Effect of Different Laser Wavelengths on Periodontopathogens in Peri-Implantitis: A Review of In Vivo Studies

Nowadays, many studies are examining the effectiveness of dental lasers in the treatment of peri-implantitis; however, most of them only report periodontal parameter changes. The authors of this review tried to address the question: &#8220;What is the effect of different laser wavelengths on oral bacteria that cause peri-implantitis?&#8221; An electronic search of PubMed and Cochrane Central Register of Controlled Trials was performed. The following search terms were used: (peri-implantitis OR periimplantitis) OR/AND (microbial OR microbiologic) AND (laser OR Er:YAG OR erbium OR diode OR Nd:YAG OR neodymium-doped OR Er,Cr:YSGG OR chromium-doped). Initially, 212 studies were identified. After screening the titles and abstracts and excluding studies according to predefined inclusion criteria, seven publications were included in the review. Three studies about the effect of aPDT (antimicrobial photodynamic therapy) reported a decrease in the different bacterial strains associated with peri-implantitis, e.g., <i>A. actinomycetemcomitans</i>, <i>P. gingivalis</i>, <i>P. intermedia</i>, <i>T. denticola</i>, <i>T. forsythia</i>, <i>F. nucleatum</i>, and <i>C. rectus</i>. Two studies showed that the high-power diode laser may have some effect on peri-implant pathogens. Two articles about the Er:YAG laser reported a lowering in the count of oral pathogens; however, it was hard to determine if this was due to the use of the laser. aPDT has the ability to decrease the count of peri-implant pathogens, whereas Er:YAG laser application shows no significant effect on oral bacteria in the long term.

Abstract licence: CC BY

1. 34.

   Definition, etiology, prevention and treatment of peri-implantitis – a review · 2014

39 more references, whose wording the paper’s licence keeps private.

• Photobiomodulation—Underlying Mechanism and Clinical Applications · 2020

• The Microbiome of Peri-Implantitis: A Systematic Review and Meta-Analysis · 2020

A person counts once a day per paper. We keep no cookie and no address: a reader is a hash that changes every day. Any month under five reads shows no number.