959 resultados para Prediction systems


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Objective: The aim was to compare there ulcer classification systems as predictors of the outcome of diabetic foot ulcers; the Wagner, the University of Texas (UT) and the size (area, depth), sepsis, arteriopathy, denervation system (S(AD)SAD) systems in specialist clinic in Brazil. Methods: Ulcer area, depth, appearance, infection and associated ischaemia and neuropathy were recorded in a consecutive series of 94 subjects. A novel score, the S(AD)SAD score, was derived from the sum of individual items of the S(AD)SAD system, and was evaluated. Follow-up was for at least 6 months. The primary outcome measure was the incidence of healing. Results: Mean age was 57.6 years; 57 (60.6%) were made. Forty-eight ulcers (51.1%) healed without surgery; 11 (12.2%) subjects underwent minor amputation. Significant differences in terms of healing were observed for depth (P = 0.002), infection (P = 0.006) and denervation (P = 0.002) using the S(AD)SAD system, for UT grade (P = 0.002) and stage (P = 0.032) and for Wagner grades (P = 0.002). Ulcers with an S(AD)SAD score of <= 9 (total possible 15) were 7.6 times more likely to heal than scores >= 10 (P < 0.001). Conclusions: All three systems predicted ulcer outcome. The S(AD)SAD score of ulcer severity could represent a useful addition to routine clinical practice. The association between outcome and ulcer depth confirms earlier reports. The association with infection was stronger than that reported from the centres in Europe or North America. The very strong association with neuropathy has only previously been observed in Tanzania. Studies designed to compare the outcome in different countries should adopt systems of classification, which are valid for the populations studied.

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PURPOSE. To assess whether baseline Glaucoma Probability Score (GPS; HRT-3; Heidelberg Engineering, Dossenheim, Germany) results are predictive of progression in patients with suspected glaucoma. The GPS is a new feature of the confocal scanning laser ophthalmoscope that generates an operator-independent, three-dimensional model of the optic nerve head and gives a score for the probability that this model is consistent with glaucomatous damage. METHODS. The study included 223 patients with suspected glaucoma during an average follow-up of 63.3 months. Included subjects had a suspect optic disc appearance and/or elevated intraocular pressure, but normal visual fields. Conversion was defined as development of either repeatable abnormal visual fields or glaucomatous deterioration in the appearance of the optic disc during the study period. The association between baseline GPS and conversion was investigated by Cox regression models. RESULTS. Fifty-four (24.2%) eyes converted. In multivariate models, both higher values of GPS global and subjective stereophotograph assessment ( larger cup-disc ratio and glaucomatous grading) were predictive of conversion: adjusted hazard ratios (95% CI): 1.31 (1.15 - 1.50) per 0.1 higher global GPS, 1.34 (1.12 - 1.62) per 0.1 higher CDR, and 2.34 (1.22 - 4.47) for abnormal grading, respectively. No significant differences ( P > 0.05 for all comparisons) were found between the c-index values ( equivalent to area under ROC curve) for the multivariate models (0.732, 0.705, and 0.699, respectively). CONCLUSIONS. GPS values were predictive of conversion in our population of patients with suspected glaucoma. Further, they performed as well as subjective assessment of the optic disc. These results suggest that GPS could potentially replace stereophotograph as a tool for estimating the likelihood of conversion to glaucoma.

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Objective: Several limitations of published bioelectrical impedance analysis (BIA) equations have been reported. The aims were to develop in a multiethnic, elderly population a new prediction equation and cross-validate it along with some published BIA equations for estimating fat-free mass using deuterium oxide dilution as the reference method. Design and setting: Cross-sectional study of elderly from five developing countries. Methods: Total body water (TBW) measured by deuterium dilution was used to determine fat-free mass (FFM) in 383 subjects. Anthropometric and BIA variables were also measured. Only 377 subjects were included for the analysis, randomly divided into development and cross-validation groups after stratified by gender. Stepwise model selection was used to generate the model and Bland Altman analysis was used to test agreement. Results: FFM = 2.95 - 3.89 (Gender) + 0.514 (Ht(2)/Z) + 0.090 (Waist) + 0.156 (Body weight). The model fit parameters were an R(2), total F-Ratio, and the SEE of 0.88, 314.3, and 3.3, respectively. None of the published BIA equations met the criteria for agreement. The new BIA equation underestimated FFM by just 0.3 kg in the cross-validation sample. The mean of the difference between FFM by TBW and the new BIA equation were not significantly different; 95% of the differences were between the limits of agreement of -6.3 to 6.9 kg of FFM. There was no significant association between the mean of the differences and their averages (r = 0.008 and p = 0.2). Conclusions: This new BIA equation offers a valid option compared with some of the current published BIA equations to estimate FFM in elderly subjects from five developing countries.

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In this work, we take advantage of association rule mining to support two types of medical systems: the Content-based Image Retrieval (CBIR) systems and the Computer-Aided Diagnosis (CAD) systems. For content-based retrieval, association rules are employed to reduce the dimensionality of the feature vectors that represent the images and to improve the precision of the similarity queries. We refer to the association rule-based method to improve CBIR systems proposed here as Feature selection through Association Rules (FAR). To improve CAD systems, we propose the Image Diagnosis Enhancement through Association rules (IDEA) method. Association rules are employed to suggest a second opinion to the radiologist or a preliminary diagnosis of a new image. A second opinion automatically obtained can either accelerate the process of diagnosing or to strengthen a hypothesis, increasing the probability of a prescribed treatment be successful. Two new algorithms are proposed to support the IDEA method: to pre-process low-level features and to propose a preliminary diagnosis based on association rules. We performed several experiments to validate the proposed methods. The results indicate that association rules can be successfully applied to improve CBIR and CAD systems, empowering the arsenal of techniques to support medical image analysis in medical systems. (C) 2009 Elsevier B.V. All rights reserved.

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Methods: We assessed the outcome of 56 patients with Chagas` cardiomyopathy ([31 men]; mean age of 55 years; mean left ventricular ejection fraction [LVEF] 42%) presenting with either sustained ventricular tachycardia (VT) or nonsustained VT (NSVT), before therapy with implantable cardioverter-defibrillator was available at our center. Results: Over a mean follow-up of 38 +/- 16 months (range, 1-61 months), 16 patients (29%) died, 11 due to sudden cardiac death (SCD), and five from progressive heart failure. Survivors and nonsurvivors had comparable baseline characteristics, except for a lower LVEF (46 +/- 7% vs 31 +/- 9%, P < 0.001) and a higher New York Heart Association class (P = 0.003) in those who died during follow-up. Receiver-operator characteristic curve analysis showed that an LVEF cutoff value of 38% had the best accuracy for predicting all-cause mortality and an LVEF cutoff value of 40% had the best accuracy for prediction of SCD. Using the multivariate Cox regression analysis, LVEF < 40% was the only predictor of all-cause mortality (hazard ratio [HR] 12.22, 95% confidence interval [CI] 3.46-43.17, P = 0.0001) and SCD (HR 6.58, 95% CI 1.74-24.88, P = 0.005). Conclusions: Patients with Chagas` cardiomyopathy presenting with either sustained VT or NSVT run a major risk for mortality when had concomitant severe or even moderate LV systolic dysfunction. (PACE 2011; 54-62).