PubMed Health⌕ Search

Biomedical subjects

A P Rocha

Publications and source records attributed to A P Rocha.

7 recordsLinked to original sources
PubMed1997

[Is autonomic control of the heart rate at rest altered by detraining? A study of heart rate variability in professional soccer players after the pretraining period and after the preparatory period for competitions].

The aim of this study was to assess the influence of detraining and training on the autonomic control of heart rate (HR), using time and frequency (spectral analysis) domain components of heart rate variability. Sixteen professional football players (26.7 +/- 3.8 years; 74.9 +/- 4.1 kg; 177 +/- 6.3 cm) were analysed at the end of a 1 month holiday (detraining) and after a 6 week training period (training). HR was recorded over 15 minutes with Holter equipment. The athletes rested in a supine position, in a quiet place and all test were performed between 8 and 10 AM. The subjects were requested to refrain from meals or caffeine for 12 hours before testing. In spite of the high intensity of the training period, there was no significant change in results from detraining condition to training condition. These results can have two possible explanations: (i) the high level of cardiovascular capacity in the detraining trial originated by the recreative physical activity that the players underwent during their holidays, and/or (ii) the training period was not long enough to promote any relevant effect on the autonomic control of HR.

Adaptation, Physiological↗
PubMed1996

Heart rate variability in brain death.

The sensitivity and specificity of heart rate variability (HRV) in the corroboration of brain death diagnosis in patients with acute traumatic intracranial lesions was evaluated in 20 patients with clinical criteria of brain death, nine patients in deep coma (Glasgow scale < 7) and 18 normal controls, all age matched. The electrocardiogram was sampled at 650 Hz and several parameters of HRV were calculated, in both time and frequency domains. The HRV parameters were significantly lower in the brain death group compared with the deep coma group. Linear discriminant analysis between brain death and deep coma patients was performed on a data set made of nine randomly selected patients with clinical criteria of brain death and nine patients in deep coma. Cross-validation was performed on the remaining 11 patients with clinical criteria of brain death. All patients in the data set were correctly classified (sensitivity and specificity of 100%). All patients in the cross-validation set were correctly classified (sensitivity of 100%). Further studies are necessary to evaluate the specificity of the method in the independent set of deep coma patients and in the follow-up of comatose and vegetative patients to identify irreversibility of HRV. Nevertheless, these results suggest that HRV analysis constitutes a fully sensitive and specific method for assessing brain death in potential organ donors with acute traumatic lesions of the brain. This fast, quantitative and bedside method seems very promising for the early confirmation of brain death, which is an important factor for the success of transplantation procedures and could have a high predictive value of brain death in comatose patients with brain injuries without fully diagnostic criteria.

Adolescent↗
PubMed1995

[The spectral analysis of heart rate variability. A comparative study between nonparametric and parametric spectral analysis in short series].

OBJECTIVE: to compare parametric (AR) and non parametric (FFT) spectral analysis results obtained in 512 beats series. INTERVENTIONS: 104 healthy subjects with normal physical examination and electrocardiogram were studied. The Ecg was recorded at rest, with controlled breathing at 15 cycles/min., and sampled at 300 Hz. The spectral VLF, LF and HF were calculated with FFT algorithm. For the same series, an auto-regressive analysis (AR) with optimized choice of the order of the model (AIC criterion) have been computed, VLF, LF and HF components were identified by AR spectral decomposition. RESULTS: In both groups, athletes and sedentary, there were no statistically differences between VLF, LF, HF and LF/HF spectral indices computed by the two methods. CONCLUSION: the results suggest that with controlled breathing it does not seems to exist any advantage in the use of AR spectral analysis to compute spectral components of heart rate variability, which is much more laborious that fixed bands non parametric FFT analysis.

Adolescent↗
PubMed1994

Heart rate variability in 24-hour Holter recordings. Comparative study between short- and long-term time- and frequency-domain analyses.

Mean hourly parameters obtained from all beats (long series) were compared with those obtained from a sample of 512 beats extracted each hour (short series) in nine presumably normal subjects. For both the short and long series, the spectral components, very low frequency, (VLF), low frequency (LF), and high frequency (HF), and time-domain indices (such as the Ewing statistic [PNN50] and RR standard deviation [SD-RR]), have been estimated. The spectral components LF and HF, estimated from the short and long series, were not significantly different, whereas significant differences were found between VLF, SD--RR, and PNN50. In both the short and long series, a strong correlation was found between LF and SD-RR and between HF and PNN50. The results suggest that, over a period of 24 hours, hourly LF and HF spectral components can be obtained using a single series of 512 beats every hour, with a great advantage over the evaluation of the mean hourly parameters. This method would be particularly useful in the study of circadian heart rate spectral analysis in Holter recordings with multiple artifacts or ectopic beats, and in general, when analysis of the entire 24-hour series is not feasible.

Adult↗
PubMed1989

Covariance density estimation for autoregressive spectral modelling of point processes.

The use of autoregressive modelling has acquired great importance in time series analysis and in principle it may also be applicable in the spectral analysis of point processes with similar advantages over the nonparametric approach. Most of the methods used for autoregressive spectral analysis require positive semidefinite estimates for the covariance function, while current methods for the estimation of the covariance density function of a point process given a realization over the interval [0, T] do not guarantee a positive semidefinite estimate. This paper discusses methods for the estimation of the covariance density and conditional intensity function of point processes and present alternative computational efficient estimation algorithms leading always to positive semidefinite estimates, therefore adequate for autoregressive spectral analysis. Autoregressive spectral modelling of point processes from Yule-Walker type equations and Levinson recursion combined with the minimum AIC or CAT principle is illustrated with neurobiological data.

Animals↗