Introduction
Dental implants have become one of the primary methods for tooth replacement and have gained widespread global application in recent years (1-3). Compared with traditional restorative methods, implant-supported restorations not only markedly improve masticatory function, speech, and comfort but also enhance aesthetic outcomes, Patients achieve higher satisfaction in these parameters, including an overall aesthetic satisfaction rate of 96.67% (4-10). Furthermore, implant-supported restorations boost patient self-confidence and life quality (11,12). As a result, dental implant rehabilitation has become the preferred method for tooth replacement in modern dentistry. The survival rate (SR) of dental implants is associated with osseointegration; successful osseointegration is influenced by multiple factors, including implant design, surgical technique, systemic metabolic status and immune function (13). Diabetic patients, due to metabolic dysregulation, may experience secondary vascular and bone tissue complications, which interfere with osseointegration and long-term implant stability, increasing the risk of peri-implantitis (14). Additionally, microvascular complications in diabetic patients may decrease the release of repair cells and growth factors, impair collagen synthesis and hinder soft tissue regeneration (1). Consequently, diabetic patients are typically considered unsuitable for implant rehabilitation (4,15).
Diabetes mellitus (DM) has seen a notable increase in prevalence over the past decades, with the number of affected individuals worldwide exceeding 800 million (16). Diabetic patients typically exhibit poorer oral health, with a markedly higher prevalence of edentulism compared with non-diabetic populations. Adults with diabetes exhibit approximately twice the tooth loss rate as those without diabetes (17). This disparity is primarily attributed to their increased susceptibility to oral disease, such as periodontitis and dental caries, and experience accelerated alveolar bone resorption following tooth loss (14,18,19). As a result, implant-supported restorations have become a key option for diabetic patients to restore masticatory function and improve life quality. Well-controlled diabetic patients do not experience a significant decrease in implant SR following implant placement (20,21) For example, Diehl et al (22) observed that implant SR reached 100% in both diabetic and normoglycemic groups, with no significant differences in probing depth (PD), marginal bone loss (MBL), and bleeding on probing (BOP). Similarly, Tulbah et al (23) conducted a 5-year follow-up study and observed that, despite a higher incidence of complications in diabetic patients, implant SR did not markedly decline, further supporting the hypothesis that diabetic patients can achieve long-term implant success. These findings have led to the increasing application of implant-supported restoration in the dental treatment of diabetic patients (24,25).
Research on implant rehabilitation in diabetic patients has primarily focused on delayed implant placement strategies. Most studies indicate that, with well-controlled blood glucose levels, the implant SR in diabetic patients is comparable with those in non-diabetic patients (26,27). However, rapid alveolar bone resorption following tooth extraction may lead to insufficient bone volume, necessitating bone augmentation procedures, which not only increase surgical risk but also impose additional financial burdens on patients (8,28-30). Moreover, the extended treatment duration may compromise masticatory efficiency, negatively impacting patient quality of life. Compared with delayed implantation, immediate implant placement (IIP) simplifies the repair process by placing implants during tooth extraction, reducing the number of surgeries and overall waiting time for the final prosthesis. In addition, this method helps to maintain the size of the alveolar ridge, thereby supporting the overlying soft tissue (31-34). To date, there is limited research on IIP in diabetic patients, and existing meta-analyses exhibit limitations (35). For example, Andrade et al (35) found no significant differences in implant SR between diabetic and healthy individuals. However, the aforementioned meta-analysis included seven studies, with only five being utilized for quantitative synthesis. In the analysis of MBL, the comparison was limited to immediate vs. conventional loading in diabetic patients, without a thorough exploration of differences compared with healthy patients. Additionally, key soft tissue indicators such as probing depth (PD) and BOP were not analyzed. In conclusion, the limitations of existing meta-analyses include a small number of included studies, incomplete observation indicators and a lack of comprehensive evaluation of both hard and soft tissue health. It was hypothesized that IIP could be applied in diabetes patients. The present study aimed to determine whether IIP could be adopted in diabetic patients by assessing its feasibility and safety in diabetic patients.
Discussion
IIP offers the advantages of decreasing treatment duration, minimizing the number of surgical procedures and maintaining the contour of the alveolar ridge. This is beneficial in the maxillary anterior region, where good soft tissue profiles and aesthetic outcomes can be achieved (31,32). However, IIP demands high initial stability; patients with acute infection, severe bone defect or high occlusal loads may face increased risk of early failure (33,34). By contrast, delayed implantation is typically performed 3-6 months after tooth extraction, allowing healing of the extraction socket and sufficient bone regeneration before implant placement. This approach improves the success rate of osseointegration and long-term stability. However, delayed implantation results in a longer treatment timeline, requiring patients to wear temporary dentures, which may affect chewing efficiency and life quality and increase psychological burden (47-50). For diabetic patients, particularly those with well-controlled diabetes, the question of whether IIP can be performed is a key issue in clinical practice. The present meta-analysis demonstrated no obvious difference was in implant SR between diabetic patients and healthy individuals who undergo IIP. However, obvious differences were observed between in terms of MBL, PD and BOP Diabetic patients, particularly those with inadequate glycemic management, exhibited worse outcomes.
The primary evaluation criterion for survival in the present study was implant retention. The present findings indicated that, when glycemic control was good, implant SR did not differ markedly between diabetic patients and healthy individuals. Although hyperglycemia can affect the blood supply to the implant area, impair soft and bone tissue healing and increase the risk of peri-implantitis, maintaining strict blood sugar control and enhancing oral hygiene guidance improve long-term implant success (40,51-53). However, the present results also showed that diabetic patients with poor glycemic control did not experience a markedly lower SR compared with healthy individuals, which is inconsistent with current research. Ayele et al (54) provided further evidence on the impact of diabetes on implant survival, indicating that uncontrolled type 2 DM leads to increased peri-implant bone loss and decreased implant SR. The discrepancy in the present study may be attributed to the fact that Tawil et al (44) only enrolled one patient with poorly controlled blood sugar, who received 11 implants, all of which remained intact. Al Amri et al (40) reported that all patients had a 100% implant SR during the follow-up period, resulting in consistent data. Aguilar-Salvatierra et al (39) reported that diabetic patients with high hemoglobin A1c (HbA1C) levels initially showed good glycemic control, with HbA1C levels markedly decreasing after 24 months follow-up. Therefore, satisfactory blood sugar control in diabetic patients following IIP is a key factor influencing implant SR.
Diabetes may induce secondary vascular and osseous complications, which interfere with the osseointegration of implants. This affects the success rate of implants and the healing of peri-implant bone tissue. Therefore, the present meta-analysis investigated MBL in diabetic patients and healthy individuals to evaluate bone tissue healing. MBL is an effective indicator of peri-implant bone integration and bone healing and one of the key metrics for assessing long-term implant success (55,56). Diabetic patients exhibited slightly higher MBL compared with healthy individuals. This may be attributed to abnormal bone metabolism and heightened inflammatory responses induced by the hyperglycemic states in diabetic patients. Alsahhaf et al (57) observed that, compared with well-controlled diabetic patients and healthy individuals, poorly controlled diabetic patients experience markedly greater bone loss around the implants. The hyperglycemic environment promotes oxidative stress and the accumulation of advanced glycation end-products, which inhibit osteoblast activity and stimulate osteoclast formation, leading to increased bone resorption (8). Moreover, diabetic patients typically have microvascular complications, which may impair blood supply and healing capacity of peri-implant bone tissue (39). However, in the present study, the actual bone loss in well-controlled diabetic patients was relatively small (0.07 mm); in clinical practice, bone loss of 0.07 mm is almost negligible (55). The actual bone loss in patients with poorly controlled diabetes was 0.39 mm, which remains within an acceptable range (bone loss <0.2 mm/year is considered normal) (56). Therefore, such levels of bone loss are unlikely to have a notable impact on the long-term survival of implants. As previously noted, the similarity in implant SR between diabetic patients and healthy individuals further indicated that bone damage in diabetic patients does not affect implant survival. Therefore, diabetic patients can undergo IIP.
BOP and PD are key clinical indicators for assessing the health of peri-implant soft tissue. The present study found no significant difference in PD between well-controlled diabetic patients and healthy individuals, while BOP was markedly higher in diabetic patients. PD and BOP were markedly increased in patients with poor blood glucose control, suggesting more pronounced inflammation around the peri-implant tissue in diabetic individuals. For example, Gómez-Moreno et al (37) showed that poorly controlled diabetic patients (HbA1c ≥10.0%) have a significant increase in BOP during a 3-year follow-up after implant placement. Additionally, Lv et al (58) found that as HbA1c levels increased, the levels of bone metabolism negative regulators such as IL-6, TNF-α and RANKL also markedly increased, accompanied by a notable increase in PD around the implant. Hyperglycemia may decrease the resistance of periodontal tissues to bacterial infections, leading to microvascular changes in the gums and increased release of inflammatory mediators, thus exacerbating the inflammatory response in peri-implant tissues (59,60). Furthermore, impaired immune function in diabetic patients intensifies the inflammation around the implant (61). In the present study, PD for poorly controlled diabetic patients was 0.62 mm higher than in healthy patients. In clinical practice, a 0.62 mm increase in PD typically indicates mild inflammation, which usually does not have a notable impact on implant stability or success rates (62). While the differences in BOP were significant, the actual values were relatively small (0.12 and 0.23). It is typically considered that BOP <10% is indicative of healthy peri-implant tissue (63). Therefore, although diabetes increased the risk of inflammation in peri-implant soft tissues, effective glycemic control prevented severe inflammatory infections.
The included studies exhibited significant heterogeneity. Numerous factors may contribute to this variability. Firstly, the cohort studies may have been influenced by confounders, such as differences in implant types. Certain studies utilized Straumann Bone Level implants (Straumann AG), Brånemark System® MKIV (Nobel Biocare AB), or NobelSpeedy Groovy® (Nobel Biocare AB, Göteborg, Sweden) (37-40,44), which may impact the outcomes. Additionally, patients had varying HbA1c levels, and in certain cases, HbA1c levels decreased during follow-up (38). The follow-up duration also differed: Certain studies had follow-up periods <6 months (45), while others had follow-up durations of 24 or 36 months (37,43). The type of implants also varied, including single teeth, full-arch and all-on-four approaches. Furthermore, there were differences in the imaging methods used to measure MBL, such as intra-oral x-rays (38,39,43) and panoramic radiograph (41) or cone beam CT (46), which may lead to discrepancies in precision and consistency. Despite these differences, the main results remained consistent in subgroup and sensitivity analyses, indicating the robustness of the findings. Moreover, the use of a random-effects model mitigated the impact of heterogeneity on the results. Nevertheless, the presence of heterogeneity suggests that caution should be exercised when interpreting the findings, especially when extrapolating to a broader population. Future research should investigate the sources of heterogeneity and decrease its impact through standardized study designs and measurement techniques.
The present meta-analysis has several limitations. Firstly, certain studies included had small sample sizes, particularly the group of patients with poorly controlled diabetes (44,45). Small sample sizes may lead to insufficient statistical power, potentially failing to detect underlying differences and affecting the stability of the results. Secondly, due to the limited number of studies available for funnel plot analysis in some outcome measures, statistical tests such as Egger's test were not performed, as they would have low power and potentially yield misleading results (64). Therefore, publication bias was assessed qualitatively based on visual inspection of funnel plot symmetry. Future studies with larger sample sizes are needed to validate the robustness of our findings. Thirdly, while the studies categorized diabetic patients into well- and poorly controlled groups, there was a lack of detailed analysis of HbA1c levels. The precise level of blood glucose control may have a notable impact on implant success rates and the health of surrounding tissue, but the included studies did not fully explore this aspect. Furthermore, although the present study examined indicators such as MBL, PD and BOP, it lacked a detailed assessment of peri-implantitis, which is one of the primary causes of implant failure (53). Future research should investigate the incidence and risk factors of peri-implantitis in diabetic patients. Finally, the type of implants and surgical techniques varied, which could affect the comparability of the results. Future studies should aim to standardize implant types and surgical techniques to decrease the influence of confounding factors.
The present meta-analysis indicated that diabetic patients with good blood glucose control showed no significant difference in implant SR compared with healthy individuals, suggesting that IIP is feasible in diabetic patients. However, diabetic patients, especially those with poor blood glucose control, exhibit significant differences in MBL, PD and BOP, indicating that they may face a higher risk of peri-implant inflammation and tissue destruction following implant placement. Clinicians should pay particular attention to preoperative blood glucose control and postoperative peri-implant maintenance in diabetic patients. Regular monitoring of MBL, PD and BOP around the implant, along with personalized oral hygiene instructions and periodontal maintenance plans, may decrease the risk of peri-implantitis and improve the long-term SR of implants.