Articles

This research is a collaboration involving a university team, a partnering corporation, and a hemodialysis clinic, which is a cross-disciplinary research initiative in the field of Artificial Intelligence of Things (AIoT) within the medical informatics domain. The research has two objectives: (1) The development of an <i>Internet of Things (IoT)</i><i>-based</i><i> Information System</i> customized for the hemodialysis machines at the clinic, including transmission bridges, clinical personnel dedicated web/app, and a backend server. The system has been deployed at the clinic and is now officially operational; (2) The research also utilized de-identified, anonymous data (collected by the officially operational system) to train, evaluate, and compare <i>Deep Learning-based Intradialytic Blood Pressure</i><i> (BP)</i><i>/Pulse </i><i>Rate (PR) </i><i>Predictive Models</i>, with subsequent suggestions provided. Both objectives were executed under the supervision of the Institutional Review Board (IRB) at Mackay Memorial Hospital in Taiwan. The system completed for objective one has introduced three significant services to the clinic, including automated hemodialysis data collection, digitized data storage, and an information-rich human-machine interface as well as graphical data displays, which replaces traditional paper-based clinical administrative operations, thereby enhancing healthcare efficiency. The graphical data presented through web and app interfaces aids in real-time, intuitive comprehension of the patients’ conditions during hemodialysis. Moreover, the data stored in the backend database is available for physicians to conduct relevant analyses, unearth insights into medical practices, and provide precise medical care for individual patients. The training and evaluation of the predictive models for objective two, along with related comparisons, analyses, and recommendations, suggest that in situations with limited computational resources and data, an Artificial Neural Network (ANN) model with six hidden layers, SELU activation function, and a focus on artery-related features can be employed for hourly intradialytic BP/PR prediction tasks. It is believed that this contributes to the collaborating clinic and relevant research communities.

<b>Background:</b> Peripartum cardiomyopathy (PPCM) is a life-threatening heart muscle disease of unknown aetiology that affects women during the peripartum period, particularly in sub-Saharan Africa. While many studies have observed normal blood pressure (BP) in PPCM patients, none have explored whether their BP is appropriate for their body size. This study investigated the correlation between body anthropometric parameters and BP in PPCM patients, comparing the findings with those of age-matched normal peripartum controls. <b>Methods: </b>A cohort of 105 women, each from PPCM and matched normal peripartum control groups, were recruited from three healthcare facilities in Sokoto. Blood pressure (BP) parameters were assessed in relation to their anthropometric measurements, and the findings were compared between the two groups. <b>Results:</b> The PPCM patients were significantly smaller in body weight (57.0 ±11.6 Kg vs 66.8 ±13.8 Kg, P <.0001), body mass index (BMI) (21.9 ±4.1 Kg/m2 vs 25.4 ±5.4 Kg/m2, P <.0001, body surface area (BSA) (1.3 ±0.7 m2 vs 1.7 ±0.2 m2, P <.0001), Lean body mass (LBM) (45.3 ±7.0 Kg vs 49.4 ±4.1 Kg, P <.0001) and Percentage body fat (BF) (23.5 ±10.9 % vs 31.2 ±6.9 %, P <.0001). Similarly, PPCM patients had significantly higher systolic BP (SBP), Pulse pressure (PP) and Mean arterial blood pressure (MABP) compared to the normal peripartum PPCM control. Further, linear regression analysis showed that there was higher slope of the relationship between anthropometric indices and SBP and PP in the PPCM cohort, compared to the normal peripartum control group. A similar trend of the slope was seen in the Pearson’s coefficient of the relationship of the anthropometries and BP parameters. <b>Conclusions:</b> This study found that women with peripartum cardiomyopathy (PPCM) exhibited disproportionately higher systolic blood pressure (SBP) and pulse pressure (PP) for each unit increase in anthropometric measurements compared to normal peripartum controls. Notably, PPCM patients had significantly lower anthropometric measures, potentially attributable to poverty and chronic undernutrition. Additionally, the effects of poor antenatal care, lack of immunization and recurrent infection should be considered. These findings suggest an abnormal relationship between anthropometry and blood pressure in PPCM patients, which may have detrimental effects on their cardiovascular health. This abnormal relationship may contribute to the development of heart failure (HF) in PPCM patients and potentially increase the risk in women susceptible to PPCM. Even-though our assumption, yet to be proven. To address this concerning trend in vulnerable populations, improvements in nutritional status, socioeconomic determinants health, adequate antenatal care (ANC), immunization, and infection prevention should be considered.

<b>Background:</b> Although some neural mechanisms underlying socioeconomic status (SES) disparities are known, the role of brain-wide resting-state functional connectivity in these effects remains less understood. <b>Aim:</b> This study aims to identify brain-wide resting-state functional connectivity signatures that may mediate the effects of SES on body mass index (BMI) and blood pressure in children, using data from the Adolescent Brain Cognitive Development (ABCD) study. <b>Methods:</b> Data were drawn from the ABCD study, a large, diverse cohort of children aged 9-10. Pre-processed resting-state functional MRI data were used, and factor analysis was conducted to extract a whole-brain connectivity factor. The first factor, capturing the greatest variance in brain-wide resting-state connectivity, was selected for further analysis in a structural equation model (SEM). This connectivity factor was tested as a potential mediator of the relationship between SES (measured by parental education, family income, and neighborhood characteristics) and two indicators of cardiometabolic health: BMI and systolic blood pressure. <b>Results:</b> Factor analysis revealed a robust first factor that accounted for a significant proportion of variance in brain-wide resting-state functional connectivity. This factor was significantly associated with SES, indicating that children from lower SES backgrounds exhibited distinct connectivity patterns. Additionally, the factor was linked to both BMI and systolic blood pressure, suggesting its relevance to cardiometabolic health. Mediation analysis showed that this connectivity factor partially mediated the relationship between SES and both BMI and systolic blood pressure. <b>Conclusions:</b> Brain-wide functional connectivity may be a mediator of SES effects on BMI and blood pressure in children. The first connectivity factor provides a promising neural signature linking SES with cardiometabolic risk. Comprehensive brain-wide approaches to functional connectivity may offer valuable insights into how social determinants of health shape neural and physical development in childhood.

<b>Background: </b>Cigarette smoking is one of the 10 greatest contributors to global death and disease. Cigarette smoking is the most common type of tobacco use. In average, to date 47.5% of men and 10.3% of women are current smokers. Tobacco continues to be the second major cause of death in the world. It consists of many chemicals, including cytotoxic, carcinogenic and free radicals, therefore it affects many organs if not all. <b>Objective:</b> The aim of this study is to assess the extent of adverse effect of cigarette smoking on blood pressure, liver function, and hemoglobin concentration in male population on the West Coast of Libya. <b>Methods:</b> This study was conducted on (200) healthy male subjects, their ages ranged from 15 to 85 years. They were divided into four groups; 50 non-smokers as control group (age between 15-35 years), 50 smokers (age between 15-35 years), 50 non-smokers as control group (age between 36-84 years) and 50 smokers (age between 36-84 years). The blood was collected in EDTA tubes to test the Complete blood count (CBC) and in plain tubes for biochemical assay (activities of liver enzymes). The Blood pressure of subjects was measured directly after sample collection. <b>Result</b>: The blood pressure among the group of age 36-84y was significantly higher (<i>P < 0.05</i>) when compared between the smokers and the nonsmokers group, while among the group of age 15-35 was not significant. The results of liver enzymes activities among the group of age 36-84y showed that ALT and ALP were significantly high (<i>P <0.05</i>) in the smoker group when compared with the nonsmoker group, while serum AST was not significant (<i>P>0.05</i>). However, among the group of age between 15-35 years, the results showed that statistically significant differences (<i>P<0.05</i>) were observed in ALT and AST activities for the smoker group when compared with the nonsmoker group. Regarding RBCs count and hemoglobin concentration among both of groups (age between 15-35 &#x26; 36-84 years), the results showed that a significant difference in mean RBCs count and hemoglobin concentration were noted between the smokers and the nonsmokers. <b>Conclusion</b>: It can be concluded that exposure to cigarette smoking leads to an increase the blood pressure. Cigarette smoking can lead to an increase in liver enzymes activities, RBCs count and Hb concentration.