title: A metabonomic approach to early prognostic evaluation of experimental sepsis.
abstract: OBJECTIVE
  Early prognostic evaluation of sepsis is an attractive strategy to decrease the mortality of septic patients, but presently there are no satisfactory approaches. Our goal is to establish an early, rapid and efficient approach for prognostic evaluation of sepsis.
  
  
  METHODS
  Forty-five septic rats, induced by cecal ligation and puncture, were divided into surviving (n=23) and nonsurviving group (n=22) on day 6. Serum samples were obtained from septic and sham-operated rats (n=25) at 12h after surgery. HPLC/MS assays were performed to acquire serum metabolic profiles, and radial basis function neural network (RBFNN) was employed to build predictive model for prognostic evaluation of sepsis.
  
  
  RESULTS
  Principle component analysis allows a clear discrimination of the pathologic characteristics among rats from surviving, nonsurviving and sham-operated groups. Six metabolites related to the outcome of septic rats were then structurally identified, which included linolenic acid, linoleic acid, oleic acid, stearic acid, docosahexaenoic acid and docosapentaenoic acid. A RBFNN model was built upon the metabolic profile data from rat serum, and a high predictive accuracy over 94% was achieved.
  
  
  CONCLUSIONS
  HPLC/MS-based metabonomic approach combined with pattern recognition permits accurate outcome prediction of septic rats in the early stage. The proposed approach has advantages of rapid, low-cost and efficiency, and is expected to be applied in clinical prognostic evaluation of septic patients.
authors.affiliation: Department of Anaesthesia, Changhai Hospital, Second Military Medical University, Shanghai 200433, PR China.
authors.forename: Ping-bo
authors.initials: PB
authors.lastname: Xu
authors.forename: Zhong-ying
authors.initials: ZY
authors.lastname: Lin
authors.forename: Hai-bing
authors.initials: HB
authors.lastname: Meng
authors.forename: Shi-kai
authors.initials: SK
authors.lastname: Yan
authors.forename: Yun
authors.initials: Y
authors.lastname: Yang
authors.forename: Xin-ru
authors.initials: XR
authors.lastname: Liu
authors.forename: Jin-bao
authors.initials: JB
authors.lastname: Li
authors.forename: Xiao-ming
authors.initials: XM
authors.lastname: Deng
authors.forename: Wei-dong
authors.initials: WD
authors.lastname: Zhang
mesh_terms: D000818:Animals; D002851:Chromatography, High Pressure Liquid; D008297:Male; D013058:Mass Spectrometry; D008660:Metabolism / Q000502:physiology*; D025341:Principal Component Analysis; D011379:Prognosis; D011897:Random Allocation; D051381:Rats; D017207:Rats, Sprague-Dawley; D018805:Sepsis / Q000097:blood / Q000378:metabolism*; D013047:Specific Pathogen-Free Organisms