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Table 4 The joint effects of time-varying CD4 cell counts levels and orthogonal CD4 cell counts variables on the viral load transition rates Markov model

From: Markov modelling of viral load adjusting for CD4 orthogonal variable and multivariate conditional autoregressive mapping of the HIV immunological outcomes among ART patients in Zimbabwe

Transition
Rate λij
Baseline Log-linear
βij
Hazard
exp(βij)
Time-varying CD4 cell counts levels CD4states, k
  λij(VL, 0) CD4states, k \( {P}_{CD4(k)}^{\ast } \) CD4states, k \( {P}_{CD4(k)}^{\ast } \) State 1 State 2 State 3
State 1 to 2 λ12 0.0286 0.0434 −0.3383 1.0443 0.713 0.0305 0.0321 0.0337
State 1 to 3 λ13 0.0025 − 1.0072 − 0.3336 0.3652 0.7163 0.0167 0.0059 0.0021
State 1 to 4 λ14 0.0082 0.0288 0.0247 1.0292 1.0243 0.0078 0.0081 0.0083
State 1 to 5 λ15 0.0159 − 0.7155 −1.1045 0.4889 0.3312 0.1774 0.0422 0.0206
State 2 to 1 λ21 0.0161 − 0.3926 − 0.2849 0.6762 0.7521 0.0351 0.0237 0.0161
State 2 to 3 λ23 0.0008 0.2065 0.6052 1.2293 1.8315 0.0004 0.0005 0.0006
State 2 to 4 λ24 0.0057 0.0725 −0.2381 1.0752 0.7881 0.0056 0.0061 0.0066
State 2 to 5 λ25 0.0305 − 0.7458 − 0.9312 0.4744 0.3941 0.3372 0.0759 0.0361
State 3 to 1 λ31 0.0266 − 0.9855 −0.7571 0.3733 0.4691 0.1926 0.0728 0.0275
State 3 to 2 λ32 0.0035 − 1.4092 −2.8306 0.2443 0.0589 0.1359 0.0324 0.0077
State 3 to 4 λ34 0.0272 − 0.0811 0.3475 0.9221 1.4155 0.0255 0.0237 0.0221
State 3 to 5 λ35 0.0343 − 0.5176 0.0947 0.5959 1.0993 0.1273 0.0457 0.0273
  1. model information: −2*log-likelihood = 6930.71; Akaike’s information criterion = 7002.71