How can we detect HIV during the acute or primary stage of infection?

A Simple Symptom Score for Acute Human Immunodeficiency Virus Infection in a San Diego Community-Based Screening Program

Background

Treatment of acute human immunodeficiency virus (HIV) infection (AHI) decreases transmission and preserves immune function, but AHI diagnosis remains resource intensive. Risk-based scores predictive for AHI have been described for high-risk groups; however, symptom-based scores could be more generalizable across populations.

Methods

Adults who tested either positive for AHI (antibody-negative, HIV nucleic acid test [NAT] positive) or HIV NAT negative with the community-based San Diego Early Test HIV screening program were retrospectively randomized 2:1 into a derivation and validation set. In the former, symptoms significant for AHI in a multivariate logistic regression model were assigned a score value (the odds ratio [OR] rounded to the nearest integer). The score was assessed in the validation set using receiver operating characteristics and areas under the curve (AUC). An optimal cutoff score was found using the Youden index.

Results

Of 998 participants (including 261 non-men who have sex with men [MSM]), 113 had AHI (including 4 non-MSM). Compared to HIV-negative cases, AHI cases reported more symptoms (median, 4 vs 0; P < .01). Fever, myalgia, and weight loss were significantly associated with AHI in the multivariate model and corresponded to 11, 8, and 4 score points, respectively. The summed score yielded an AUC of 0.85 (95% confidence interval [CI], .77-.93). A score of ≥11 was 72% sensitive and 96% specific (diagnostic OR, 70.27).

Conclusions

A 3-symptom score accurately predicted AHI in a community-based screening program and may inform allocation of resources in settings that do not routinely screen for AHI.