Cross-Sectional Study of Clinical Predictors of Coccidioidomycosis, Arizona, USA
| Autor: | Ferris A. Ramadan, Katherine D. Ellingson, Robert A. Canales, Edward J. Bedrick, John N. Galgiani, Fariba M. Donovan |
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| Jazyk: | angličtina |
| Rok vydání: | 2022 |
| Předmět: | |
| Zdroj: | Emerging Infectious Diseases, Vol 28, Iss 6, Pp 1091-1100 (2022) |
| Druh dokumentu: | article |
| ISSN: | 1080-6040 1080-6059 |
| DOI: | 10.3201/eid2806.212311 |
| Popis: | Demographic and clinical indicators have been described to support identification of coccidioidomycosis; however, the interplay of these conditions has not been explored in a clinical setting. In 2019, we enrolled 392 participants in a cross-sectional study for suspected coccidioidomycosis in emergency departments and inpatient units in Coccidioides-endemic regions. We aimed to develop a predictive model among participants with suspected coccidioidomycosis. We applied a least absolute shrinkage and selection operator to specific coccidioidomycosis predictors and developed univariable and multivariable logistic regression models. Univariable models identified elevated eosinophil count as a statistically significant predictive feature of coccidioidomycosis in both inpatient and outpatient settings. Our multivariable outpatient model also identified rash (adjusted odds ratio 9.74 [95% CI 1.03–92.24]; p = 0.047) as a predictor. Our results suggest preliminary support for developing a coccidioidomycosis prediction model for use in clinical settings. |
| Databáze: | Directory of Open Access Journals |
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