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We identified urinary albumin creatinine ratio, but not eGFR, as an independent associate of LEA in the multivariable models involving FDS1 and pooled data, consistent with previous studies reporting albuminuria as an important risk factor [ 20, 44, 45].
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Some of these variables separate the two patient clusters (e.g. CCI, higher cognitive scores etc)., but these have not featured in the final multivariable model involving the total patient cohort, possibly due to differences being most extreme at very high and very low scores.
Logistic regression is a multivariable method devised for dichotomous outcomes [24] and particularly appropriate for models involving disease states [25].
Multivariable models adjusted for age and illness severity.
Thus, the basis of more complex multivariable models is provided.
These associations remained significant in multivariable models.
No other factor predicted funding in multivariable models.
Multivariable models yielded similar results.
We therefore used gender-specific multivariable models.
Therefore two multivariable models were developed.
Therefore, we constructed three multivariable models.
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