"Optimum" formulae for heart rate correction of the QT interval

The study investigated the performance of several generic QT/RR regression models in a dataset of QT and RR intervals obtained from resting electrocar diograms of 1,100 healthy subjects (913 male, mean age 33 +/- 12 years). Al l the investigated models have three degrees of freedom and included the hy perparabolic and hyper-hyperbolic models, algorithmic models, negative expo nential models, and models involving inverse tangent, hyperbolic tangent, a nd inverse hyperbolic sign functions. For each generic model, the combinati on of parameters leading to the lowest regression residuum was found. The r esults of the study show that the goodness of the optimum fit is practicall y independent of the generic form of the regression model and that differen t datasets lead to different combinations of the numerical values of parame ters of the corresponding regression models. The study concludes that the s earch for a universally applicable QT/RR regression model that would provid e the best fit in all circumstances is most likely fruitless. Rather, indiv idual studies such as those investigating drug related QT prolongation migh t benefit from establishing a best-fit regression that would provide the op timum model for each particular dataset.