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The data on vertical, horizontal curvature of cornea and and fasting blood sugar levels has been included in multivariate analyze and there was no significant difference in vertical, horizontal curvature and fasting blood glucose levels adjusted with age between premenopausal and postmenopausal groups (P = 0.352, P = 0.250, P = 0.065, respectively).
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Consistent with these results, in a multivariate analyze, the cognitive impairment, measured in 98 patients, was also related to the decrease in Testosterone in men and in FT3 and to the increase in IGF-1.
In multivariate analyzes, among all CXR findings, only multilobar involvement on CXR was found to be a risk factor for NIV (OR: 2.36, 95% CIs: 1.27-4.38, p = 0.006).
In those studies where this variable was included in the multivariate analyzes results are conflicting.
For an alpha probability of.05 and a power of.80, the recommended sample size (N) to correctly evaluate the predictor variables (m) in the multivariate analyzes is: N = 50 + 8 m.
Maintaining this category in bivariate and multivariate analyzes, resulted in very imprecise estimates.
We built an adjusted model in multivariate regression to analyze the independent variables associated with in-hospital death: age, family history of CAD, prior coronary artery disease, hypertension, smoking, diabetes, categorical admission blood glucose < or ≥ 200 mg/dL, gender, ejection fraction and serum creatinine.
Patients receiving a graft carrying CAV1 rs4730751 AA genotype displayed a significant decrease in estimated glomerular filtration rate and a significant increase in serum creatinine in both univariate and multivariate analyzes.
Table 6 briefly shows the observed significant associations.> Among the sociodemographic variables used in this study, after multivariate analyzes, education was associated with individual empowerment and religiosity with collective empowerment.
However, the single CEA values, measured on postoperative days 7 and 30, did not have more significance in DFS or OS in multivariate analysis when analyzed with R values.
Significant results of these multivariate analyzes are summarized in Table 6.> MPlus could not estimate the standard errors of the children nested within clinician model because of low sample size at both levels, so multiple regression was used to analyze the model.
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