Tradução e validação para o português do Medication Regimen Complexity Index

FUNDAMENTO: A complexidade da farmacoterapia consiste de múltiplas características do regime prescrito, incluindo o número de diferentes medicações no esquema, o número de unidades de dosagem por dose, o número total de doses por dia e os cuidados na administração dos medicamentos. O Medication Regimen Complexity Index (MRCI) é um instrumento específico, validado e utilizado para medir a complexidade da farmacoterapia, desenvolvido originalmente em língua inglesa. OBJETIVO: Tradução transcultural e validação desse instrumento para o português do Brasil. MÉTODOS: Foi desenvolvido um estudo transversal envolvendo 95 pacientes com diabete do tipo 2 utilizando múltiplas medicações. O processo de validação teve início pela tradução, retrotradução e pré-teste do instrumento, gerando uma versão adaptada chamada Índice de Complexidade da Farmacoterapia (ICFT). Em seguida foram analisados parâmetros psicométricos, incluindo validade convergente, validade divergente, confiabilidade entre avaliadores e teste-reteste. RESULTADOS: A complexidade da farmacoterapia medida pelo ICFT obteve média de 15,7 pontos (desvio padrão = 8,36). O ICFT mostrou correlação significativa com o número de medicamentos em uso (r = 0,86; p < 0,001) e a idade dos pacientes (r = 0,28; p = 0,005). A confiabilidade entre avaliadores obteve correlação intraclasse igual a 0,99 (p < 0,001) e a confiabilidade teste-reteste obteve correlação de 0,997 (p < 0,001). CONCLUSÃO: Os resultados demonstraram que o ICFT apresenta bom desempenho de validade e confiabilidade, podendo ser utilizado como ferramenta útil na prática clínica e em pesquisas envolvendo análise da complexidade da terapia.

Assessing the performance of macroinvertebrate metrics in the Challhuaco-Ñireco System (Northern Patagonia, Argentina)

ABSTRACT Seven sites were examined in the Challhuaco-Ñireco system, located in the reserve of the Nahuel Huapi National Park, however part of the catchment is urbanized, being San Carlos de Bariloche (150,000 inhabitants) placed in the lower part of the basin. Physico-chemical variables were measured and benthic macroinvertebrates were collected during three consecutive years at seven sites from the headwater to the river outlet. Sites near the source of the river were characterised by Plecoptera, Ephemeroptera, Trichoptera and Diptera, whereas sites close to the river mouth were dominated by Diptera, Oligochaeta and Mollusca. Regarding functional feeding groups, collector-gatherers were dominant at all sites and this pattern was consistent among years. Ordination Analysis (RDA) revealed that species assemblages distribution responded to the climatic and topographic gradient (temperature and elevation), but also were associated with variables related to human impact (conductivity, nitrate and phosphate contents). Species assemblages at headwaters were mostly represented by sensitive insects, whereas tolerant taxa such as Tubificidae, Lumbriculidae, Chironomidae and crustacean Aegla sp. were dominant at urbanised sites. Regarding macroinvertebrate metrics employed, total richness, EPT taxa, Shannon diversity index and Biotic Monitoring Patagonian Stream index resulted fairly consistent and evidenced different levels of disturbances at the stream, meaning that this measures are suitable for evaluation of the status of Patagonian mountain streams.

Detection of the B"-GWGR variant in the southernmost region of Brazil: unveiling the complexity of the human immunodeficiency virus-1 subtype B epidemic

Typical human immunodeficiency virus-1 subtype B (HIV-1B) sequences present a GPGR signature at the tip of the variable region 3 (V3) loop; however, unusual motifs harbouring a GWGR signature have also been isolated. Although epidemiological studies have detected this variant in approximately 17-50% of the total infections in Brazil, the prevalence of B"-GWGR in the southernmost region of Brazil is not yet clear. This study aimed to investigate the C2-V3 molecular diversity of the HIV-1B epidemic in southernmost Brazil. HIV-1 seropositive patients were ana-lysed at two distinct time points in the state of Rio Grande do Sul (RS98 and RS08) and at one time point in the state of Santa Catarina (SC08). Phylogenetic analysis classified 46 individuals in the RS98 group as HIV-1B and their molecular signatures were as follows: 26% B"-GWGR, 54% B-GPGR and 20% other motifs. In the RS08 group, HIV-1B was present in 32 samples: 22% B"-GWGR, 59% B-GPGR and 19% other motifs. In the SC08 group, 32 HIV-1B samples were found: 28% B"-GWGR, 59% B-GPGR and 13% other motifs. No association could be established between the HIV-1B V3 signatures and exposure categories in the HIV-1B epidemic in RS. However, B-GPGR seemed to be related to heterosexual individuals in the SC08 group. Our results suggest that the established B"-GWGR epidemics in both cities have similar patterns, which is likely due to their geographical proximity and cultural relationship.

Understanding the complexity in low dimensional systems

Complex System is any system that presents involved behavior, and is hard to be modeled by using the reductionist approach of successive subdivision, searching for ''elementary'' constituents. Nature provides us with plenty of examples of these systems, in fields as diverse as biology, chemistry, geology, physics, and fluid mechanics, and engineering. What happens, in general, is that for these systems we have a situation where a large number of both attracting and unstable chaotic sets coexist. As a result, we can have a rich and varied dynamical behavior, where many competing behaviors coexist. In this work, we present and discuss simple mechanical systems that are nice paradigms of Complex System, when they are subjected to random external noise. We argue that systems with few degrees of freedom can present the same complex behavior under quite general conditions.

Heart rate recovery after exercise: relations to heart rate variability and complexity

Physical exercise is associated with parasympathetic withdrawal and increased sympathetic activity resulting in heart rate increase. The rate of post-exercise cardiodeceleration is used as an index of cardiac vagal reactivation. Analysis of heart rate variability (HRV) and complexity can provide useful information about autonomic control of the cardiovascular system. The aim of the present study was to ascertain the association between heart rate decrease after exercise and HRV parameters. Heart rate was monitored in 17 healthy male subjects (mean age: 20 years) during the pre-exercise phase (25 min supine, 5 min standing), during exercise (8 min of the step test with an ascending frequency corresponding to 70% of individual maximal power output) and during the recovery phase (30 min supine). HRV analysis in the time and frequency domains and evaluation of a newly developed complexity measure - sample entropy - were performed on selected segments of heart rate time series. During recovery, heart rate decreased gradually but did not attain pre-exercise values within 30 min after exercise. On the other hand, HRV gradually increased, but did not regain rest values during the study period. Heart rate complexity was slightly reduced after exercise and attained rest values after 30-min recovery. The rate of cardiodeceleration did not correlate with pre-exercise HRV parameters, but positively correlated with HRV measures and sample entropy obtained from the early phases of recovery. In conclusion, the cardiodeceleration rate is independent of HRV measures during the rest period but it is related to early post-exercise recovery HRV measures, confirming a parasympathetic contribution to this phase.

Learning about brain physiology and complexity from the study of the epilepsies

The brain is a complex system, which produces emergent properties such as those associated with activity-dependent plasticity in processes of learning and memory. Therefore, understanding the integrated structures and functions of the brain is well beyond the scope of either superficial or extremely reductionistic approaches. Although a combination of zoom-in and zoom-out strategies is desirable when the brain is studied, constructing the appropriate interfaces to connect all levels of analysis is one of the most difficult challenges of contemporary neuroscience. Is it possible to build appropriate models of brain function and dysfunctions with computational tools? Among the best-known brain dysfunctions, epilepsies are neurological syndromes that reach a variety of networks, from widespread anatomical brain circuits to local molecular environments. One logical question would be: are those complex brain networks always producing maladaptive emergent properties compatible with epileptogenic substrates? The present review will deal with this question and will try to answer it by illustrating several points from the literature and from our laboratory data, with examples at the behavioral, electrophysiological, cellular and molecular levels. We conclude that, because the brain is a complex system compatible with the production of emergent properties, including plasticity, its functions should be approached using an integrated view. Concepts such as brain networks, graphics theory, neuroinformatics, and e-neuroscience are discussed as new transdisciplinary approaches dealing with the continuous growth of information about brain physiology and its dysfunctions. The epilepsies are discussed as neurobiological models of complex systems displaying maladaptive plasticity.

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.