Вестник анестезиологии и реаниматологии (Aug 2022)

Predictive Risk Model for the Development of Encephalopathy in Patients with Nutritional Pancreatic Necrosis

  • V. S Mikhin,
  • N. Sh. Burchuladze,
  • A. S. Popov,
  • M. I. Turovets,
  • I. V. Mikhin,
  • A. V. Kitaeva

DOI
https://doi.org/10.21292/2078-5658-2022-19-4-22-30
Journal volume & issue
Vol. 19, no. 4
pp. 22 – 30

Abstract

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The objective: to develop a predictive model for assessing the risk of developing encephalopathy (EP) in patients with nutritional pancreatic necrosis.Subjects and Methods. A single-center prospective cohort study was conducted at Faculty Surgery Clinic of Volgograd State Medical University from 2010 to 2020. Logistic regression analysis was used to build a model for predicting the risk of developing EP.Results. A total of 429 patients were included in the study. It was determined that in the majority of patients EP manifested in the first three days after hospitalization. A statistically significant predictive model of correlation of the risk to develop EP with clinical and demographic variables showed that an increase in the severity of the patient's condition (according to the SOFA scale) by 1 point increased the risk by 1.9 times, and an increase in bilirubin levels by 1 μmol/l, and urea by 1 mmol/l increased the risk of AED by 8.0% and 28.0%, respectively. In non-alcoholic pancreatic necrosis, compared with the alcoholic genesis of the disease, and when using early (before day 3) enteral nutrition, there was a significant reduction in the risk of developing EP by 175.5% and 137% of cases. The specificity and sensitivity of the model were 78.7% and 82.8%, respectively.Conclusions. In nurtitional pancreatic necrosis, an increase in the severity of the patient's condition, alcoholic genesis of the disease, progression of signs of liver and kidney failure significantly increased the risk of developing EP. At the same time, early enteral nutrition contributed to a significant reduction in the risk of this complication. The presented predictive model is recommended to be used in routine clinical practice.

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