CAC remained a highly significant independent predictor of all-cause mortality overall and in both sexes after adjusting for age and seven cardiovascular or non-cardiovascular risk factors ( p < 0.001; Supplementary Table S1 ).
Excerpts
Chi-square tests were employed to compare binary data outcomes, with a p -value < 0.05 indicating probable significance and a p -value < 0.001 indicating statistical significance. 3.4.
Significance Analysis As demonstrated in Table 4 , in both 1-month and 1-year mortality predictions, several key prognostic factors were identified as highly significant ( p < 0.001).
We found a highly significant increase over the 15-year period with regard to PPH (r = 0.200, p < 0.001) and cardiorespiratory instability (r = 0.282, p < 0.001), which stands in contrast to the other causes that remained unchanged over time.
In separate sensitivity models that combined age and GDS with one alternative geriatric instrument, depressive symptoms remained a strong and highly significant independent correlate of FACT-Cog (GDS standardized β between −0.44 and −0.57, all p < 0.001; Appendix A , Table A2 ).
For the girls aged 7–12, a highly significant, positive, and strong-to-moderate correlation was identified between age and VAI (R = 0.61, p < 0.001), HOMA-IR (R = 0.56; p = 0.001), triglycerides (R = 0.59, p < 0.001), sitting time (R = 0.4, p = 0.025) and fasting glucose (R = 0.38, p = 0.031).
In non-parametric testing, the difference was statistically highly significant ( p < 0.001) for all conventional retinal imaging modalities: NIR, GAF, BAF and multicolor imaging.
The results indicated a highly significant difference in performance across the different questions (F(13, 42) = 12.91, p < 0.001).
The Linear Mixed-Effects Model (LMM) analysis for longitudinal NRS data demonstrated a highly significant main effect for time ( p < 0.001).
The incorporation of first visit information led to a decrease in AIC (Akaike Information Criteria) that was highly significant ( p < 0.001) compared to the model using baseline data alone.
In an overall analysis, a highly significant correlation of VASp with movement restriction (MR) ( p -value ≤ 0.001), the presence of joint effusion ( p -value ≤ 0.001), and the diagnosis of RA ( p -value ≤ 0.001) were observed.
Moreover, a negative trend was found among four groups regarding total lymphocytes, CD4 + , CD8 + and B lymphocytes ( p < 0.001, p < 0.005, p < 0.000, p < 0.044, respectively).
These differences were highly significant ( p < 0.001) with a large effect size (V = 0.54).
In addition, it was observed that HbA1c level was one of the variables with the highest standardized effect on depression scores (β = 0.37), and this relationship was found to be statistically highly significant (B = 1.50, p < 0.001). 4.
The transformation also altered the apparent significance of individual predictors: the ST/HR index, which appeared highly significant in untransformed models ( p < 0.001), lost significance after log transformation ( p = 0.501), whereas HRR at 1 min became significant ( p < 0.001).
We conducted further analysis only with aIAB that was highly significant ( p < 0.001) in the univariate regression analysis after Bonferroni correction.
The non-HbA1c-XGBckd model showed the same pattern: both the positive predictive value and likelihood ratio increased monotonically across the four risk strata, and the Cochran–Armitage test again indicated a highly significant linear trend ( p < 0.001). 4.
We found a highly significant and strongly positive correlation between maternal hCG serum levels and the PUQE-24 score (r = 0.70; p < 0.001), as shown in Figure 2 A.
The model’s pseudo-R 2 of 0.34 and highly significant likelihood ratio test ( p < 0.001) indicate a moderate ability to discriminate patients with and without reproducible field defects based on the included covariates.
Correlations of the Level of ED and the Severity of ID Correlational analyses between the SED-S and the severity of ID revealed highly significant ( p < 0.001) negative associations for the overall score (r s = −0.753).
All Cohen’s κ values were highly significant ( p < 0.001), indicating agreement well beyond chance.
In the RMS model, total RMS was not associated with BCVA (β ≈ 0.00 logMAR per μm, p = 0.997), whereas the time effect remained highly significant (β ≈ −0.97, p = 0.001).
One-way analysis of variance (ANOVA) confirmed a highly significant difference across groups ( p < 0.001).
Inflammatory and Thrombophilia Markers, Angiographic Distribution, and Treatment Outcomes Inflammatory activity, measured by ESR, was significantly higher in stroke-positive Takayasu patients (50.6 ± 11.4 mm/h) compared to stroke-negative cases (26.3 ± 10.6 mm/h) and controls (22.4 ± 8.4 mm/h), indicating a highly significant difference ( p < 0.001).
According to segmented regression analysis, there was a decreasing trend in the amount of aminoglycoside and quinolone consumption before the intervention ( p < 0.001 for each antibiotic) ( Table 2 ).