Description

• Title:
  Model for predicting the vaginal dysbiosis’ severity according to the index of conditionally pathogenic microflora
• Creator:
  Hruzevskyi, O. A.;
  Venger, A. M.;
  Minukhin, V. V.
• Description:
  A model for predicting the severity of dysbiosis according to the index of opportunistic pathogenic microflora has been developed. The aim of the study is to identify the most informative indicators that objectively reflect the condition of the pathological process and develop a system for predicting the risk of occurrence and severity of dysbiosis behind these indicators. Statistical processing of data was carried out using variational and correlation analysis methods using the Application software package Statistica v.10 (StatSoft, Inc.). At the first stage of the analysis, the index of conditionally pathogenic microflora was considered as a resultant trait. To identify factors that are more associated with the risk of developing dysbiosis with IOPM, a selection of significant traits was performed using a genetic selection algorithm. The prediction of the severity of dysbiosis with IOPM was considered. The nine factor attributes obtained with the help of mathematical analysis allowed to predict the severity of vaginal dysbiosis with high accuracy and to calculate the IOPM indices. Phasal nature of development of the immune system reaction during the development of vaginal dysbiosis is revealed. Possibility of practical use of the developed model is shown.
• Object availability:
  free access
• Rights:
  Prawa autorskie (c) 2020 © The Author (s)
• Date:
  2020.07.31
• Type:
  info:eu-repo/semantics/article;
  info:eu-repo/semantics/publishedVersion
• Language:
  English
• Source:
  Journal of Education, Health and Sport; Vol. 10 No. 7 (2020); 456-464;
  Journal of Education, Health and Sport; Tom 10 Nr 7 (2020); 456-464;
  2391-8306
• Format:
  application/pdf
• Publisher:
  Nicolaus Copernicus University, Toruń, Poland
• Relation: https://apcz.umk.pl/JEHS/article/view/JEHS.2020.10.07.047/28311
• Subject:
  index of opportunistic pathogenic microflora;
  normobiota;
  prediction model;
  dysbiosis
• Identifier: https://apcz.umk.pl/JEHS/article/view/JEHS.2020.10.07.047
• Data provider:
  Akademicka Platforma Czasopism
• Can I use it?:
  seek permission
• Type:
  text