СRITERIA FOR ASSESSING ENDOGENOUS INTOXICATION IN PATIENTS WITH MULTIPLE PERITONITIS

Area of Science:

• Biochemistry
• Surgical Pathology
• Clinical Diagnostics

Background:

• Generalized peritonitis (RP) is a severe condition often associated with significant morbidity and mortality.
• Endogenous intoxication, a state of systemic toxicity due to the body's own metabolic byproducts, plays a critical role in RP progression.
• Malondialdehyde (MDA), a secondary product of lipid peroxidation, serves as a marker for oxidative stress and cellular damage.

Purpose of the Study:

• To evaluate the diagnostic and prognostic value of malondialdehyde (MDA) levels in various biological media for patients with generalized peritonitis (RP).
• To assess the correlation between MDA levels and the severity of RP, as classified by the Mannheim Peritoneal Index (MPI).
• To determine if MDA levels can predict disease course and patient outcomes, including mortality.

Main Methods:

• The study analyzed surgical treatment data from 60 patients with RP, categorized by MPI severity (I, II, III).
• MDA levels were measured in blood serum, peritoneal exudate, and urine.
• A control group of 15 healthy individuals provided baseline biochemical parameters.

Main Results:

• Patients with a lethal outcome exhibited significantly higher average MDA levels in blood serum and peritoneal exudate compared to recovered patients.
• Pre-operative MDA levels in non-survivors were substantially elevated (190% in blood serum, 110% in urine) compared to the norm.
• Recovered patients showed significantly higher MDA levels in urine (300%) compared to the norm, suggesting altered elimination pathways.

Conclusions:

• Elevated MDA in blood serum and peritoneal exudate, coupled with reduced urinary MDA excretion post-surgery, are unfavorable prognostic indicators in RP.
• These findings suggest persistent endogenous intoxication and an increased risk of mortality in such patients.
• MDA measurement holds diagnostic significance for assessing RP severity and predicting patient prognosis.