Diagnostic indicators including conjunctivitis, platelet count, and monocyte count can be used to reliably distinguish between Zika virus and dengue fever, according to new findings published in Emerging Infectious Diseases.
The co-circulation of Zika virus and dengue fever poses a formidable challenge to healthcare providers, as the 2 viruses present with similar signs and symptoms including fever, rash, and myalgia. To determine whether the 2 viruses have any symptoms, signs, or basic laboratory findings that could help distinguish them from one another, the authors conducted a case-control study at an academic center in Singapore. The cohort included 121 patients, of whom 34 had Zika virus and 87 had dengue fever.
Conjunctivitis was strongly indicative of Zika virus (odds ratio [OR], 30.1; 95% CI, 9.57–94.44; P <.001), whereas fever (OR, 0.05; 95% CI, 0.01-0.47; P =.008), myalgia (OR, 0.20; 95% CI, 0.08-0.48; P <.001), and headache (OR, 0.12, 95% CI, 0.05-0.30; P <.001) were all more pronounced in the dengue fever group. Thrombocytopenia (median platelet count, 132 × 109/µL; range, 15-386 × 109/µL) and monocytosis (median monocyte count, 0.50 × 109/µL; range, 0.11-1.70 × 109/µL) were associated with dengue fever, whereas individuals with Zika tended to have normal platelet (median, 225 × 109/µL; range, 128-326 × 109/µL; P <.001) and monocyte (median, 0.35 × 109/µL; range, 0.13-1.00 × 109/µL; P =.021) counts.
Further, although individuals with Zika did not have significant evidence of hepatic abnormalities, those with dengue infections demonstrated biochemical evidence of hepatic alanine aminotransferase (ALT) and aspartate aminotransferase (AST) levels >2 times the upper reference limit (ALT: median, 51.0, range, 12-465 U/L; AST: median, 65; range, 20-720 U/L). The reference range for ALT is 10 to 70 U/L, and for AST it is 10 to 50 U/L.
In a validation cohort, conjunctivitis and normal platelet and monocyte counts resulted in a combined area under the receiving operating characteristic curve of 0.90, with a positive predictive value of 83% and negative predictive value of 87%, for identifying Zika virus in patients.
“Distinguishing Zika virus from [dengue infection] on clinical grounds remains daunting, and it will be ideal to validate these derived indices in a prospective patient cohort,” write the investigators.
Yan G, Pang L, Cook AR, et al. Distinguishing Zika and dengue viruses through simple clinical assessment, Singapore. Emerg Infect Dis. 2018;24(8):1565-1568.