METHOD FOR PREDICTION OF DEVELOPING DISABILITY IN CHILDREN SUFFERED HAEMORRHAGIC STROKE Russian patent published in 2015 - IPC A61B5/00 

Abstract RU 2559927 C1

FIELD: medicine.

SUBSTANCE: 24 clinical-laboratory and past medical signs are detected and analysed in the children suffering the acute period: patient's sex, signs of intrauterine growth retardation syndrome in the past medical history, Apgar score, diagnosed hypoxia at discharge, thrombotic episodes in natural relatives aged up to 50 years, a suffered injury as a pre-stroke factor, signs of paresis/paralysis during the first 6 hours of the disease, detected stroke area, specified anaesthetic techniques used during the hospital stay, specified antibacterial therapy used during the hospital stay, specified transfusion therapy (red blood cells) used during the hospital stay, specified transfusion therapy (fresh frozen plasma) used during the hospital stay, symptoms of bulbar paresis/paralysis during the first 7 days of the disease, tongue deviation during the first 7 days of the disease, persistent symptoms of depression of consciousness by the 21st day of the hospital stay, the need for artificial pulmonary ventilation for more than 7 days, specified prescription of an anti-thrombotic therapy at discharge, acute red blood cell count as shown by general blood test - absolute value × 1012/l, acute white blood cell count as shown by general blood test - absolute value × 109/l, diagnosed thrombocytosis, detected high fibrinogen level and high levels as shown by ethanol gelation test or orthophenanthroline test, diagnosed fibrinolysis disorders as shown by thromboelastography. The detected values are inserted into a discriminator function, and its value is derived. The calculated discriminator function is used to predict if a disability needs to be assigned on completing the rehabilitation period following haemorrhagic stroke of childhood.

EFFECT: method enables predicting the developing disability in the children suffered haemorrhagic stroke in the acuity by detecting and analysing the past medical data and clinical-laboratory findings.

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RU 2 559 927 C1

Authors

L'Vova Ol'Ga Aleksandrovna

Gusev Vadim Venal'Evich

Tyrsin Aleksandr Nikolaevich

Shal'Kevich Leonid Valentinovich

Dates

2015-08-20Published

2014-08-26Filed