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. 2017 Jun 30;8:731. doi: 10.3389/fimmu.2017.00731

Table 2.

Latent growth-curve modelinga showing associations between immune parameter outcomes and time (linear and quadratic) post-combination antiretroviral therapy (post-cART) initiation in HIV+ individuals (n = 20).

Immune parameter outcome b (SE) 95% CI Wald χ2 p-Value
Activated/adaptive-like NK cells
NK cell (% CD69+) χ2(1) = 9.1 0.003
 Linear −0.12 (0.04) −0.21; −0.04
 Quadratic
NK cell (% HLA DR+/CD38+) χ2(1) = 2.3c 0.129
 Linear −0.05 (0.03) −0.11; 0.01
 Quadratic
CD56dim FcRγ NK cells χ2(1) = 2.5 0.115
 Linear −0.22 (0.14) −0.50; 0.05
 Quadratic
T cell activation
CD4+ T cell (% HLA DR+/CD38+) χ2(2) = 32.5b <0.001
 Linear −0.23 (0.05) −0.34; −0.13
 Quadratic 0.004 (0.002) 0.0004; 0.01
CD8+ T cell (% HLA DR+/CD38+) χ2(2) = 68.1 <0.001
 Linear −1.08 (0.16) −1.38; −0.77
 Quadratic 0.03 (0.01) 0.01; 0.04
Monocyte subsets
% Classical monocytes χ2(2) = 28.5 <0.001
 Linear 1.49 (0.39) 0.72; 2.26
 Quadratic −0.07 (0.03) −0.13; −0.01
% Intermediate monocytes χ2(2) = 61.2 <0.001
 Linear −0.78 (0.11) −1.00; −0.56
 Quadratic 0.03 (0.01) 0.02; 0.05
% Non-classical monocytes χ2(1) = 10.9 0.001
 Linear −0.30 (0.09) −0.48; −0.12
 Quadratic

Table shows regression coefficient (b), SE, 95% confidence intervals (95% CI), Wald tests (Wald χ2) and probability value (p-value).

aLatent growth-curve modeling specifying a random intercept (baseline marker level) and coefficient (linear time) and unstructured covariance terms for random effects.

bIntercept and slope covariance term not able to be computed for this model.

cRandom intercept model only—random coefficient model did not converge.

Note: Where a quadratic coefficient is not shown for an outcome, nested likelihood ratio tests did not reject the null hypothesis that the functional form of time on cART was linear.