People With Patellofemoral Pain Have Bilateral Deficits in Physical Performance Regardless of Pain Laterality.

CONTEXT: People with patellofemoral pain (PFP) may have lower performance during the forward step-down and single-leg hop with their painful (unilateral complaints) or most painful (bilateral complaints) limb when compared to pain-free controls. Yet, no study has investigated the appropriateness of using the pain-free/less painful limb as a reference standard in clinical practice or whether deficits might be present depending on the laterality of pain. OBJECTIVE: To compare performance scores and proportion of side-to-side limb symmetry during the forward step-down and single-leg hop tests among people with unilateral and bilateral PFP, and pain-free controls. DESIGN: Cross-sectional study. SETTING: Laboratory. PATIENTS OR OTHER PARTICIPANTS: Fifty-two young adults (18-35 years old) with unilateral PFP, 72 with bilateral PFP, and 76 controls. MAIN OUTCOME MEASURE(S): Group-by-limb interactions on the performance during the step- down (repetitions) and hop test (distance [cm] normalized by the limb length) were investigated using a repeated-measures analysis of covariance controlling for sex. Pairwise comparisons were interpreted using effect sizes. A Chi-square test was used to compare the proportion of symmetry/asymmetry (cutoff point of ≥ 90% for symmetries indices) across groups and tests. RESULTS: Main effects for groups (small-to-medium effects) but not limbs indicated lower performance of both limbs of individuals with unilateral and bilateral PFP compared to controls during forward step-downs and single-leg hop tests. No significant differences for the proportion of symmetry/asymmetry were identified across groups (p ≥ 0.05), which further suggests an impaired physical performance of the contralateral limb. CONCLUSIONS: Our results indicate bilateral deficits in the physical performance of people with unilateral and bilateral PFP when compared to pain-free controls during the forward step-down and single-leg hop tests. Limb symmetries indices greater than 90% should be interpreted with caution, as they may overstate the physical performance by not assuming bilateral deficits.

Group- and sex-related differences in psychological and pain processing factors in people with and without patellofemoral pain: correlation with clinical outcomes.

BACKGROUND: People with patellofemoral pain (PFP) exhibit impaired psychological and pain processing factors (i.e., kinesiophobia, pain catastrophizing and pressure pain thresholds [PPTs]). However, it remains unclear whether these factors have different presentations in women and men with PFP, as well as whether their correlation with clinical outcomes differ according to sex. The aims of this study were to: (1) compare psychological and pain processing factors between women and men with and without patellofemoral pain (PFP); (2) investigate their correlation with clinical outcomes in people with PFP. METHODS: This cross-sectional study included 65 women and 38 men with PFP, 30 women and 30 men without PFP. The psychological and pain processing factors were assessed with the Tampa Scale of Kinesiophobia, Pain Catastrophizing Scale, and PPTs of shoulder and patella measured with an algometer. Clinical outcomes assessed were self-reported pain (Visual Analogue Scale), function (Anterior Knee Pain Scale), physical activity level (Baecke's Questionnaire), and physical performance (Single Leg Hop Test). Generalized linear models (GzLM) and effect sizes [Cohen's d] were calculated for group comparisons and Spearman's correlation coefficients were calculated to investigate correlations between outcomes. RESULTS: Women and men with PFP had higher kinesiophobia (d = .82, p = .001; d = .80, p = .003), pain catastrophizing (d = .84, p < .001; d = 1.27, p < .001), and lower patella PPTs (d = -.85, p = .001; d = -.60, p = .033) than women and men without PFP, respectively. Women with PFP had lower shoulder and patella PPTs than men with PFP (d = -1.24, p < .001; d = -.95, p < .001), but there were no sex differences in those with PFP for psychological factors (p > .05). For women with PFP, kinesiophobia and pain catastrophizing had moderate positive correlations with self-reported pain (rho = .44 and .53, p < .001) and moderate negative correlations with function (rho = -.55 and -.58, p < .001), respectively. For men with PFP, only pain catastrophizing had moderate positive correlations with self-reported pain (rho = .42, p = .009) and moderate negative correlations with function (rho = -.43, p = .007). CONCLUSIONS: Psychological and pain processing factors differ between people with and without PFP and between sexes, respectively. Also, correlations between psychological and pain processing factors with clinical outcomes differ among women and men with PFP. These findings should be considered when assessing and managing people with PFP.

Face-to-face Assessment of COGTEL in Adolescents: Test-Retest Reliability and Association with School Grades / Aplicação Presencial do COGTEL em Adolescentes: a Fiabilidade Teste-Reteste e a Associação com as Notas Escolares

Abstract The Cognitive Telephone Screening Instrument (COGTEL) has shown to be a brief, reliable, and valid instrument to assess cognitive functioning in adults in face-to-face procedures as well as over the phone. So far, no psychometric evaluation exists on its use in adolescents. The present study set out to evaluate the psychometric properties of the face-to-face application of the COGTEL in adolescents in the school context and to analyse the association with school grades. We assessed cognitive performance using COGTEL in face-to-face assessments of 170 adolescents, with retests after 6 months for test-retest reliability. Predictive validity was assessed using school grades. Test-retest reliability for the COGTEL was good (ICC = .77; p < .001). The partial correlation controlling for age between COGTEL and school grades was medium and positive (r = .40; p < .001). School grades alone explained 42% and 36% of the variance in the COGTEL total score in elementary and secondary students, respectively. The present study suggests that COGTEL is a reliable and valid instrument to assess cognitive functioning in adolescents, with the advantage of feasibility in multiple contexts.

Resumo O Instrumento de Rastreio Cognitivo por Telefone (COGTEL) tem demostrado ser um instrumento fiável, válido e breve para avaliar o funcionamento cognitivo em adultos, quer por telefone, quer de forma presencial. Até à data, não foram estudadas as suas características psicométricas para uso em adolescentes. O presente estudo teve por objetivo avaliar as propriedades psicométricas do COGTEL em adolescentes no contexto escolar, através da aplicação presencial, e analisar a associação dos scores com as notas escolares. O desempenho cognitivo foi avaliado em 170 adolescentes, usando o COGTEL em entrevistas presenciais, com um reteste após 6 meses para avaliar a fiabilidade teste-reteste. A validade preditiva foi avaliada com base nas notas escolares. A fiabilidade teste-reteste para o COGTEL foi boa (ICC = 0.77; p < .001). As correlações parciais, controlando pelo efeito da idade, entre o score total do COGTEL e as notas escolares foram moderadas e positivas (r = .40; p < .001). As notas escolares, individualmente, explicaram 42% e 36% da variância total no score total do COGTEL, em alunos do ensino básico e secundário, respetivamente. O presente estudo sugere que o COGTEL é um instrumento fiável e válido para avaliar o funcionamento cognitivo em adolescentes, com a vantagem de ser aplicável em múltiplos contextos.

Paraconsistents artificial neural networks applied to the study of mutational patterns of the F subtype of the viral strains of HIV-1 to antiretroviral therapy.

The high variability of HIV-1 as well as the lack of efficient repair mechanisms during the stages of viral replication, contribute to the rapid emergence of HIV-1 strains resistant to antiretroviral drugs. The selective pressure exerted by the drug leads to fixation of mutations capable of imparting varying degrees of resistance. The presence of these mutations is one of the most important factors in the failure of therapeutic response to medications. Thus, it is of critical to understand the resistance patterns and mechanisms associated with them, allowing the choice of an appropriate therapeutic scheme, which considers the frequency, and other characteristics of mutations. Utilizing Paraconsistents Artificial Neural Networks, seated in Paraconsistent Annotated Logic Et which has the capability of measuring uncertainties and inconsistencies, we have achieved levels of agreement above 90% when compared to the methodology proposed with the current methodology used to classify HIV-1 subtypes. The results demonstrate that Paraconsistents Artificial Neural Networks can serve as a promising tool of analysis.

Index of alpha/theta ratio of the electroencephalogram: a new marker for Alzheimer's disease.

OBJECTIVE: We evaluated quantitative EEG measures to determine a screening index to discriminate Alzheimer's disease (AD) patients from normal individuals. METHODS: Two groups of individuals older than 50 years, comprising a control group of 57 normal volunteers and a study group of 50 patients with probable AD, were compared. EEG recordings were obtained from subjects in a wake state with eyes closed at rest for 30 min. Logistic regression analysis was conducted. RESULTS: Spectral potentials of the alpha and theta bands were computed for all electrodes and the alpha/theta ratio calculated. Logistic regression of alpha/theta of the mean potential of the C3 and O1 electrodes was carried out. A formula was calculated to aid the diagnosis of AD yielding 76.4% sensitivity and 84.6% specificity for AD with an area under the ROC curve of 0.92. CONCLUSION: Logistic regression of alpha/theta of the spectrum of the mean potential of EEG represents a good marker discriminating AD patients from normal controls.

Alzheimer's disease qEEG: spectral analysis versus coherence. which is the best measurement? / EEGq na doença de Alzheimer: análise espectral versus coerência. O que é melhor?

There is evidence in electroencephalography that alpha, theta and delta band oscillations reflect cognitive and memory performances and that quantitative techniques can improve the electroencephalogram (EEG) sensitivity. This paper presents the results of comparative analysis of qEEG variables as reliable markers for Alzheimer's disease (AD). We compared the sensitivity and specificity between spectral analysis (spectA) and coherence (Coh) within the same group of AD patients. SpectA and Coh were calculated from EEGs of 40 patients with mild to moderate AD and 40 healthy elderly controls. The peak of spectA was smaller in the AD group than in controls. AD group showed predominance of slow spectA in theta and delta bands and a significant reduction of inter-hemispheric Coh for occipital alpha 2 and beta 1 and for frontal delta sub-band. ROC curve supported that alpha band spectA was more sensitive than coherence to differentiate controls from AD.

Há evidências de que as oscilações das bandas teta, alfa e delta no eletroencefalograma podem refletir diferenças na cognição e memória; a sensibilidade deste método diagnóstico pode ser melhorada por técnicas de quantificação. Comparamos a sensibilidade e especificidade entre a análise espectral (spectA) e coerência (Coh) dentro do mesmo grupo de pacientes com doença de Alzheimer (DA) e contra um grupo controle. SpectA e Coh foram calculadas a partir de EEGs de 40 pacientes com DA leve a moderada e 40 idosos saudáveis. O pico do espectro foi menor no grupo DA que nos controles. O grupo DA também apresentou um espectro mais lento nas bandas teta e delta e menor coerência inter-hemisférica para as sub-bandas alfa 2 e beta 1 posterior e delta frontal. A curva ROC suporta que a análise espectral da banda alfa foi mais sensível que a coerência para diferenciar controles de DA.

Alzheimer's disease qEEG: spectral analysis versus coherence. Which is the best measurement?

There is evidence in electroencephalography that alpha, theta and delta band oscillations reflect cognitive and memory performances and that quantitative techniques can improve the electroencephalogram (EEG) sensitivity. This paper presents the results of comparative analysis of qEEG variables as reliable markers for Alzheimer's disease (AD). We compared the sensitivity and specificity between spectral analysis (spectA) and coherence (Coh) within the same group of AD patients. SpectA and Coh were calculated from EEGs of 40 patients with mild to moderate AD and 40 healthy elderly controls. The peak of spectA was smaller in the AD group than in controls. AD group showed predominance of slow spectA in theta and delta bands and a significant reduction of inter-hemispheric Coh for occipital alpha 2 and beta 1 and for frontal delta sub-band. ROC curve supported that alpha band spectA was more sensitive than coherence to differentiate controls from AD.

Application of paraconsistent artificial neural networks as a method of aid in the diagnosis of Alzheimer disease.

The visual analysis of EEG has shown useful in helping the diagnosis of Alzheimer disease (AD) when the diagnosis remains uncertain, being used in some clinical protocols. However, such analysis is subject to the inherent equipment imprecision, patient movement, electrical records, and physician interpretation of the visual analysis variation. The Artificial Neural Network (ANN) could be a helpful tool, appropriate to address problems such as prediction and pattern recognition. In this work, it has use a new class of ANN, the Paraconsistent Artificial Neural Network (PANN), which is capable of handling uncertain, inconsistent, and paracomplete information, for recognizing predetermined patterns of EEG and to assess its value as a possible auxiliary method for AD diagnosis. Thirty three patients with Alzheimer's disease and 34 controls patients of EEG records were obtained during relaxed wakefulness. It was considered as normal patient pattern, the background EEG activity between 8.0 and 12.0 Hz (with an average frequency of 10 Hz), allowing a range of 0.5 Hz. The PANN was able to recognize waves that belonging to their respective bands of clinical use (theta, delta, alpha, and beta), leading to an agreement with the clinical diagnosis at 82% of sensitivity and at 61% of specificity. Supported with these results, the PANN could be a promising tool to manipulate EEG analysis, bearing in mind the following considerations: the growing interest of specialists in EEG analysis visual and the ability of the PANN to deal directly imprecise, inconsistent and paracomplete data, providing an interesting quantitative and qualitative analysis.

Paraconsistent artificial neural networks and Alzheimer disease: a preliminary study.

EEG visual analysis has proved useful in aiding AD diagnosis, being indicated in some clinical protocols. However, such analysis is subject to the inherent imprecision of equipment, patient movements, electric registers, and individual variability of physician visual analysis. OBJECTIVES: To employ the Paraconsistent Artificial Neural Network to ascertain how to determine the degree of certainty of probable dementia diagnosis. METHODS: Ten EEG records from patients with probable Alzheimer disease and ten controls were obtained during the awake state at rest. An EEG background between 8 Hz and 12 Hz was considered the normal pattern for patients, allowing a variance of 0.5 Hz. RESULTS: The PANN was capable of accurately recognizing waves belonging to Alpha band with favorable evidence of 0.30 and contrary evidence of 0.19, while for waves not belonging to the Alpha pattern, an average favorable evidence of 0.19 and contrary evidence of 0.32 was obtained, indicating that PANN was efficient in recognizing Alpha waves in 80% of the cases evaluated in this study. Artificial Neural Networks - ANN - are well suited to tackle problems such as prediction and pattern recognition. The aim of this work was to recognize predetermined EEG patterns by using a new class of ANN, namely the Paraconsistent Artificial Neural Network - PANN, which is capable of handling uncertain, inconsistent and paracomplete information. An architecture is presented to serve as an auxiliary method in diagnosing Alzheimer disease. CONCLUSIONS: We believe the results show PANN to be a promising tool to handle EEG analysis, bearing in mind two considerations: the growing interest of experts in visual analysis of EEG, and the ability of PANN to deal directly with imprecise, inconsistent, and paracomplete data, thereby providing a valuable quantitative analysis.

A análise visual de EEG tem se mostrado útil na ajuda de diagnóstico de DA, sendo indicado em alguns protocolos clínicos. Porém, tal análise está sujeita à imprecisão inerente de equipamentos, movimentos do paciente, registros elétricos e variação individual da análise visual do médico. OBJETIVOS: Utilizar a Rede Neural Artificial Paraconsistente para saber como determinar um grau de certeza no diagnóstico da doença de Alzheimer provável. MÉTODOS: Dez pacientes com doença de Alzheimer provável e 10 controles foram submetidos ao registro de exames de EEG durante a vigília em repouso. Considerou-se como padrão normal de um paciente, a atividade de base entre 8,0 Hz a 12,0 Hz, permitindo uma variação de 0.5 Hz. RESULTADOS: A RNAP foi capaz de reconhecer ondas que pertencem à banda Alfa como banda Alfa com evidência favorável de 0.30 e evidência contrária de 0.19, enquanto ondas não pertencentes ao padrão Alfa, foi obtido uma evidência favorável média de 0.19 e evidência contrária de 0.32, mostrando que a RNAP foi eficiente para reconhecer ondas Alfa, o que leva a uma concordância com o diagnóstico clínico de 80%. CONCLUSÕES: RNAP pode ser ferramenta promissora para manipular análise de EEG, tendo em mente ambas considerações: o interesse crescente de especialistas em análise visual de EEG e a capacidade da RNAP tratar diretamente dados imprecisos, inconsistentes e paracompletos, fornecendo uma interessante análise quantitativa.