“highly significant”

Compared to the untreated group, the difference was highly significant ( p < 0.0001). 2.9.

We confirmed previous findings by showing highly significant differences in rates of neurological and gastrointestinal symptoms ( p < 0.0001).

The apparent 10.2/7.6 mmHg difference between inpatients and outpatients was only slightly reduced to 8.0/5.1 mmHg after adjustment for baseline and remained highly significant (p < 0.0001/p < 0.0001) even after correction for cluster effects.

Comparison with the full data set of 180 outbreaks reveals a highly significant reduction in goodness-of-fit ( P <0.0001), indicating that the 1967–1968 outbreak was unusually large given prior estimates for R .

S3 and Table S4) revealed highly significant ( p -value <0.0001) influences of the sampling time, type of compound, and CP.

The overall rate of recorded sinusitis in the multiple sclerosis group was over four times that found in control group A and control group B and this difference was highly significant (p < 0.0001).

A highly significant in- crease in the number of tumors was ob- tained with the positive asbestos controls (p<0.0001) (Table 3).

Error bars indicate 95% confidence limits. and then by a second increase in MN-NCE levels at the end of the study. MN-PCE Levels Exposure to benzene by inhalation or by gavage in- duced a highly significant increase (p < 0.0001) in the fre- quency of MN-PCE detected in the peripheral blood of mice (Figs. 2 and 3; Table 2).

There were highly significant effects of dose and subject for AUC after 5–20 g glucose (dose, p < 0.0001; subjects, p = 0.0001) and 5–20 g WB (dose, p < 0.0001; subjects, p < 0.0001).

The analysis of blood loss showed that the median (IQR) total blood loss was 575 mL (375, 875) in the NTA group compared to 450 mL (325, 675) in the TA group, a highly significant difference (p < 0.0001 Mann-Whitney test).

Publication bias and sensitivity analysis Initially, the plausible sources of publication bias were visualized through a funnel plot with Egger test, where the publication bias was found to be highly significant ( P < .0001) (Fig. 5 ).

The ANOVA results of the regression model demonstrated that the model is highly significant ( p < 0.0001), and the lack-of-fit value ( p = 0.7403) showed that the model fit well in the experimental design.

Season × region interactions were highly significant ( p < 0.0001), indicating strong environmental modulation of milk trace mineral profiles. 3.2.

The overall model for time, treatment and route was highly significant (R 2 = 0.5055; p < 0.0001).

Paired Wilcoxon rank sum tests revealed highly significant differences ( P < 0.0001 for BLAST and k-mer matching) in accuracy favoring the rRNA operon.

Expectedly both S100 proteins correlated highly significant ( r = 0.82; p < 0.0001) and reproduced elevated levels in M649V homozygous FMF patients during inactive disease, and a gene-dose effect with significantly lower levels in heterozygous M694V FMF patients (Fig. 1 C and D).

The comparison was highly significant (P = 0.0001), suggesting that harvest time is also a determining factor in the amount of ART in A. annua herbal teas.

A one-way ANOVA demonstrated a highly significant difference in ALP levels across the four clinical severity grades (F = 399.79, p < 0.0001) (Table 1 ).

subquinaria revealed a highly significant effect of population type (sympatric versus allopatric; Wald χ 2 = 17.88, p < 0.0001), but no effect of individual population within population type (χ 2 = 1.02, p = 0.91) or trial (χ 2 = 2.12, p = 0.35).

These effects were highly significant ( P < 0.0001) throughout all feeding phases of the trial.

Repeatabilities (intra-class correlation coefficients, r 1 ) of FAs calculated from mammograms were calculated on a random sub-set of 20 mammograms from the study and showed highly significant r 1 values (repeated measures ANOVA, 20 sets of mammograms, FA breast width r 1 0.98, p = 0.0001; FA breast height r 1 0.86, p = 0.0001).

The interaction between the mutational subgroup and treatment was highly significant (P<0.0001).

2 ), and this difference is highly significant (p = 10 -4 ).

These differences in thyroid shield visibility across three decades were highly significant (p < 0.0001).

The coefficients for the two main explanatory variables (GDP per capita and occupancy rate) are highly significant (p < 0.0001), as well as most of the control dummies, e.g., hospital level.