PERSONALIZED MATHEMATICAL MODEL OF OUTCOME IN PATIENTS WITH TRAUMATIC BRAIN INJURIES
Introduction. Previously, determining the prognosis based on epidemiological data was the key to informing about the treatment of patients [1,2], but modern prognostic models based on demographic data, clinical examination, radiological imaging have limited prognostic ability [3,4]. At the same time, a reliable prognosis of the outcome of the disease with modern highly specific and sensitive markers is of great clinical importance [5,6].
Aim. Developing a method for mathematical modeling of the outcome of acute traumatic cerebral injuries based on complex clinical, laboratory, and neuroimaging studies with integral scales for assessing neurological status.
Materials and methods. The studies were conducted in 79 patients with various acute traumatic brain injuries. All patients underwent a detailed clinical and neurological examination using the Glasgow Coma Scale (GCS), computed tomography, X-ray, ultrasound, hematological and biochemical examinations. To identify dependent and independent risk factors for death in the acute period of injury, a one-dimensional and multidimensional regression analysis was performed. To determine the predictive variables, an analysis of the receiver's performance characteristics (ROC) was performed with the calculation of sensitivity and specificity.
The results obtained. We found that the strongest predictors of a poor outcome were - AVDO2 > 52% of the left side (OR) - 9.01 (95% СI: 3.45 - 23.51), p<0.0001; AVDO2 >52%, right side (OR) - 5.71 (95% СI: 2.31-14.16), p=0.0002. Lactate level >3.3 mmol/l (OR) - 4.30 (95% СI: 1.61-11.51), p=0.0036. With an increase in S100ß 0.1 mcg/l> (OR) - 3.77 (95% СI:1.63-8.73), p=0.0020 and NSE ng/ml>12.5 (OR) - 2.69 (95% СI:1.14-6.36), p=0.0240; SAD>169 mmHg (OR) - 3.27 (95% СI:1.26-8.48), p=0.0146; at the age of > 65 years (OR) - 2.43 (95% СI: 1.04-5.68), p=0.0406. The measure of reliability of the model obtained by the criterion of pseudo R2, Nagelkerke - 627.3% and logLikelihood - 112.7.
Сonclusion. These data were used to develop a mathematical model that allows predicting the outcome of the disease. The best predicted value of the model had a cut-off point of 99.13%, AuROC-0.912; Se-93.26%; Sp-80.00%; NPV-94.55%; PPV-76.15%.
Жанслу Н. Саркулова1, https://orcid.org/0000-0001-6669-1244
Айнур Б. Токшилыкова1, https://orcid.org/0000-0003-4416-0180
Марат Н. Саркулов1, https://orcid.org/0000-0003-1165-9049
Марат Х. Жанкулов1, https://orcid.org/0000-0002-9184-7316
Ботагоз М. Калиева1, https://orcid.org / 0000-0002-0143-0761
Камила Р. Даниярова1, https://orcid.org/0000-0002-6145-1839
Жулдыз Ж. Жулдызбаева1, https://orcid.org/0009-0004-5743-6240
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Sarkulova Zh.N., Tokshilykova A.B., Sarkulov M.N., Zhankulov M.B., Kalieva B.M., Daniyarova K.R., Zhuldyzbaeva Zh.Zh. Personalized mathematical model of outcome in patients with traumatic brain injuries // Nauka i Zdravookhranenie [Science & Healthcare]. 2024. Vol.26 (4), pp. 92-98. doi 10.34689/SH.2024.26.4.012Похожие публикации:
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