Standard determination of clinical case of measles in conditions of its elimination

Abstract

Objective. To develop a standard determination of a clinical case of measles in conditions of its elimination.

Materials and methods. The study included 28 patients with measles (main group) and 30 with infectious mononucleosis (comparison group). By means of correlation analysis, among clinicolaboratory indicators there was determined a list of clinical signs, which statistically significantly were more often identified in patients with measles compared to patients with infectious mononucleosis. The mathematical model was developed using the method of logistic regression, which helped to single out the most qualitative binary classifiers directly connected with diagnostic probability of measles. Sensitivity and specificity of the obtained model were calculated. For statistical processing IBM SPSS Statistics 26 was used.

Results. To carry out a standard determination of a clinical case of measles with the presence of combined clinicolaboratory symptoms, the mathematical model was developed, described by the following equation: р=1/(1+е^-z) · 100, where z=71,7+36,8 · Х _{dry cough} +53,5 · Х _{maculo-papular rash} +17,6 · Х _{damages of eyes in the form of conjunctivitis and/or sclerite.} Taking into account the regression coefficient values, such clinicolaboratory symptoms as maculo-papular rash, damages of eyes in the form of conjunctivitis and/or sclerite were directly connected with diagnostic probability of the diagnosis “Measles”. The determination coefficient of the obtained model was R² = 0,97, p < 0,001. The sensitivity of the model was 96.4 %, specificity – 100 %, efficiency – 98 %.

Conclusions. In conditions of measles elimination, the combination of maculo-papular rash, damages of eyes in the form of conjunctivitis and/or sclerite allows confirming the clinical diagnosis of measles with the probability of 98 %.

Keywords

measles / standard determination of clinical case / mathematical model

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RIGHTS & PERMISSIONS

Semerikov V.V., Vorobyova N.N., Postanogova N.O., Okishev M.A., Uvarova E.Y., Nebolsina A.P., Metelkina N.A., Sofronova L.V., Nikolaev A.V.