Exemplos de uso de C-index em Inglês e suas traduções para o Português
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The C-index was a good predictor for chronic non-communicable diseases.
The best cutoff point for the C-Index was 1.12 for boys and 1.06 for girls.
Both independent variables entered in the multivariate model(PAL score P 0.050, air flow:0.016) and C-index was 0.83.
Therefore, C-Index had the highest discriminatory power of HCR for younger women.
The waist-to-height ratio WHtR andthe conicity index C-Index have also been used as indicators to diagnose body fat.
However, the C-Index was the index with the best performance to discriminate HCR in comparison with the others.
Both in Brazil and in other countries, no studies investigating the C-Index for the prediction of high body fat were found.
PanelAcompares the C-index of the model versus GRACE score, indicating similar prediction.
The following anthropometric indices were measured: body mass index(bmi), waist circumference(wc), waist/height ratio(whtr)and conicity index(c-index).
C-Index was determined by measuring body mass weight and height and waist circumference, using the Valdez mathematical equation.
To evaluate the diagnostic performance of BMI,WHtR and C-Index in detecting excess body fat, the ROC curve analysis was applied.
The C-index shows up as an evolution of the H-index, because, besides enabling the calculation of national comparability, it considers multiple accounting choices.
Few studies determining the best cut-off point for the C-Index and WHeR to estimate abdominal obesity in women were found in the literature.
Discrimination was measured by use of the statistical technique called area under the ROC Receiver Operating Characteristic,sometimes called c-statistic or c-index.
The diagnostic accuracy refers to the ability of BMI,WHtR and C-Index to discriminate adolescents with excess body fat from those without excess body fat.
C-Index seems to be a good indicator of fat distribution, especially in women, by detecting changes in body composition, and thus permitting comparisons between subjects who present different body weight and height measurements.
Publications on the prediction of high body fat through the C-Index were not found, which makes it difficult to compare the results found in this study.
Initially, we calculated the sensitivity and specificity between the anthropometric indicators of AOB WC,WHR, C-Index, and WHeR and HCR, as identified based on the FRS.
Model discrimination and calibration were assessed by the c-index and the Hosmer-Lemeshow statistic larger probability value means better calibration, respectively.
Significant differences were observed between the ROC curves in both genders,which show that the ROC curve for the C-Index has the lowest percentage under the curve when compared to BMI, WC and WHtR p.
However, cutoff points for the C-Index were developed to detect high blood pressure boys=1.13 and girls=1.14, high levels of total cholesterol boys=1.10 and low levels of HDL-c girls=1.10.
WHR was determined by dividing waist circumference cm by hip circumference cm. C-Index, as proposed by Valdez, was calculated using the following mathematical equation.
If these authors' hypothesis were confirmed, C-Index and WHeR would be the most adequate anthropometric indexes to diagnose AOB in women, since height is included in the calculation of both.
Unlike the result found in the present study 1.25,Pitanga& Lessa suggested 1.18 as the best cut-off point for the C-Index, with values of sensitivity of 73.39%, specificity of 61.15%, and area under the ROC curve of 0.75 95%CI 0.70-0.80.
Boys had higher body mass, height, WC,WHtR and C-Index, while girls had higher averages of TSFT, MCST, sum of two skinfolds?2DC and fat percentage BF% p.
Thus, the objective of this study was to evaluate the performance of different cut-off points of C-index, waist-hip ratio WHR, waist circumference WC, and waist-to-height ratio WHeR in discriminating a high coronary risk HCR in women.
These results were similar to those presented by Brazilian adults in relation to the C-Index, which is an anthropometric indicator with low discriminatory power for health problems compared to other anthropometric indicators.