Mapping of inflammatory biomarkers in the peri-implant crevicular fluid before and after the occlusal loading of narrow diameter implants.

Abstract

To monitor the cytokine release patterns in the peri-implant crevicular fluid (PICF) and to investigate which factors affect the success rate of narrow diameter implants (NDI) during the first year. Mandibular implant overdentures (IOD) retained by 2 NDI were installed in 16 clinically atrophic edentulous patients. The following parameters were monitored during the first year: (i) peri-implant health parameters (plaque index (PI), calculus presence (CP), gingival index (GI), probing depth (PD) and bleeding on probing (BoP); (ii) cytokine concentrations in the PICF (TNF-α, IL-1β, IL-6, IL-10); (iii) implant stability quotient (ISQ); (iv) marginal bone level (MBL) and bone level change (BLC); (v) implant success. The insertion torque, bone type, mandibular atrophy, time since edentulism, and smoking habits were also recorded. All data were analyzed using multivariable multilevel mixed-effects regression models. The variability in the TNF-α release patterns temporarily reduced at weeks (w) 8-12, while the IL-1β concentrations remained low until they peaked at w48 [p < 0.05; + 177.55pg/μl (+ 96.13 - + 258.97)]. Conversely, IL-10 release decreased significantly at w48 [p < 0.05; - 456.24pg/μl (- 644.41 - - 268.07)]. The PD and ISQ decreased significantly (p < 0.05) over the follow-up period, while the MBL was stable after w48 with a BLC of 0.12 ± 0.71mm. The overall success rate was 81.3%, and was influenced by TNF-α, IL-1β, IL-10, PI, GI, PD, smoking, and time since edentulism. Pro- and anti-inflammatory cytokine release was balanced during the first 24weeks. The GI, smoking, and time since edentulism are the most important factors determining the implant success. The study contributes to the understanding of the osseointegration process in a clinically atrophic population rehabilitated with IOD, and highlights the importance of monitoring clinical peri-implant health-related parameters, smoking habit, and time since edentulism to predict implant success rates.