Prevalence and associated factors of undiagnosed hypertension among women aged 15-49 years in India: an analysis of National Family Health Survey-4 data.

Hypertension is a major risk factor for cardiovascular diseases globally. Fortunately, there is a vast armamentarium of effective therapeutic options at our disposal so undiagnosed hypertension represents a missed opportunity. In a previous analysis [1] of the NFHS-4 dataset for the prevalence and risk factors for undiagnosed hypertension and its associated risk factors among Indian women aged 15-49 years, we had overestimated prevalence by inclusion of self-reported cases. We have since retracted when this anomaly was highlighted [2]. We have now re-analyzed the same database and here present these data. The current analysis shows that the overall prevalence of undiagnosed hypertension was 8.05% among women aged 15-49 years in India. In rural areas, it was 7.89% compared with 8.38% for urban areas. Factors associated with undiagnosed hypertension in rural and urban areas were age, BMI, wealth quintiles, educational level, religion, caste and geographical zones. Nearly half the women aged 15-49 years in India with hypertension are unaware and this has implications for personal and reproductive health.

Rapid Environmental Monitoring, Capture, and Destruction Activities of SARS-CoV-2 and Bacterial Pathogens During the COVID-19 Health Emergency.

BACKGROUND: The SARS-CoV-2 pandemic is a health emergency for occupational healthcare workers at COVID-19 hospital wards in Italy. The objective of the study was to investigate the bioreactor's effectivity in monitoring and improving air quality via detection, capture, and destruction of the SARS-CoV-2 virus and bacterial pathogens, reducing the risk of transmission among healthcare workers. METHODS: Bioreactors are a demonstrated effective biomonitoring system. We implemented a methodological approach wherein they were placed at various hospitals treating COVID-19 patients in Italy. The detection of the SARS-CoV-2 virus was achieved through rapid biomonitoring testing of the solutes from the AIRcel bioreactors via SARS-CoV-2 rapid test antigen and consecutive reverse transcription-polymerase chain reaction (RT-PCR) analysis with the multiplex platform (XABT) and the real-time PCR rotor-gene. RESULTS: The marked presence of the SARS-CoV-2 virus was found in multiple water samples via the detection of ORF1ab + N and/or E gene involved in gene expression and cellular signaling of the SARS-CoV-2 virus. The AIRcel bioreactors were able to neutralize the virus and bacterial pathogens effectively as traces of the viruses and bacteria were no longer found in multiple solute samples after an overnight period. CONCLUSIONS: Transmission of COVID-19 via bioaerosols, transmitted by infected patients, remains a viable threat for health workers. AIRcel bioreactors allow for rapid biomonitoring testing for early virus detection within the environment, reducing the risk of exponential contagion exposure and maintaining good air quality without endangering health workers. This same protocol can also be extended to public spaces as a bio-monitoring hotspot tool for early detection.

The Evaluation of Remote Monitoring Technology Across Participants With Different Skin Tones.

BACKGROUND: Many research studies seek to improve vital sign monitoring to enhance the conditions under which doctors and caregivers track patients' health. Non-invasive and contactless monitoring has emerged as an optimal solution for this problem, with telemedicine, self-monitoring, and well-being tools being the next generation of technology in the biomedical field. However, there is worldwide concern about the general purpose and bias toward a certain demographic group of these techniques. In particular, skin tone and the accuracy of monitoring dark skin tone groups have been key questions among researchers, with the lack of results and studies contributing to this uncertainty. METHODS: This paper proposes a benchmark for remote monitoring solutions against a medical device across different skin tone people. Around 330 videos from 90 patients were analyzed, and heart rate (HR) and heart rate variability (HRV) were compared across different subgroups. The Fitzpatrick scale (1-6) was used to classify participants into three skin tone groups: 1 and 2, 3 and 4, and 5 and 6. RESULTS: The results showed that our proposed methodology could estimate heart rate with a mean absolute error of 3 bpm across all samples and subgroups. Moreover, for heart rate variability (HRV) metrics, we achieved the following results: in terms of mobility assistive equipment (MAE), the HRV-inter-beat interval (IBI) was 10 ms, the HRV-standard deviation of normal to normal heartbeats (SDNN) was 14 ms, and the HRV-root mean square of successive differences (RMSSD) between normal heartbeats was 22 ms. No significant performance decrease was found for any skin tone group, and there was no error trend toward a certain group. CONCLUSIONS: The study showed that our methodology meets acceptable agreement levels for the proposed metrics. Furthermore, the experiments showed that skin tone did not impact the results, which remained within the same range across all groups. Moreover, it enables the end users to understand their general well-being and improve their overall health.

Evaluation of Atrial Fibrillation Detection in Short-Term Photoplethysmography (PPG) Signals Using Artificial Intelligence.

Background Atrial fibrillation (AFIB) is a common atrial arrhythmia that affects millions of people worldwide. However, most of the time, AFIB is paroxysmal and can pass unnoticed in medical exams; therefore, regular screening is required. This paper proposes machine learning (ML) methods to detect AFIB from short-term electrocardiogram (ECG) and photoplethysmography (PPG) signals. Aim Several experiments were conducted across five different databases, with three of them containing ECG signals and the other two consisting of only PPG signals. Experiments were conducted to investigate the hypothesis that an ML model trained to predict AFIB from ECG segments could be used to predict AFIB from PPG segments. Materials and methods A random forest (RF) ML algorithm achieved the best accuracy and achieved a 90% accuracy rate on the University of Mississippi Medical Center (UMMC) dataset (216 samples) and a 97% accuracy rate on the Medical Information Mart for Intensive Care (MIMIC)-III datasets (2,134 samples). Results A total of 269,842 signal segments were analyzed across all datasets (212,266 were of normal sinus rhythm (NSR) and 57,576 corresponded to AFIB segments). Conclusions The ability to detect AFIB with significant accuracy using ML algorithms from PPG signals, which can be acquired via non-invasive contact or contactless, is a promising step forward toward the goal of achieving large-scale screening for AFIB.

Anticancer Phytochemical-Based Nanoformulations: Therapeutic Intervention in Cancer Cell Lines.

Phytochemicals have the potential to treat resistant cancer. They are delivered to the target site via nano-based carriers. Promising results are seen in preclinical and in vitro models, as phytochemical-based nanoformulations have improved cell cytotoxicity compared to single agents. They can synergistically inhibit cancer cell growth through p53 apoptosis in MCF-7 breast cancer cell lines. Moreover, synergic viability in reproducible glioma models at half inhibitory concentrations has been shown. Through caspase activation, phytochemical-based nanoformulations also increase cell death in 4T1 breast cancer cell lines. They have shown improved cytotoxicity at half inhibitory concentrations compared to single-agent drugs in cervical cancer. In terms of colorectal cancer, they have the potential to arrest cells in the S phase of the cell cycle and synergistically inhibit cell proliferation. In squamous cell carcinoma of the tongue, they inhibit protein kinase B (Akt)/mammalian target of rapamycin (mTOR) pathways. This review reports on developments in the therapeutic management of various cancers using phytochemical-based nanoformulations, which have shown potential benefits in the clinical management of cancer patients, halting/slowing the progression of the disease and ameliorating chemotherapy-induced toxicities.

Evaluation of a Camera-Based Monitoring Solution Against Regulated Medical Devices to Measure Heart Rate, Respiratory Rate, Oxygen Saturation, and Blood Pressure.

Background Regularly monitoring common physiological signs, including heart rate, blood pressure, and oxygen saturation, can effectively prevent or detect several potential conditions. In particular, cardiovascular diseases (CVDs) are a worldwide concern. According to the World Health Organization, 31% of all deaths worldwide are from CVDs. Recently, the coronavirus disease 2019 pandemic has increased the interest in remote monitoring. At present, contact devices are required to extract most of an individual's physiological information, which can be inconvenient for users and may cause discomfort. Methodology However, remote photoplethysmography (rPPG) technology offers a solution for this issue, enabling contactless monitoring of the blood volume pulse signal using a regular camera. Ultimately, it can provide the same physiological information as a contact device. In this paper, we propose an evaluation of Vastmindz's rPPG technology against medical devices in a clinical environment with a variety of subjects in a wide range of age, height, weight, and baseline vital signs. Results This study confirmed the findings that the contactless technology for the estimation of vitals proposed by Vastmindz was able to estimate heart rate, respiratory rate, and oxygen saturation with a mean error of ±3 units as well as ±10 mmHg for systolic and diastolic blood pressure. Conclusions Reported results have shown that Vastmindz's rPPG technology was able to meet the initial hypothesis and is acceptable for users who want to understand their general health and wellness.

Evaluating Visual Photoplethysmography Method.

Regular monitoring of common physiological signs, including heart rate, blood pressure, and oxygen saturation, can be an effective way to either prevent or detect many kinds of chronic conditions. In particular, cardiovascular diseases (CVDs) are a worldwide concern. According to the World Health Organization, 32% of all deaths worldwide are from CVDs. In addition, stress-related illnesses cost $190 billion in healthcare costs per year. Currently, contact devices are required to extract most of an individual's physiological information, which can be uncomfortable for users and can cause discomfort. However, in recent years, remote photoplethysmography (rPPG) technology is gaining interest, which enables contactless monitoring of the blood volume pulse signal using a regular camera, and ultimately can provide the same physiological information as a contact device. In this paper, we propose a benchmark comparison using a new multimodal database consisting of 56 subjects where each subject was submitted to three different tasks. Each subject wore a wearable device capable of extracting photoplethysmography signals and was filmed to allow simultaneous rPPG signal extraction. Several experiments were conducted, including a comparison between information from contact and remote signals and stress state recognition. Results have shown that in this dataset, rPPG signals were capable of dealing with motion artifacts better than contact PPG sensors and overall had better quality if compared to the signals from the contact sensor. Moreover, the statistical analysis of the variance method had shown that at least two heart-rate variability (HRV) features, NNi 20 and SAMPEN, were capable of differentiating between stress and non-stress states. In addition, three features, inter-beat interval (IBI), NNi 20, and SAMPEN, were capable of differentiating between tasks relating to different levels of difficulty. Furthermore, using machine learning to classify a "stressed" or "unstressed" state, the models were able to achieve an accuracy score of 83.11%.

Role of Information Technology in COVID-19 Vaccination Drive: An Analysis of the COVID-19 Global Beliefs, Behaviors, and Norms Survey.

With the onset of the COVID-19 pandemic, information technology has played a critical role in healthcare. A broad spectrum of information technology tools and applications played an essential role to create awareness of the COVID-19 vaccination drive and its health benefits. Research conducted by Massachusetts Institute of Technology (MIT) in collaboration with information technology platforms like Facebook with inputs from World Health Organization (WHO), John Hopkins University (JHU), and Global Outbreak Alert and Response Network (GOARN) shows that 65.06% of people all over the globe are willing to get vaccinated. Vaccine acceptance depends upon social norms and human behavior. These organizations conducted the global survey in over 60 countries with a sample size of 437,236 responses. The international survey was organized using a pre-registered randomized experiment demonstrating the role of technology in reaching out to people based in diverse communities and evaluating their beliefs, behavior, and social norms. The study shows that vaccine acceptance can vary due to descriptive norms. All the respondents in the study were adults with access to the internet. Moreover, a large proportion of the population thinks that the COVID-19 pandemic is a viable threat to the community and preventive measures need to be taken including vaccination drives to eradicate the menace. The survey consisted of five blocks involving questions related to healthcare, demographics, vaccines, knowledge, and information exposure. Sampling and weighting were done using a pool of 3,000 respondents over two weeks, and weights were provided per respondent to represent the target population as a whole. It reduces the representation error and minimizes non-response biases.

Strategic Role and Challenges of Community Pharmacists in SARS-CoV-2 Outbreak.

This study highlights the importance of community pharmacists' strategic role in hindering the progression of the SARS-CoV-2 virus in the community setting and innovative measures to protect themselves. This article focuses on the features, control, and prevention of COVID-19 and social awareness measures of the pandemic. The means employed by the community pharmacist to safeguard his health while providing pharmaceutical services during COVID-19 is compiled and presented to benefit health-care professionals around the world. As per the US Center for Disease Control and Prevention, community pharmacists play a crucial role in providing essential drugs to patients without knowing their current COVID-19 status. They also work in conditions that make them susceptible to COVID-19 exposure. Despite the availability of guidelines, community pharmacists need to be trained in personal protective equipment for efficient protection and prevention of spread. Community pharmacists are essential frontline warriors against transmission of the SARS-CoV-2 virus in the community and act as frontline workers to educate the public on COVID-19. They are at high risk and need to observe necessary precautions to mitigate the spread of the virus.

Prevalence and associated factors of undiagnosed hypertension among women aged 15-49 years in India: an analysis of National Family Health Survey-4 data.

Hypertension is a major risk factor for cardiovascular disease globally. Although Indian studies have addressed the prevalence of hypertension and its associated factors, this study focuses upon women in the reproductive age group, 15-49 years, who have undiagnosed hypertension. We use NFHS-4 data for secondary analyses of prevalence and factors associated with undiagnosed hypertension among women aged 15-49 years in India. Multiple logistic regression was undertaken to identify associated factors. Our analyses showed that overall prevalence of undiagnosed hypertension was 18.69% among women aged 15-49 years in India. In rural areas, it was 17.09% compared  and 21.73% in urban areas. By comparison, only 8.86% self-reported a diagnosis of hypertension. Factors associated with undiagnosed hypertension were age, less than or more than normal BMI, higher wealth quintiles, no education, religion, caste, and geographical zones. Almost one in five women aged 15-49 years in India has undiagnosed hypertension with implications for personal and reproductive health.

Comparative Quality Control Study of Different Brands of Diclofenac Sodium Tablet Available in Local and Government Pharmacies by In-Vitro Testing.

The objective of this study is to conduct in-vitro quality control testing of diclofenac sodium tablets involves weight variation test, drug assay, friability test, and the disintegration and dissolution test. Two brands of diclofenac sodium tablets were used in the study, named Brand A and Brand B. Quality control (QC) test results for diclofenac sodium tablets show that both Brand A and Brand B conform to the United States Pharmacopeia (USP) standards. In terms of weight variation, Brand A and B have an above the mean weight limit variation of 2.79% and 2.05%, respectively. The lower mean weight limit variations are 1.21% and 1.27%, respectively, which are within the 10% standard limits of USP. Friability tests show that Brands A and B have an average friability of 0.062% and 0.01% mass loss, which are within the 1% mass loss limits of USP. In terms of drug assay, both Brands A and B fall under the USP parameter of 85%-115%, respectively. The disintegration test shows that Brand A and Brand B fall within a 15-minute time interval segment with disintegration time calculated as 6.69 min and 7.02 min for Brands A and B, respectively. Brand B of Diclofenac Sodium has a drug dissolution percentage of 90.7% within a 45-min sampling time interval. Brands A and B pass the pharmacopeia limits set under the USP standards. The friability test shows that the loss of mass for both Brands A and B was within the 1% standard limit. Similarly, with regard to weight variation, both brands conform under the normal limit of 10% above or lower the mean weight. In terms of drug assay, both brands' drug availability was within the specified 85%-115% standard range. They passed the disintegration and dissolution test within a time limit of less than 15 minutes and 45 minutes, respectively.

Correlating possible predisposing demographics and systemic conditions with the aortic root.

Background: The aortic root is an aggregate of various components that connects the left ventricle to the aorta. The most predominant pathologies have been associated with the dilation of the aortic root leading to aneurysms. Aim: This study is designed to measure the role of systemic morbidities such as hypertension, diabetes, and body mass index (BMI) on the dimension of the aortic root. Materials and Methods: Participants were volunteers of African descent who were recruited during and after an organized health fair by the medical students' body from All Saints University, School of Medicine. 169 participants consisting of 62 males and 107 females with ages ranging from 9 to 84 years agreed to volunteer by signing the consent after which a questionnaire was administered and a preliminary clinical procedure was used to check for blood pressure (BP), blood glucose (BG), and BMI. The measurement of the aortic root was carried out by an experienced single investigator who was not aware of the purpose of measurements, using a DUS-5000 ultrasound machine (Miami, Florida, USA) at a low-frequency micro-convex transducer preset to "adult cardiac" with a default frequency of 4 MHz. Results: Among the participants, 35.03%, 47.80%, and 29.11% had normal BP, BG, and BMI readings, respectively. The Chi-squared analysis identified a significant correlation between the diameter of the aortic annulus (AA) and BMI. Diastolic BP is also correlated with the diameter of the AA. Sinus of Valsalva (SV) showed an unusual correlation with BG as opposed to BP and BMI. Conclusion: The disparity in how a systemic factor individually correlates with the AA and the SV is not clear. The study targets to provide educational concept in this regard.

RésuméContexte: La racine aortique est un agrégat de divers composants qui relie le ventricule gauche à l'aorte. Les pathologies les plus prédominantes ont été associées à la dilatation de la racine aortique conduisant à des anévrismes. But: Cette étude est conçue pour mesurer le rôle des morbidités systémiques telles que l'hypertension, le diabète et l'indice de masse corporelle (IMC) sur la dimension de la racine aortique. Matériel et méthodes: Les participants étaient des volontaires d'origine africaine qui ont été recrutés pendant et après une foire organisée de la santé par le corps des étudiants en médecine de l'école de médecine All Saints University. 169 participants, soit 62 hommes et 107 femmes âgés de 9 à 84 ans, ont accepté de faire du bénévolat en signant le consentement après l'administration du questionnaire et en utilisant une procédure clinique préliminaire pour vérifier la tension artérielle, la glycémie (glycémie), et BMI. La mesure de la racine aortique a été effectuée par un chercheur expérimenté qui ne connaissait pas le but des mesures, en utilisant une échographe DUS-5000 (Miami, Floride, USA) à un transducteur micro-convexe basse fréquence préréglé à "adultcardiac" avec une fréquence par défaut de 4 MHz. Résultats: Parmi les participants, 35,03%, 47,80% et 29,11% avaient respectivement des valeurs normales de BP, de BG et de BMI. L'analyse du khi carré a mis en évidence une corrélation significative entre le diamètre de l'anneau aortique (AA) et l'IMC. La pression artérielle diastolique est également corrélée avec le diamètre de l'AA.Sinus de Valsalva (SV) a montré une corrélation inhabituelle avec BG par opposition à BP et BMI. CONCLUSION: La disparité dans la façon dont un facteur systémique est individuellement corrélé avec l'AA et le SV n'est pas clair. L'étude vise à fournir un concept éducatif à cet égard.