TY  - GEN
AU  - Canullo, Luigi
AU  - Radovanović, Sandro
AU  - Delibasic, Boris
AU  - Blaya, Juan Antonio
AU  - Penarrocha, David
AU  - Rakić, Mia
PY  - 2016
UR  - http://www.scopus.com/inward/record.url?eid=2-s2.0-84963502806&partnerID=tZOtx3y1
UR  - https://radar.ibiss.bg.ac.rs/handle/123456789/2526
AB  - AIM: 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. MATERIAL AND 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. CONCLUSION: 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.
PB  - Blackwell Munksgaard
T2  - Clinical oral implants research
T1  - The predictive value of microbiological findings on teeth, internal and external implant portions in clinical decision making.
DO  - 10.1111/clr.12828
ER  - 

@misc{
author = "Canullo, Luigi and Radovanović, Sandro and Delibasic, Boris and Blaya, Juan Antonio and Penarrocha, David and Rakić, Mia",
year = "2016",
abstract = "AIM: 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. MATERIAL AND 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. CONCLUSION: 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.",
publisher = "Blackwell Munksgaard",
journal = "Clinical oral implants research",
title = "The predictive value of microbiological findings on teeth, internal and external implant portions in clinical decision making.",
doi = "10.1111/clr.12828"
}

Canullo, L., Radovanović, S., Delibasic, B., Blaya, J. A., Penarrocha, D.,& Rakić, M.. (2016). The predictive value of microbiological findings on teeth, internal and external implant portions in clinical decision making.. in Clinical oral implants research
Blackwell Munksgaard..
https://doi.org/10.1111/clr.12828

Canullo L, Radovanović S, Delibasic B, Blaya JA, Penarrocha D, Rakić M. The predictive value of microbiological findings on teeth, internal and external implant portions in clinical decision making.. in Clinical oral implants research. 2016;.
doi:10.1111/clr.12828 .

Canullo, Luigi, Radovanović, Sandro, Delibasic, Boris, Blaya, Juan Antonio, Penarrocha, David, Rakić, Mia, "The predictive value of microbiological findings on teeth, internal and external implant portions in clinical decision making." in Clinical oral implants research (2016),
https://doi.org/10.1111/clr.12828 . .