factor rates of HI (65.8 ± 16.0) were significantly greater compared to CT (18.8 ± 8.7), IL (26.0 ± 11.9), MA (26.9 ± 6.6), MD (29.3 ± 9.9), NJ (30.6 ± 17.9), and non-mandated states in aggregate (29.7 ± 13.7), all p < 0.0001. No significant differences were reported for use of PGT and/or live birth rates across all age groups regardless of mandate status., Conclusions: ICSI use varied significantly among ART-mandated states while demonstrating no differences in live birth rates. These data suggest that the prevalence of male factor and the presence of a state insurance mandate are not the only factors influencing ICSI use. It is suggested that other non-clinical factors may impact the rate of ICSI utilization in a given state., (© 2021. The Author(s).)

Neighborhood walkability is key to promoting health, accessibility, and pedestrian safety. The Accessible, Connected Communities Encouraging Safe Sidewalks (ACCESS) project was developed to assess sidewalks throughout an urban community in Pontiac, Michigan. Data were collected from 2016 to 2018 along eighty miles of sidewalk for tripping hazards, cracking, vegetation, obstructions, overhead coverage, street lighting, buffers, and crosswalks. Data were mapped in ArcGIS with sociodemographic characteristics by U.S. Census block group. The majority of sidewalks had moderate (57.6%) or major (29.4%) sidewalk quality issues, especially maintenance-related impediments (68.6%) and inadequate street lighting or shade coverage (87.2%). The majority of crosswalks had a curb ramp to improve access for people with disabilities (84.4%), however over half lacked a detectable warning strip (55.8%). Degraded sidewalk quality was associated with lower neighborhood socioeconomic status and a higher proportion of Black and Latinx residents. Equity-centered pedestrian infrastructure improvement plans can address these disparities by increasing accessible, safe active transport options that promote physical activity and reduce health disparities. Evaluations like ACCESS can connect public health professionals with municipal planners to advance Complete Streets plans and promote healthy living., Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (© 2021 The Authors.)

Populations with COPD demonstrate higher survival in overweight and obese compared with normal weight; the "obesity paradox". Relationships in less-severe COPD are unclear, as is the impact of cardiovascular risk, and few studies include individuals at extremes of obesity.  We examined the relationship between body mass index (BMI; defined as underweight: <20 kg·m -2 , normal: 20-25 kg·m -2 , overweight: 25- <30 kg·m -2 , obese class I: 30- <35 kg·m -2 , class II: 35- <40 kg·m -2 and class III: ≥40 kg·m -2 ), morbidity, and mortality in the SUMMIT trial population (n=16 485), characterised by moderate COPD and heightened cardiovascular risk with a substantial proportion with class III obesity. The association between BMI category and time to event was modelled via proportional hazards (reference normal weight) adjusted for demographics and cardiorespiratory disease.  Consistent with the paradox, underweight individuals demonstrated higher mortality (hazard ratio (HR) 1.31 (95% CI 1.04-1.64)), with lower mortality among overweight (HR 0.62 (95% CI 0.52-0.73)) and obese class I (HR 0.75 (95% CI 0.62-0.90)). However, mortality increased in obese class III (HR 1.36 (95% CI 1.00-1.86)). Death was primarily attributable to cardiovascular causes.  Within a large, multinational cohort with moderate COPD and increased cardiovascular risk, the phenomenon of reduced mortality with obesity did not persist at BMI >40 kg·m -2 , suggesting that obesity may not remain protective at the extremes in this population., Competing Interests: Conflict of interest: E.P. Brigham has nothing to disclose. Conflict of interest: J.A. Anderson is an employee of and owns shares in GSK. Conflict of interest: R.D. Brook reports personal fees from GSK for a steering committee during the conduct of the study. Conflict of interest: P.M.A. Calverley reports that he was a member of the SUMMIT Science Committee supported by GSK; and he was paid for the conduct of the SUMMIT study by GSK, was paid for speaking at a company meeting and for advice on study design by AstraZeneca, he advised on development of new trials and has spoken for Boehringer Ingelheim at sponsored meetings, and he has received personal fees for speaking at sponsored meeting from Novartis, outside the submitted work. Conflict of interest: B.R. Celli reports personal fees from GlaxoSmithKline during the conduct of the study; and personal fees from AstraZeneca, Sanofi Aventis, Chiesi, Novartis, Menarini and Pulmonx outside the submitted work. Conflict of interest: N.J. Cowans reports this study was funded by GlaxoSmithKline plc.; and he is an employee of Veramed Ltd, a contract research organisation undertaking contracted statistical analyses of respiratory studies funded by GlaxoSmithKline plc. Conflict of interest: C. Crim is an employee of GSK and holds GSK stocks/shares; this study was funded by GSK (NCT01313676, GSK study number 113782; Study to Understand Mortality and Morbidity In COPD Trial (SUMMIT)). Conflict of interest: J.E. Diserens reports this study was funded by GlaxoSmithKline plc.; and he is an employee of Veramed Ltd, a contract research organisation undertaking contracted statistical analyses of respiratory studies funded by GlaxoSmithKline plc. Conflict of interest: F.J. Martinez reports grants from the NHLBI during the conduct of the study; and grants from the National Institutes of Health, personal fees from Continuing Education and Forest Laboratories, other support from Janssen, and personal fees from GlaxoSmithKline, Nycomed/Takeda, AstraZeneca, Boehringer Ingelheim, Bellerophon (formerly Ikaria), Genentech, Novartis, Pearl, Roche, Sunovion, Theravance, CME Incite, Annenberg Center for Health Sciences at Eisenhower, Integritas, InThought, the National Association for Continuing Education, Paradigm Medical Communications, LLC, PeerVoice, UpToDate, Haymarket Communications, the Western Society of Allergy and Immunology, Proterixbio (formerly Bioscale), Unity Biotechnology, ConCert Pharmaceuticals, Lucid, Methodist Hospital, Columbia University, Prime Healthcare Ltd, WebMD, PeerView Network, the California Society of Allergy and Immunology, Chiesi and the Puerto Rico Thoracic Society, outside the submitted work. Conflict of interest: M.C. McCormack reports support from UpToDate outside the submitted work. Conflict of interest: D.E. Newby reports grants and personal fees from GSK during the conduct of the study. Conflict of interest: J.C. Yates is an employee of and owns shares in GSK. Conflict of interest: J. Vestbo was partly reimbursed for his work as Chair of the SUMMIT Steering Committee buy GlaxoSmithKline during the conduct of the study; and reports consultancy for COPD phase 2 and 3 programmes and payment for lectures including service in speaker bureaus from GlaxoSmithKline, Chiesi Pharmaceuticals, Boehringer Ingelheim, Novartis and AstraZeneca, outside the submitted work. Conflict of interest: T.D. Wu has nothing to disclose. Conflict of interest: R.A Wise reports grants and personal fees from GlaxoSmithKline during the conduct of the study; grants and personal fees from AstraZeneca/Medimmune and Boehringer Ingelheim, personal fees from Contrafect, Pulmonx, Roche/Genentech, Spiration, Sunovion, Pearl Therapeutics, Merck, Circassia, Pneuma, Verona, Bonti, Denali, Aradigm, Mylan, Theravance, Propeller Health, Kiniksa and Syneos, outside the submitted work., (Copyright ©The authors 2021.)