Clinical Predictors of Monkeypox Diagnosis: A Case-Control Study in a Nonendemic Region during the 2022 Outbreak

Microorganisms. 2023 Sep 11;11(9):2287. doi: 10.3390/microorganisms11092287.

Abstract

Monkeypox (Mpox) is an emerging zoonotic disease with the potential for severe complications. Early identification and diagnosis are essential to prompt treatment, control its spread, and reduce the risk of human-to-human transmission. This study aimed to develop a clinical diagnostic tool and describe the clinical and sociodemographic features of 19 PCR-confirmed Mpox cases during an outbreak in a nonendemic region of northwestern Mexico. The median age of patients was 35 years, and most were male. Mpox-positive patients commonly reported symptoms such as fever, lumbago, and asthenia, in addition to experiencing painful ulcers and a high frequency of HIV infection among people living with HIV (PLWH). Two diagnostic models using logistic regression were devised, with the best model exhibiting a prediction accuracy of 0.92 (95% CI: 0.8-1), a sensitivity of 0.86, and a specificity of 0.93. The high predictive values and accuracy of the top-performing model highlight its potential to significantly improve early Mpox diagnosis and treatment in clinical settings, aiding in the control of future outbreaks.

Keywords: Mpox epidemiology; ROC curves; case–control study; clinical diagnosis; clinical predictors; logistic regression; monkeypox (Mpox); nonendemic region; outbreak.

Grants and funding

This research received no external funding, and the APC was funded by the PAIPC (Programa de apoyo e incentivos a publicaciones científicas, acronyms in spanish) program of CONFÍE (Coordinación General para el Fomento a la Investigación Científica e Innovación del Estado de Sinaloa).