Flowchart of the study population.

<p>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).</p

Bivariable and multivariable analyses of predictors of CHIK+ status using logistic regression, and the corresponding weighted point values of the score.

<p>Bivariable and multivariable analyses of predictors of CHIK+ status using logistic regression, and the corresponding weighted point values of the score.</p

Baseline characteristics of subjects with suspected Chikungunya virus infection.

<p>Baseline characteristics of subjects with suspected Chikungunya virus infection.</p

Do Two Screening Tools for Chikungunya Virus Infection that were Developed among Younger Population Work Equally as Well in Patients Aged over 65 Years?

<div><p>Background</p><p>Chikungunya is an endemo-epidemic infection, which is still considered as an emerging public health problem. The aim of this study was to evaluate in a 65+ population, the accuracy of two chikungunya screening scores that were developed in younger people.</p><p>Methods</p><p>It was performed in the Martinique University Hospitals from retrospective cases. Patients were 65+, admitted to acute care units, for suspected Chikungunya virus infection (CVI) in 2014, with biological testing using Reverse Transcription Polymerase Chain Reaction. Mayotte tool and Reunion Island tool were also computed. Sensitivity, specificity, positive predictive value, negative predictive value, and Youden’s statistic were calculated.</p><p>Results</p><p>In all, 687 patients were included, 68% with confirmed CVI, and 32% with laboratory-unconfirmed CVI. Fever (73.1%) and arthralgia (51.4%) were the most frequent symptoms. Sensitivity ranged from 6% (fever+headache) to 49% (fever+polyarthralgia); and Youden’s index ranged from 1% (fever + headache) to 30% (fever+polyarthralgia). PPV and NPV ranged from 70% to 95%, and from 32% to 43%, respectively.</p><p>Conclusion</p><p>Performances were very poor for both tools, although specificity was good to excellent. Our results suggest that screening scores developed in young population are not accurate in identifying CVI in older people.</p></div

Clinical and biological characteristics at admission to hospital of subjects declaring symptoms of Chikungunya virus infection.

<p>Clinical and biological characteristics at admission to hospital of subjects declaring symptoms of Chikungunya virus infection.</p

Diagnostic performances of the Mayotte tool and the Reunion Island tool in the study population.

<p>Diagnostic performances of the Mayotte tool and the Reunion Island tool in the study population.</p

Baseline characteristics of the 1,415 PLHIV aged 60 years or more from the Dat’AIDS cohort.

<p>Baseline characteristics of the 1,415 PLHIV aged 60 years or more from the Dat’AIDS cohort.</p

Five-year Kaplan-Meier survival probabilities among each risk group.

<p>Five-year Kaplan-Meier survival probabilities among each risk group.</p

Model discrimination: Hazard ratio across risk groups.

<p>Model discrimination: Hazard ratio across risk groups.</p

Assessment of model calibration: Observed (Kaplan Meier, black) versus predicted (Cox, gray) survival curves.

<p>Assessment of model calibration: Observed (Kaplan Meier, black) versus predicted (Cox, gray) survival curves.</p