Severity: Warning
Message: file_get_contents(https://...@gmail.com&api_key=61f08fa0b96a73de8c900d749fcb997acc09&a=1): Failed to open stream: HTTP request failed! HTTP/1.1 429 Too Many Requests
Filename: helpers/my_audit_helper.php
Line Number: 197
Backtrace:
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 197
Function: file_get_contents
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 271
Function: simplexml_load_file_from_url
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 3165
Function: getPubMedXML
File: /var/www/html/application/controllers/Detail.php
Line: 597
Function: pubMedSearch_Global
File: /var/www/html/application/controllers/Detail.php
Line: 511
Function: pubMedGetRelatedKeyword
File: /var/www/html/index.php
Line: 317
Function: require_once
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Objective: Maximum-voluntary-ventilation (MVV) is the maximal volume of which an individual can move by voluntary effort in one minute. It is possible that the first second forced-expiratory-volume (FEV) could be more to reliable assess respiratory muscle endurance to estimate MVV.
Methods: For this aim, 422 athletes (Age 22.9 ± 8.5 years; 98/324 - females/males) were performed a MVV, and FEV measurements.
Results: The coefficient of determination was R = 0.594 between MVV and FEV, with a predictive equation for overall participants: MVV = (FEV × 33.5)+12.7. The robust regression showed a good multiple correlation coefficient (R = 0.815) with the coefficient of determination R = 0.661 for the model including FEV, age and gender as predictors. These equations MVV = (FEV X 27.3)+(Age(y) × 1.1)+20.5 and MVV = (FEV × 27.3)+(Age(y) × 1.1) were derived for male and female, respectively.
Conclusion: FEV can predict MVV in different athletes with greater accuracy when stratified per gender. Therefore, this new approach can be used in a short all-out test without stress of the respiratory muscle to predict MVV in athletes.
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http://dx.doi.org/10.1080/13813455.2025.2465333 | DOI Listing |