The Effects of Reduced Physical Activity on the Lipid Profile in Patients with High Cardiovascular Risk during COVID-19 Lockdown.

Background: The COVID-19 pandemic is a serious global health problem. In Italy, to limit the infections, the government ordered lockdown from March 2020. This measure, designed to contain the virus, led to serious limitations on the daily life of the individuals it affected, and in particular in the limitation of physical exercise. The aim of this study was to evaluate the effects of reduced physical activity on the lipid profile in patients with high cardiovascular risk. Methods: We enrolled 38 dyslipidemic patients, 56% male, with an age range of 44-62 years, considered to be at high cardiovascular risk. All patients were prescribed statin drug therapy (atorvastatin 40 mg) and a vigorous physical activity program four times a week, 1 h per session. In addition, a personalized Mediterranean diet was prescribed to all the patients. Total cholesterol, LDL, HDL and triglycerides were measured in patients at T0 before lockdown and at T1 during lockdown. Results: Data showed a significant increase (p < 0.01) in total cholesterol (+6,8%) and LDL (+15,8%). Furthermore, the analysis of the data revealed a reduction in HDL (-3%) and an increase in triglycerides (+3,2%), although both were not significant (p > 0.05). Conclusions: Our study showed that the reduction in physical activity during lockdown led to an increase in LDL levels, and therefore, in the risk of ischemic heart disease in dyslipidemic patients with high cardiovascular risk.

Is the achievement of 85% of age-predicted heart ratemax at exercise test sufficient to make diagnosis of myocardial ischemia in athletes?

BACKGROUND: Exercise test (ET) is a validated tool for the identification of coronary artery disease (CAD) even among athletes. A "cut-off" of 85% HRmax is often chosen as an "end point" although it has been shown that this percentage is far from a maximal effort and might be insufficient to evaluate athletes who often reach HRs close to 100% of the theoretical HRmax during sport activity. The aim of this study was to identify the percentage of theoretical HRmax (% HRmax) at which ST segment depression due to a coronary insufficiency on ECG at ET became significant and how much this value would be different from the "cut-off" of 85% of the theoretical HRmax. METHODS: Forty-two male competitive athletes of three different sport disciplines (58±7.9 years) tested positive during ET at HRmax greater than 85% with ST depression ≥2 mm from V1 to V6 and / or ≥1 mm from D1 to aVf at J point + 80 ms, were included. ECG traces recorded at 85% of HRmax, were compared with those recorded at the percentage of HRmax corresponding to the significant ST depression (%HRmaxST). RESULTS: % HRmax at which the ST depression become significant was 93.4±3.4% with a Δ% of + 8.4% compared to 85%. ST segment depression at peak exercise on precordial leads was significantly different from that at 85% HRmax (P<0.0001). TC coronary scan confirmed CAD. CONCLUSIONS: The cut off of 85% HRmax is insufficient to identify signs of reduced coronary reserve in competitive athletes.

A Sensor Platform for Athletes' Training Supervision: A Proof of Concept Study.

One of the basic needs of professional athletes is the real-time and non-invasive monitoring of their activities. The use of these kind of data is necessary to develop strategies for specific tailored training in order to improve performances. The sensor system presented in this work has the aim to adopt a novel approach for the monitoring of physiological parameters, and athletes' performances, during their training. The anaerobic threshold is herein identified with the monitoring of the lactate concentration and the respiratory parameters. The data collected by the sensor are used to build a model using a supervised method (based on the partial least squares method, PLS) to predict the values of the parameters of interest. The sensor is able to measure the lactate concentration from a sample of saliva and it can estimate a respiratory parameter, such as maximal oxygen consumption, maximal carbon dioxide production and respiratory rate from a sample of exhaled breath. The main advantages of the device are the low power; the wireless communication; and the non-invasive sampling method, which allow its use in a real context of sport practice.