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. Author manuscript; available in PMC: 2022 Sep 7.
Published in final edited form as: Am J Kidney Dis. 2019 Feb 21;74(1):47–55. doi: 10.1053/j.ajkd.2018.12.027

Table 5.

Coefficient Estimates for the Interactions with Time in Modeling Proteinuria Risk over Observation Period in Patients with Sickle Cell Disease.

HbSS/HbSβ0-Thalassemia (Severe genotypes)
Estimate (SE) P
Hemoglobin −0.046 (0.032) 0.1
LDH 0.000032 (0.000084) 0.7
Reticulocyte count 0.00041 (0.00039) 0.3
Hemoglobin F −0.011 (0.014) 0.4
WBC count −0.012 (0.014) 0.4
Ferritin 0.000021 (0.000052) 0.7
Total bilirubin 0.012 (0.024) 0.6
Direct bilirubin 1.89 (1.57) 0.2
Indirect bilirubin 0.041 (0.058) 0.5
Baseline eGFR −0.00001 (0.0015) 0.9
Hemoglobinuria −0.27 (0.22) 0.2
Urine specific gravity −32.68 (21.78) 0.1
Systolic BP −0.0028 (0.0028) 0.3
Diastolic BP −0.0049 (0.0030) 0.1
Weight −0.0067 (0.0032) 0.04
Diabetes mellitus −0.33 (0.24) 0.2
History of stroke 0.044 (0.12) 0.7
History of acute chest syndrome 0.45 (0.24) 0.06
History of avascular necrosis 0.079 (0.10) 0.4
History of leg ulcers 0.0069 (0.10) 0.9
ACEi/ARB therapy −0.11 (0.098) 0.3
Hydroxyurea therapy −0.13 (0.085) 0.1
Ongoing need for RBC transfusion −0.41 (0.65) 0.5

Estimates expressed log-odds of proteinuria over time; for continuous covariates, estimate is per 1-unit increase.

Results from minimally adjusted (age and sex) generalized linear mixed effects model with random intercept and random time effect for each covariate.

ACEi = Angiotensin-converting enzyme inhibitor, ARB = angiotensin receptor blocker; RBC, _______; LDH, _____; WBC, _____; BP, blood pressure; eGFR, estimated glomerular filtration rate; SE, _____.