Circadian heart rate and blood pressure variability considered for research and patient care

A blood pressure monitoring method for stroke management

Blood pressure is one important risk factor for stroke prognosis. Therefore, continuous monitoring of blood pressure is crucial for preventing and predicting stroke. However, current blood pressure devices are mainly air-cuff based, which only can provide measurements intermittently. This study proposed a new blood pressure estimation method based on the pulse transit time to realize continuous monitoring. The proposed method integrated a linear model with a compensation algorithm. A calibration method was further developed to guarantee that the model was personalized for individuals. Variation and variability of pulse transit time were introduced to construct the compensation algorithm in the model. The proposed method was validated by the data collected from 30 healthy subjects, aged from 23 to 25 years old. By comparing the estimated value to the measurement from an oscillometry, the result showed that the mean error of the estimated blood pressure was −0.2 ± 2.4 mmHg and 0.5 ± 3.9 mmHg for systolic and diastolic blood pressure, respectively. In addition, the estimation performance of the proposed model is better than the linear model, especially for the diastolic blood pressure. The results indicate that the proposed method has promising potential to realize continuous blood pressure measurement.

DETRENDED FLUCTUATION ANALYSES OF SHORT-TERM HEART RATE VARIABILITY IN SURGICAL INTENSIVE CARE UNITS

We examine the dynamics of complex physiologic fluctuations using methods developed very recently in statistical physics. The method based on detrended fluctuation analysis (DFA) has been used to investigate the profile of different types of physiologic states under long term (i.e., 24 hr) analysis of heart rate variability (HRV). In this paper, this method to investigate the output of central physiologic control system under short term (i.e., 1 hr) of HRV in surgical intensive care units (SICU). Electrocardiograph (ECG) signals lasting around 1 hr were collected from ten college student volunteers as group A. Ten computes-generates white noise signals as group B also provided ECG signals lasting around 1 hr. Finally, seventeen patients representing 37 cases undergoing different types of neurosurgery were studied as group C. From this group, 25 cases were selected from 15 patients with brain injury and 12 cases were selected from 2 patients with septicemia. Group A and B were used as high and low limits of baseline for comparison with pathologic states in the SICU. The a values of DFA of groups A, B, and C were 0.958 ± 0.034, 0.521 ± 0.010, and 0.815 ± 0.183, respectively. It was found that the α value of patients in the SICU was significantly lower (P < 0.05) than that of healthy volunteers and significantly higher (P < 0.05) than white noise signals. Hence, it can be concluded that α values based on the DFA statistical concept can clearly distinguish pathologic states in SICU patients from the healthy group and from white noise signals.

Heart rate and blood pressure variability as markers of sensory blockade with labour epidural analgesia

PURPOSE

To evaluate the correlation between the progression of somatosensory blockade and changes in autonomic outflow following the onset of labour epidural analgesia.

METHODS

Twelve labouring parturients consented to participate in the study. Baseline electrocardiogram, blood pressure (BP) and respiratory rate were recorded for ten minutes. The epidural consisted of 0.125% bupivacaine with 50 microg of fentanyl (total volume 20 mL). Measurements were repeated for ten minutes after initiation of the block. The level of sensory block was measured bilaterally with loss of sensation to ice at two-minute intervals. Wavelet transform was used to obtain heart rate (HR) and BP variability every two minutes following the loading dose of epidural medication. High frequency power of HR variability was used to assess changes in parasympathetic activity. The total power of BP variability was used to assess changes in sympathetic activity. A nonparametric repeated measures ANOVA was used for the variability data, and a Spearman rank correlation test was used to evaluate the relationship between the sensory block and HR and BP variability.

RESULTS

The sensory block progressed to T9 at ten minutes post-epidural and was the mirror image of the decrease in total power of BP variability. High frequency power of HR variability increased to a plateau at six minutes post-epidural. A significant correlation was found between the increase in sensory block and the observed decrease in BP variability (r = -1.000, P = 0.0028).

CONCLUSION

In this study of labouring parturients, BP variability correlated with the progression of both sympathetic and somatosensory block following epidural anesthesia, while HR variability was shown to be a surrogate marker of increased parasympathetic activity.

Spectral analysis of pulse transit time variability and its coherence with other cardiovascular variabilities

Pulse transit time (PTT) has been reported correlated with heart rate (HR) and blood pressure (BP), however, the results are not consistent in different investigations. Towards a better understanding of the underlying mechanisms of the PTT changes, this study compares the power spectrum density of the variability in PTT with that in HR and BP under rest and post-exercise physiological conditions. Coherence function is also examined to quantify the strength of coupling between paired variabilities. The results show that the pulse transit time variability (PTTV) has significant coherence (>0.5) with heart rate variability (HRV) and blood pressure variability (BPV) under all physiological conditions at high frequency (HF). However, at the low frequency (LF) band, the coherence reduced to insignificance immediately after the exercise (< or =5 minutes after exercise) and then return back to significant level 9 minutes after the exercise. The results show that PTTV is strongly coupled with HRV and BPV at the HF, indicating that the parasympathetic modulation could be the main cause of PTTV. The unstable coupling relationship of PTTV with BPV at LF should raise caution in the beat-to-beat BP estimation by PTT in the dynamic situation.

Toward chronocardiologic and chronomic insights: dynamics of heart rate associated with head-up tilting

As a step towards investigating the chronome (i.e. the inferential endpoints of chaos, trends and rhythms) of heart rate (HR) variability (HRV), we investigated whether the fractality or complexity of HRV is affected by a head-up tilting (HUT) test in the morning after an overnight fast. Spectral and non-linear analyses of HR were performed on data gathered during an 80 degrees passive HUT test in 15 men and 28 women 32.8 +/- 11.5 years of age. The non-linear endpoints included the scaling exponents alpha1 (<11 beats) and alpha2 (>11 beats), which indicate fractal properties, calculated with detrended fluctuation analysis, and the approximate entropy (ApEn), a measure of overall complexity. Passive HUT increased alpha1 (from 0.986 +/- 0.217 to 1.370 +/- 0.185; P = 0.0001), but did not alter alpha2 (from 0.925 +/- 0.110 to 0.958 +/- 0.130; P = 0.19). A slight but statistically significant decrease in ApEn was seen during HUT (from 1.114 +/- 0.131 to 1.013 +/- 0.197; P = 0.002). In the tilt-up position, there was a statistically significant negative correlation between alpha1 and ApEn (r = -0.490; P < 0.05). In both the supine and the tilt-up position, alpha1 was correlated weakly with HF (r = -0.343 and r = -0.322, respectively), and strongly with LF/HF (r = 0.557 and r = 0.795), respectively. There was also a negative correlation between ApEn and LF/HF (r = -0.406 and r = -0.357, respectively). alpha2 did not correlate with any spectral or non-linear measures of HRV. Short-term fractal properties and complexity of HR were lowered with orthostatic stress. Alterations of the autonomic activities could be partly responsible for these changes and await extension of such studies to assess the broad spectral element of HRV, that includes, with components of approximately 3.6 and approximately 10.5 s, cycles with very much lower frequencies, along the scales of hours and even years, that critically modulate the mislabeled (only relatively high- and low-frequency) components in the range of seconds or minutes.