Background Parkinson’s disease (PD) is a neurological disease that affects the motor system. The associated motor symptoms are muscle rigidity or stiffness, bradykinesia, tremors, and gait disturbances. The correct diagnosis, especially in the initial stages, is fundamental to the life quality of the individual with PD. However, the methods used for diagnosis of PD are still based on subjective criteria. As a result, the objective of this study is the proposal of a method for the discrimination of individuals with PD (in the initial stages of the disease) from healthy groups, based on the inertial sensor recordings. Methods A total of 27 participants were selected, 15 individuals previously diagnosed with PD and 12 healthy individuals. The data collection was performed using inertial sensors (positioned on the back of the hand and on the back of the forearm). Different numbers of features were used to compare the values of sensitivity, specificity, precision, and accuracy of the classifiers. For group classification, 4 classifiers were used and compared, those being [Random Forest (RF), Support Vector Machine (SVM), K-Nearest Neighbor (KNN), and Naive Bayes (NB)]. Results When all individuals with PD were analyzed, the best performance for sensitivity and accuracy (0.875 and 0.800, respectively) was found in the SVM classifier, fed with 20% and 10% of the features, respectively, while the best performance for specificity and precision (0.933 and 0.917, respectively) was associated with the RF classifier fed with 20% of all the features. When only individuals with PD and score 1 on the Hoehn and Yahr scale (HY) were analyzed, the best performances for sensitivity, precision and accuracy (0.933, 0.778 and 0.848, respectively) were from the SVM classifier, fed with 40% of all features, and the best result for precision (0.800) was connected to the NB classifier, fed with 20% of all features. Conclusion Through an analysis of all individuals in this study with PD, the best classifier for the detection of PD (sensitivity) was the SVM fed with 20% of the features and the best classifier for ruling out PD (specificity) was the RF classifier fed with 20% of the features. When analyzing individuals with PD and score HY = 1, the SVM classifier was superior across the sensitivity, precision, and accuracy, and the NB classifier was superior in the specificity. The obtained result indicates that objective methods can be applied to help in the evaluation of PD.

Introdução As perspectivas de que o HIV/AIDS possa tornar os indivíduos mais vulneráveis à SARS-CoV-2 e apresentar COVID-19 grave é grande. Indivíduos com contagens baixas de CD4 e em uso de TARV, manifestam sintomas graves de COVID-19. Estudos sugerem que a imunossupressão e as baixas contagens de células CD4 protegem da explosão de citocinas em pacientes com COVID-19. Se faz necessário mensurar a propagação e os resultados do COVID-19. Objetivo Elaborar uma revisão sistemática e meta-análise da literatura avaliativa do risco de infecção por SARS-CoV-2 entre Pessoas Vivendo com HIV/Aids e mensurar a morbimortalidade do COVID-19 desse grupo. Foram incluídos estudos envolvendo indivíduos com e sem HIV testados para SARS-CoV-2, independentemente da idade, país ou terapia antirretroviral. Metodologia O estudo é uma revisão Sistemáticas e Meta-análises pesquisada no DATASUS, UNAIDS de 3 de fevereiro de 2020 a 20 de junho de 2021. Estudos de suscetibilidade e óbito por COVID-19 em não infectados por HIV foram incluídos para análise. A pesquisa abrange publicações em outros idiomas para melhor analise. Foram elegíveis ensaios clínicos randomizados, coorte observacional (prospectivo ou retrospectivo), e estudos de caso-controle. Excluímos relatos de caso. Resultados:: 18 estudos foram incluídos e analisados, A idade média dos pacientes incluídos no estudo foi de 45 anos. Em média, 58,0% dos participantes eram do sexo masculino. As comorbidades mais comuns na população HIV positiva foram hipertensão, diabetes, DPOC e DRC. No geral, a contagem média de CD4 foi de 470 células/μL. Mais de 85% das PVHA usavam TARV, e mais de 70% dos pacientes HIV-positivos tinham supressão viral. O HIV foi associado significativamente a um risco maior de infecção por SARS-CoV-2 (RR 1,16). A variação entre os estudos foi (I 2  = 83, p  = 0,0004). A prevalência de HIV em pacientes com COVID-19 foi 0,32%. Discussão/Conclusão É afirmativo que pessoas HIV positivo têm mais risco de infecção por SARS-CoV-2 e de mortalidade por COVID-19 do que pessoas HIV negativo. Ademais, estimativas concluem que a prevalência de HIV em pacientes com COVID-19 e a mortalidade são globalmente plurais. O HIV permanece como importante fator de risco para a contaminação da infecção por SARS-CoV-2 e está associado a maior mortalidade por COVID-19. Portanto, PVHA deve priorizar a proteção. Mais estudos são necessários para avaliar os resultados de sobreviventes do COVID-19.

Introduction: Human tremor is a clinical disorder characterized by involuntary movement resulting from contractions of antagonistic muscles. The physiological tremor is associated with natural processes and the pathological tremor associated with several factors, such as neurological dysfunctions. One possible cause of the disease is Parkinson's disease (DP). Among the clinical signs associated with DP, the present study focused on tremor. For an understanding of the tremor, there are subjective and objective methods. Subjective use clinical scales of severity, such as the Unified Parkinson's Disease Rating Scale (UPDRS). However, this scale depends on the experience and knowledge of the evaluator. Thus, studies suggest objective methods. These use inertial sensors, such as accelerometer, magnetometer and gyroscope, as they measure the activities of the evaluated member in real time. Objective: Use of inertial sensors for the characterization and classification of hand tremor in individuals with DP and correlation with the UPDRS, motor examination-part III. Methodology: This study was supported by the Ethics Committee on Research in Human Beings of the Federal University of Uberlândia (CEP: 270,782 and CEP: 2,001,535). Twenty-two subjects with DP participated in the study, allocated to only one group. The limb most affected by the tremor was submitted to activity. The protocol was: (i) reading and signing the informed consent form; completing an identification form, and a questionnaire assessing the severity of the disease, UPDRS; (ii) collection of activities: fist at rest and in mild extension maintained (0o), without and with load of 92 g and 184 g. After the collection, the results were generated and the analysed items were: (i) characteristics of the tremor signal by amplitude and frequency; (ii) different variables of the experimental protocol; (iii) different inertial sensors; (iv) at different times of the protocol. Statistical analysis was used to estimate the mean and standard deviation, and the Spearman's test, for the correlation. The analyses were performed using software R. p <0.05. Results: the equipment collected data objectively, characterized, and classified the tremor signs. There was a strong correlation between the characteristics of the signals between experimental variables and different protocols. The load used (92 and 184 g) did not have a significant effect. The characteristics, median of RMS and wE4 of the signal were those that presented a higher mean of correlation for the analysis. The accelerometer and gyroscope sensors presented a strong correlation for all the experimental variables. The magnetometer had a weak correlation. The two sensors (1 and 2) presented a strong correlation, thus, as their coordinates (x, y, z). Conclusion: The biomedical device, characterized and classified the cuff tremor in PD. Strong correlation between the characteristics of the signal, with the sensors, accelerometer and gyroscope, and with the UPDRS scale (motor examination, part III) was found. Stron...