31 resultados para Predictive values
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Objectives: The stair-climbing test as measured in meters or number of steps has been proposed to predict the risk of postoperative complications. The study objective was to determine whether the stair-climbing time can predict the risk of postoperative complications. Methods: Patients aged more than 18 years with a recommendation of thoracotomy for lung resection were included in the study. Spirometry was performed according to the criteria by the American Thoracic Society. The stair-climbing test was performed on shaded stairs with a total of 12.16 m in height, and the stair-climbing time in seconds elapsed during the climb of the total height was measured. The accuracy test was applied to obtain stair-climbing time predictive values, and the receiver operating characteristic curve was calculated. Variables were tested for association with postoperative cardiopulmonary complications using the Student t test for independent populations, the Mann-Whitney test, and the chi-square or Fisher exact test. Logistic regression analysis was performed. Results: Ninety-eight patients were evaluated. Of these, 27 showed postoperative complications. Differences were found between the groups for age and attributes obtained from the stair-climbing test. The cutoff point for stair-climbing time obtained from the receiver operating characteristic curve was 37.5 seconds. No differences were found between the groups for forced expiratory volume in 1 second. In the logistic regression, stair-climbing time was the only variable associated with postoperative complications, suggesting that the risk of postoperative complications increases with increased stair-climbing time. Conclusions: The only variable showing association with complications, according to multivariate analysis, was stair-climbing time. © 2013 by The American Association for Thoracic Surgery.
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Introduction: The analysis of body composition through direct and indirect methods allows the study of the various components of the human body, becoming the central hub for assessing nutritional status. Objective: The objective of the study was to develop equations for predicting body fat% from circumferential body arm, waist and calf and propose percentiles to diagnose the nutritional status of school children of both sexes aged 4-10 years. Methods: We selected intentionally (non-probabilistic) 515 children, 261 children and 254 being girls belonging to Program interaction and development of children and adolescents from the State University of Campinas (Sao Paulo, Brazil). Anthropometric variables were evaluated for weight, height, triceps and subscapular skinfolds and body circumferences of arm, waist and calf, and the% fat determined by the equation proposed by Boileau, Lohman and Slaughter (1985). Through regression method 2 were generated equations to predict the percentage of fat from the body circumferences, the equations 1 and 2 were validated by cross validation method. Results: The equations showed high predictive values ranging with a R2 = 64-69%. In cross validation between the criterion and the regression equation proposed no significant difference (p > 0.05) and there was a high level of agreement to a 95% CI. Conclusion: It is concluded that the proposals are validated and shown as an alternative to assess the percentage of fat in school children of both sexes aged 4-10 years in the region of Campinas, SP (Brazil).
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Pós-graduação em Patologia - FMB
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Pós-graduação em Ginecologia, Obstetrícia e Mastologia - FMB
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Pós-graduação em Ginecologia, Obstetrícia e Mastologia - FMB
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Pós-graduação em Ginecologia, Obstetrícia e Mastologia - FMB
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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Pós-graduação em Ginecologia, Obstetrícia e Mastologia - FMB
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)
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Coordenação de Aperfeiçoamento do Pessoal de Nível Superior (CAPES)
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Objective To assess the diagnostic accuracy of the surface electromyography (sEMG) parameters associated with referred anterior knee pain in diagnosing patellofemoral pain syndrome (PFPS). Design Sensitivity and specificity analysis. Setting Physical rehabilitation center and laboratory of biomechanics and motor control. Participants Pain-free subjects (n=29) and participants with PFPS (n=22) selected by convenience. Interventions Not applicable. Main Outcome Measure The diagnostic accuracy was calculated for sEMG parameters’ reliability, precision, and ability to differentiate participants with and without PFPS. The selected sEMG parameter associated with anterior knee pain was considered as an index test and was compared with the reference standard for the diagnosis of PFPS. Intraclass correlation coefficient, SEM, independent t tests, sensitivity, specificity, negative and positive likelihood ratios, and negative and positive predictive values were used for the statistical analysis. Results The medium-frequency band (B2) parameter was reliable (intraclass correlation coefficient=.80–.90), precise (SEM=2.71–3.87 normalized unit), and able to differentiate participants with and without PFPS (P<.05). The association of B2 with anterior knee pain showed positive diagnostic accuracy values (specificity, .87; sensitivity, .70; negative likelihood ratio, .33; positive likelihood ratio, 5.63; negative predictive value, .72; and positive predictive value, .86). Conclusions The results provide evidence to support the use of EMG signals (B2 – frequency band of 45–96Hz) of the vastus lateralis and vastus medialis muscles with referred anterior knee pain in the diagnosis of PFPS.
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Genomewide marker information can improve the reliability of breeding value predictions for young selection candidates in genomic selection. However, the cost of genotyping limits its use to elite animals, and how such selective genotyping affects predictive ability of genomic selection models is an open question. We performed a simulation study to evaluate the quality of breeding value predictions for selection candidates based on different selective genotyping strategies in a population undergoing selection. The genome consisted of 10 chromosomes of 100 cM each. After 5,000 generations of random mating with a population size of 100 (50 males and 50 females), generation G(0) (reference population) was produced via a full factorial mating between the 50 males and 50 females from generation 5,000. Different levels of selection intensities (animals with the largest yield deviation value) in G(0) or random sampling (no selection) were used to produce offspring of G(0) generation (G(1)). Five genotyping strategies were used to choose 500 animals in G(0) to be genotyped: 1) Random: randomly selected animals, 2) Top: animals with largest yield deviation values, 3) Bottom: animals with lowest yield deviations values, 4) Extreme: animals with the 250 largest and the 250 lowest yield deviations values, and 5) Less Related: less genetically related animals. The number of individuals in G(0) and G(1) was fixed at 2,500 each, and different levels of heritability were considered (0.10, 0.25, and 0.50). Additionally, all 5 selective genotyping strategies (Random, Top, Bottom, Extreme, and Less Related) were applied to an indicator trait in generation G(0), and the results were evaluated for the target trait in generation G(1), with the genetic correlation between the 2 traits set to 0.50. The 5 genotyping strategies applied to individuals in G(0) (reference population) were compared in terms of their ability to predict the genetic values of the animals in G(1) (selection candidates). Lower correlations between genomic-based estimates of breeding values (GEBV) and true breeding values (TBV) were obtained when using the Bottom strategy. For Random, Extreme, and Less Related strategies, the correlation between GEBV and TBV became slightly larger as selection intensity decreased and was largest when no selection occurred. These 3 strategies were better than the Top approach. In addition, the Extreme, Random, and Less Related strategies had smaller predictive mean squared errors (PMSE) followed by the Top and Bottom methods. Overall, the Extreme genotyping strategy led to the best predictive ability of breeding values, indicating that animals with extreme yield deviations values in a reference population are the most informative when training genomic selection models.
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Objective: To evaluate data from patients with normal oral glucose tolerance test (OGTT) results and a normal or impaired glycemic profile (GP) to determine whether lower cutoff values for the OGTT and GP (alone or combined) could identify pregnant women at risk for excessive fetal growth. Methods: We classified 701 pregnant women with positive screening for gestational diabetes mellitus (GDM) into 2 categories - (1) normal 100-g OGTT and normal GP and (2) normal 100-g OGTT and impaired GP - to evaluate the influence of lower cutoff points in a 100-g OGTT and GP (alone or in combination) for identification of pregnant women at excessive fetal growth risk. The OGTT is considered impaired if 2 or more values are above the normal range, and the GP is impaired if the fasting glucose level or at least 1 postprandial glucose value is above the normal range. To establish the criteria for the OGTT (for fasting and 1, 2, and 3 hours after an oral glucose load, respectively), we considered the mean (75 mg/dL, 120 mg/dL, 113 mg/dL, and 97 mg/dL), mean plus 1 SD (85 mg/dL, 151 mg/dL, 133 mg/dL, and 118 mg/dL), and mean plus 2 SD (95 mg/dL, 182 mg/dL, 153 mg/dL, and 139 mg/dL); and for the GP, we considered the mean and mean plus 1 SD (78 mg/dL and 92 mg/dL for fasting glucose levels and 90 mg/dL and 130 mg/dL for 1- or 2-hour postprandial glucose levels, respectively). Results: Subsequently, the women were reclassified according to the new cutoff points for both tests (OGTT and GP). Consideration of values, in isolation or combination, yielded 6 new diagnostic criteria. Excessive fetal growth was the response variable for analysis of the new cutoff points. Odds ratios and their respective confidence intervals were estimated, as were the sensitivity and specificity related to diagnosis of excessive fetal growth for each criterion. The new cutoff points for the tests, when used independently rather than collectively, did not help to predict excessive fetal growth in the presence of mild hyperglycemia. Conclusion: Decreasing the cutoff point for the 100-g OGTT (for fasting and 1, 2, and 3 hours) to the mean (75 mg/dL, 120 mg/dL, 113 mg/dL, and 97 mg/dL) in association with the GP (mean or mean plus 1 SD-78 mg/dL and 92 mg/dL for the fasting state and 90 mg/dL and 130 mg/dL for 1- or 2-hour postprandial values-increased the sensitivity and specificity, and both criteria had statistically significant predictive power for detection of excessive fetal growth. © 2008 AACE.
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Food base excess (BE, mEq/kg) can be calculated from the diet macroelements, together with either the sulfur amino acids methionine and cysteine (BEaa) or total sulfur (BEs) concentrations. The present study compared the use of sulfur or methionine and cysteine for calculating the food BE (experiment 1) and investigated the influence of food BE on blood gas analysis and the urine pH of cats, and proposes a prediction equation to estimate the urine pH of cats fed kibble diets based on the calculated food BE (experiments 2 and 3). In experiment 1, nine healthy, adult cats were used in a change-over design and fed with nine commercial dry cat foods. The cats were housed in metabolism cages over seven days for adaptation and three days for total urine collection. All of the urine produced over 24h was pooled by cat and diet. The cats' acid-base status was assessed through blood gas analysis after 10 days of diet consumption. A mean difference of -115mEq/kg between BEs and BEaa was observed, which could be explained by a greater concentration of sulfur in the whole diet than in methionine and cysteine. Urine pH presented a stronger correlation with food BEs (R2=0.95; P<0.001) than with food BEaa (R2=0.86; P<0.001). Experiment 2 included 30 kibble diets, and each diet was tested in six cats. The food BEs varied between -180 and +307mEq/kg, and the urine pH of the cats varied between 5.60 and 7.74. A significant correlation was found between the measured urine pH and the food BEs (urinary pH=6.269+[0.0036×BEs]+[0.000003×BEs2]; R2=0.91; P<0.001). In experiment 3, eight kibble diets were tested (food BEs between -187mEq/kg and +381mEq/kg) to validate the equation proposed in experiment 2 and to compare the obtained results with previously published formulae. The results of the proposed formula presented a high concordance correlation coefficient (0.942) and high accuracy (0.979) with the measured values, and the estimates of urine pH did not differ from the values obtained in cats (P>0.05). The cats' venous blood pH, bicarbonate, and blood BE were correlated with food BEs (P<0.001); the consumption of diets with low food BEs induced a reduction in these parameters. In conclusion, food macroelement composition has a strong influence on cats' acid-base equilibrium and food BEs calculation is a useful tool to formulate and balance kibble diets for felines. © 2013 Elsevier B.V.