Predictive model of mortality based on logistic regression of laboratory indicators

Objective. To develop and validate a mathematical model for predicting the risk of mortality based on patients’ laboratory indicators from blood and urine tests. Materials and methods. Clinical data of patients, including laboratory test results of blood and urine, were analyzed. Mathematical modeling and statistical analysis methods were used to develop the predictive model. Results. A predictive model demonstrating high accuracy in assessing the risk of adverse outcomes was developed. The model is based on readily available laboratory indicators and can be easily integrated into clinical practice. Conclusion. The proposed mathematical model represents an effective tool for early diagnosis of mortality risk. The practical significance of the study lies in the potential application of the developed model across various fields of clinical medicine to optimize the diagnostic and therapeutic process