14 resultados para cognitive diagnostic model
em Biblioteca Digital da Produção Intelectual da Universidade de São Paulo
Resumo:
Rationale Cannabidiol, the main nonpsychotropic constituent of Cannabis sativa, possesses a large number of pharmacological effects including anticonvulsive, sedative, hypnotic, anxiolytic, antipsychotic, anti-inflammatory, and neuroprotective, as demonstrated in clinical and preclinical studies. Many neurodegenerative disorders involve cognitive deficits, and this has led to interest in whether cannabidiol could be useful in the treatment of memory impairment associated to these diseases. Objectives We used an animal model of cognitive impairment induced by iron overload in order to test the effects of cannabidiol in memory-impaired rats. Methods Rats received vehicle or iron at postnatal days 12-14. At the age of 2 months, they received an acute intraperitoneal injection of vehicle or cannabidiol (5.0 or 10.0 mg/kg) immediately after the training session of the novel object recognition task. In order to investigate the effects of chronic cannabidiol, iron-treated rats received daily intraperitoneal injections of cannabidiol for 14 days. Twenty-four hours after the last injection, they were submitted to object recognition training. Retention tests were performed 24 h after training. Results A single acute injection of cannabidiol at the highest dose was able to recover memory in iron-treated rats. Chronic cannabidiol improved recognition memory in iron-treated rats. Acute or chronic cannabidiol does not affect memory in control rats. Conclusions The present findings provide evidence suggesting the potential use of cannabidiol for the treatment of cognitive decline associated with neurodegenerative disorders. Further studies, including clinical trials, are warranted to determine the usefulness of cannabidiol in humans suffering from neurodegenerative disorders.
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Cognitive dissonance is the stress that comes from holding two conflicting thoughts simultaneously in the mind, usually arising when people are asked to choose between two detrimental or two beneficial options. In view of the well-established role of emotions in decision making, here we investigate whether the conventional structural models used to represent the relationships among basic emotions, such as the Circumplex model of affect, can describe the emotions of cognitive dissonance as well. We presented a questionnaire to 34 anonymous participants, where each question described a decision to be made among two conflicting motivations and asked the participants to rate analogically the pleasantness and the intensity of the experienced emotion. We found that the results were compatible with the predictions of the Circumplex model for basic emotions. (C) 2012 Elsevier Ltd. All rights reserved.
Resumo:
We propose a new general Bayesian latent class model for evaluation of the performance of multiple diagnostic tests in situations in which no gold standard test exists based on a computationally intensive approach. The modeling represents an interesting and suitable alternative to models with complex structures that involve the general case of several conditionally independent diagnostic tests, covariates, and strata with different disease prevalences. The technique of stratifying the population according to different disease prevalence rates does not add further marked complexity to the modeling, but it makes the model more flexible and interpretable. To illustrate the general model proposed, we evaluate the performance of six diagnostic screening tests for Chagas disease considering some epidemiological variables. Serology at the time of donation (negative, positive, inconclusive) was considered as a factor of stratification in the model. The general model with stratification of the population performed better in comparison with its concurrents without stratification. The group formed by the testing laboratory Biomanguinhos FIOCRUZ-kit (c-ELISA and rec-ELISA) is the best option in the confirmation process by presenting false-negative rate of 0.0002% from the serial scheme. We are 100% sure that the donor is healthy when these two tests have negative results and he is chagasic when they have positive results.
Resumo:
Objectives: The aim of this pilot study was to investigate whether patients with social anxiety disorder (SAD) differ from controls in the quality of skill-related behaviors displayed during a speech and in overall behavioral adequacy as perceived by observers and by the patients themselves. Design: A total of 18 SAD patients and 18 controls were screened by a diagnostic interview and took part in a 3-minute speech of their own choosing. For each videotaped speech, observers rated the adequacy of the skill-related behaviors and overall performance adequacy. After the experiment, participants were asked to rate their own overall performance adequacy. Results: The results showed that SAD patients exhibited significantly worse voice intonation and fluency of the speech, however no differences were found in global self-ratings. Moreover, the performance evaluations of the SAD group were consistent with the observers, while the controls evaluated their performance lower than the observers. Conclusions: The results are inconsistent with the cognitive model, because patients with SAD did not underestimate their performance. Compared with spontaneous interactions, the clear rules established for such social situations as speeches may result in less cognitive distortion for SAD patients. (C) 2012 Wiley Periodicals, Inc. J. Clin. Psychol. 68:397-402, 2012.
Resumo:
Although praised for their rationality, humans often make poor decisions, even in simple situations. In the repeated binary choice experiment, an individual has to choose repeatedly between the same two alternatives, where a reward is assigned to one of them with fixed probability. The optimal strategy is to perseverate with choosing the alternative with the best expected return. Whereas many species perseverate, humans tend to match the frequencies of their choices to the frequencies of the alternatives, a sub-optimal strategy known as probability matching. Our goal was to find the primary cognitive constraints under which a set of simple evolutionary rules can lead to such contrasting behaviors. We simulated the evolution of artificial populations, wherein the fitness of each animat (artificial animal) depended on its ability to predict the next element of a sequence made up of a repeating binary string of varying size. When the string was short relative to the animats' neural capacity, they could learn it and correctly predict the next element of the sequence. When it was long, they could not learn it, turning to the next best option: to perseverate. Animats from the last generation then performed the task of predicting the next element of a non-periodical binary sequence. We found that, whereas animats with smaller neural capacity kept perseverating with the best alternative as before, animats with larger neural capacity, which had previously been able to learn the pattern of repeating strings, adopted probability matching, being outperformed by the perseverating animats. Our results demonstrate how the ability to make predictions in an environment endowed with regular patterns may lead to probability matching under less structured conditions. They point to probability matching as a likely by-product of adaptive cognitive strategies that were crucial in human evolution, but may lead to sub-optimal performances in other environments.
Resumo:
The log-Burr XII regression model for grouped survival data is evaluated in the presence of many ties. The methodology for grouped survival data is based on life tables, where the times are grouped in k intervals, and we fit discrete lifetime regression models to the data. The model parameters are estimated by maximum likelihood and jackknife methods. To detect influential observations in the proposed model, diagnostic measures based on case deletion, so-called global influence, and influence measures based on small perturbations in the data or in the model, referred to as local influence, are used. In addition to these measures, the total local influence and influential estimates are also used. We conduct Monte Carlo simulation studies to assess the finite sample behavior of the maximum likelihood estimators of the proposed model for grouped survival. A real data set is analyzed using a regression model for grouped data.
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This article describes the development and evaluation of software that verifies the accuracy of diagnoses made by nursing students. The software was based on a model that uses fuzzy logic concepts, including PERL, the MySQL database for Internet accessibility, and the NANDA-I 2007-2008 classification system. The software was evaluated in terms of its technical quality and usability through specific instruments. The activity proposed in the software involves four stages in which students establish the relationship values between nursing diagnoses, defining characteristics/risk factors and clinical cases. The relationship values determined by students are compared to those of specialists, generating performance scores for the students. In the evaluation, the software demonstrated satisfactory outcomes regarding the technical quality and, according to the students, helped in their learning and may become an educational tool to teach the process of nursing diagnosis.
Resumo:
Studies have shown that platelet APP ratio (representing the percentage of 120-130 kDa to 110 kDa isoforms of the amyloid precursor protein) is reduced in patients with mild cognitive impairment (MCI) and Alzheimer's disease (AD). In the present study, we sought to determine if baseline APP ratio predicts the conversion from MCI to AD dementia after 4 years of longitudinal assessment. Fifty-five older adults with varying degrees of cognitive impairment (34 with MCI and 21 with AD) were assessed at baseline and after 4 years. MCI patients were re-classified according to the conversion status upon follow-up: 25 individuals retained the diagnostic status of MCI and were considered as stable cases (MCI-MCI); conversely, in nine cases the diagnosis of dementia due to AD was ascertained. The APP ratio (APPr) was determined by the Western blot method in samples of platelets collected at baseline. We found a significant reduction of APPr in MCI patients who converted to dementia upon follow-up. These individuals had baseline APPr values similar to those of demented AD patients. The overall accuracy of APPr to identify subjects with MCI who will progress to AD was 0.74 +/- A 0.10, p = 0.05. The cut-off of 1.12 yielded a sensitivity of 75 % and a specificity of 75 %. Platelet APPr may be a surrogate marker of the disease process in AD, with potential implications for the assessment of abnormalities in the APP metabolism in patients with and at risk for dementia. However, diagnostic accuracy was relatively low. Therefore, studies in larger samples are needed to determine whether APPr may warrant its use as a biomarker to support the early diagnosis of AD.
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This paper introduces a skewed log-Birnbaum-Saunders regression model based on the skewed sinh-normal distribution proposed by Leiva et al. [A skewed sinh-normal distribution and its properties and application to air pollution, Comm. Statist. Theory Methods 39 (2010), pp. 426-443]. Some influence methods, such as the local influence and generalized leverage, are presented. Additionally, we derived the normal curvatures of local influence under some perturbation schemes. An empirical application to a real data set is presented in order to illustrate the usefulness of the proposed model.
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Purpose: Dynamic near infrared fluorescence imaging of the urinary tract provides a promising way to diagnose ureteropelvic junction obstruction. Initial studies demonstrated the ability to visualize urine flow and peristalsis in great detail. We analyzed the efficacy of near infrared imaging in evaluating ureteropelvic junction obstruction, renal involvement and the anatomical detail provided compared to conventional imaging modalities. Materials and Methods: Ten swine underwent partial or complete unilateral ureteral obstruction. Groups were survived for the short or the long term. Imaging was performed with mercaptoacetyltriglycine diuretic renogram, magnetic resonance urogram, excretory urogram, ultrasound and near infrared imaging. Scoring systems for ureteropelvic junction obstruction were developed for magnetic resonance urogram and near infrared imaging. Physicians and medical students graded ureteropelvic junction obstruction based on magnetic resonance urogram and near infrared imaging results. Results: Markers of vascular and urinary dynamics were quantitatively consistent among control renal units. The same markers were abnormal in obstructed renal units with significantly different times of renal phase peak, start of pelvic phase and start of renal uptake. Such parameters were consistent with those obtained with mercaptoacetyltriglycine diuretic renography. Near infrared imaging provided live imaging of urinary flow, which was helpful in identifying the area of obstruction for surgical planning. Physicians and medical students categorized the degree of obstruction appropriately for fluorescence imaging and magnetic resonance urogram. Conclusions: Near infrared imaging offers a feasible way to obtain live, dynamic images of urine flow and ureteral peristalsis. Qualitative and quantitative parameters were comparable to those of conventional imaging. Findings support fluorescence imaging as an accurate, easy to use method of diagnosing ureteropelvic junction obstruction.
Resumo:
PURPOSE: Apply the educational software Fuzzy Kitten with undergraduate Brazilian nursing students. METHODS: This software, based on fuzzy logic, generates performance scores that evaluate the ability to identify defining characteristics/risk factors present in clinical cases, relate them with nursing diagnoses, and determine the diagnoses freely or using a decision support model. FINDINGS: There were differences in student performance compared to the year of the course. The time to perform the activity did not present a significant relation to the performance. The students' scores in the diagnoses indicated by the model was superior (p = .01). CONCLUSIONS: The software was able to evaluate the diagnostic accuracy of students. IMPLICATIONS: The software enables an objective evaluation of diagnostic accuracy.
Resumo:
Trichoepithelioma is a benign neoplasm that shares both clinical and histological features with basal cell carcinoma. It is important to distinguish these neoplasms because they require different clinical behavior and therapeutic planning. Many studies have addressed the use of immunohistochemistry to improve the differential diagnosis of these tumors. These studies present conflicting results when addressing the same markers, probably owing to the small number of basaloid tumors that comprised their studies, which generally did not exceed 50 cases. We built a tissue microarray with 162 trichoepithelioma and 328 basal cell carcinoma biopsies and tested a panel of immune markers composed of CD34, CD10, epithelial membrane antigen, Bcl-2, cytokeratins 15 and 20 and D2-40. The results were analyzed using multiple linear and logistic regression models. This analysis revealed a model that could differentiate trichoepithelioma from basal cell carcinoma in 36% of the cases. The panel of immunohistochemical markers required to differentiate between these tumors was composed of CD10, cytokeratin 15, cytokeratin 20 and D2-40. The results obtained in this work were generated from a large number of biopsies and resulted in the confirmation of overlapping epithelial and stromal immunohistochemical profiles from these basaloid tumors. The results also corroborate the point of view that trichoepithelioma and basal cell carcinoma tumors represent two different points in the differentiation of a single cell type. Despite the use of panels of immune markers, histopathological criteria associated with clinical data certainly remain the best guideline for the differential diagnosis of trichoepithelioma and basal cell carcinoma. Modern Pathology (2012) 25, 1345-1353; doi: 10.1038/modpathol.2012.96; published online 8 June 2012
Resumo:
Abstract Background In areas with limited structure in place for microscopy diagnosis, rapid diagnostic tests (RDT) have been demonstrated to be effective. Method The cost-effectiveness of the Optimal® and thick smear microscopy was estimated and compared. Data were collected on remote areas of 12 municipalities in the Brazilian Amazon. Data sources included the National Malaria Control Programme of the Ministry of Health, the National Healthcare System reimbursement table, hospitalization records, primary data collected from the municipalities, and scientific literature. The perspective was that of the Brazilian public health system, the analytical horizon was from the start of fever until the diagnostic results provided to patient and the temporal reference was that of year 2006. The results were expressed in costs per adequately diagnosed cases in 2006 U.S. dollars. Sensitivity analysis was performed considering key model parameters. Results In the case base scenario, considering 92% and 95% sensitivity for thick smear microscopy to Plasmodium falciparum and Plasmodium vivax, respectively, and 100% specificity for both species, thick smear microscopy is more costly and more effective, with an incremental cost estimated at US$549.9 per adequately diagnosed case. In sensitivity analysis, when sensitivity and specificity of microscopy for P. vivax were 0.90 and 0.98, respectively, and when its sensitivity for P. falciparum was 0.83, the RDT was more cost-effective than microscopy. Conclusion Microscopy is more cost-effective than OptiMal® in these remote areas if high accuracy of microscopy is maintained in the field. Decision regarding use of rapid tests for diagnosis of malaria in these areas depends on current microscopy accuracy in the field.
Resumo:
OBJECTIVE: The frequent occurrence of inconclusive serology in blood banks and the absence of a gold standard test for Chagas'disease led us to examine the efficacy of the blood culture test and five commercial tests (ELISA, IIF, HAI, c-ELISA, rec-ELISA) used in screening blood donors for Chagas disease, as well as to investigate the prevalence of Trypanosoma cruzi infection among donors with inconclusive serology screening in respect to some epidemiological variables. METHODS: To obtain estimates of interest we considered a Bayesian latent class model with inclusion of covariates from the logit link. RESULTS: A better performance was observed with some categories of epidemiological variables. In addition, all pairs of tests (excluding the blood culture test) presented as good alternatives for both screening (sensitivity > 99.96% in parallel testing) and for confirmation (specificity > 99.93% in serial testing) of Chagas disease. The prevalence of 13.30% observed in the stratum of donors with inconclusive serology, means that probably most of these are non-reactive serology. In addition, depending on the level of specific epidemiological variables, the absence of infection can be predicted with a probability of 100% in this group from the pairs of tests using parallel testing. CONCLUSION: The epidemiological variables can lead to improved test results and thus assist in the clarification of inconclusive serology screening results. Moreover, all combinations of pairs using the five commercial tests are good alternatives to confirm results.