BACKGROUND

The aim of this case-control study was to estimate the diagnostic accuracy of the standard clinical parameters in diagnosing healthy peri-implant tissues, peri-implant mucositis, and peri-implantitis.

METHODS

A case-control study was designed to compare the clinical parameters used in the diagnosis of peri-implant diseases such as: probingdepth (PD), bleeding on probing (BOP), mucosal redness (MR), suppuration (SUP), and plaque index (PI). Furthermore, the influence of patient- (sex, age) and implant-related variables (implant neck configuration, time in function after loading) were evaluated to investigate the association with the clinical findings. The inferential analysis consisted of estimation by generalized estimating equations (GEE) of multilevel logistic regression models.

RESULTS

In total, 1,572 sites were evaluated around 262 implants from 141 patients. Sites with implant mucositis showed significant levels of BOP (OR = 3.56), MR (OR = 7.66) and PD (OR = 1.48) compared to healthy sites. The specificity was 90.3% while the sensitivity was only 43.6%. Likewise, sites exhibiting peri-implantitis showed significant levels of BOP (OR = 2.32), MR (OR = 7.21), PD (OR = 2.43) and SUP (OR = 6.81) compared to healthy sites. Again, the multiple logistic regressions showed high specificity (92.1%) but modest sensitivity (52.5%). PD was the only diagnostic marker displaying significance comparing peri-implant mucositis and peri-implantitis sites (OR = 1.76). Moreover, tissue-level compared to bone-level implants were less associated with SUP+ (OR = 0.20), and PI (OR = 0.36) and demonstrated statistical significance. In addition, age, sex, and function time significantly influenced the tested clinical parameters.

CONCLUSIONS

The diagnosis of peri-implant diseases cannot rely solely upon individual clinical parameters but rather require a combination of criteria. The clinical parameters, particularly probing depth, might accurately discern between diagnoses among peri-implant conditions. Nevertheless, the specificity of the clinical parameters surpasses the sensitivity in the detection of peri-implant diseases, validating its potential use as a diagnostic tool.