title: [Application of proteomic models for the diagnosis of inflammatory and non-inflammatory preterm delivery].
abstract: OBJECTIVE
  To establish the serum proteomic models for the identification of premature delivery with inflammation or non-inflammation.
  
  
  METHODS
  The laboring patients from 2008 to 2010 at our hospital were divided into 5 groups according to placental pathology, including inflammatory preterm group, non-inflammatory preterm group and blind test group (n = 50 each). The control group was normal full-term. The preterm models with or without inflammation were established by the methods of SELDI-TOF-MS (matrix-assisted laser desorption/ionization-time of flight-mass spectrometry) and bioinformatics. And statistical analysis was performed after a blind test. Then differential protein fingerprints were compared and analyzed.
  
  
  RESULTS
  A total of 36 different proteins were harvested after a comparison of inflammatory preterm and control groups. The model was established by eight markers. The rates of specificity, sensitivity, positive predictive value and negative predictive value were 80.85%, 84.44%, 93.33% and 46.67% respectively. Fifteen different proteins existed between non-inflammatory preterm and control groups. There were 4 marker proteins. The rates of specificity, sensitivity, positive predictive value and negative predictive value were 75.68%, 64.44%, 80.00% and 66.67% respectively. Different marker proteins existed between the identification models of inflammatory preterm labor and inflammatory full-term.
  
  
  CONCLUSIONS
  Different serum proteomic models may be used for the diagnosis of preterm labor and the differentiation of preterm labor with or without inflammation. And different proteins are expressed during different stages of pregnancy with chorioamnionitis.
authors.affiliation: Department of Obstetrics & Gynecology, No. 306 Hospital of PLA, Beijing 100101, China.
authors.forename: Wen-ying
authors.initials: WY
authors.lastname: Zhang
authors.forename: Yan-li
authors.initials: YL
authors.lastname: Dang
authors.forename: Ling
authors.initials: L
authors.lastname: Zhou
authors.forename: Li
authors.initials: L
authors.lastname: Yu
authors.forename: Gen-lan
authors.initials: GL
authors.lastname: Liu
authors.forename: Yan
authors.initials: Y
authors.lastname: Zhang
authors.forename: Xiu-fang
authors.initials: XF
authors.lastname: Chen
authors.forename: Min
authors.initials: M
authors.lastname: Wang
authors.forename: Jun
authors.initials: J
authors.lastname: Zhang
mesh_terms: D000328:Adult; D005260:Female; D006801:Humans; D007249:Inflammation / Q000175:diagnosis; D008954:Models, Biological; D010449:Peptide Mapping; D011237:Predictive Value of Tests; D011247:Pregnancy; D047928:Premature Birth / Q000175:diagnosis*; D020543:Proteome / Q000032:analysis*; D040901:Proteomics; D012680:Sensitivity and Specificity
chemical_list: D020543:Proteome