An advanced prediction model for postoperative complications and early implant failure

Abstract

Objectives: Risk prediction in implant dentistry presents specific challenges including the dependence of observations from patients with multiple implants and rare outcome events. The aim of this study was to use advanced statistical methods based on penalized regression to assess risk factors in implant dentistry. Material and methods: We conducted a retrospective study from January 2016 to November 2018 recording postoperative complications including bleeding, hematoma, local infection, and nerve damage, as well as early implant failure. We further assessed patient-and implant-related risk factors including smoking and diabetes, as well as treatment parameters including types of gaps and surgical procedures. Univariable and multivariable generalized estimating equation (GEE) models were estimated to assess predictor effects, and a prediction model was fitted using L1 penalized estimation (lasso). Results: In a total of 1,132 patients (mean age: 50.6 ± 16.5 years, 55.4% female) and 2,413 implants, postoperative complications occurred in 71 patients. Sixteen implants were lost prior to loading. Multivariable GEE models showed a higher risk of any complication for diabetes mellitus (p = .006) and bone augmentation (p = .039). The models further revealed a higher risk of local infection for bone augmentation (p = .003), and a higher risk of hematoma formation for diabetes mellitus (p = .007) and edentulous jaws (p = .024). The lasso model did not select any risk factors into the prediction model. Conclusions: Using novel methodology well-suited to tackle the specific challenges of risk prediction in implant dentistry, we were able to reliably estimate associations of risk factors with outcomes.

Surgery start time and early implant failure: A case–control study

“…Beyond the effect of SST, we observed in our study that implant placement with sedation (3.4‐fold), simultaneous bone grafting (3.7‐fold), simultaneous soft tissue grafting (5‐fold), occurrence of intra‐operative complications (6‐fold), pre‐placement ridge augmentation (7.5‐fold), and number of implants (1.2‐fold) increase the risk for EIF. The finding that EIF was significantly higher in sites with pre‐placement ridge augmentation contradicts two earlier retrospective studies that reported no association between bone augmentation (guided bone regeneration or sinus floor elevation) and early or late implant loss (Feher et al., 2020; Tran et al., 2016). However, in another study, less marginal bone loss was associated with implants placed in native compared with augmented bone (Thoma et al., 2019).…”

The Effectiveness of Osseodensification Drilling Protocol for Implant Site Osteotomy: A Systematic Review of the Literature and Meta-Analysis

“…The evolution of the techniques and materials adopted has allowed more doctors and patients to use this type of therapy, making possible the placement of implant elements in very hard situations where only a few years ago the professional would have chosen a different therapeutic choice [ 36 ]. One of the main principles for successful therapy is the achievement of suitable primary stability during the implant placement [ 37 ] in respect to the biology of the host [ 38 ] and factors depending on the invasiveness of the operation; the more the preparation of the implant site will be performed in an atraumatic way by avoiding the overheating, and so the necrosis of the site, the more we will be able to respect tissues of the host by avoiding intra- and post-operation complications (bleeding, swelling, local infection, invasion of the noble structures adjacent to the surgery, implant early loss, inadequate healing of hard and soft tissues involved during the operation, presence and/or formation of pus immediately after the operation, pain, alteration of the sensitivity of the area) [ 39 , 40 , 41 ].…”

“…After the surgery, we may assess the primary stability of the placed implants, a value that indicates the contact of the implant surface with the surrounding bone [ 42 ]; after this, the secondary stability will follow, which is reached after the processes of remodeling and healing of the bone [ 43 ]; usually, the achievement of good primary stability will be followed by correct secondary stability [ 44 ]. In this way, the dynamic functional response of the bone tissue is determined by the bone-to-implant contact percentage (BIC), which is constantly interested in remodeling processes under the functional loading [ 25 , 26 , 40 , 41 , 42 , 43 , 45 , 46 , 47 , 48 ]. In order to assess the implant stability, we may use an index called the implant stability quotient (ISQ), a unit of measurement, which allows us to assess the degree of integration of the placed implants [ 49 ]; the clinical range of the ISQ is ranged between 55 and 80, and if the value is higher than 65, it is commonly accepted as a favorable situation for implant stability; on the contrary, values under 45 are considered as insufficient implant stability [ 42 ].…”

The Effect of the COVID-19 Pandemic on Patient Selection, Surgical Procedures, and Postoperative Complications in a Specialized Dental Implant Clinic

“…One possible explanation is the overall lower prevalence of comorbidities and extensive augmentative procedures, albeit these differences were not significant in this study. Nonetheless, it should be noted that in our previous work using a dataset of over 2400 implants in over 1100 patients, neither comorbidities nor surgical procedures could accurately predict early implant failure [26]. Third, the data suggest that datasets containing dental implant treatments during the pandemic are comparable to pre-pandemic datasets, allowing their use for training or validation of statistical models.…”