A comparative analysis of preprocessing techniques of cardiac event series for the study of heart rhythm variability using simulated signals

In the present study, using noise-free simulated signals, we performed a comparative examination of several preprocessing techniques that are used to transform the cardiac event series in a regularly sampled time series, appropriate for spectral analysis of heart rhythm variability (HRV). First, a group of noise-free simulated point event series, which represents a time series of heartbeats, was generated by an integral pulse frequency modulation model. In order to evaluate the performance of the preprocessing methods, the differences between the spectra of the preprocessed simulated signals and the true spectrum (spectrum of the model input modulating signals) were surveyed by visual analysis and by contrasting merit indices. It is desired that estimated spectra match the true spectrum as close as possible, showing a minimum of harmonic components and other artifacts. The merit indices proposed to quantify these mismatches were the leakage rate, defined as a measure of leakage components (located outside some narrow windows centered at frequencies of model input modulating signals) with respect to the whole spectral components, and the numbers of leakage components with amplitudes greater than 1%, 5% and 10% of the total spectral components. Our data, obtained from a noise-free simulation, indicate that the utilization of heart rate values instead of heart period values in the derivation of signals representative of heart rhythm results in more accurate spectra. Furthermore, our data support the efficiency of the widely used preprocessing technique based on the convolution of inverse interval function values with a rectangular window, and suggest the preprocessing technique based on a cubic polynomial interpolation of inverse interval function values and succeeding spectral analysis as another efficient and fast method for the analysis of HRV signals

The availability of full match sibling donors and feasibility of allogeneic bone marrow transplantation in Brazil

The feasibility of allogeneic bone marrow transplantation (alloBMT) in a developing country has not yet been demonstrated. Many adverse factors including social and economic limitations may reduce the overall results of this complex and expensive procedure. Our objective was to characterize the most important clinical, social and economic features of candidates for transplantation and their potential donors as well as the influence of these factors on overall survival in a retrospective and exploratory analysis at a university hospital. From July 1993 to July 2001, candidates for BMT were referred to the Bone Marrow Transplantation Unit by Hematology and Oncology Centers from several regions of Brazil. A total of 1138 patients were referred to us as candidates for alloBMT. Median age was 25 years (range: 2 months-60 years), 684 (60.1%) were males and 454 (39.9%) were females. The clinical indications were severe aplastic anemia and hematological malignancies. From the total of 1138 patients, 923 had HLA-typing; 497/923 (53.8%) candidates had full match donors; 352/1138 (30.8%) were eligible for alloBMT. Only 235 of 352 (66.7%) were transplanted. Schooling was 1st to 8th grade for 123/235 (52.3%); monthly family income ranged from US$60 (7%) to more than US$400 (36%). Overall survival for patients with chronic myeloid leukemia, severe aplastic anemia and acute myeloid leukemia was 58, 60 and 30%, respectively. Thus, overall survival rates for the most frequent hematological diseases were similar to those reported in the International Registry, except for acute myeloid leukemia. This descriptive and exploratory analysis suggests the feasibility of alloBMT in a developing country like Brazil.

Time motion analysis of football (soccer) referees during official matches in relation to the type of fluid consumed

The aim of the present study was to determine the effect of volume and composition of fluid replacement on the physical performance of male football referees. Ten referees were evaluated during three official matches. In one match the participants were asked to consume mineral water ad libitum, and in the others they consumed a pre-determined volume of mineral water or a carbohydrate electrolyte solution (6.4% carbohydrate and 22 mM Na+) equivalent to 1% of their baseline body mass (half before the match and half during the interval). Total water loss, sweat rate and match physiological performance were measured. When rehydrated ad libitum (pre-match and at half time) participants lost 1.97 ± 0.18% of their pre-match body mass (2.14 ± 0.19 L). This parameter was significantly reduced when they consumed a pre-determined volume of fluid. Sweat rate was significantly reduced when the referees ingested a pre-determined volume of a carbohydrate electrolyte solution, 0.72 ± 0.12 vs 1.16 ± 0.11 L/h ad libitum. The high percentage (74.1%) of movements at low speed (walking, jogging) observed when they ingested fluid ad libitum was significantly reduced to 71% with mineral water and to 69.9% with carbohydrate solution. An increase in percent movement expended in backward running was observed when they consumed a pre-determined volume of carbohydrate solution, 7.7 ± 0.5 vs 5.5 ± 0.5% ad libitum. The improved hydration status achieved with the carbohydrate electrolyte solution reduced the length of time spent in activities at low-speed movements and increased the time spent in activities demanding high-energy expenditure.

Early detection of metabolic and energy disorders by thermal time series stochastic complexity analysis

Maintenance of thermal homeostasis in rats fed a high-fat diet (HFD) is associated with changes in their thermal balance. The thermodynamic relationship between heat dissipation and energy storage is altered by the ingestion of high-energy diet content. Observation of thermal registers of core temperature behavior, in humans and rodents, permits identification of some characteristics of time series, such as autoreference and stationarity that fit adequately to a stochastic analysis. To identify this change, we used, for the first time, a stochastic autoregressive model, the concepts of which match those associated with physiological systems involved and applied in male HFD rats compared with their appropriate standard food intake age-matched male controls (n=7 per group). By analyzing a recorded temperature time series, we were able to identify when thermal homeostasis would be affected by a new diet. The autoregressive time series model (AR model) was used to predict the occurrence of thermal homeostasis, and this model proved to be very effective in distinguishing such a physiological disorder. Thus, we infer from the results of our study that maximum entropy distribution as a means for stochastic characterization of temperature time series registers may be established as an important and early tool to aid in the diagnosis and prevention of metabolic diseases due to their ability to detect small variations in thermal profile.