789 resultados para Predictive-validity
Resumo:
A pilot study consisting of a parent questionnaire, four APD tests and an acceptability questionnaire were presented to normal hearing and cognitively developing children between the ages of 8-12 years. Responses to a standard and modified response format of the APD tests were obtained over two test sessions. Results indicated that the modified response formats of the four APD tests were acceptable, fairly reliable and three out of the four APD tests were valid.
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Objectives: To evaluate risk factors for recurrence of carcinoma of the uterine cervix among women who had undergone radical hysterectomy without pelvic lymph node metastasis, while taking into consideration not only the classical histopathological factors but also sociodemographic, clinical and treatment-related factors. Study design: This was an exploratory analysis on 233 women with carcinoma of the uterine cervix (stages IB and IIA) who were treated by means of radical hysterectomy and pelvic lymphadenectomy, with free surgical margins and without lymph node metastases on conventional histopathological examination. Women with histologically normal lymph nodes but with micrometastases in the immunohistochemical analysis (AE1/AE3) were excluded. Disease-free survival for sociodemographic, clinical and histopathological variables was calculated using the Kaplan-Meier method. The Cox proportional hazards model was used to identify the independent risk factors for recurrence. Results: Twenty-seven recurrences were recorded (11.6%), of which 18 were pelvic, four were distant, four were pelvic + distant and one was of unknown location. The five-year disease-free survival rate among the study population was 88.4%. The independent risk factors for recurrence in the multivariate analysis were: postmenopausal status (HR 14.1; 95% CI: 3.7-53.6; P < 0.001), absence of or slight inflammatory reaction (HR 7.9; 95% CI: 1.7-36.5; P = 0.008) and invasion of the deepest third of the cervix (FIR 6.1; 95% CI: 1.3-29.1; P = 0.021). Postoperative radiotherapy was identified as a protective factor against recurrence (HR 0.02; 95% CI: 0.001-0.25; P = 0.003). Conclusion: Postmenopausal status is a possible independent risk factor for recurrence even when adjusted for classical prognostic factors (such as tumour size, depth of turnout invasion, capillary embolisation) and treatment-related factors (period of treatment and postoperative radiotherapy status). (C) 2009 Elsevier Ireland Ltd. All rights reserved.
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The aim of this study was to develop and validate the Disordered Eating Attitude Scale to measure disordered eating attitudes, defined as abnormal beliefs, thoughts, feelings, behaviors, and relationship regarding food. Exploratory factor analysis was performed and internal consistency assessed in a sample of female university students (N=196). Convergent validity was acceptable based on statistically significant correlations with the Eating Attitude Test-26 and Restraint Scale. Known-groups validity was determined by comparing the student sample`s mean scores against scores of an eating disorder group (N=51). The Disordered Eating Attitude Scale comprises 25 questions and five subscales explaining 54.3% of total variance. The total scores differentiated student, bulimia, and anorexia groups. The scale should prove useful for evaluating eating attitudes in various population groups and eating disordered patients.
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In 2004 the National Household Survey (Pesquisa Nacional par Amostras de Domicilios - PNAD) estimated the prevalence of food and nutrition insecurity in Brazil. However, PNAD data cannot be disaggregated at the municipal level. The objective of this study was to build a statistical model to predict severe food insecurity for Brazilian municipalities based on the PNAD dataset. Exclusion criteria were: incomplete food security data (19.30%); informants younger than 18 years old (0.07%); collective households (0.05%); households headed by indigenous persons (0.19%). The modeling was carried out in three stages, beginning with the selection of variables related to food insecurity using univariate logistic regression. The variables chosen to construct the municipal estimates were selected from those included in PNAD as well as the 2000 Census. Multivariate logistic regression was then initiated, removing the non-significant variables with odds ratios adjusted by multiple logistic regression. The Wald Test was applied to check the significance of the coefficients in the logistic equation. The final model included the variables: per capita income; years of schooling; race and gender of the household head; urban or rural residence; access to public water supply; presence of children; total number of household inhabitants and state of residence. The adequacy of the model was tested using the Hosmer-Lemeshow test (p=0.561) and ROC curve (area=0.823). Tests indicated that the model has strong predictive power and can be used to determine household food insecurity in Brazilian municipalities, suggesting that similar predictive models may be useful tools in other Latin American countries.
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This study investigated the orienting of visual attention in rats using a 3-hole nose-poke task analogous to Posner, Information processing in cognition: the Loyola Symposium, Erlbaum, Hillsdale, (1980) covert attention task for humans. The effects of non-predictive (50% valid and 50% invalid) and predictive (80% valid and 20% invalid) peripheral visual cues on reaction times and response accuracy to a target stimulus, using Stimuli-Onset Asynchronies (SOAs) varying between 200 and 1,200 ms, were investigated. The results showed shorter reaction times in valid trials relative to invalid trials for both subjects trained in the non-predictive and predictive conditions, particularly when the SOAs were 200 and 400 ms. However, the magnitude of this validity effect was significantly greater for subjects exposed to predictive cues, when the SOA was 800 ms. Subjects exposed to invalid predictive cues exhibited an increase in omission errors relative to subjects exposed to invalid non-predictive cues. In contrast, valid cues reduced the proportion of omission errors for subjects trained in the predictive condition relative to subjects trained in the non-predictive condition. These results are congruent with those usually reported for humans and indicate that, in addition to the exogenous capture of attention promoted by both predictive and non-predictive peripheral cues, rats exposed to predictive cues engaged an additional slower process equivalent to human`s endogenous orienting of attention. To our knowledge, this is the first demonstration of an endogenous-like process of covert orienting of visual attention in rats.
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The Prospective and Retrospective Memory Questionnaire (PRMQ) has been shown to have acceptable reliability and factorial, predictive, and concurrent validity. However, the PRMQ has never been administered to a probability sample survey representative of all ages in adulthood, nor have previous studies controlled for factors that are known to influence metamemory, such as affective status. Here, the PRMQ was applied in a survey adopting a probabilistic three-stage cluster sample representative of the population of Sao Paulo, Brazil, according to gender, age (20-80 years), and economic status (n=1042). After excluding participants who had conditions that impair memory (depression, anxiety, used psychotropics, and/or had neurological/psychiatric disorders), in the remaining 664 individuals we (a) used confirmatory factor analyses to test competing models of the latent structure of the PRMQ, and (b) studied effects of gender, age, schooling, and economic status on prospective and retrospective memory complaints. The model with the best fit confirmed the same tripartite structure (general memory factor and two orthogonal prospective and retrospective memory factors) previously reported. Women complained more of general memory slips, especially those in the first 5 years after menopause, and there were more complaints of prospective than retrospective memory, except in participants with lower family income.
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Predictive performance evaluation is a fundamental issue in design, development, and deployment of classification systems. As predictive performance evaluation is a multidimensional problem, single scalar summaries such as error rate, although quite convenient due to its simplicity, can seldom evaluate all the aspects that a complete and reliable evaluation must consider. Due to this, various graphical performance evaluation methods are increasingly drawing the attention of machine learning, data mining, and pattern recognition communities. The main advantage of these types of methods resides in their ability to depict the trade-offs between evaluation aspects in a multidimensional space rather than reducing these aspects to an arbitrarily chosen (and often biased) single scalar measure. Furthermore, to appropriately select a suitable graphical method for a given task, it is crucial to identify its strengths and weaknesses. This paper surveys various graphical methods often used for predictive performance evaluation. By presenting these methods in the same framework, we hope this paper may shed some light on deciding which methods are more suitable to use in different situations.
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The study of pharmacokinetic properties (PK) is of great importance in drug discovery and development. In the present work, PK/DB (a new freely available database for PK) was designed with the aim of creating robust databases for pharmacokinetic studies and in silico absorption, distribution, metabolism and excretion (ADME) prediction. Comprehensive, web-based and easy to access, PK/DB manages 1203 compounds which represent 2973 pharmacokinetic measurements, including five models for in silico ADME prediction (human intestinal absorption, human oral bioavailability, plasma protein binding, bloodbrain barrier and water solubility).
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Canalizing genes possess such broad regulatory power, and their action sweeps across a such a wide swath of processes that the full set of affected genes are not highly correlated under normal conditions. When not active, the controlling gene will not be predictable to any significant degree by its subject genes, either alone or in groups, since their behavior will be highly varied relative to the inactive controlling gene. When the controlling gene is active, its behavior is not well predicted by any one of its targets, but can be very well predicted by groups of genes under its control. To investigate this question, we introduce in this paper the concept of intrinsically multivariate predictive (IMP) genes, and present a mathematical study of IMP in the context of binary genes with respect to the coefficient of determination (CoD), which measures the predictive power of a set of genes with respect to a target gene. A set of predictor genes is said to be IMP for a target gene if all properly contained subsets of the predictor set are bad predictors of the target but the full predictor set predicts the target with great accuracy. We show that logic of prediction, predictive power, covariance between predictors, and the entropy of the joint probability distribution of the predictors jointly affect the appearance of IMP genes. In particular, we show that high-predictive power, small covariance among predictors, a large entropy of the joint probability distribution of predictors, and certain logics, such as XOR in the 2-predictor case, are factors that favor the appearance of IMP. The IMP concept is applied to characterize the behavior of the gene DUSP1, which exhibits control over a central, process-integrating signaling pathway, thereby providing preliminary evidence that IMP can be used as a criterion for discovery of canalizing genes.
Predictive models for chronic renal disease using decision trees, naïve bayes and case-based methods
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Data mining can be used in healthcare industry to “mine” clinical data to discover hidden information for intelligent and affective decision making. Discovery of hidden patterns and relationships often goes intact, yet advanced data mining techniques can be helpful as remedy to this scenario. This thesis mainly deals with Intelligent Prediction of Chronic Renal Disease (IPCRD). Data covers blood, urine test, and external symptoms applied to predict chronic renal disease. Data from the database is initially transformed to Weka (3.6) and Chi-Square method is used for features section. After normalizing data, three classifiers were applied and efficiency of output is evaluated. Mainly, three classifiers are analyzed: Decision Tree, Naïve Bayes, K-Nearest Neighbour algorithm. Results show that each technique has its unique strength in realizing the objectives of the defined mining goals. Efficiency of Decision Tree and KNN was almost same but Naïve Bayes proved a comparative edge over others. Further sensitivity and specificity tests are used as statistical measures to examine the performance of a binary classification. Sensitivity (also called recall rate in some fields) measures the proportion of actual positives which are correctly identified while Specificity measures the proportion of negatives which are correctly identified. CRISP-DM methodology is applied to build the mining models. It consists of six major phases: business understanding, data understanding, data preparation, modeling, evaluation, and deployment.
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The aim of this study was to investigate if a telemetry test battery can be used to measure effects of Parkinson’s disease (PD) treatment intervention and disease progression in patients with fluctuations. Sixty-five patients diagnosed with advanced PD were recruited in an open longitudinal 36-month study; 35 treated with levodopa-carbidopa intestinal gel (LCIG) and 30 were candidates for switching from oral PD treatment to LCIG. They utilized a test battery, consisting of self-assessments of symptoms and fine motor tests (tapping and spiral drawings), four times per day in their homes during week-long test periods. The repeated measurements were summarized into an overall test score (OTS) to represent the global condition of the patient during a test period. Clinical assessments included ratings on Unified PD Rating Scale (UPDRS) and 39-item PD Questionnaire (PDQ-39) scales. In LCIG-naïve patients, mean OTS compared to baseline was significantly improved from the first test period on LCIG treatment until month 24. In LCIG-non-naïve patients, there were no significant changes in mean OTS until month 36. The OTS correlated adequately with total UPDRS (rho = 0.59) and total PDQ-39 (0.59). Responsiveness measured as effect size was 0.696 and 0.536 for OTS and UPDRS respectively. The trends of the test scores were similar to the trends of clinical rating scores but dropout rate was high. Correlations between OTS and clinical rating scales were adequate indicating that the test battery contains important elements of the information of well-established scales. The responsiveness and reproducibility were better for OTS than for total UPDRS.
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Background: The Swedish Maternal Health Care Register (MHCR) is a national quality register that has been collecting pregnancy, delivery, and postpartum data since 1999. A substantial revision of the MHCR resulted in a Web-based version of the register in 2010. Although MHCR provides data for health care services and research, the validity of the MHCR data has not been evaluated. This study investigated degree of coverage and internal validity of specific variables in the MHCR and identified possible systematic errors. Methods: This cross-sectional observational study compared pregnancy and delivery data in medical records with corresponding data in the MHCR. The medical record was considered the gold standard. The medical records from nine Swedish hospitals were selected for data extraction. This study compared data from 878 women registered in both medical records and in the MHCR. To evaluate the quality of the initial data extraction, a second data extraction of 150 medical records was performed. Statistical analyses were performed for degree of coverage, agreement and correlation of data, and sensitivity and specificity. Results: Degree of coverage of specified variables in the MHCR varied from 90.0% to 100%. Identical information in both medical records and the MHCR ranged from 71.4% to 99.7%. For more than half of the investigated variables, 95% or more of the information was identical. Sensitivity and specificity were analysed for binary variables. Probable systematic errors were identified for two variables. Conclusions: When comparing data from medical records and data registered in the MHCR, most variables in the MHCR demonstrated good to very good degree of coverage, agreement, and internal validity. Hence, data from the MHCR may be regarded as reliable for research as well as for evaluating, planning, and decision-making with respect to Swedish maternal health care services.
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Model Predictive Control (MPC) is a control method that solves in real time an optimal control problem over a finite horizon. The finiteness of the horizon is both the reason of MPC's success and its main limitation. In operational water resources management, MPC has been in fact successfully employed for controlling systems with a relatively short memory, such as canals, where the horizon length is not an issue. For reservoirs, which have generally a longer memory, MPC applications are presently limited to short term management only. Short term reservoir management can be effectively used to deal with fast process, such as floods, but it is not capable of looking sufficiently ahead to handle long term issues, such as drought. To overcome this limitation, we propose an Infinite Horizon MPC (IH-MPC) solution that is particularly suitable for reservoir management. We propose to structure the input signal by use of orthogonal basis functions, therefore reducing the optimization argument to a finite number of variables, and making the control problem solvable in a reasonable time. We applied this solution for the management of the Manantali Reservoir. Manantali is a yearly reservoir located in Mali, on the Senegal river, affecting water systems of Mali, Senegal, and Mauritania. The long term horizon offered by IH-MPC is necessary to deal with the strongly seasonal climate of the region.
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Objetivos: Desenvolver e validar instrumento que auxilie o pediatra a determinar a probabilidade de ocorrência do abuso sexual em crianças. Métodos: Estudo de caso-controle com 201 crianças que consultaram em ambulatórios de pediatria e locais de referência para vítimas de abuso sexual, entre março e novembro de 2004: grupo caso (com suspeita ou revelação de abuso sexual) e grupo controle (sem suspeita de abuso sexual). Aplicou-se, junto aos responsáveis, um questionário com 18 itens e cinco opções de respostas segundo a escala Likert, abordando comportamento, sintomas físicos e emocionais apresentados pelas crianças. Excluíram-se nove crianças sem controle esfincteriano e um item respondido por poucas pessoas. A validade e consistência interna dos itens foram avaliadas com obtenção de coeficientes de correlação (Pearson, Spearman e Goodman-Kruskal), coeficiente α de Cronbach e cálculo da área da curva ROC. Calculou-se, após, a razão de verossimilhança (RV) e os valores preditivo positivos (VPP) para os cinco itens do questionário que apresentaram os melhores desempenhos. Resultados: Obteve-se um questionário composto pelos cinco itens que melhor discriminaram crianças com e sem abuso sexual em dois contextos. Cada criança recebeu um escore resultante da soma das respostas com pesos de 0 a 4 (amplitude de 0 a 20), o qual, através do teorema de Bayes (RV), indicou sua probabilidade pós-teste (VPP) de abuso sexual. Conclusões: O instrumento proposto é útil por ser de fácil aplicação, auxiliando o pediatra na identificação de crianças vítimas de abuso sexual. Ele fornecerá, conforme o escore obtido, a probabilidade (VPP) de abuso sexual, orientando na conduta de cuidado à criança.