The application of decision trees for constructing an algorithm for the differential diagnosis of zoonotic infections

To attempt to construct an algorithm using the routine epidemiological, clinical and laboratory data for the differential diagnosis of ixodid tick-borne borreliosis (ITBB) caused by Borrelia miyamotoi (BM-ITBB) and other zoonotic infections that are endemic in Russia. The investigation enrolled the...

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Bibliographic Details
Published inTerapevtic̆eskii arhiv Vol. 85; no. 11; pp. 21 - 26
Main Authors Platonov, A E, Sarkasian, D S, Maleev, V V
Format Journal Article
LanguageRussian
Published Russia (Federation) "Consilium Medicum" Publishing house 01.01.2013
Subjects
Adolescent
Adult
Aged
Algorithms
Animals
borrelia miyamotoi
Decision Trees
Diagnosis, Differential
differential diagnosis
Female
Follow-Up Studies
Humans
Incidence
ixodid tick-borne borreliosis
Male
Middle Aged
Retrospective Studies
Russia - epidemiology
Young Adult
Zoonoses - diagnosis
Zoonoses - epidemiology
zoonotic infections
Russia
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Summary:To attempt to construct an algorithm using the routine epidemiological, clinical and laboratory data for the differential diagnosis of ixodid tick-borne borreliosis (ITBB) caused by Borrelia miyamotoi (BM-ITBB) and other zoonotic infections that are endemic in Russia. The investigation enrolled the adult patients treated at the Republican Hospital for Infectious Diseases (Izhevsk) in 2010-2012 with diagnoses of BM-ITBB (n = 71), Lyme disease (n = 38), tick-borne encephalitis (TBE) (n = 25), and hemorrhagic fever with renal syndrome (n = 27). The Decision Tree procedure in IBM SPSS Statistics was used to analyze more than 65 variables characterizing a disease case. The final decision tree had 7 dichotomous fissions in accordance with the values of several indices (presence of erythema migrans, tick bite, goat's milk consumption, sweating, vertigo, nausea, abdominal pain, as well as blood concentrations of platelets, alanine aminotransferase, and count, and urea) and formed 8 terminal nodes. The proposed algorithm provides correct classification in 95% of disease cases. ITBB caused by B. miyamotoi can be successfully discriminated from other widespread zoonotic infections. Thus, practitioners have an additional opportunity to detect and diagnose the "new" infection BM-ITBB.
ISSN:0040-3660
2309-5342