The association between overall mortality and increasing age remained highly significant when adjusted for underlying co-morbidities or immunosuppression (p = 0.001).
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We found highly significant differences ( p <0.001) in severity of pancreatitis, Ranson score, and mortality between the AKI and non-AKI groups: in the AKI group there were 8 mild and 44 severe panceatitis cases, the average Ranson score was 4.98±1.59, and mortality was 36.5%, whereas in the non- AKI group there were 190 mild and 63 severe panceatitis cases, the average Ranson score was 2.75±1.58, and mortality was 5.8%.
The human group demonstrated a highly significant advantage in procedure time (p = 0.001).
Then the Mann-Whitney test was used to analyse the post-test dart scores, which showed that the extremely significant difference between the two groups ( Z = -4.37, p < 0.001, η 2 p = 0.55), the performance of the self-talk group (median: 103.87; IQR: 3.52) was higher than that of the control group (median: 100.87; IQR: 0.75).
There was a highly significant relationship between the average score of clinical competence and the participant’s age, sex, level of education, and years of clinical work experience ( P <0.001).
For Dim1 difference, the effect was highly significant (p < 0.001; estimate: –0.30; CI: –0.47 – –0.13).
According to the perMANOVA results ( Table 3 ), temperature had the strongest effect on the PC scores, explaining 47.9% of the total variance (R2 = 0.479), showing in parallel highly significant results ( p < 0.001).
Statistically significant ( p < 0.05), highly significant ( p < 0.01), and extremely significant ( p < 0.001) features are indicated with ( * ) , (**) , and (***) , respectively.
However, in the analysis of floret germination during three years by GLZ with multinomial model (three categories; germinated in the 1 st , 2 nd and 3 rd year) the effect of site was not significant (Wald Statistics 0.8, p>0.05), while effect of floret position within a spikelet was highly significant (Wald Statistics 138, p<0.001).
The global permutation test, using CCA, demonstrated that the relation between the diet of the species and their evolutionary history (phylogeny) was highly significant ( F = 3.796; P = 0.0010).
Compared to sham mice, the levels of serum creatinine were significantly increased at all three time points in IR-injured WT and KO mice and the differences in the means of serum creatinine were highly significant among all different groups of WT mice ( p < 0.001), KO mice ( p < 0.001), or all groups from both WT and KO ( p < 0.001), as indicated by one-way analysis of variance (ANOVA).
Two significance levels were chosen, moderate, P <0.01 and highly significant, P <0.001.
The only other significant (or even marginally significant) correlation was between the two risk-taking scores, r( 108) = .37, p <.001.
A Fisher’s exact test confirmed a highly significant association between stimulus type and sentence production ( p < .001, OR = 143.75), demonstrating that the target stimuli successfully and reliably elicited subjective motion sentences compared to controls.
Intraindividual differences in both BMI and V VAT-T were highly significant (p<0.001).
A significant trend ( χ 2 = 70.328, P <0.001) was identified that showed a growing proportion of rural cases.
ANOVA with post-hoc trend analysis for increasing FAK phosphorylation with increasing stiffness was highly significant ( p < 0.001).
Interaction analyses In the logistic regression modelling, we found highly significant ( p <0.001) additive gene effects for the LOC387715 and CFH loci, both having approximately the same effect size ( Table 3 ).
All differences were highly significant (p≤0.001) or significant for DUM R7 vs.
The regression coefficient for linear terms X 1 , X 2 , X 3 , and X 4 were highly significant (p ≤ 0.001) for responses R1 and R2.
We also confirmed the interaction between these factors was highly significant in explaining species richness pattern (ANOVA F = 14.376; p <0.001).
The overall effect of generational cohort on the group of variables was highly significant (Wilk’s Lambda, df = 6, 284, F = 49.32, p < . 001 , partial eta squared = .510, a large effect size).
In contrast, there was a highly significant influence of walking speed and position on all parameters (all p values < 0.001).
This point of change was highly significant ( p <0.001), and the following piecewise linear regression equation can be used to model the underestimation of clay (UnClay) at Highfield: (2) UnClay = − 0.78 ( p = 0.19 ) + 0.66 ( p = 0.07 ) SOC + 5.22 ( p < 0.001 ) ( SOC − 2.27 ) + , R 2 = 0.90 The last term in the equation is only applicable for SOC contents above 2.27 g C 100 g -1 minerals.
rosea on egg mortality ANOVA showed that spore concentration had a highly significant effect on egg mortality ( p < 0.001), with mortality increasing at higher concentrations of both fungal species ( Table 3 ).