A Simple Symptom Score for Acute HIV Infection in a San Diego Community Based Screening Program

Abstract

Background

Treatment of acute 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 Early Test HIV screening program in San Diego 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 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 cut-off score was found using Youden's index.

Results

Of 998 participants (including 737 men who have sex with men (MSM), 149 non-MSM men, 109 ciswomen and 3 trans women), 113 had AHI (including 109 MSM). Compared to HIV-negative cases, AHI cases reported more symptoms (median 4 vs 0, p<0.01). 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 AUC of 0.85 (95%CI 0.77-0.93). A score of ≥11 was 72% sensitive, 96% specific with diagnostic odds ratio of 70.27 (95%CI 28.14-175.93).

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.