Heart rate variability and target organ damage in hypertensive patients

Background

We evaluated the association between linear standard Heart Rate Variability (HRV) measures and vascular, renal and cardiac target organ damage (TOD).

Methods

A retrospective analysis was performed including 200 patients registered in the Regione Campania network (aged 62.4 ± 12, male 64%). HRV analysis was performed by 24-h holter ECG. Renal damage was assessed by estimated glomerular filtration rate (eGFR), vascular damage by carotid intima-media thickness (IMT), and cardiac damage by left ventricular mass index.

Results

Significantly lower values of the ratio of low to high frequency power (LF/HF) were found in the patients with moderate or severe eGFR (p-value < 0.001). Similarly, depressed values of indexes of the overall autonomic modulation on heart were found in patients with plaque compared to those with a normal IMT (p-value <0.05). These associations remained significant after adjustment for other factors known to contribute to the development of target organ damage, such as age. Moreover, depressed LF/HF was found also in patients with left ventricular hypertrophy but this association was not significant after adjustment for other factors.

Conclusions

Depressed HRV appeared to be associated with vascular and renal TOD, suggesting the involvement of autonomic imbalance in the TOD. However, as the mechanisms by which abnormal autonomic balance may lead to TOD, and, particularly, to renal organ damage are not clearly known, further prospective studies with longitudinal design are needed to determine the association between HRV and the development of TOD.

Pupillometric analysis for assessment of gene therapy in Leber Congenital Amaurosis patients

BACKGROUND

Objective techniques to assess the amelioration of vision in patients with impaired visual function are needed to standardize efficacy assessment in gene therapy trials for ocular diseases. Pupillometry has been investigated in several diseases in order to provide objective information about the visual reflex pathway and has been adopted to quantify visual impairment in patients with Leber Congenital Amaurosis (LCA). In this paper, we describe detailed methods of pupillometric analysis and a case study on three Italian patients affected by Leber Congenital Amaurosis (LCA) involved in a gene therapy clinical trial at two follow-up time-points: 1 year and 3 years after therapy administration.

METHODS

Pupillary light reflexes (PLR) were measured in patients who had received a unilateral subretinal injection in a clinical gene therapy trial. Pupil images were recorded simultaneously in both eyes with a commercial pupillometer and related software. A program was generated with MATLAB software in order to enable enhanced pupil detection with revision of the acquired images (correcting aberrations due to the inability of these severely visually impaired patients to fixate), and computation of the pupillometric parameters for each stimulus. Pupil detection was performed through Hough Transform and a non-parametric paired statistical test was adopted for comparison.

RESULTS

The developed program provided correct pupil detection also for frames in which the pupil is not totally visible. Moreover, it provided an automatic computation of the pupillometric parameters for each stimulus and enabled semi-automatic revision of computerized detection, eliminating the need for the user to manually check frame by frame. With reference to the case study, the amplitude of pupillary constriction and the constriction velocity were increased in the right (treated eye) compared to the left (untreated) eye at both follow-up time-points, showing stability of the improved PLR in the treated eye.

CONCLUSIONS

Our method streamlined the pupillometric analyses and allowed rapid statistical analysis of a range of parameters associated with PLR. The results confirm that pupillometry is a useful objective measure for the assessment of therapeutic effect of gene therapy in patients with LCA.

TRIAL REGISTRATION

ClinicalTrials.gov NCT00516477.

Nonlinear Heart Rate Variability features for real-life stress detection. Case study: students under stress due to university examination

Background

This study investigates the variations of Heart Rate Variability (HRV) due to a real-life stressor and proposes a classifier based on nonlinear features of HRV for automatic stress detection.

Methods

42 students volunteered to participate to the study about HRV and stress. For each student, two recordings were performed: one during an on-going university examination, assumed as a real-life stressor, and one after holidays. Nonlinear analysis of HRV was performed by using Poincaré Plot, Approximate Entropy, Correlation dimension, Detrended Fluctuation Analysis, Recurrence Plot. For statistical comparison, we adopted the Wilcoxon Signed Rank test and for development of a classifier we adopted the Linear Discriminant Analysis (LDA).

Results

Almost all HRV features measuring heart rate complexity were significantly decreased in the stress session. LDA generated a simple classifier based on the two Poincaré Plot parameters and Approximate Entropy, which enables stress detection with a total classification accuracy, a sensitivity and a specificity rate of 90%, 86%, and 95% respectively.

Conclusions

The results of the current study suggest that nonlinear HRV analysis using short term ECG recording could be effective in automatically detecting real-life stress condition, such as a university examination.

New indices for quantification of the power spectrum of heart rate variability time series without the need of any frequency band definition

This paper presents a new family of indices for the frequency domain analysis of heart rate variability time series that do not need any frequency band definition. After proper detrending of the time series, a cumulated power spectrum is obtained and frequencies that contain a certain percentage of the power below them are identified, so median frequency, bandwidth and a measure of the power spectrum asymmetry are proposed to complement or improve the classical spectral indices as the ratio of the powers of LF and HF bands (LF/HF). In normal conditions the median frequency provides similar information as the classical indices, while the bandwidth and asymmetry can be complementary measures of the physiological state of the tested subject. The proposed indices seem to be a good choice for tracking changes in the power spectrum in exercise stress, and they can guide in the determination of frequency band limits in other animal species.

Discrimination power of long-term heart rate variability measures for chronic heart failure detection

The aim of this study was to investigate the discrimination power of standard long-term heart rate variability (HRV) measures for the diagnosis of chronic heart failure (CHF). The authors performed a retrospective analysis on four public Holter databases, analyzing the data of 72 normal subjects and 44 patients suffering from CHF. To assess the discrimination power of HRV measures, an exhaustive search of all possible combinations of HRV measures was adopted and classifiers based on Classification and Regression Tree (CART) method was developed, which is a non-parametric statistical technique. It was found that the best combination of features is: Total spectral power of all NN intervals up to 0.4 Hz (TOTPWR), square root of the mean of the sum of the squares of differences between adjacent NN intervals (RMSSD) and standard deviation of the averages of NN intervals in all 5-min segments of a 24-h recording (SDANN). The classifiers based on this combination achieved a specificity rate and a sensitivity rate of 100.00 and 89.74%, respectively. The results are comparable with other similar studies, but the method used is particularly valuable because it provides an easy to understand description of classification procedures, in terms of intelligible "if … then …" rules. Finally, the rules obtained by CART are consistent with previous clinical studies.