## 4 Discussion  
Our main findings demonstrated (1) substantial disparities in HDF between controls and MR patients with preserved EF, indicating altered force distribution; (2) noteworthy variations between controls and patients across different MR severities; (3) strong correlation between HDF parameters and LV function, showing an altered relationship while comparing controls and patients with MR; (4) significant linear correlation between MR severity and HDF, especially in the B-A direction; (5) systolic RMS B-A and diastolic RMS S-L as significant predictors of increased MR severity. Hemodynamic forces are recognized as an important factor in heart development and exert influences on the pathophysiology of the mature heart. [PERSON] et al. investigated in vivo model of patients who presented a stable normal heart function when the pacemaker was on and who were expected to develop LV remodeling when the pacemaker was switched off. They found that HDF developed misalignment hammering onto lateral walls when the pacing was temporarily switched off. They concluded that HDF was the first event that evoked a physiological activity anticipating cardiac changes and suggested that HDF could help in predicting longer-term heart adaptations [17]. A study performed by [PERSON] et al. on HF with preserved EF (HFpEF) demonstrated HDF alteration between controls and patients. They indicated the association of HDF with cardiac events [19]. Another study by [PERSON] et al. showed a similar result for dilated cardiomyopathy and concluded that HDF altered significantly between controls and patients [16]. A similar study by [PERSON] et al. showed the ability of HDF to discriminate between controls and HFpEF [37]. [PERSON] et al. showed that HDF assessment is a novel approach to  
Figure 8: The multi-linear regression model demonstrates the predictive power of RMS forces in the systolic B-A (\(p\)-value = 0.003) and diastolic S-L (\(p\)-value = 0.029) directions to predict mitral regurgitation with preserved ejection fraction. Out of seventeen HDF parameters, those two stood out as significant predictors. The overall model fit was F = 3.414 (\(p\)-value = 0.003). Notes: The predictive value, beta (B), was considered significant when the \(p\)-value \(<\) 0.05. Abbreviations: S-L = septal–lateral; B-A = basal–apical; RMS = root mean square; HDF = hemodynamic force; CI = confidence interval; S = systole; D = diastole. identifying LV pressure gradients. They also reported that the HDF pattern might be altered in myocardial infarction and non-ischemic cardiomyopathy [14]. None of the previous studies addressed the impact of HDF on patients with MR or the relationship between HDF and standard MR severity metrics. To the best of our knowledge, the present study is the first and only study that focuses on MR patients with preserved EF and reports on the association between the degree of MR, HDF, and LV function. [PERSON]. [PERSON] et al. analyzed controls and patients with rTOF and found significant differences in diastolic HDF [12]. Similarly, our study found that the diastolic RMS in the I-A direction was significantly increased in MR patients than in healthy controls. We further extended our study to examine if there were considerable differences among MR severities. We found the diastolic RMS in the S-L and I-A directions demonstrated notable diversity among MR severities. Our study showed that all the systolic AVG, systolic RMS, and overall AVG in the B-A direction differ significantly between controls and MR patients with preserved EF. Systolic AVG and overall AVG in the S-L direction showed considerable differences. Again, the systolic AVG and systolic RMS in the B-A direction stood out as a common variable that differentiated between controls and MR severities. Besides these, the systolic AVG in the S-L direction, and systolic RMS in the I-A direction demonstrated significant differences among MR severities. A very recent study by [PERSON] et al.