Trends and Adaptive Optimal Set Points of CD4(+) Count Clinical Covariates at Each Phase of the HIV Disease Progression

In response to invasion by the human immunodeficiency virus (HIV), the self-regulatory immune system attempts to restore the CD4(+) count fluctuations. Consequently, many clinical covariates are bound to adapt too, but little is known about their corresponding new optimal set points. It has been reported that there exist few strongest clinical covariates of the CD4(+) count. The objective of this study is to harness them for a streamlined application of multidimensional viewing lens (statistical models) to zoom into the behavioural patterns of the adaptive optimal set points. We further postulated that the optimal set points of some of the strongest covariates are possibly controlled by dietary conditions or otherwise to enhance the CD4(+) count. This study investigated post-HIV infection (acute to therapy phases) records of 237 patients involving repeated measurements of 17 CD4(+) count clinical covariates that were found to be the strongest. The overall trends showed either downwards, upwards, or irregular behaviour. Phase-specific trends were mostly different and unimaginable, with LDH and red blood cells producing the most complex CD4(+) count behaviour. The approximate optimal set points for dietary-related covariates were total protein 60–100 g/L (acute phase), <85 g/L (early phase), <75 g/L (established phase), and >85 g/L (ART phase), whilst albumin approx. 30–50 g/L (acute), >45 g/L (early and established), and <37 g/L (ART). Sodium was desirable at approx. <45 mEq/L (acute and early), <132 mEq/L (established), and >134 mEq/L (ART). Overall, desirable approximates were albumin >42 g/L, total protein <75 g/L, and sodium <137 mEq/L. We conclude that the optimal set points of the strongest CD4(+) count clinical covariates tended to drift and adapt to either new ranges or overlapped with the known reference ranges to positively influence the CD4(+) cell counts. Recommendation for phase-specific CD4(+) cell count influence in adaptation to HIV invasion includes monitoring of the strongest covariates related to dietary conditions (sodium, albumin, and total protein), tissue oxygenation (red blood cells and its haematocrit), and hormonal control (LDH and ALP).