Nocturnal indicators of increased cardiovascular risk in depressed adolescent girls

Recent Advances in Non-Invasive Blood Pressure Monitoring and Prediction Using a Machine Learning Approach

Blood pressure (BP) monitoring can be performed either invasively via arterial catheterization or non-invasively through a cuff sphygmomanometer. However, for conscious individuals, traditional cuff-based BP monitoring devices are often uncomfortable, intermittent, and impractical for frequent measurements. Continuous and non-invasive BP (NIBP) monitoring is currently gaining attention in the human health monitoring area due to its promising potentials in assessing the health status of an individual, enabled by machine learning (ML), for various purposes such as early prediction of disease and intervention treatment. This review presents the development of a non-invasive BP measuring tool called sphygmomanometer in brief, summarizes state-of-the-art NIBP sensors, and identifies extended works on continuous NIBP monitoring using commercial devices. Moreover, the NIBP predictive techniques including pulse arrival time, pulse transit time, pulse wave velocity, and ML are elaborated on the basis of bio-signals acquisition from these sensors. Additionally, the different BP values (systolic BP, diastolic BP, mean arterial pressure) of the various ML models adopted in several reported studies are compared in terms of the international validation standards developed by the Advancement of Medical Instrumentation (AAMI) and the British Hypertension Society (BHS) for clinically-approved BP monitors. Finally, several challenges and possible solutions for the implementation and realization of continuous NIBP technology are addressed.

Effects of 12 Weeks of Resistance Training on Cardiovascular Risk Factors in School Adolescents

Background and objectives: The practice of physical exercise, especially resistance exercise, is important for the treatment and/or prevention of cardiovascular risk factors in adult individuals. However, there are few studies on its effects on adolescent individuals. Therefore, the aim of the present study was to evaluate the effects of applying a 12-week resistance training program on cardiovascular risk factors in adolescents. Materials and Methods: Thus, 122 adolescents aged 13-16 years of both genders participated in the study from school in the city of Lagarto, Sergipe (SE), Brazil, divided into two groups: Control Group (CG) and Group undergoing resistance training (RTG). Blood collection and anthropometric measurements were performed before and after the 12-week resistance training program (RTP). Results: After 12 weeks of the RTP in the adolescents, there was a reduction in the triglyceride variables (9.55%, p = 0.0286), Low-Density Lipoproteins (LDL) (5.42%, p = 0.0244), non-High-Density Lipoproteins (HDL) (5.40%, p = 0.0019), blood glucose (6.71%, p = 0.0040), systolic blood pressure (10.13%, p < 0.0001), as well as an increase in the body weight variable (1.73%, p = 0.0003). Conclusions: It was concluded that a 12-week RTP can prevent and/or alleviate the development of several chronic degenerative diseases in adulthood and that resistance training is important for maintaining the health of adolescents.

Heart rate variability alterations in late life depression: A meta-analysis

OBJECTIVE

There is strong evidence for a bi-directional relationship between heart-health and depression in later life, but the physiological mechanisms underlying this relationship remain unclear. Heart rate variability is one promising factor that might help explain this relationship. We present results of a meta-analysis that considers heart rate variability alterations in older adults with depression.

METHODS

Literature search of Embase, PsychInfo and Medline revealed five clinical studies and six observational studies that examined the relationship between heart rate variability and depression in adults with a mean age over 60. These studies were included in this meta-analysis.

RESULTS

Heart rate variability was reduced among older adults with clinical depression (N = 550), relative to healthy controls (Hedges' g = -0.334, 95%CI [-0.579, -0.090], p = .007). When high-frequency and low-frequency heart rate variability were investigated separately, only low-frequency heart rate variability was significantly reduced in depressed patients (Hedges' g = -0.626, 95%CI [-1.083, -0.169], p = .007). A similar but weaker pattern of results was found in the observational studies. Most findings remained significant among unmedicated depressed older adults.

LIMITATIONS

Evidence of effect-size heterogeneity was found in the clinical studies, indicating the need for more well-designed research in the area.

CONCLUSION

Heart rate variability is reduced among older adults with depression, and this effect is not fully attributable to antidepressant medication use. Specifically, low-frequency heart rate variability may be reduced in depressed older adults. Heart rate variability warrants further attention, as it could help inform research into the prevention and treatment of depression in later life.