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Multivariate models did not improve the performance of CRP alone.
The different age-adjusted and multivariate models did not differ materially from each other.
Moreover, including sampling year as a covariate in the multivariate models did not change the associations.
Using multivariate models did not reveal any clinical or laboratory predictors of fatigue change over time.
Even attempting to force the variable into the multivariate models did not alter the analyses.
The multivariate models did not contain any interactions, and they passed post-estimation controls.
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Although the TIMI UA/NSTEMI multivariate model did not calibrate well (Figure S3B, Table 6), it too displayed a marked improvement in discrimination (C = 0.70, 95% CI: 0.66 0.74; Figure S4B) as compared to the corresponding risk score (C = 0.56, Figure 1B); however, it was significantly inferior to the GRACE 6-month multivariate model (0.84, 95% CI: 0.81 0.87; p<0.81 0.87
The multivariate modelling did not use interaction terms.
Further, adding race to the multivariate model did not modify the observed associations.
Further adjustment for rs4646 in the multivariate model did not alter the results.
Adding gestational length to the multivariate model did not significantly change the result for di- ortho PCBs (Table 3).
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