Scale probability of measles in primary care physician practice
Abstract
Darya Khavkina
Statement of the Problem: Measles is characterized by a high incidence of complications with predominance of pneumonia. There is an increase in the number of death cases among adult population. It is clear that interpreting clinical symptoms of measles is a difficult task in the daily practice of a physician. Methodology & Theoretical Orientation: We have analyzed the clinical picture and available anamnestic data since the first examination of 20 patients with subsequently confirmed laboratory methods of measles. The comparison group consisted of 20 patients to whom this diagnosis was made mistakenly. The assessment was carried out among the examined and hospitalized by the crews of Moscow ambulance station in 2016-2017. The patients were ranged in age from 6 months to 75 years old. Confirmation of the diagnosis was based on the clinical picture in dynamic combination with the serological method-by the presence of virus-specific antibodies (IgM). Anamnesis data and clinical symptoms, which allowed making a correct diagnosis, are represented by estimating scale of measles by the sum of points. Findings: High probability-8-10 points, average probability-5-7 points, unlikely-1-4 points. Scale is based on the data of anamnesis, anamnesis of life and clinical symptoms. Clinical criteria of the scale are: hyperthermia or subfebrility, cervical lymphadenopathy, enanthema, conjunctivitis, inflammatory changes in the respiratory tract, maculo-papular rash, phasing in the appearance of a rash. Patient anamnesis includes in children 2-5 years old, adults 20-35 and the absence of previous disease. Epidemiological history criteria: contact with a measles patient 7-21 days before the onset of symptoms, lack of vaccination or its prescription for more than 10 years. Conclusion & Significance: Our technique has demonstrated its effectiveness/ Scale allows us to reduce the time of the inspection, avoid mistakes in diagnosis and reduce non-core hospitalization.
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