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Simple Summary: Diabetes mellitus is a metabolic disorder characterized by an increased blood glucose concentration. The most common diabetes is type 2, corresponding to approximately 95% of the diagnosed cases. Chronic hyperglycemia can lead to many complications such as increased incidence of cardiovascular diseases as well as renal and ophthalmologic complications. Physical exercise is seen as an effective non-pharmacological strategy for managing the disease. In the present study, 44 middle-aged adults with type 2 diabetes were recruited and stratified into three exercise groups: HIIT-30:30, HIIT-2:2, and MICT. All patients were submitted to anamnesis, evaluation of cardiorespiratory fitness, and cardiac autonomic modulation, and were submitted to physical exercise programs for eight weeks. From the results found, it was possible to infer that high intensity physical training programs can be safe and effective for patients with type 2 diabetes and might be performed in different phases of a rehabilitation program. However, it is necessary to know how to work with the prescription of these exercises considering its cost effectiveness, because, in this study, the protocols HIIT-2:2 and HIIT-30:30 presented superior benefits to the MICT protocol. Different exercise models have been used in patients with type 2 diabetes mellitus (T2D), like moderate intensity continuous training (MICT) and high intensity interval training (HIIT); however, their effects on autonomic modulation are unknown. The present study aimed to compare the effects of different exercise modes on autonomic modulation in patients with T2D. In total, 44 adults with >5 years of T2D diagnosis were recruited and stratified into three groups: HIIT-30:30 (n = 15, age 59.13 ± 5.57 years) that performed 20 repetitions of 30 s at 100% of VO2peak with passive recovery, HIIT-2:2 (n = 14, age 61.20 ± 2.88) that performed 5 repetitions of 2 min at 100% of VO2peak with passive recovery, and MICT (n = 15, age 58.50 ± 5.26) that performed 14 min of continuous exercise at 70% of VO2peak. All participants underwent anamnesis and evaluation of cardiorespiratory fitness and cardiac autonomic modulation. All protocols were equated by total distance and were performed two times per week for 8 weeks. Group × time interactions were observed for resting heart rate (HRrest) [F(2.82) = 3.641; p = 0.031] and SDNN [F(2.82) = 3.462; p = 0.036]. Only the HIIT-30:30 group significantly reduced SDNN (p = 0.002 and 0.025, respectively). HRrest reduced more in the HIIT-30:30 group compared with the MICT group (p = 0.038). Group × time interactions were also observed for offTAU [F(2.82) = 3.146; p = 0.048] and offTMR [F(2.82) = 4.424; p = 0.015]. The MICT group presented increased values of offTAU compared with the HIIT-30:30 and HIIT-2:2 groups (p = 0.001 and 0.013, respectively), representing a slower HR response after eight weeks of intervention. HIIT, specially HIIT-30:30, represents a promising measure for improving autonomic modulation in patients with T2D. [ABSTRACT FROM AUTHOR]

Simple Summary: The clustering of metabolic syndrome (MetS) risk factors is becoming more prevalent in young people (up to the age of 19 years) leading to the development of type 2 diabetes (T2D) and cardiovascular diseases in early adulthood. The impact of MetS risk factors on cardiac autonomic modulation (CAM) or vice versa have been noted to track from childhood to pre-adolescence and adolescence. Understating associations in this age group may help improve the clinical outcomes of the MetS, even when MetS symptoms are not visible. Potential damage from each individual MetS component and the ability to predict early cardiac damage or upcoming cardiovascular events is very important. Therefore, the present systematic review and meta-analysis investigated the associations between CAM and MetS risk factors individually to verify which MetS risk components were significantly correlated with which heart rate variability (HRV) indices before or at the onset of the MetS among young people. The purpose of this review was to outline the importance of potentially screening HRV indices in young people even with only one MetS risk factor, as a pre-indicator for early cardiovascular risk stratification. Cross-sectional studies that examined the relationship of MetS risk factors with HRV indices were searched using four databases including PubMed, the Cochrane clinical trials library, Medline and the Web of Science. Correlation coefficients with 95% confidence intervals (95% CI), and random effects meta-analyses of the association between MetS risk factors with HRV indices were performed. Our results propose that lipid profiles including high density lipoprotein (HDL) and triglycerides (TGs), waist circumference (WC) and blood pressure (BP) are associated with CAM in young people up to the age of 19 years. The use of HRV indices to predict future MetS risk, and relationships with individual risk factors including HDL, BP, WC and TGs, were established. Furthermore, arterial pressure, respiration, stress and physical activity must be taken into consideration for future studies along with CAM related to young people (up to the age of 19 years), and it is recommended to explore further the associations reported here, as CAM is not the only determinant of neurovisceral regulation. Background: the clustering of metabolic syndrome (MetS) risk factors is becoming more prevalent in children, leading to the development of type 2 diabetes (T2D) and cardiovascular diseases in early adulthood. The impact of MetS risk factors on cardiac autonomic modulation (CAM) or vice versa has been noted to track from childhood to pre-adolescence and adolescence. Understating associations in this age group may help to improve the clinical outcomes of the MetS, even when MetS symptoms are not visible. Potential damage from each individual MetS component and the ability to predict early cardiac damage or upcoming cardiovascular events is very important. Therefore, the present systematic review and meta-analysis investigated the associations between CAM and MetS risk factors individually to verify which of the MetS risk components were significantly correlated with heart rate variability (HRV) indices before or at the onset of the MetS among young people. The purpose of this review was to outline the importance of potentially screening HRV indices in young people even with only one MetS risk factor, as a pre-indicator for early cardiovascular risk stratification. Methods: cross-sectional studies that examined the relationship of MetS risk factors with HRV indices were searched using four databases including PubMed, the Cochrane clinical trials library, Medline and the Web of Science. Correlation coefficients with 95% confidence intervals (95% CI), and random effects meta-analyses of the association between MetS risk factors with HRV indices were performed. Results: out of 14 cross-sectional studies and one case-control study, 8 studies (10 data sets) provided association data for the meta-analysis. Our results indicated significant positive correlations for systolic blood pressure (SBP) (correlation coefficient 0.13 (95%CI: 0.06; 0.19), I2 = 47.26%) and diastolic blood pressure (DBP) (correlation coefficient 0.09 (95%CI: −0.01; 0.18), I2 = 0%) with a Low Frequency/High Frequency ratio (LF/HF). Significant negative correlations for waist circumference (WC) (correlation coefficient −0.12 (95%CI: −0.19; −0.04), I2 = 51.50%), Triglycerides (TGs) (correlation coefficient −0.09 (95%CI: −0.15; −0.02), I2 = 0%) and ≥2 MetS risk factors (correlation coefficient −0.10 (95%CI: −0.16; −0.03), I2 = 0%); with high frequency (HF) were revealed. Significant positive correlations for high density lipoprotein (HDL) (correlation coefficient 0.08 (95%CI: 0.05; 0.11), I2 = 0%) and significant negative correlations of ≥2 MetS risk (correlation coefficient −0.04 (95%CI: −0.12; 0.03), I2 = 0.0%) with low frequency (LF) were revealed. Significant negative correlations for TGs (correlation coefficient −0.09 (95%CI: −0.23; 0.05), I2 = 2.01%) with a mean square root of the sum of differences between mean time between two successive intervals (rMSSD) and significant positive correlation of HDL (correlation coefficient 0.09 (95%CI: −0.01; 0.19), I2 = 0.33%) with standard deviation of the time between two successive intervals (SDNN) were also revealed. An Egger's test indicated that there was no obvious publication bias for any of the above relationships except for TGs and rMSSD. The significance level stipulated for the meta-analysis was p < 0.05. Conclusions: lipid profiles (HDL and TGs), WC and BP were associated with CAM in young people up to the age of 19 years. The use of HRV indices to predict future MetS risk, and relationships with individual risk factors including HDL, BP, WC and TGs, were established. Future studies related to young people (up to the age of 19 years) are recommended to explore the associations reported here further. [ABSTRACT FROM AUTHOR]