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The eight variables included in the final DETECT algorithm were derived from univariable and multivariable statistical analyses; some of these variables have previously been verified as predictive factors for the presence of SSc-PAH, such as FVC/DLCO [ 8- 10], NT-proBNP [ 11, 12], telangiectasia [ 20], ACA [ 21, 22], serum urate [ 23, 24], and TRV [ 2].
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A surprising number, however, have actually been verified as true.
This can be verified as follow.
Good predictive ability of the models was verified as high values of the statistics R2 and F were obtained for the linear relationship between predicted cross-validated and experimental values of the dependent variable.
The significant digits were verified, as suggested.
Specificity was verified as described [ 8].
All samples were verified as Caucasian descendants.
NDN is verified as an epigenetic target.
This predictive capability has been verified in laboratory experiments.
The predictive power of the model has been verified.
The predictive capabilities of the numerical model are verified by past experimental data, as well as wind tunnel experiments in the current paper, to compare two particular geometric designs.
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