An 11-Year Retrospective Research Study of the Predictive Factors of Peri-Implantitis and Implant Failure: Analytic-Multicentric Study of 1279 Implants in Peru

Table 3

Multivariate logistic regression model of each risk factor on the success and survival of osseointegrated implants.

Independent variables	OR		95% CI
Age (X0)	1.0	0.122	0.98–1.10
Sex (X1)	0.9	0.879	0.23–3.48
Location (X2)	0.5	0.312	0.13–1.88
Hypertension (X3)	0.5	0.463	0.11–2.72
Antibiotic therapy (X4)	—	—	—
Diabetes (X5)	5.6	0.167	0.48–65.9
Osteoporosis (X6)	44.8	0.011	2.40–834.8
Bisphosphonates (X7)	0.09	0.205	0.00–3.65
History of periodontitis (X8)	3.1	0.082	0.86–11.31
Hypercholesterolemia (X9)	5.1	0.046	1.02–25.44
Bone quality (X10)	5.8	0.021	1.30–26.6
Bone quantity (X11)	0.5	0.268	0.15–1.69
Design (X12)	1.5	0.388	0.57–4.16
Smoker (X13)	1.6	0.798	0.04–60.4
Connection (X14)	0.4	0.038	0.22–0.95
Type of edentulism (X15)	0.4	0.527	0.03–5.26
Staging (X16)	—	—	—
3D surgery (X17)	—	—	—
Load (X18)	—	—	—
Bone graft (X19)	0.1	0.183	0.01–2.16
GBR (X22)	24.1	0.007	2.34–249.6
Follow-up (X23)	1.7	0.000	1.35–2.31
Number of implants (X24)	1.1	0.290	0.90–1.39

OR: odds ratio; CI: confidence interval; GBR: guided bone regeneration. Logit model: all the variables were entered in the statistical analysis of the multivariate model. The logit model showed that age, sex, location of the implant, antibiotic therapy, diabetes, bisphosphonates, history of periodontitis, bone quantity, implant design, smoking habit, type of edentulism, bone graft, and number of implants placed were not factors of statistically significant risk in the general logistic model for the failure of the implants ().