Background: The CD4 T cell count recovery in human immunodeficiency virus type 1 (HIV-1)-infected individuals receiving potent antiretroviral therapy (ART) shows high variability. We studied the determinants and the clinical relevance of incomplete CD4 T cell restoration.

Methods: Longitudinal CD4 T cell count was analyzed in 293 participants of the Swiss HIV Cohort Study who had had a plasma HIV-1 RNA load <1000 copies/mL for > or =5 years. CD4 T cell recovery was stratified by CD4 T cell count 5 years after initiation of ART (> or =500 cells/microL was defined as a complete response, and <500 cells/microL was defined as an incomplete response). Determinants of incomplete responses and clinical events were evaluated using logistic regression and survival analyses.

Results: The median CD4 T cell count increased from 180 cells/microL at baseline to 576 cells/microL 5 years after ART initiation. A total of 35.8% of patients were incomplete responders, of whom 47.6% reached a CD4 T cell plateau <500 cells/microL. Centers for Disease Control and Prevention HIV-1 disease category B and/or C events occurred in 21% of incomplete responders and in 14.4% of complete responders (P>.05). Older age (adjusted odds ratio [aOR], 1.71 per 10-year increase; 95% confidence interval [CI], 1.21-2.43), lower baseline CD4 T cell count (aOR, 0.37 per 100-cell increase; 95% CI, 0.28-0.49), and longer duration of HIV infection (aOR, 2.39 per 10-year increase; 95% CI, 1.19-4.81) were significantly associated with a CD4 T cell count <500 cells/microL at 5 years. The median increases in CD4 T cell count after 3-6 months of ART were smaller in incomplete responders (P<.001) and predicted, in conjunction with baseline CD4 T cell count and age, incomplete response with 80% sensitivity and 72% specificity.

Conclusion: Individuals with incomplete CD4 T cell recovery to <500 cells/microL had more advanced HIV-1 infection at baseline. CD4 T cell changes during the first 3-6 months of ART already reflect the capacity of the immune system to replenish depleted CD4 T lymphocytes.

Download full-text PDF

Source
http://dx.doi.org/10.1086/431484DOI Listing

Publication Analysis

Top Keywords

characteristics determinants
4
determinants clinical
4
clinical relevance
4
relevance cd4
4
cd4 cell
4
cell recovery
4
recovery =500
4
=500 cells/microl
4
cells/microl defined
4
defined complete
4

Similar Publications

Background: Kidney tumors, common in the urinary system, have widely varying survival rates post-surgery. Current prognostic methods rely on invasive biopsies, highlighting the need for non-invasive, accurate prediction models to assist in clinical decision-making.

Purpose: This study aimed to construct a K-means clustering algorithm enhanced by Transformer-based feature transformation to predict the overall survival rate of patients after kidney tumor resection and provide an interpretability analysis of the model to assist in clinical decision-making.

View Article and Find Full Text PDF

Cigarette smoke extract (CSE)-induced airway mucus hypersecretion and inflammation are prominent features of chronic obstructive pulmonary disease (COPD). As a factor associated with inflammation regulation, T cell immunoglobulin and mucin domain-1 (TIM-1) is found to be involved in various inflammatory disorders such as asthma and COPD. In this study, the GEO database provides two human COPD gene expression datasets (GSE67472, n = 62) along with the relevant controls (n = 43) for differentially expressed gene (DEG) analyses.

View Article and Find Full Text PDF

Background: Tumor size (TS) in pancreatic ductal adenocarcinoma (PDAC) is one of the most important prognostic factors. However, discrepancies between TS on preoperative images (TSi) and pathological specimens (TSp) have been reported. This study aims to evaluate the factors associated with the differences between TSi and TSp.

View Article and Find Full Text PDF

Analysis of the symmetry of the brain hemispheres at the level of individual structures and dominant tissue features has been the subject of research for many years in the context of improving the effectiveness of imaging methods for the diagnosis of brain tumor, stroke, and Alzheimer's disease, among others. One useful approach is to reliably determine the midline of the brain, which allows comparative analysis of the hemispheres and uncovers information on symmetry/asymmetry in the relevant planes of, for example, CT scans. Therefore, an effective method that is robust to various geometric deformations, artifacts, varying noise characteristics, and natural anatomical variability is sought.

View Article and Find Full Text PDF

In this paper, we propose a method to address the class imbalance learning in the classification of focal liver lesions (FLLs) from abdominal CT images. Class imbalance is a significant challenge in medical image analysis, making it difficult for machine learning models to learn to classify them accurately. To overcome this, we propose a class-wise combination of mixture-based data augmentation (CCDA) method that uses two mixture-based data augmentation techniques, MixUp and AugMix.

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!