Background
Chikungunya virus (CHIKV) diagnosis has become a challenge for primary care physicians in areas where the Zika virus and/or Dengue virus are present. Case definitions for the three arboviral infections overlap.
Conclusion
We developed a screening tool for CHIKV diagnosis using only clinical symptoms as well as proposed an algorithm to aid the primary care physician.
Methods
A cross-sectional analysis was carried out. A bivariate analysis was made using confirmed CHIKV infection as the outcome. Variables with significant statistical association were included in an agreement consensus. Agreed variables were analyzed in a multiple regression model. The area under the receiver operating characteristic (ROC) curve was calculated to determine a cut-off value and performance.
Results
295 patients with confirmed CHIKV infection were included. A screening tool was created using symmetric arthritis (4 points), fatigue (3 points), rash (2 points), and ankle joint pain (1 point). The ROC curve identified a cut-off value, and a score ≥ 5.5 was considered positive for identifying CHIKV patients with a sensibility of 64.4% and a specificity of 87.4%, positive predictive value of 85.5%, negative predictive value of 67.7%, area under the curve of 0.72, and an accuracy of 75%.