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Aspects of Left Ventricular Morphology Outperform Left Ventricular Mass for Prediction of QRS Duration

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Background: The knowledge of the case-specific normal QRS duration in each individual is needed when determining the onset, severity and progression of the heart disease. However, large interindividual variability even of the normal QRS duration exists. The aims of the study were to develop a model for prediction of normal QRS complex duration and to test it on healthy individuals.

Methods: The study population of healthy adult volunteers was divided into a sample for development of a prediction model (n = 63) and a testing sample (n = 30). Magnetic resonance imaging data were used to assess anatomical characteristics of the left ventricle: the angle between papillary muscles (PMA), the length of the left ventricle (LVL) and left ventricular mass (LVM). Twelve-lead electrocardiogram (ECG) was used for measurement of the QRS duration. Multiple linear regression analysis was used to develop a prediction model to estimate the QRS duration. The accuracy of the prediction model was assessed by comparing predicted with measured QRS duration in the test set.

Results: The angle between PMA and the length of the LVL were statistically significant predictors of QRS duration. Correlation between QRS duration and PMA and LVL was r = 0.57, P = 0.0001 and r = 0.45, P = 0.0002, respectively. The final model for prediction of the QRS was: QRSPredicted= 97 + (0.35 × LVL) − (0.45 × PMA). The predicted and real QRS duration differed with median 1 ms.

Conclusions: The model for prediction of QRS duration opens the ability to predict case-specific normal QRS duration. This knowledge can have clinical importance, when determining the normality on case-specific basis.

Ann Noninvasive Electrocardiol 2010;15(2):124–129
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Keywords: QRS duration; papillary muscles; prediction

Document Type: Research Article

Affiliations: 1: Department of Clinical Physiology, Lund University Hospital, Lund, Sweden 2: Department of Health Services, University of Washington, WA

Publication date: April 1, 2010

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