title: The predictive value of microbiological findings on teeth, internal and external implant portions in clinical decision making.
abstract: OBJECTIVE
  The primary aim of this study was to evaluate 23 pathogens associated with peri-implantitis at inner part of implant connections, in peri-implant and periodontal pockets between patients suffering peri-implantitis and participants with healthy peri-implant tissues; the secondary aim was to estimate the predictive value of microbiological profile in patients wearing dental implants using data mining methods.
  
  
  METHODS
  Fifty participants included in the present case─control study were scheduled for collection of plaque samples from the peri-implant pockets, internal connection, and periodontal pocket. Real-time polymerase chain reaction was performed to quantify 23 pathogens. Three predictive models were developed using C4.5 decision trees to estimate the predictive value of microbiological profile between three experimental sites.
  
  
  RESULTS
  The final sample included 47 patients (22 healthy controls and 25 diseased cases), 90 implants (43 with healthy peri-implant tissues and 47 affected by peri-implantitis). Total and mean pathogen counts at inner portions of the implant connection, in peri-implant and periodontal pockets were generally increased in peri-implantitis patients when compared to healthy controls. The inner portion of the implant connection, the periodontal pocket and peri-implant pocket, respectively, presented a predictive value of microbiologic profile of 82.78%, 94.31%, and 97.5% of accuracy.
  
  
  CONCLUSIONS
  This study showed that microbiological profile at all three experimental sites is differently characterized between patients suffering peri-implantitis and healthy controls. Data mining analysis identified Parvimonas micra as a highly accurate predictor of peri-implantitis when present in peri-implant pocket while this method generally seems to be promising for diagnosis of such complex infections.
authors.affiliation: Private Practice, Rome, Italy.
authors.forename: Luigi
authors.initials: L
authors.lastname: Canullo
authors.affiliation: Centre for Business Decision-making, Faculty of Organizational Sciences, University of Belgrade, Belgrade, Serbia.
authors.forename: Sandro
authors.initials: S
authors.lastname: Radovanović
authors.affiliation: Centre for Business Decision-making, Faculty of Organizational Sciences, University of Belgrade, Belgrade, Serbia.
authors.forename: Boris
authors.initials: B
authors.lastname: Delibasic
authors.affiliation: Department of Oral Surgery, University of Valencia, Valencia, Spain.
authors.forename: Juan Antonio
authors.initials: JA
authors.lastname: Blaya
authors.affiliation: Department of Oral Surgery, University of Valencia, Valencia, Spain.
authors.forename: David
authors.initials: D
authors.lastname: Penarrocha
authors.affiliation: Institute for Biological Research "Sinisa Stankovic", University of Belgrade, Belgrade, Serbia.|Centre for Osteoarticular and Dental Tissue Engineering, INSERM U791, Faculty of Dental Surgery, University of Nantes, Nantes, France.
authors.forename: Mia
authors.initials: M
authors.lastname: Rakic
mesh_terms: D000328:Adult; D000368:Aged; D016301:Alveolar Bone Loss / Q000000981:diagnostic imaging / Q000382:microbiology; D016022:Case-Control Studies; D000066491:Clinical Decision-Making / Q000379:methods*; D003757:Dental Implantation / Q000009:adverse effects; D015921:Dental Implants / Q000382:microbiology*; D003773:Dental Plaque / Q000382:microbiology; D005260:Female; D006801:Humans; D008297:Male; D008875:Middle Aged; D057873:Peri-Implantitis / Q000382:microbiology; D010514:Periodontal Pocket / Q000382:microbiology; D011861:Radiography, Dental; D060888:Real-Time Polymerase Chain Reaction; D014070:Tooth / Q000382:microbiology*
chemical_list: D015921:Dental Implants
keywords: data mining; decision trees; infection; peri-implantitis; periodontitis