Functional Capacity and Cardiac Function in 10-Year-Old-Boys and Girls with High and Low Running Performance

1984 ◽  
pp. 182-188 ◽  
Author(s):  
C. A. R. Thorén ◽  
K. Asano
2004 ◽  
Vol 36 (Supplement) ◽  
pp. S157???S158
Author(s):  
Luke S. Acree ◽  
Samantha A. Whitman ◽  
Scott R. Richmond ◽  
Charles B. Porter ◽  
Michael P. Godard

2020 ◽  
Vol 31 (3) ◽  
pp. 369
Author(s):  
Alexandra Arvanitaki ◽  
George Giannakoulas ◽  
Eva Triantafyllidou ◽  
Haralambos Karvounis ◽  
Theodoros Dimitroulas

2019 ◽  
Author(s):  
Po-Jen Hsiao ◽  
Chih-Chien Chiu ◽  
Ke-Hsin Lin ◽  
Fu-Kang Hu ◽  
Pei-Jan Tsai ◽  
...  

BACKGROUND Long-distance running can be a form of stress to the heart. Technological improvements combined with the public’s gradual turn toward mobile health (mHealth), self-health, and exercise effectiveness have resulted in the widespread use of wearable exercise products. The monitoring of dynamic cardiac function changes during running and running performance should be further studied. OBJECTIVE We investigated the relationship between dynamic cardiac function changes and finish time for 3000-meter runs. Using a wearable device based on a novel cardiac force index (CFI), we explored potential correlations among 3000-meter runners with stronger and weaker cardiac functions during running. METHODS This study used the American product BioHarness 3.0 (Zephyr Technology Corporation), which can measure basic physiological parameters including heart rate, respiratory rate, temperature, maximum oxygen consumption, and activity. We investigated the correlations among new physiological parameters, including CFI = weight * activity / heart rate, cardiac force ratio (CFR) = CFI of running / CFI of walking, and finish times for 3000-meter runs. RESULTS The results showed that waist circumference, smoking, and CFI were the significant factors for qualifying in the 3000-meter run. The prediction model was as follows: ln (3000 meters running performance pass probability / fail results probability) = –2.702 – 0.096 × [waist circumference] – 1.827 × [smoke] + 0.020 × [ACi7]. If smoking and the ACi7 were controlled, contestants with a larger waist circumference tended to fail the qualification based on the formula above. If waist circumference and ACi7 were controlled, smokers tended to fail more often than nonsmokers. Finally, we investigated a new calculation method for monitoring cardiac status during exercise that uses the CFI of walking for the runner as a reference to obtain the ratio between the cardiac force of exercise and that of walking (CFR) to provide a standard for determining if the heart is capable of exercise. A relationship is documented between the CFR and the performance of 3000-meter runs in a healthy 22-year-old person. During the running period, data are obtained while participant slowly runs 3000 meters, and the relationship between the CFR and time is plotted. The runner’s CFR varies with changes in activity. Since the runner’s acceleration increases, the CFR quickly increases to an explosive peak, indicating the runner’s explosive power. At this period, the CFI revealed a 3-fold increase (CFR=3) in a strong heart. After a time lapse, the CFR is approximately 2.5 during an endurance period until finishing the 3000-meter run. Similar correlation is found in a runner with a weak heart, with the CFR at the beginning period being 4 and approximately 2.5 thereafter. CONCLUSIONS In conclusion, the study results suggested that measuring the real-time CFR changes could be used in a prediction model for 3000-meter running performance.


1993 ◽  
Vol 18 (12) ◽  
pp. 710-758 ◽  
Author(s):  
Louis J. Dell'Italia ◽  
Gregory L. Freeman ◽  
William H. Gaasch

10.2196/15331 ◽  
2020 ◽  
Vol 8 (7) ◽  
pp. e15331 ◽  
Author(s):  
Po-Jen Hsiao ◽  
Chih-Chien Chiu ◽  
Ke-Hsin Lin ◽  
Fu-Kang Hu ◽  
Pei-Jan Tsai ◽  
...  

Background Long-distance running can be a form of stress to the heart. Technological improvements combined with the public’s gradual turn toward mobile health (mHealth), self-health, and exercise effectiveness have resulted in the widespread use of wearable exercise products. The monitoring of dynamic cardiac function changes during running and running performance should be further studied. Objective We investigated the relationship between dynamic cardiac function changes and finish time for 3000-meter runs. Using a wearable device based on a novel cardiac force index (CFI), we explored potential correlations among 3000-meter runners with stronger and weaker cardiac functions during running. Methods This study used the American product BioHarness 3.0 (Zephyr Technology Corporation), which can measure basic physiological parameters including heart rate, respiratory rate, temperature, maximum oxygen consumption, and activity. We investigated the correlations among new physiological parameters, including CFI = weight * activity / heart rate, cardiac force ratio (CFR) = CFI of running / CFI of walking, and finish times for 3000-meter runs. Results The results showed that waist circumference, smoking, and CFI were the significant factors for qualifying in the 3000-meter run. The prediction model was as follows: ln (3000 meters running performance pass probability / fail results probability) = –2.702 – 0.096 × [waist circumference] – 1.827 × [smoke] + 0.020 × [ACi7]. If smoking and the ACi7 were controlled, contestants with a larger waist circumference tended to fail the qualification based on the formula above. If waist circumference and ACi7 were controlled, smokers tended to fail more often than nonsmokers. Finally, we investigated a new calculation method for monitoring cardiac status during exercise that uses the CFI of walking for the runner as a reference to obtain the ratio between the cardiac force of exercise and that of walking (CFR) to provide a standard for determining if the heart is capable of exercise. A relationship is documented between the CFR and the performance of 3000-meter runs in a healthy 22-year-old person. During the running period, data are obtained while participant slowly runs 3000 meters, and the relationship between the CFR and time is plotted. The runner’s CFR varies with changes in activity. Since the runner’s acceleration increases, the CFR quickly increases to an explosive peak, indicating the runner’s explosive power. At this period, the CFI revealed a 3-fold increase (CFR=3) in a strong heart. After a time lapse, the CFR is approximately 2.5 during an endurance period until finishing the 3000-meter run. Similar correlation is found in a runner with a weak heart, with the CFR at the beginning period being 4 and approximately 2.5 thereafter. Conclusions In conclusion, the study results suggested that measuring the real-time CFR changes could be used in a prediction model for 3000-meter running performance.


2003 ◽  
Vol 49 (8) ◽  
pp. 1337-1346 ◽  
Author(s):  
Urban Alehagen ◽  
Göran Lindstedt ◽  
Henry Eriksson ◽  
Ulf Dahlström

Abstract Background: The aims of this study were to measure the N-terminal fragment of pro-brain natriuretic peptide (proBNP) in plasma in medical conditions commonly found in primary care and to evaluate the utility of these measurements in identifying impaired cardiac function in elderly patients with symptoms associated with heart failure. Methods: We studied 415 patients (221 men and 194 women; mean age, 72 years) who had contacted a primary healthcare center for dyspnea, fatigue, and/or peripheral edema. One cardiologist evaluated the patients in terms of history, physical examination, functional capacity, electrocardiography, and suspicion of heart failure. Plasma N-terminal proBNP was measured by an in-house RIA. An ejection fraction ≤40% by Doppler echocardiography was regarded as reduced cardiac function. Abnormal diastolic function was defined as an abnormal mitral inflow defined as reduced ratio of peak early diastolic filling velocity to peak filling velocity at atrial contraction (E/A ratio), or as abnormal pulmonary venous flow pattern. Results: Patients with impaired functional capacity, impaired systolic function, and/or impaired renal function had significantly increased N-terminal proBNP concentrations. By multiple regression analysis, N-terminal proBNP concentrations were also influenced by ischemic heart disease, cardiac enlargement, and certain medications but not by increased creatinine. No gender differences were observed. Patients with isolated diastolic dysfunction attributable to relaxation abnormali-ties had lower concentrations than those with normal cardiac function, whereas those with pseudonormal E/A ratios or restrictive filling patterns had higher concentrations. Conclusions: Plasma N-terminal proBNP concentrations increase as a result of impaired systolic function, age, impaired renal function, cardiac ischemia and enlargement, and certain medications. Values are high in diastolic dysfunction with pseudonormal patterns, but not in patients with relaxation abnormalities. An increase in plasma N-terminal proBNP might be an earlier sign of abnormal cardiac function than abnormalities identified by currently used echocardiographic measurements.


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