VFA BIA and VAT CT ( r = 0.60, p < 0.001) showed moderately significant correlations in the total population and strong correlations in the gender-specific subgroup analysis (female r = 0.73; male r = 0.82; p < 0.001) (Fig. 3E, F ).
Excerpts
Moreover, our results showed an increasing trend in WC and BMI across the quartiles of non-HDL/HDL and TG/HDL (P-value < 0.001).
Statistical significance was defined as highly significant (*** p < 0.001).
In all three phenotypic classes and for both DE and GE assays, genotype, temperature, and their interaction all had highly significant ( P <0.001; Table 1 ) effects on cold tolerance.
In OSMF, comparison between mild (grade1) versus moderate (grade 2) is not significant ( P = 0.367), but mild (grade 1) versus severe (grade 3) and moderate (grade 2) versus severe (grade 3) is highly significant ( P < 0.001) [ Table 7 ].
Compared with the “Very Low” category, the risk of death increased progressively across other categories, being not significant in the ‘Low’ (RR 1.37; 95% CI 0.99–1.89, p = 0.14), but significant in the “Intermediate” (RR 1.66; 95% CI 1.23–2.23, p = 0.018) and highly significant in the “High” (RR 2.24; 95% CI 1.69–2.97, p < 0.001) after Bonferroni adjustment.
Phenotypic diversity and GWA study The analysis of variance revealed a highly significant ( P < 0.001) variability due to the genotypes for all traits (Table 1 ).
In contrast, BMI, prevalence of PCOS, AMH levels, and the number of oocytes retrieved showed a decreasing trend (all P < 0.001) ( Table 1 ). 3.2 Univariate analysis for number of oocytes retrieved The univariate analysis results are shown in Table 2 .
The cross validation of the model using CV-ANOVA provided highly significant results (F = 10.3017, p < 0.001).
Univariate analyses ( Table 2 ) show that all the FOT parameters presented highly significant correlations with pack–years ( p <0.001).
This difference is very highly significant statistically ( p < 0.001).
All variables in the model were highly significant ( P < 0.001).
The correlation between our study sample and the population in each state is highly significant (Spearman rank R = 0.87, p < 0.001).
In contrast, depression exhibited a decreasing trend with age, especially in ages 60+ years, declining from 8.6% in 50‐ to 59‐year‐olds to 4.0% in the oldest ( χ 2 [5] = 26.14, p < 0.001; slope = −0.13).
Notably, in Model 4, which replaced the PSI score with the CURB-65 score, the prognostic value of LAR remained highly significant and the effect estimates remained stable (30-day HR = 2.52, 95% CI: 1.51–4.21, p < 0.001; 90-day HR = 2.55, 95% CI: 1.59–4.08, p < 0.001), indicating that the independent predictive ability of LAR is robust to the specific disease severity score employed for adjustment.
Similarly, diabetes showed a pronounced increase from 0.8% in the youngest group to 13.9% in the oldest, with results confirming a significant trend ( χ 2 [5] = 249.08, p < 0.001; slope = 0.56).
The most comprehensive model, incorporating all three factors (age, WBC, and D-dimer), also yielded a highly significant AUC area of 0.723 ( p < 0.001).
Between-subjects contrasts indicated a non-significant group effect (F (1,23) = 2.132, P = 0.152), a highly significant gender effect (F (1,23) = 53.257, P < 0.001), and a non-significant group × gender interaction (F (1,23) = 1.086, P = 0.304).
Repeated measures ANOVA indicated highly significant effects of dose ( F 3,12 = 51.40, P < 0.001, partial η 2 = 0.93), chemical ( F 5,20 = 12.41, P < 0.001, partial η 2 = 0.76), and dose x chemical interaction ( F 15,60 = 26.13, P < 0.001, partial η 2 = 0.87).
The associations between symptoms and all the remaining variables did not reach statistical significance (according to the Bonferroni adjusted level of p = 0.001). 3.4.
The robust and favorable association in model 2 was still highly significant (OR = 0.994, 95% CI: 0.991–0.997; P < 0.001) even after taking into account factors such as gender, age, marriage, race, and education.
The results show that serum CHI3L1 levels were significantly elevated in lymphoma patients compared to healthy controls, with a highly significant difference (P < 0.001) ( Figure 2A ).
Overall batch effects were highly significant (p<0.001) for most traits, and were generally more significant than the gender or genetic type effects.
Further post-hoc test showed that the significant interaction was attributed to a highly significant increase of the inverse efficiency score in session 1 [ t (19) = −4.590, p < 0.001] in comparison to a significant increase in session 2 [ t (19) = −2.549, p = 0.020] (see Figure 2 ).
An increasing trend in APTT ( p < 0.001) was associated with greater likelihood for transfusion between D1 and D28, as was VAECMO therapy ( p = 0.005) ( Table 4 and Table 5 ).