Sentence examples for uppermost quartile from inspiring English sources

Because there was a threshold (nonlinear) effect, we modeled our associations comparing the uppermost quartile of each index to the bottom three quartiles combined.

The adjusted odds ratio of all anomalies combined among children with prenatal exposure in the uppermost quartile was 1.5 (95% CI: 0.9, 2.5).

For each left ventricular mass measure, the rate of diabetes was highest in the uppermost quartile versus the lower three (Table 1).

Similarly, small dense LDL and very small LDL concentrations were higher in the lowest than in the uppermost quartile of insulin sensitivity in both races (Fig. 3 A and B), irrespective of sex.

Here we found that those with cortisol in the uppermost quartile experienced a 56%% higher risk of newborn stunting compared to those in the lowest quartile (RR: 1.56; 95 % CI 1.08 to 2.25) in a multivariate adjusted model.

Of note, 35% of subjects in group-1 (p < 0.05 as compared to other two groups), and 25.3% of all subjects had levels of sICAM-1 in uppermost quartile (>850 ng/ml).

Among the actively detected cases, 75.8% were from the lower two quartiles, while among the passive TB cases more than half, 57.1%, were from the uppermost two quartiles, 40.8% from the second quartile and 2.1% from the lowest quartile of the population.

They prevail in the uppermost frequency quartile (Fig. 2A).

No significant association was observed for either VAT (multivariable-adjusted relations of uppermost vs. lowermost quartile and log aldosterone concentration: p = 0.2) or SAT (multivariable-adjusted relations of uppermost vs. lowermost quartile and log-aldosterone concentration p = 0.7) in this analysis.

It is acknowledged that misclassification of exposure is an important issue that usually will produce bias toward the null but in this study the average exposure levels in the uppermost and lowest exposure quartiles varied by a factor 2 3 and therefore exposure misclassification seems of minor importance.

Finally, these ratios were dichotomized to create a binomial 'atrophy' variable for use in the regression analyses, in which zero values indicated a grey matter index in the uppermost 26th 100th percentile (i.e. no/mild atrophy), and a value of 1 indicated a grey matter index in the bottom quartile (i.e. moderate atrophy).