Evaluation of new Vectorcardiography Algorithms for identifying Patients with reduced Left Ventricular Ejection Fraction and Left Ventricular Hypertrophy

https://doi.org/10.1007/s00392-025-02625-4

Sarah Wolfsteller (Heidelberg)1, J. Salatzki (Heidelberg)1, A. K. Schwarz (Hamburg)2, E. Poyo Medina (Heidelberg)1, N. Frey (Heidelberg)1, F. André (Heidelberg)1, H. Steen (Heidelberg)1, A. Passow (Leipzig)3

1Universitätsklinikum Heidelberg Klinik für Innere Med. III, Kardiologie, Angiologie u. Pneumologie Heidelberg, Deutschland; 2Katholisches Marienkrankenhaus gGmbH Kardiovaskuläre MRT Hamburg, Deutschland; 3Universität Leipzig Medizinische Fakultät Institut für Medizinische Informatik, Statistik und Epidemiologie (IMISE) Leipzig, Deutschland

 

Background:

Reduced left ventricular ejection fraction (LV-EF) and left ventricular hypertrophy (LVH) are associated with high mortality and morbidity. Early and accurate diagnosis is essential, but non-invasive, cost-effective diagnostic tools are still needed for clinical application. This study evaluated the diagnostic performance of a modified vectorcardiography algorithm, using Cardisiography (CSG), a technique which records cardiac electrical activity in three dimensions, for detecting reduced LV-EF and LVH. 

 

Methods:

This prospective, single-center, case-control study included patients with reduced LV-EF (< 40%), and LVH, defined as indexed LV mass > 55 g/m², compared with controls without cardiac pathology. Cardiac magnetic resonance imaging was performed as part of routine clinical care and used as the reference standard for measuring LV-EF and LV mass. Patients were enrolled consecutively. The CSG analyzed 583 vectorcardiography parameters per heartbeat to classify cardiac status, consisting of 533 regular parameters and 50 Frenet-Serret parameters. Parameters were selected based on a low p-value from the Mann-Whitney-Wilcoxon test, indicating statistical significance. Bayes' theorem was used to update prior probabilities and to derive posterior probabilities for reduced LV-EF and LVH when compared with controls.

 

Results:

A total of 280 patients were included in the analysis. The group with reduced LV-EF (n=40) had a mean age of 56 ± 16 years and was predominantly male (78%), with a median LV-EF of 31.5% (IQR: 23.4-36.3%). The LVH group (n=209) had a mean age of 60 ± 16 years (87% male) with an indexed LVM of 67g/m² (IQR: 61-77 g/m²). Controls (n=31) had a mean age of 50 ± 16 years (61% male), normal LV-EF of 62 ± 5.6% and indexed LV mass of 40g/m² (IQR: 35-47g/m²).

A CSG parameter with p-value <0.1% after conservative Bonferroni adjustment and AUC of 87.5% was identified among CSG parameters and demonstrated a sensitivity of 80.0% and specificity of 85.7% for detecting reduced LV-EF (accuracy 82.9%). For detecting LVH, it achieved a sensitivity of 74.5% and specificity of 68.6% (accuracy 73.6%) using 3 CSG parameters. In cases with patients revealing both reduced LV-EF and LVH (n=64), the CSG demonstrated a sensitivity of 79.3% and a specificity of 85.7% (accuracy 82.8%).

 

Conclusion:

The modified vectorcardiography algorithms showed diagnostic value for detecting reduced LV-EF and LVH. CSG could serve as a fast, non-invasive, and cost-effective method to assist clinicians in identifying significant cardiac conditions and to guide further diagnostic steps.

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