Is it possible to predict one's physical capacity?
Why is it important to know physical capacity and its potential limitations?
Physical capacity is the body's ability to perform without excessive fatigue, while maintaining the ability to recover quickly. Exercise capacity assessment is widely used in clinical medicine, such as in determining the severity of heart failure, as well as sports diagnostics, for periodization and monitoring of training, among others.
Knowing physical capacity and its potential limitations is crucial for many people, not only patients, but also doctors and healthy people. For athletes, accurate predictions can help plan training and avoid overtraining. Those struggling with chronic diseases and their doctors can use the data to better monitor health and plan activities. In turn, healthy lifestyle enthusiasts gain tools to monitor progress and control exercise intensity.
Models and predictive equations in sports medicine
A few examples of indicators used to assess physical fitness are: maximal oxygen uptake [VO2max], maximal heart rate [HRmax], and, increasingly used, total hemoglobin mass [tHBmass]. However, the most popular and widely discussed indicator is VO2max, which is considered the “gold standard” in assessing physical fitness. VO2max represents the maximum amount of oxygen that the body can take in and use during exercise, usually on a per minute and per body weight basis. The higher the VO2max, the better the body's ability to continue demanding exercise. This parameter is now used by most popular sports devices (such as watches).
The results of current scientific research offer a wide range of tools for predicting physical capacity, including mathematical models and advanced statistical analysis. Such equations make it possible to calculate not only VO2max, but also other variables using simple, readily available coefficients. The least complicated equations use age, gender or body weight, but the possibilities for expansion are endless and can include laboratory parameters, medical history and much more.
Most equations have been developed to date for VO2max. However, a comprehensive analysis of exercise capacity should also include other variables that may add value in selected situations (e.g., ventilatory efficiency slope [VE/VCO2-slope] in heart failure). Hence, in the NOODLE (“predictioN mOdels fOr enDurance athLetEs”) study, we evaluated the accuracy of current models and developed new equations for less common parameters like: VE/VCO2-slope, peak oxyegn pulse [O2Ppeak], oxygen uptake efficiency slope [OUES], and oxygen uptake efficiency plateau [OUEP].
And importantly, some predictors are already showing enough promise that they may soon be used as an alternative to full cardiopulmonary exercise testing [CPET]. Especially since CPET may be difficult to access, too burdensome or expensive in some circumstances.
Accuracy of predictions
The effectiveness of existing predictive models is very high, although not without limitations. In many studies, the values predicted by the models correlate with actual results with an accuracy of more than 90% and the difference is comparable to measurement error (so-called test-retest reliability). However, this accuracy can vary depending on the population, the level of training of the participants and the quality of the input data used during model generation.
For example, in athletes with high levels of training, models may not account for factors such as training adaptations that are difficult to measure with standard methods. Conversely, in the elderly or those suffering from chronic diseases such as diabetes and hypertension, the equations may require additional calibration and adjustment.
New promising determinants of performance
In addition to the aforementioned cardiorespiratory parameters, physical capacity is determined by a number of other factors, including genetic predisposition, diet and health status. Hematological variables, which until now have mainly been used in clinical medicine, are also increasingly being used in sports diagnostics. An example is tHBmass, which among healthy individuals is used in the early identification of talent in endurance sports and helps decide whether an athlete has doped.
Will technology revolutionize forecasting?
In recent years, more and more technologies have been emerging that can significantly enrich the quality of methods for predicting physical fitness. One example is popular sports devices, i.e. watches and wristbands that continuously monitor heart rate, activity level or sleep quality. This data can be used in building predictive equations, providing valuable, highly personalized information about participants.
Artificial intelligence also plays a key role. Machine learning algorithms can analyze huge amounts of data and identify subtle patterns that are invisible to traditional statistical methods. As a result, predictions are becoming more precise, taking into account the complexity of the human body.
The challenges and the future
Despite tremendous advances in the area of cardiopulmonary parameter prediction, there are many challenges. One of them is the need to standardize measurement methods and take into account the diversity of the population. In the future, we can expect to see even more advanced solutions, such as personalized training programs determined in accordance between results obtained directly from CPET and those predicted, as well as the integration of prediction with telemedicine platforms. Models are also being developed that will predict not only physical fitness, but also injury risk or responses to particular types of training.
Summary
So is it possible to predict one's physical capacity? Today's technologies and statistical models have enormous potential. Advances in this field can not only improve the assessment of a patient's health, but also revolutionize the approach to individually tailored training. That's why it's worth following this rapidly developing area of science, because the future of our fitness may lie in the math and data.
Przemysław Kasiak is a sixth-year medical student, and for the past three years he has also been a doctoral student at the 3rd Department of Internal Diseases and Cardiology MUW. His area of scientific interest is in cardiology and sports medicine. He has co-authored 31 original articles (IF=80; h-index=11) and two textbooks. He is an editor of the journal PLOS ONE (IF=2.9) and a reviewer of >100 scientific publications. He is also a member of Club30 of the Polish Society of Cardiology, which brings together outstanding young cardiologists. During his studies, he collaborated with the Medical University of Lausanne, the University of Zurich and the University Medical Center in Utrecht, among others. Among other awards, he received twice the Scholarship of the Minister of Health for Significant Scientific Achievements, the Medical Laurel of the Polish Academy of Sciences, and several times Award of the Rector of MUW for Outstanding Scientific Publications. He is passionate about soccer and has been a soccer referee for 8 years.