Fig 1.
Flowchart of the study population.
In all 894 individuals who underwent RT-PCR testing (reference standard) were screened as potential eligible participants. Among them 207 were excluded because of missing files. So 687 were included in the study: 220 had negative RT-PCR and 467 had positive RT-PCR. Among the 220 individuals with negative RT-PCR, 14 had missing data for the score, 145 were classified as negative by both the score and the RT-PCR (true negative), and 61 were classified as positive by the score while being negative with the RT-PCR (false positive). Among the 467 individuals with positive RT-PCR, 10 had missing data for the score, 396 were classified as positive by both the score and the RT-PCR (true positive), and 61 were classified as negative by the score while being positive with the RT-PCR (false negative).
Table 1.
Baseline characteristics of subjects with suspected Chikungunya virus infection.
Table 2.
Bivariable and multivariable analyses of predictors of CHIK+ status using logistic regression, and the corresponding weighted point values of the score.
Fig 2.
Receiver operating characteristic of the screening score for Chikungunya virus infection.
The Receiver Operating Characteristic (ROC) Curve is a plot of the true positive rate (Sensitivity) against the false positive rate (1-Specificity). The cut-off value represents the point on the curve that maximizes both sensitivity and specificity. In this analysis, the cut-off value identified to best distinguish between CHIK+ and CHIK- patients was 12 points (★).
Table 3.
Diagnostic performances of the score dichotomised at 12 points*.