DIAGNOSIS, RISK FACTORS, AND MULTIFACTORIAL MODEL FOR PREDICTING SEVERE LEPTOSPIROSIS
DOI:
https://doi.org/10.32782/2226-2008-2026-1-3Keywords:
leptospirosis, diagnosis, prediction, multifactorial modelAbstract
Introduction. Leptospirosis is a common zoonotic infection with high mortality. Despite increasing incidence, diagnosis and severity assessment remain inadequate due to varied clinical signs and limitations of current diagnostic methods. The aim of this study was to stratify the risk coefficient for an unfavorable course of leptospirosis based on a developed mathematical prediction model. Materials and methods. Clinical and laboratory data from 60 leptospirosis patients were analyzed using multifactorial regression to identify independent predictors of severe disease. Results. Significant predictors of severe leptospirosis included: seasonality, initial diagnosis, vomiting, calf pain, serovar type, age, delayed antibiotic therapy, hepatosplenomegaly, neutrophil count, ESR, and urinary changes (diuresis, erythrocytes, protein). The regression model showed high prognostic value for early detection of patients at risk of severe disease. Conclusions. The proposed algorithm and model enable reliable early assessment of severe leptospirosis risk, support timely treatment, and help prevent complications and reduce mortality.
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