Microorganisms (Sep 2023)

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

  • Alberto Kousuke De la Herrán-Arita,
  • Cuitláhuac González-Galindo,
  • Gerardo Kenny Inzunza-Leyva,
  • Marco Antonio Valdez-Flores,
  • Claudia Desiree Norzagaray-Valenzuela,
  • Alejandro Camacho-Zamora,
  • José Candelario Batiz-Beltrán,
  • Francisco Javier Urrea-Ramírez,
  • Alejandra Romero-Utrilla,
  • Carla Angulo-Rojo,
  • Alma Marlene Guadrón-Llanos,
  • Verónica Judith Picos-Cárdenas,
  • Josué Camberos-Barraza,
  • Ángel Radamés Rábago-Monzón,
  • Juan Fidel Osuna-Ramos

DOI
https://doi.org/10.3390/microorganisms11092287
Journal volume & issue
Vol. 11, no. 9
p. 2287

Abstract

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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.

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