Clinical Trial Details
— Status: Completed
Administrative data
| NCT number |
NCT04740554 |
| Other study ID # |
09942913.4.0000.5505 |
| Secondary ID |
|
| Status |
Completed |
| Phase |
|
| First received |
|
| Last updated |
|
| Start date |
March 1, 2013 |
| Est. completion date |
February 1, 2015 |
Study information
| Verified date |
February 2021 |
| Source |
University of Sao Paulo |
| Contact |
n/a |
| Is FDA regulated |
No |
| Health authority |
|
| Study type |
Observational
|
Clinical Trial Summary
A cross-sectional study was carried out, in which 40 boys, aged 11 to 18 years, were
evaluated. The recruitment of groups was carried out at the neuromuscular disease outpatient
clinic of the Federal University of São Paulo (UNIFESP). The recruited individuals were
divided into 4 groups, namely: DMD that used deflazacort (DMD-D); DMD that used
Prednisone/Prednisolone (DMD-P); DMD Control with no corticoid use (DMD-C) and Controls with
typical development (CTD). The protocol was applied during the evaluation that was carried
out at outpatient follow-up visits.
To assess the functionality of each patient, the Vignos scales were used to characterize the
sample and the Motor Function Measure (MFM) for association with HRV indices.
All heart rate records were performed using a cardiofrequencymeter (V800, Polar). After
placing the brace and monitor, the individuals were placed in the supine position and
remained at rest spontaneously breathing for 25 minutes. For HRV analysis, indexes obtained
by linear methods, in the domain of time and frequency, and non-linear methods were used.
Description:
A cross-sectional study was carried out, in which 40 boys, aged 11 to 18 years, were
evaluated. The recruitment of groups was carried out at the neuromuscular disease outpatient
clinic of the Federal University of São Paulo (UNIFESP). The recruited individuals were
divided into 4 groups, namely: DMD that used deflazacort (DMD-D) with n=11; DMD that used
Prednisone/Prednisolone (DMD-P), with n=9; DMD Control with no corticoid use (DMD-C), and
n=10 and Controls with typical development (CTD) with n=10. The protocol was applied during
the evaluation that was carried out at outpatient follow-up visits. Anthropometry was
analyzed in 4 groups and functionality was assessed in 3 groups with DMD. To assess the
functionality of each patient, the Vignos scales were used to characterize the sample and the
Motor Function Measure (MFM) for association with HRV indices.
Initially, the resting ECG was analyzed to verify the existence of sinus rhythm and to
exclude individuals with arrhythmias and blocks. The measurements at rest were performed
immediately before and after the HRV assessment, including systolic (SBP) and diastolic
(DBP), heart rate (HR), Respiratory Rate (RF - blood pressure) to ensure that at the
beginning and at the end of the collection FR remains between 9 - 24rpm, in the range of 0.15
- 0.40Hz) and partial oxygen saturation (SO2). Heart rate was recorded by the cardiofrequency
meter (RS800CX, Polar). And the partial oxygen saturation by means of a digital oximeter
(DX2010, Dixtal) connected to the participant's index finger or hallux, through a sensor of
age-appropriate size, in room air. Hemoglobin saturation by oxygen was recorded after the
first minute of stabilization, as the value that remains most constant during the second
minute.
All heart rate records were performed using a cardiofrequencymeter (V800, Polar). After
placing the brace and monitor, the individuals were placed in the supine position and
remained at rest spontaneously breathing for 25 minutes. For HRV analysis, indexes obtained
by linear methods, in the domain of time and frequency, and non-linear methods were used.
In the time domain, for linear analyses, each normal RR interval (sinus beats) was verified
during a certain time interval and, using statistical and non-linear methods, the translating
indexes of fluctuations in the duration of the cardiac cycles were calculated. With this, the
indices expressed in ms were obtained: SDNN (Standard deviation of the normal RR intervals
recorded in a time interval); rMSSD (square root of the mean of the square of the differences
between adjacent normal RR intervals in a time interval).
In the frequency domain, the spectral power density is more used, mainly when treating
individuals in resting conditions. This analysis divides HRV into fundamental oscillatory
components, which were used the main: High Frequency normalized unite (HFnu) component and
Low Frequency normalized unite (LFnu) component. O algoritmo utilizado para a análise
espectral foi a transformada rápida de Fourier - FFT (janela de 256 s com 50% de overlap).
Among the nonlinear methods used for HRV analysis, we can mention the Detrended Fluctuations
Analysis (DFA), Visual Recurrence Analysis (VRA) and symbolic analysis (SA), the three of
which were verified in this study.
DFA is used to quantify the fractal property of RR interval time series, being used to detect
possible abnormalities present in a subject, based on α coefficients. For this, short memory
parameters α1, which corresponds to a period of 4 to 11 beats, and long memory α2, which
corresponds to the period from 64 to 1024 beats, were used.
The VRA is used to study the time dependence of a series, that is, in the study of
stationarity35. The recurrence graph makes it possible to visualize the behavior of
trajectories in the phase space and, in addition, to show the times in which a state of a
dynamic system is repeated, besides these factors can be confirmed regarding the quantitative
analysis of this, wich presents such indices: Mean, SD, PerRec, PerDet, PerLam, TrapTim,
Ratio.
The evaluation of the symbolic analysis is based on the quantification of the information
carried in a time series, in the transformation of the previously selected iRRs into integers
from zero to six, from which sequences of 3 symbols (symbolic patterns) are constructed. For
this, all possible patterns will be grouped according to the number and type of variations
between the symbols, shown subsequently. The patterns were (1) patterns, without variation
(0V), three identical symbols; (2) patterns with a variation (1V), that is, two subsequent
symbols that are the same and a different one; (3) patterns with two similar variations (2LV)
that is, the three symbols form a ramp; (4) patterns with two different variations (2ULV),
that is, the three symbols form a peak or a valley.
