Table 1.
Subject characterisitcs.
Table 2.
Summary of study protocols.
Fig 1.
Cross validation results for Model D1: = e-9.59HR2.39age0.274sex-0.204FVC0.520, where HR is beats per minute, age is in years, FVC is the GLI predicted value expressed in liters, and sex is 1 for males and 2 for females.
The median(IQR) percent error from cross-validation for this model is -0.664(45.4)%. Circles are persons without an FVC measurement; triangles are persons with measured FVC = 85–115% of the predicted value; diamonds are persons with measured FVC < 85% predicted, and squares are persons with measured FVC > 115% predicted. Dashed lines are ±25% error.
Fig 2.
Cross validation results for Model D2: = e-8.57HR1.72fB0.611age0.298sex-0.206FVC0.614, where HR is beats per minute, fB is breaths per minute, age is in years, FVC is the GLI predicted value expressed in liters, and sex is 1 for males and 2 for females.
The median(IQR) percent error from cross validation for this model is 1.20(37.9)%. Circles are persons without an FVC measurement; triangles are persons with measured FVC = 85–115% of the predicted value; diamonds are persons with measured FVC < 85% predicted, and squares are persons with measured FVC > 115% predicted. Dashed lines are ±25% error.
Table 3.
Results of general linear mixed models using log-transformed as the dependent variable, and all predictor variables are likewise log-transformed.
These models yield a power function of the form where β0 is the model intercept.
Table 4.
Effect of lung capacity on predictions of using calculated FVC as a predictor according to Model D2.
Model performance is shown for subjects with and without FVC measurements, and subjects with FVC measurements are further stratified into low, high, and normal FVC groups.
Table 5.
Effect of lung capacity on predictions of using measured FVC to calculate
according to Model D2.
Model performance is shown for subjects with FVC measurements stratified into low, high, and normal FVC groups.
Table 6.
The results of applying previously-published predictive models to this assembled dataset.
For reference, the results of Models D1 and D2 from this paper are shown, including both random 10-fold cross-validation and cross-validation by study.