Variáveis psicológicas e percepção do estado de saúde em indivíduos submetidos a ressincronização cardíaca

A insuficiência cardíaca afecta cerca de 261 mil pessoas em Portugal constituindo um problema de saúde pública. Pretendemos avaliar aspectos associados à recuperação do estado de saúde nesta síndrome, em particular a esperança, o afecto e a felicidade. Recorremos a um estudo longitudinal com 128 indivíduos sintomáticos com má fracção de ejecção do ventrículo esquerdo. Utilizámos um questionário para caracterizar os aspectos sóciodemográficos, clínicos e funcionais, o Kansas City Cardiomiopathy Questionnaire (KCCQ) para avaliar a qualidade de vida, a Subjective Hapiness Scale (SHS) para a felicidade, a HOPE Scale (HOPE) para a esperança e a Positive And Negative Afect Schedule (PANAS) para o afecto. Os questionários de caracterização sócio-demográfica, clínica e funcional, KCCQ e o SHS foram aplicados em três momentos: no internamento, prévio à instituição de terapêutica médica na sua totalidade e ao terceiro e sexto mês após a intervenção médica, na consulta externa. A maioria dos participantes eram homens em classe III da classificação da New York Heart Association com etiologia isquémica. No internamento e antes da terapêutica médica, observámos que a esperança, a felicidade e o afecto se relacionaram com a qualidade de vida, a felicidade e o afecto positivo com a esperança. No período avaliado foram submetidos a: terapia de ressincronização cardíaca (n=52), cardioversor-desfibrilhador implantável (n=44), cirurgia valvular com revascularização do miocárdio (n=14), optimização terapêutica farmacológica (n=10), transplante cardíaco (n=8). Foram significativos os resultados da qualidade de vida, da classificação da New York Heart Association, do exercício físico, da fracção de ejecção do ventrículo esquerdo e das arritmias cardíacas (estrasístoles e taquicardias ventriculares). A felicidade foi preditora da qualidade de vida e da funcionalidade. O afecto negativo foi preditor da satisfação com a insuficiência cardíaca. Concluímos da importância das variáveis positivas a par dos procedimentos médicos no tratamento das pessoas com insuficiência cardíaca. ABSTRACT - Heart failure affects about 261 000 people in Portugal constituting a public health problem. We intend to evaluate aspects of the health recovery in this syndrome, in particular hope, affection and happiness. We used a longitudinal study with 128 symptomatic patients with poor ejection fraction of left ventricle. We used a questionnaire to characterize the socio-demographic, clinical and functional aspects, the Kansas City Cardiomiopathy Questionnaire (KCCQ) to assess the quality of life, the Subjective Happiness Scale (SHS) for happiness, the HOPE Scale (HOPE) for hope and the Positive And Negative Affect Schedule (PANAS) for affection. The questionnaires of sociodemographic, clinical and functional KCCQ and SHS were applied on three occasions: on admission, prior to the execution of medical therapy in its totality and in the third and sixth months after medical intervention in the outpatient. Most of the participants were men in Class III New York Heart Association classification with ischemic etiology. At admission and before medical therapy, we observed that the hope, happiness and affection were related to the quality of life, happiness and positive affect with hope. Over the studied period were submitted to: cardiac resynchronization therapy (n=52), implantable cardioverter-defibrillator (n=44), valvular surgery with coronary artery bypass graft surgery (n=14), optimizing drug therapy (n=10), heart transplant (n=8). The significant results were the quality of life, the New York Heart Association classification, the exercise, the ejection fraction and left ventricular cardiac arrhythmias (ventricular tachycardia and estrasistoles). Happiness was a predictor of quality of life and functionality. The negative affect was a predictor of satisfaction with heart failure. We concluded that the positive variables and the medical procedures were important in treating people with heart failure.

Propriedades psicométricas da versão portuguesa do Kansas City Cardiomyopathy Questionnaire na miocardiopatia dilatada com insuficiência cardíaca congestiva

Vários estudos demonstraram que os doentes com insuficiência cardíaca congestiva (ICC) têm um compromisso da qualidade de vida relacionada com a saúde (QVRS), tendo esta, nos últimos anos, vindo a tornar-se um endpoint primário quando se analisa o impacto do tratamento de situações crónicas como a ICC. Objectivos: Avaliar as propriedades psicométricas da versão portuguesa de um novo instrumento específico para medir a QVRS na ICC em doentes hospitalizados: o Kansas City Cardiomyopathy Questionnaire (KCCQ). População e Métodos: O KCCQ foi aplicado a uma amostra consecutiva de 193 doentes internados por ICC. Destes, 105 repetiram esta avaliação 3 meses após admissão hospitalar, não havendo eventos ocorridos durante este período de tempo. A idade era 64,4± 12,4 anos (entre 21 e 88), com 72,5% a pertencer ao sexo masculino, sendo a ICC de etiologia isquémica em 42%. Resultados: Esta versão do KCCQ foi sujeita a validação estatística semelhante à americana com a avaliação da fidelidade e validade. A fidelidade foi avaliada pela consistência interna dos domínios e dos somatórios, apresentando valores Alpha de Cronbach idênticos nos vários domínios e somatórios ( =0,50 a =0,94). A validade foi analisada pela convergência, pela sensibilidade às diferenças entre grupos e pela sensibilidade à alteração da condição clínica. Avaliou-se a validade convergente de todos os domínios relacionados com funcionalidade, pela relação verificada entre estes e uma medida de funcionalidade, a classificação da New York Heart Association (NYHA), tendo-se verificado correlações significativas (p<0,01), como medida para avaliar a funcionalidade em doentes com ICC. Efectuou-se uma análise de variância entre o domínio limitação física, os somatórios e as classes da NYHA, tendo-se encontrado diferenças estatisticamente significativas (F=23,4; F=36,4; F=37,4; p=0,0001), na capacidade de descriminação da gravidade da condição clínica. Foi realizada uma segunda avaliação em 105 doentes na consulta do 3º mês após a intervenção clínica, tendo-se observado alterações significativas nas médias dos domínios avaliados entre o internamento e a consulta (diferenças de 14,9 a 30,6 numa escala de 0-100), indicando que os domínios avaliados são sensíveis à mudança da condição clínica. A correlação interdimensões da qualidade de vida que compõe este instrumento é moderada, sugerindo dimensões independentes, apoiando a sua estrutura multifactorial e a adequabilidade desta medida para a sua avaliação. Conclusão: O KCCQ é um instrumento válido, sensível à mudança e específico para medir a QVRS numa população portuguesa com miocardiopatia dilatada e ICC. ABSTRACT - Several studies have shown that patients with congestive heart failure (CHF) have a compromised health-related quality of life (HRQL), and this, in recent years, has become a primary endpoint when considering the impact of treatment of chronic conditions such as CHF. Objectives: To evaluate the psychometric properties of the Portuguese version of a new specific instrument to measure HRQL in patients hospitalized for CHF: the Kansas City Cardiomyopathy Questionnaire (KCCQ). Methods: The KCCQ was applied to a sample of 193 consecutive patients hospitalized for CHF. Of these, 105 repeated the assessment 3 months after admission, with no events during this period. Mean age was 64.4±12.4 years (21-88), and 72.5% were 72.5% male. CHF was of ischemic etiology in 42% of cases. Results: This version of the KCCQ was subjected to statistical validation, with assessment of reliability and validity, similar to the American version. Reliability was assessed by the internal consistency of the domains and summary scores, which showed similar values of Cronbach alpha (0.50-0.94). Validity was assessed by convergence, sensitivity to differences between groups and sensitivity to changes in clinical condition. We evaluated the convergent validity of all domains related to functionality, through the relationship between them and a measure of functionality, the New York Heart Association (NYHA) classification. Significant correlations were found (p<0.01) for this measure of functionality in patients with CHF. Analysis of variance between the physical limitation domain, the summary scores and NYHA class was performed and statistically significant differences were found (F=23.4; F=36.4; F=37.4, p=0.0001) in the ability to discriminate severity of clinical condition. A second evaluation was performed on 105 patients at the 3-month follow-up outpatient appointment, and significant changes were observed in the mean scores of the domains assessed between hospital admission and the clinic appointment (differences from 14.9 to 30.6 on a scale of 0-100), indicating that the domains assessed are sensitive to changes in clinical condition. The correlation between dimensions of quality of life in the KCCQ is moderate, suggesting that the dimensions are independent, supporting the multifactorial nature of HRQL and the suitability of this measure for its evaluation. Conclusion: The KCCQ is a valid instrument, sensitive to change and a specific measure of HRQL in a population with dilated cardiomyopathy and CHF.

Comparative evaluation of underlying causes of death processed by the Automated Classification of Medical Entities and the Underlying Cause of Death Selection Systems

INTRODUCTION: The correct identification of the underlying cause of death and its precise assignment to a code from the International Classification of Diseases are important issues to achieve accurate and universally comparable mortality statistics These factors, among other ones, led to the development of computer software programs in order to automatically identify the underlying cause of death. OBJECTIVE: This work was conceived to compare the underlying causes of death processed respectively by the Automated Classification of Medical Entities (ACME) and the "Sistema de Seleção de Causa Básica de Morte" (SCB) programs. MATERIAL AND METHOD: The comparative evaluation of the underlying causes of death processed respectively by ACME and SCB systems was performed using the input data file for the ACME system that included deaths which occurred in the State of S. Paulo from June to December 1993, totalling 129,104 records of the corresponding death certificates. The differences between underlying causes selected by ACME and SCB systems verified in the month of June, when considered as SCB errors, were used to correct and improve SCB processing logic and its decision tables. RESULTS: The processing of the underlying causes of death by the ACME and SCB systems resulted in 3,278 differences, that were analysed and ascribed to lack of answer to dialogue boxes during processing, to deaths due to human immunodeficiency virus [HIV] disease for which there was no specific provision in any of the systems, to coding and/or keying errors and to actual problems. The detailed analysis of these latter disclosed that the majority of the underlying causes of death processed by the SCB system were correct and that different interpretations were given to the mortality coding rules by each system, that some particular problems could not be explained with the available documentation and that a smaller proportion of problems were identified as SCB errors. CONCLUSION: These results, disclosing a very low and insignificant number of actual problems, guarantees the use of the version of the SCB system for the Ninth Revision of the International Classification of Diseases and assures the continuity of the work which is being undertaken for the Tenth Revision version.

Towards an efficient and robust foot classification from pedobarographic images

O documento em anexo encontra-se na versão post-print (versão corrigida pelo editor).

Integrated vehicle classification system

This paper presents an integrated system for vehicle classification. This system aims to classify vehicles using different approaches: 1) based on the height of the first axle and_the number of axles; 2) based on volumetric measurements and; 3) based on features extracted from the captured image of the vehicle. The system uses a laser sensor for measurements and a set of image analysis algorithms to compute some visual features. By combining different classification methods, it is shown that the system improves its accuracy and robustness, enabling its usage in more difficult environments satisfying the proposed requirements established by the Portuguese motorway contractor BRISA.

Short-term Feature Space and Music Genre Classification

In music genre classification, most approaches rely on statistical characteristics of low-level features computed on short audio frames. In these methods, it is implicitly considered that frames carry equally relevant information loads and that either individual frames, or distributions thereof, somehow capture the specificities of each genre. In this paper we study the representation space defined by short-term audio features with respect to class boundaries, and compare different processing techniques to partition this space. These partitions are evaluated in terms of accuracy on two genre classification tasks, with several types of classifiers. Experiments show that a randomized and unsupervised partition of the space, used in conjunction with a Markov Model classifier lead to accuracies comparable to the state of the art. We also show that unsupervised partitions of the space tend to create less hubs.

Data mining techniques to support the classification of MV electricity customers

This paper describes a methodology that was developed for the classification of Medium Voltage (MV) electricity customers. Starting from a sample of data bases, resulting from a monitoring campaign, Data Mining (DM) techniques are used in order to discover a set of a MV consumer typical load profile and, therefore, to extract knowledge regarding to the electric energy consumption patterns. In first stage, it was applied several hierarchical clustering algorithms and compared the clustering performance among them using adequacy measures. In second stage, a classification model was developed in order to allow classifying new consumers in one of the obtained clusters that had resulted from the previously process. Finally, the interpretation of the discovered knowledge are presented and discussed.

Demand response programs definition supported by clustering and classification techniques

The growing importance and influence of new resources connected to the power systems has caused many changes in their operation. Environmental policies and several well know advantages have been made renewable based energy resources largely disseminated. These resources, including Distributed Generation (DG), are being connected to lower voltage levels where Demand Response (DR) must be considered too. These changes increase the complexity of the system operation due to both new operational constraints and amounts of data to be processed. Virtual Power Players (VPP) are entities able to manage these resources. Addressing these issues, this paper proposes a methodology to support VPP actions when these act as a Curtailment Service Provider (CSP) that provides DR capacity to a DR program declared by the Independent System Operator (ISO) or by the VPP itself. The amount of DR capacity that the CSP can assure is determined using data mining techniques applied to a database which is obtained for a large set of operation scenarios. The paper includes a case study based on 27,000 scenarios considering a diversity of distributed resources in a 33 bus distribution network.

Automatic vehicle detection and classification

This paper presents a proposal for an automatic vehicle detection and classification (AVDC) system. The proposed AVDC should classify vehicles accordingly to the Portuguese legislation (vehicle height over the first axel and number of axels), and should also support profile based classification. The AVDC should also fulfill the needs of the Portuguese motorway operator, Brisa. For the classification based on the profile we propose:he use of Eigenprofiles, a technique based on Principal Components Analysis. The system should also support multi-lane free flow for future integration in this kind of environments.

Classification and staging of chronic liver disease from multimodal data

Chronic liver disease (CLD) is most of the time an asymptomatic, progressive, and ultimately potentially fatal disease. In this study, an automatic hierarchical procedure to stage CLD using ultrasound images, laboratory tests, and clinical records are described. The first stage of the proposed method, called clinical based classifier (CBC), discriminates healthy from pathologic conditions. When nonhealthy conditions are detected, the method refines the results in three exclusive pathologies in a hierarchical basis: 1) chronic hepatitis; 2) compensated cirrhosis; and 3) decompensated cirrhosis. The features used as well as the classifiers (Bayes, Parzen, support vector machine, and k-nearest neighbor) are optimally selected for each stage. A large multimodal feature database was specifically built for this study containing 30 chronic hepatitis cases, 34 compensated cirrhosis cases, and 36 decompensated cirrhosis cases, all validated after histopathologic analysis by liver biopsy. The CBC classification scheme outperformed the nonhierachical one against all scheme, achieving an overall accuracy of 98.67% for the normal detector, 87.45% for the chronic hepatitis detector, and 95.71% for the cirrhosis detector.

Data mining framework for fatty liver disease classification in ultrasound: a hybrid feature extraction paradigm

PURPOSE: Fatty liver disease (FLD) is an increasing prevalent disease that can be reversed if detected early. Ultrasound is the safest and ubiquitous method for identifying FLD. Since expert sonographers are required to accurately interpret the liver ultrasound images, lack of the same will result in interobserver variability. For more objective interpretation, high accuracy, and quick second opinions, computer aided diagnostic (CAD) techniques may be exploited. The purpose of this work is to develop one such CAD technique for accurate classification of normal livers and abnormal livers affected by FLD. METHODS: In this paper, the authors present a CAD technique (called Symtosis) that uses a novel combination of significant features based on the texture, wavelet transform, and higher order spectra of the liver ultrasound images in various supervised learning-based classifiers in order to determine parameters that classify normal and FLD-affected abnormal livers. RESULTS: On evaluating the proposed technique on a database of 58 abnormal and 42 normal liver ultrasound images, the authors were able to achieve a high classification accuracy of 93.3% using the decision tree classifier. CONCLUSIONS: This high accuracy added to the completely automated classification procedure makes the authors' proposed technique highly suitable for clinical deployment and usage.

The usefulness of ultrasound in the classification of chronic liver disease

Chronic Liver Disease is a progressive, most of the time asymptomatic, and potentially fatal disease. In this paper, a semi-automatic procedure to stage this disease is proposed based on ultrasound liver images, clinical and laboratorial data. In the core of the algorithm two classifiers are used: a k nearest neighbor and a Support Vector Machine, with different kernels. The classifiers were trained with the proposed multi-modal feature set and the results obtained were compared with the laboratorial and clinical feature set. The results showed that using ultrasound based features, in association with laboratorial and clinical features, improve the classification accuracy. The support vector machine, polynomial kernel, outperformed the others classifiers in every class studied. For the Normal class we achieved 100% accuracy, for the chronic hepatitis with cirrhosis 73.08%, for compensated cirrhosis 59.26% and for decompensated cirrhosis 91.67%.

Chronic liver disease staging classification based on ultrasound, clinical and laboratorial data

In this work the identification and diagnosis of various stages of chronic liver disease is addressed. The classification results of a support vector machine, a decision tree and a k-nearest neighbor classifier are compared. Ultrasound image intensity and textural features are jointly used with clinical and laboratorial data in the staging process. The classifiers training is performed by using a population of 97 patients at six different stages of chronic liver disease and a leave-one-out cross-validation strategy. The best results are obtained using the support vector machine with a radial-basis kernel, with 73.20% of overall accuracy. The good performance of the method is a promising indicator that it can be used, in a non invasive way, to provide reliable information about the chronic liver disease staging.

Comparing the content of instruments assessing environmental factors using the International Classification of Functioning, Disability and Health

Purpose: To describe and compare the content of instruments that assess environmental factors using the International Classification of Functioning, Disability and Health (ICF). Methods: A systematic search of PubMed, CINAHL and PEDro databases was conducted using a pre-determined search strategy. The identified instruments were screened independently by two investigators, and meaningful concepts were linked to the most precise ICF category according to published linking rules. Results: Six instruments were included, containing 526 meaningful concepts. Instruments had between 20% and 98% of items linked to categories in Chapter 1. The highest percentage of items from one instrument linked to categories in Chapters 2–5 varied between 9% and 50%. The presence or absence of environmental factors in a specific context is assessed in 3 instruments, while the other 3 assess the intensity of the impact of environmental factors. Discussion: Instruments differ in their content, type of assessment, and have several items linked to the same ICF category. Most instruments primarily assess products and technology (Chapter 1), highlighting the need to deepen the discussion on the theory that supports the measurement of environmental factors. This discussion should be thorough and lead to the development of methodologies and new tools that capture the underlying concepts of the ICF.

Comorbidity adjustment index for the international classification of diseases, 10

OBJECTIVE: To develop a Charlson-like comorbidity index based on clinical conditions and weights of the original Charlson comorbidity index. METHODS: Clinical conditions and weights were adapted from the International Classification of Diseases, 10th revision and applied to a single hospital admission diagnosis. The study included 3,733 patients over 18 years of age who were admitted to a public general hospital in the city of Rio de Janeiro, southeast Brazil, between Jan 2001 and Jan 2003. The index distribution was analyzed by gender, type of admission, blood transfusion, intensive care unit admission, age and length of hospital stay. Two logistic regression models were developed to predict in-hospital mortality including: a) the aforementioned variables and the risk-adjustment index (full model); and b) the risk-adjustment index and patient's age (reduced model). RESULTS: Of all patients analyzed, 22.3% had risk scores >1, and their mortality rate was 4.5% (66.0% of them had scores >1). Except for gender and type of admission, all variables were retained in the logistic regression. The models including the developed risk index had an area under the receiver operating characteristic curve of 0.86 (full model), and 0.76 (reduced model). Each unit increase in the risk score was associated with nearly 50% increase in the odds of in-hospital death. CONCLUSIONS: The risk index developed was able to effectively discriminate the odds of in-hospital death which can be useful when limited information is available from hospital databases.