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Vlasov A.P.

Ogarev Mordovia State University

Markin O.V.

Ogarev Mordovia State University

Vlasova T.I.

Ogarev Mordivia State University

Muratova T.A.

Ogarev National Research Mordovian State University

Alagulov A.A.

Ogarev National Research Mordovian State University

S.T.A. Al-Anbari

Ogarev National Research Mordovian State University

Dukhovnova K.M.

Penza State University

Kormishkin A.E.

Ogarev National Research Mordovian State University

Predicting the course of urgent abdominal diseases based on intensity of catabolic phenomena

Authors:

Vlasov A.P., Markin O.V., Vlasova T.I., Muratova T.A., Alagulov A.A., S.T.A. Al-Anbari, Dukhovnova K.M., Kormishkin A.E.

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Journal: Pirogov Russian Journal of Surgery. 2024;(4): 44‑48

DOI: 10.17116/hirurgia202404144

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To cite this article:

Vlasov AP, Markin OV, Vlasova TI, et al. . Predicting the course of urgent abdominal diseases based on intensity of catabolic phenomena. Pirogov Russian Journal of Surgery. 2024;(4):44‑48. (In Russ.)
https://doi.org/10.17116/hirurgia202404144

Подписка 2025 (Pirogov Russian Journal of Surgery)
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OBJECTIVE

To develop a highly informative method for predicting the course of early postoperative period in urgent abdominal surgery based on indicators of lipid metabolism.

MATERIAL AND METHODS

We analyzed 113 patients with acute surgical abdominal disease including 56 (49.6%) ones with acute appendicitis complicated by peritonitis, 23 (20.4%) ones with acute intestinal obstruction complicated by peritonitis and 34 (30.0%) patients with acute moderate pancreatitis (early phase). Leukocyte count, malondialdehyde, medium-weight molecules and lipid composition (phospholipid lysoforms) were analyzed throughout a 5-day period. Considering these data, we developed a method for predicting the course of early postoperative period (patent).

RESULTS

Original method is highly effective in predicting the course of early postoperative period in urgent abdominal diseases. Sensitivity and specificity of this method for acute abdominal diseases complicated by acute peritonitis are 94.7% and >86.3%, for acute pancreatitis — 92.7 and 85.4%, respectively.

CONCLUSION

Efficacy of original method is determined by analysis of catabolic phenomena, i.e. indicators of tissue destruction. Of course, assessment of endogenous intoxication whose toxins are components of catabolic (membrane-destructive) processes is essential.

Keywords:

acute abdominal diseases
prognosis
lipids
toxins

Authors:

Vlasov A.P.

Ogarev Mordovia State University

Markin O.V.

Ogarev Mordovia State University

Vlasova T.I.

Ogarev Mordivia State University

Muratova T.A.

Ogarev National Research Mordovian State University

Alagulov A.A.

Ogarev National Research Mordovian State University

S.T.A. Al-Anbari

Ogarev National Research Mordovian State University

Dukhovnova K.M.

Penza State University

Kormishkin A.E.

Ogarev National Research Mordovian State University

Received:

09.12.2023

Accepted:

10.01.2024

List of references:

  1. Vlasov AP, Solomakha AA, Ryazantsev VE, Muratova TA, Vlasova TI. Forecasting the course of urgent surgical diseases. Saransk. 2022. (In Russ.).
  2. Dengaev AM, Daiziev ZM. Application of a structural approach to the design of an intelligent disease forecasting system. Fundamental and applied problems of engineering and technology. 2022;351(1):154-158. (In Russ.).
  3. Bagateliya ZA, Grekov DN, Komarova AG, Kulushev VM, Sokolov NYu, Kuts IN, Lebedko MS. Integral scales in assessing the risk of postoperative morbidity and mortality. Pirogov Russian Journal of Surgery. 2023;11:25-33. (In Russ.). https://doi.org/10.17116/hirurgia202311125
  4. Ivanusa SYa, Lazutkin MV, Galchenko MI, Chebotar AV, Kulagin VI. Prognostic model of the course of acute pancreatitis. Bulletin of the Russian Military Medical Academy. 2020;71(3):103-107. (In Russ.).
  5. Lazarenko VA, Antonov AE. Assessment of the quality of functioning of artificial neural networks with logical outputs in the diagnosis of diseases of the hepatopancreatoduodenal zone. Kazan Medical Journal. 2017;98(6):928-932. (In Russ.).
  6. Abdelwahab M, Lynch CD, Schneider P, Thung S, Costantine MM, O’Malley D, Landon MB, Pawlik TM, Venkatesh KK. Postoperative complications after non-obstetric surgery among pregnant patients in the National Surgical Quality Improvement Program, 2005-2012. American Journal of Surgery. 2022;223(2):364-369.  https://doi.org/10.1016/j.amjsurg.2021.04.002
  7. Klimuk SA. The role of leukocyte intoxication indices in assessing the severity, risks and response to erysipelas treatment in the practice of a surgeon. Medicus. 2023;52(4):59-66. (In Russ.).
  8. Le Manach Y, Collins G, Rodseth R, Le Bihan-Benjamin C, Biccard B, Riou B, Devereaux PJ, Landais P. Preoperative Score to Predict Postoperative Mortality (POSPOM): Derivation and Validation. Anesthesiology. 2016;124(3):570-579.  https://doi.org/10.1097/ALN.0000000000000972
  9. Sutton R, Bann S, Brooks M, Sarin S. The Surgical Risk Scale as an improved tool for risk-adjusted analysis in comparative surgical audit. British Journal of Surgery. 2002;89(6):763-768.  https://doi.org/10.1046/j.1365-2168.2002.02080.x
  10. Vlasov AP, Trofimov VA, Vlasova TI, Vlasov PA, Myshkina NA. Systemic membrane-stabilizing distress syndrome in surgery: concept, pathogenesis, diagnosis. Pirogov Russian Journal of Surgery. 2019;5:25-30. (In Russ.). https://doi.org/10.17116/hirurgia201905125

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