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Kinematic variability was also assessed using mean standard deviations (MeanSD) across cycles.
Global hemodynamic status was assessed using mean arterial blood pressure, heart rate and cardiac index.
Quantitative variables were assessed using mean and standard deviation values after checking normality with the Kolmogorov Smirnov test.
Item quality was assessed using mean, standard deviation (SD), missing data, lowest (floor) and highest (ceiling) scores.
Validity was assessed using mean absolute percent error and coefficient of variance between oxygen uptake measures and the MWK's estimated oxygen uptake computed from counts.
The estimations of the developed model were assessed using mean error (ME) as a measure of bias and mean squared error (MSE) as a measure of precision.
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Demographic and lifestyle characteristics of study participants were assessed using means (± standard deviation) for continuous variables and counts and percentages for categorical variables.
Linear, quadratic, exponential and S-Curve models were sequentially fitted to the data and for each model its adequacy was assessed using the mean absolute percentage error, mean absolute deviation and the mean squared deviation.
Agreement between mGFR and eGFR was assessed using the mean bias (average difference between mGFR and eGFR), standard error of the mean bias, the Pearson correlation coefficient and the concordance correlation coefficient as described previously [ 25– 27].
The robustness and appropriateness of the approach were assessed using the mean relative error (MRE).
The quality of the model is assessed using a mean square error measure that depends linearly on the parameters.
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