## 4 Discussion
For long-term recordings, the guidelines were not restricted to estimating the power in any of the three spectral bands. Along with the standardization of the length of the analyzed segments, the Task Force also recommends removing the mean and trend of the signal before performing a spectral analysis to minimize the spectral contribution below the VLF band to 0 Hz. Since it is not reliable to estimate the VLF power in recordings \(\leq\)5 min, [PERSON] et al. [21] evaluated the errors obtained when estimating the spectral power distribution of a signal when the length of the analyzed segment varies from 300 s to 4000 s. The results show that the error decreases as the length increases. According to the publication, to decrease the errors in the VLF power estimation to slightly less than 20%, the length of the segment must be increased to 10 min. Following these results, we performed the STFT over 10 min segments. The results of the spectrotemporal analysis show that all powers behave similarly in the three bands. We observed that any spectral power can be modeled by a vertical parabola opened downward (Figure 4). It can also be seen that the regression models of hypotensive patients had higher mean values than those of non-hypotensive patients and that the time when the maximum power was reached (obtained with the respective quadratic models) is different for each band and depends on the presence or absence of a hypotension event. Moreover, the plots of each band show that the models for both groups have very close starting power values. The statistics of all fitted models yielded significant \(p\)-values for their correlation with time. Despite the high similarity between the two quadratic models for VLF power in the independent term and moment when the maximum is reached, the main difference between them is the rate of change, which is smaller for the hypotensive group than for the non-hypotensive group. This caused the maximum power reached by the first group to be smaller than the maximum power of the second group, although there was only 6 min of difference between them. Slow changes in the VLF power might suggest the decompensation of the CV system, which is strongly linked to an increased risk of developing major adverse cardiovascular events [32]. Although the LF and HF powers received more attention in the spectral analysis, it is important to follow changes in the VLF band because such changes are associated with the RAAS [16], which has a strong bidirectional interaction with the autonomic nervous system [39]. For the LF power, the maximum was reached during the first half of HD therapy (at 70 min) for the group of hypotensive patients. Here, the activity of the sympathetic system responded normally by increasing the heart rate. However, for the remaining time of the HD therapy, the LF power decreased slowly, while the heart rate continued to increase, showing behavior contrary to what was expected. For the group of non-hypotensive patients, this value reached its maximum at 145 min, and during the remaining 35 min of therapy, the LF power decreased minimally, favoring a lower reduction in heart rate and sustained arterial pressure for a longer time. The HF power was larger for the group of non-hypotensive patients, and the maximum value of the model occurred almost during the third hour of therapy (116 min), while for the group of hypotensive patients, the maximum value was reached during the first hour of therapy. Further, the HF power of the hypotensive patients increased very little compared to that of the non-hypotensive patients, which suggests continuous attenuation in the vagal modulatory mechanism during the therapy. All the quadratic models obtained for the spectral powers yielded \(R>0.52\) and \(R^{2}>0.27\), which indicates that the model is correctly able to describe the behavior of HRV during HDF, with statistical power greater than 0.8 in all models except one. The results we obtained are similar to those published by [PERSON] et al.