DIAGNOSIS OF POSTOPERATIVE PELVIC ADHESIONS IN WOMEN WITH CHRONIC PELVIC PAIN ON THE BACKGROUND OF UNDIFFERENTIATED CONNECTIVE TISSUE DYSPLASIA

Abstract

Objective: To optimize the diagnostic accuracy of the postoperative adhesion process on the background of undifferentiated connective tissue dysplasia (UCTD) in patients with chronic pelvic pain Methods: The study conducted based on the Regional Clinical Hospital "Regional Clinical Perinatal Center", during which 60 patients diagnosed with tubal and peritoneal infertility. Patients divided into 2 groups based on a modified scoring scale of T. I. Kadurina. A study of genotype-phenotypic predictors carried out by analyzing the expression of UCTD by the method of profiling phenotypic markers, according to a modified scale of T.I. Kadurina. The study of polymorphism of VEGF 634 [rs2010963], IL6-174 [rs1800795] genes, and the evaluation of the adhesion process according to the classification system of the American Fertility Society, the genetic predisposition to the development of the adhesion process by the method of genotyping acetylation and pain intensity on a visual analogue scale. Results: Patients with the grade of UCTD scores equal to 10 or more according to the modified scale of T.I. Kadurina assigned to the high-risk group for pelvic peritoneal adhesions (PPA). Diagnosis of predisposition to adhesions by methods of determining the type of acetylation and ultrasound suggests the presence of adhesions in the small pelvis before surgery in 76.66% and 65% of those examined respectively. The molecular-genetic predictors of UCTD are C/C IL6-174 allele C and C/G VEGFA 634 allele G. The intensity of chronic pelvic pain in the adhesive process depends on the stage of the latter. To predict the risk of development of PPA, the developed mathematical model based on P = 1/(1+еЂ(–z)) and independent predictors should be used: myopia, mitral valve prolapse, IL6-174 [rs1800795], VEGFA 634 [rs2010963] and phenotype of acetylation. Conclusion: Using the method of binary logistic regression on the basis of clinical, anamnestic, experimental and molecular-genetic data makes it possible to determine the probability of development of PPA on the background of UCTD using the formula: P = 1/(1+еЂ(–z)).

Keywords

• pelvic peritoneal adhesions
• chronic pelvic pain
• acetylation
• binary logistic regression..