Background: Human granulocytic anaplasmosis (HGA) is a vector-borne natural focal disease that is not officially registered in Ukraine. The first 13 cases of HGA in adults in Ukraine were identified in 2007. The purpose of our study was to develop a predictive model of HGA based on clinical and laboratory characteristics to develop a three-level standard case definition of HGA. Materials and Methods: Researchers examined 498 patients with suspected tick-borne infections and carried out a retrospective clinical and epidemiological analysis of 60 cases recruited from Lviv regional infectious disease hospitals. Logistic regression was used to create a model of the probability of the diagnosis of HGA depending on the presence of certain clinical and laboratory factors that, when examined, together may help to confirm a case of HGA. For logistic regression, eight clinical and laboratory factors were selected: history of tick bite, hyperthermia, signs of pharyngitis, changes in chest X-ray picture (enhancement of the pulmonary pattern and enlargement of the lung root boundaries), increased bilirubin (˃21 μmol/L), increased alanine aminotransferase (ALT ˃36 U/L), erythema migrans, and detected Lyme disease. Results: In the presence of all eight factors, the probability of HGA is 95.7%. When the five main signs are absent-signs of pharyngitis, changes in chest X-ray picture, increased bilirubin and ALT, and a history of tick bite-the probability of HGA in the patient dramatically decreases to 6.8%, meaning that HGA might be excluded. Conclusions: Based on the analysis of epidemiological, clinical, and laboratory signs, criteria for establishing a suspected, probable, and confirmed diagnosis of HGA have been developed to improve diagnosis.
Keywords: Lyme disease; diagnosis; disease model; human granulocytic anaplasmosis; logistic regression.