## 4 Discussion
Similar results were found for higher implant diameters, which was also previously confirmed, particularly for primary stability [57; 58; 59; 60]. Primary stability is strongly related to biological (bone density, quantity, and quality) and geometric (implant design, length, and diameter) factors [4; 34; 54]. All these parameters were reported as non-influential to secondary stability after osseointegration has successfully occurred [54]. Several limitations need to be considered when interpreting the provided results. Retrospective cohort studies are associated with intrinsic limitations, such as selection bias, due to the inclusion of a selected cohort, lack of control, and randomization. Nevertheless, we included important confounding variables in our regression model, allowing us to obtain more precise results than we could have with a matched control group. Furthermore, our predefined inclusion and exclusion criteria could have been stricter, as we did not exclude smokers. However, heavy smokers (>20 cigarettes/day) were not treated with implants in our cohort. Additionally, two surgeons performed all surgeries and measurements independently. This could also have led to bias and should be considered when interpreting the results. Additionally, the RFA measurements have several methodological issues that need to be considered. Micro-movements at the interface can affect tissue differentiation and destroy newly-formed cells and vessels [59]. Upon insertion of the RFA adapter into the implant, forces of up to 10 Ncm can occur [61]. This value corresponds to almost one-third of the force required to insert an implant into the bone and can disturb osseointegration during the early phase [60]. Moreover, different individual measuring adapters for the two implant systems were used, which could impair resulting measurements [62]. A direct comparison would have been difficult, as individual calibration for each implant system is required [63; 64; 65]. Another limitation of RFA is that the induced oscillation analyzes the entire bone-implant complex and not only the bone-implant interface, which is important for osseointegration [37; 66]. The relationship between high ISQ values at the time of implant placement (baseline) and high secondary stability is controversially discussed, and the prognostic value of ISQ values is ambiguous [67]. The lower increase of already high baseline (primary stability) ISQ values compared to secondary stability values was also described previously [52]. Furthermore, even artificially-induced loosening of implants with associated low ISQ values achieved sufficient strength after re-osseointegration [68]. Nevertheless, the RFA proved to be a reliable diagnostic criterion for osseointegration [69]. In contrast to most studies, which mainly considered primary stability, we included secondary stability and the ISQ change during the healing period as an outcome of interest [57; 70; 71; 72]. The osseointegration is dependent on multiple factors and can never be completely reduced to only one parameter. To adequately build predictable risk stratification models, a sufficient number of implants should be examined. As most studies focused on primary implant stability or included fewer implants, the provided results from a large cohort could help to mathematically develop highly predictable preoperative risk stratification models in the future.