Related Experiment Video
Updated: Feb 7, 2026

Chronic, Acute, and Reactivated HIV Infection in Humanized Immunodeficient Mouse Models
Published on: December 3, 2019
Predicting the outcomes of human immunodeficiency virus infection. How well are we doing
1Department of Medicine, Baylor College of Medicine, Veterans Affairs Medical Center, Houston, TX.
Abstract:
An important determinant of patient outcomes is illness severity, which must be classified to guide clinical decision making and evaluate the effectiveness of diagnostic and therapeutic interventions. Currently, no widely accepted framework for grading illness severity in human immunodeficiency virus-infected patients exists. The best known classification systems for human immunodeficiency virus infection (Centers for Disease Control and Prevention; Walter Reed) are not based on illness severity, and provide stages that are not all inclusive so that a large number of persons cannot be classified (Walter Reed). Although much previous research has focused on individual prognostic factors (oral thrush, CD4 cell count, serum beta 2-microglobulin), little attention has been given to incorporating these factors into illness severity scales that are easy to use in clinical settings. In addition, despite the progressive functional disability of human immunodeficiency virus-infected individuals, few of the existing approaches to illness severity classification have examined the contribution of functional status. We urge investigators to develop clinically sensible severity scales that are easy to use. Such scales will considerably improve existing approaches that tend to rely solely on the CD4 cell count and do not take into account the known prognostic effects of other variables.
More Related Videos
11:14Ex Vivo Infection of Human Lymphoid Tissue and Female Genital Mucosa with Human Immunodeficiency Virus 1 and Histoculture
Published on: October 12, 2018
11:19Pairwise Growth Competition Assay for Determining the Replication Fitness of Human Immunodeficiency Viruses
Published on: May 4, 2015
Related Concept Videos
Predicting Reaction Outcomes
Immunodeficiency Diseases
There are three main causes of immunodeficiency...
What are Viruses?
Predicting Molecular Geometry
Outcomes of Glycolysis
Cellular respiration can occur aerobically (with oxygen) or anaerobically (without oxygen). In the presence of oxygen, cellular respiration starts with glycolysis and continues with pyruvate...
Prediction Intervals
However, the point estimate is most likely not the exact value of the population parameter, but close to it. After calculating point estimates, we construct interval estimates, called confidence intervals or prediction intervals. This prediction interval comprises a range of values unlike the point estimate and is a better predictor of the observed sample value, y.