Systemic conditions didn't predict implant loss over 11 years

Systemic disease is often treated as a relative contraindication—or at least a risk factor requiring extra caution—for dental implant placement, but the actual magnitude of that risk in modern practice is debated. This retrospective study, following STROBE reporting guidelines, reviewed 602 patient records and 1,872 implants placed between 2000 and 2017, comparing outcomes between systemically healthy patients (743 implants) and those with one or more systemic conditions or regular medications (1,129 implants).

Implant success was 96.76% in healthy patients and 97.60% in systemically compromised patients — not significantly different (Fisher's exact test, p=0.14). Kaplan-Meier survival analysis over a mean follow-up approaching 11 years showed closely overlapping survival curves (93.84% vs. 94.92%; log-rank p=0.16), and binary logistic regression found no significant association between systemic status and implant loss, with the model explaining only about 5% of the variance. The one factor that did emerge was age: patients over 50 had higher implant loss regardless of systemic status.

As a retrospective chart review, the study cannot control for how carefully systemic conditions were managed before implant placement, nor for referral bias (compromised patients may already have been more conservatively selected for implants). It also pools a wide range of systemic conditions into a single category, which may mask risk differences between, for instance, well-controlled diabetes and uncontrolled autoimmune disease. Still, the size of the cohort and the length of follow-up make this a reassuring data point: in this population, a documented systemic condition alone — provided implants were still deemed appropriate by the treating team — was not associated with a measurably worse long-term outcome. This supports individualized risk assessment over blanket caution based on diagnosis labels, while reinforcing that age-related factors deserve separate attention in treatment planning.