Peri-implantitis is a destructive disease affecting the tissues surrounding dental implants. Biomaterials may be applied during surgical treatment to reconstruct bony defects and support soft tissue healing. However, current evidence is unclear if these treatments increase the likelihood of peri-implantitis resolution. A systematic review and meta-analysis was performed on randomized controlled trials (RCTs) comparing surgical treatment with addition of reconstructive biomaterials (intervention) versus surgical treatment of peri-implantitis alone (comparison) with follow-up periods of at least 12 months. Resolution of peri-implantitis, defined as a reduction of probing pocket depth (PPD) to ≤5 mm, absence bleeding on probing (BOP), and stable or decreasing radiographic defect level (RDL), was selected as the primary outcome. Secondary outcomes included RDL reduction, buccal mucosal recession (REC), and patient-related outcome measures (PROMs). Risk of bias and quality of evidence were calculated using established guidelines. Seven studies reporting on 402 patients with 405 implants met inclusion criteria. Wide variations in outcome reporting prevented the synthesis and quantitative comparison of peri-implantitis disease resolution between intervention and comparison groups. Individual meta-analyses showed a weighted mean difference (WMD) in PPD reduction of 0.28 mm [95% confidence interval (CI) -0.30, 0.86] and a relative risk (RR) for absence of BOP of 1.11 (95% CI 0.78, 1.59) for the inclusion of biomaterials (intervention) over access flap alone (comparison). For RDL reduction, a WMD of 1.08 mm (95% CI 0.41, 1.74) with significant heterogeneity (Q p-val: < 0.01, I2: 85%) and for REC, a WMD of -0.38 (95% CI -0.66, -0.11) was found, both in favor of the intervention. Analysis of the heterogeneity affecting RDL identified a positive effect on RDL when hydrogen peroxide but not rotary titanium brushes were used as an adjunct for implant surface debridement. Current evidence suggests that incorporating reconstructive biomaterials into surgical treatment may not definitively enhance the likelihood of peri-implantitis disease resolution. However, this lack of effect may be due to other factors such as implant surface treatments which may also affect clinical outcomes. Overall, this work highlights the critical need for standardizing the reporting of composite outcomes for the resolution of peri-implantitis disease and controlling for implant surface treatment effects when assessing reconstructive biomaterials. Peri-implantitis is a destructive disease affecting tissues around dental implants. We studied whether adding reconstructive biomaterials (i.e., biomaterials used to improve the likelihood of new bone formation or bone defect fill) to surgical treatments improves the clinical condition, meaning no further bone loss, probing pocket depths (PPD) ≤5 mm, and no bleeding on probing (BOP). We reviewed randomized controlled trials (RCTs) comparing surgery with biomaterials to surgery alone with at least 12 months of follow-up. The main outcomes measured were PPD reduction, absence of BOP, and radiographic defect level (RDL). Secondary outcomes included RDL change, buccal mucosal recession (REC), and patient-related outcomes (PROMs). Seven studies with 402 patients and 405 implants were analyzed. Due to variations in outcome reporting, it was challenging to compare the effectiveness of treatments. However, some individual analyses showed a small improvement in PPD and BOP with biomaterials. For RDL reduction, biomaterials showed better results, but with significant variability. REC also improved slightly with biomaterials. The analysis also suggested that using hydrogen peroxide, but not rotary titanium brushes, for implant cleaning could positively affect bone levels. The study concluded that adding biomaterials to surgical treatment does not definitively improve peri-implantitis resolution, possibly due to other factors like implant surface treatments. This study emphasized the need for standardized reporting and considering these factors in future research.
This critical review provides a comprehensive analysis of the histological foundations, current clinical diagnostic standards, and emerging ultrasonographic methods for diagnosing peri-implant diseases. An electronic search in Medline (PubMed) database was conducted to identify original and review articles focused on the histological foundation and diagnostic approaches of peri-implant diseases. This review provides an integrated perspective on the evolution of peri-implant diseases diagnostics, focusing on the clinical and radiographic criteria established by the latest consensus guidelines. It outlines the histological features of peri-implant diseases and discusses recent advancements in ultrasonographic imaging approaches for their characterization and diagnosis. This review further explores elements such as peri-implant anatomical landmarks, echo intensity, tissue perfusion, and strain elastography. Histological studies have defined the peri-implant mucosal architecture and inflammatory patterns characteristic of disease progression. While conventional diagnostics have relied on clinical examination and radiographic imaging, high-frequency ultrasound (HFUS) has recently emerged as a promising noninvasive imaging tool enabling detailed assessment of peri-implant tissue dimensions, echo intensity, vascular perfusion, and the extent of inflammatory involvement. Echo intensity mapping aids in the visualization and quantification of peri-implant lesions and the identification of associated bone defects. These imaging advancements not only complement current diagnostic methods but also deepen our understanding of peri-implant disease dynamics. Observed correlations between histological findings and ultrasonographic features can support the development of a new diagnostic framework incorporating HFUS-derived markers for detecting peri-implant lesions and evaluating the severity of inflammation. Integrating HFUS and power Doppler imaging into peri-implant diagnostics allows real-time, noninvasive visualization of key structures such as the supracrestal adherent connective tissue, buccal bone levels, and tissue perfusion. These modalities can complement existing standards and enhance diagnostic precision by identifying the extent of peri-implant lesions and quantifying the severity of inflammation. Peri-implant diseases can affect the tissues around dental implants and can lead to inflammation and bone loss. Understanding how these diseases develop and how best to diagnose them is essential for improving patient care. The present narrative review looked at scientific studies that examined the tissues around implants and the methods used to diagnose peri-implant diseases. It explains what researchers have learned from tissue (histological) studies and summarizes the current clinical and X-ray based diagnostic standards. It also highlights new advances in high-frequency ultrasound (HFUS), a technology that can provide detailed, real-time images of the soft tissues and bone around implants without radiation. Recent studies show that HFUS can measure tissue thickness, detect inflammation, visualize blood flow, and help identify early bone defects. These ultrasound features match what is known from histology, suggesting that HFUS could become an important tool for detecting peri-implant disease earlier and more accurately. Overall, adding HFUS and power Doppler imaging to current diagnostic methods can improve the evaluation of peri-implant tissues. These noninvasive techniques can help clinicians see key structures more clearly, assess inflammation, and better understand the severity of the disease.
Radiation-induced and drug-induced bone necrosis present significant challenges for maxillofacial surgery departments and dental clinics. While the incidence of osteoradionecrosis (ORN) has decreased, the number of cases of medication-related osteonecrosis of the jaw (MRONJ) has markedly increased. This trend is associated with higher life expectancy and more frequent use of medications linked to MRONJ. To date, no uniform, scientifically validated treatment standards have been established for these conditions. The aim of the study was to evaluate treatment outcomes in patients with ORN and MRONJ, as well as to identify risk factors for complications, with particular emphasis on differences in clinical presentation and management. A retrospective analysis of medical records over a five-year period was conducted, including the charts of patients diagnosed with MRONJ and ORN who were hospitalized at the Department of Maxillofacial Surgery, Poznan University of Medical Sciences, Poland, and subsequently followed up in the outpatient setting. Selected parameters included C-reactive protein (CRP), smoking status, type of necrosis, sex, and hospitalization time. Differences in patient characteristics, including age, sex, smoking status, and clinical presentation, were observed between the groups. Patients with MRONJ were, on average, 5 years older than those with ORN and exhibited a significantly higher concentration of CRP, indicating a more pronounced inflammatory response. Smoking was identified as a weak but notable predictor of the need for mandibular resection. Additionally, elevated concentrations of CRP were associated with longer hospitalization and a higher incidence of complications, potentially contributing to prolonged hospital stays and an increased risk of adverse outcomes. The findings highlight distinct clinical courses for MRONJ and ORN, underscoring the need for differentiated treatment strategies. Given the lack of standardized treatment protocols, the observed variations in clinical outcomes suggest the necessity for more targeted therapeutic approaches. Further research is essential to establish effective treatment protocols.
Gingivitis is a common inflammatory condition affecting the gingival tissues, often serving as a precursor to periodontitis. Ultra-high frequency ultrasonography (UHFUS) has emerged as a promising imaging modality capable of providing high-resolution visualization of superficial soft tissues. This cross-sectional study explores the application of UHFUS to the evaluation of gingival tissues, aiming to compare its findings in cases of gingivitis versus gingival health. In particular, the focus is on identifying and characterizing the ultrastructural changes associated with inflammation. Twenty participants affected by generalized gingivitis and twenty healthy controls were enrolled. All study participants underwent UHFUS scans (70 MHz) of gingival tissues on three areas per dental arch (anterior, middle right, middle left) using a standardized acquisition technique. Gingival thickness, echogenicity, and vascularization parameters (peak systolic velocity, time averaged peak velocity, resistive index, and pulsatility index) were evaluated and compared. No differences in terms of age and sex distribution were noticed between study groups. Participants affected by gingivitis exhibited significantly reduced gingival thickness (p < 0.05) and echogenicity (p < 0.001) at soft tissue level. All vascular parameters indicated the presence of increased blood flow associated to higher vascular resistance, with resistive index values consistently > 0.8 compared with healthy study participants, who showed values between 0.6 and 0.7. Ultrasonography highlighted the presence of structural modifications in the presence of gingivitis compared with healthy study participants. Further assessment is advised to better address the modifications occurring following the development of gingival inflammation. This study aimed to characterize the ultrastructural and vascular modifications in gingival tissue associated with inflammation using UHFUS. A cross-sectional clinical investigation compared 20 participants with generalized gingivitis to 20 periodontally healthy controls. Standardized UHFUS (70 MHz) imaging of designated gingival sites was performed to objectively quantify tissue thickness, echogenicity (textural echointensity), and key vascularization parameters via Doppler analysis. The results demonstrated significant morphofunctional alterations in inflamed gingiva. The objective UHFUS-derived metrics indicated that gingival inflammation involves not only increased perfusion but also substantive underlying architectural changes. The findings provide a foundational reference for detecting subclinical tissue changes and offer a potential objective framework for monitoring therapeutic outcomes in periodontal research and clinical trials.
The emergence angle (EA) and emergence profile (EP) of implant restoration are critical factors influencing peri-implant health. An EA greater than 30° with a convex EP has been associated with the risk of peri-implantitis in bone-level implants. This study aims to evaluate the impact of crown contour on the marginal bone in tissue-level (TL) implants. This retrospective study analyzed 200 TL implants in 101 patients. The EAs were categorized into two groups: <40° and ≥40°. The marginal bone level (MBL) was measured radiographically over three time periods: 1-2 years, > 2 up to 5 years, and > 5 years post-restoration. Generalized estimating equation models were used to determine potential factors influencing MBL changes. A negative relationship was observed between MBL and EA (p < 0.001). After adjusting for confounders, implants with EAs ≥40° had 0.43 mm less MBL change (95% CI: -0.60 mm, -0.25 mm) compared with EAs <40°. EP did not significantly impact MBL differences between groups. Tissue-level implants with over-contoured restorations with an EA of ≥40° did not negatively impact the MBL, and this finding was statistically significant. The risk indicators of a 30° restorative EA threshold and a convex profile did not apply to TL implants. The contours of implant crowns are critical factors that influence the health of implants. Wide crown contours with a 30° angle or more and a convex profile have been associated with implant disease. The aim of this study was to evaluate the impact of crown contours on the bone levels around tissue level (TL) implants. This is a retrospective study which analyzed 200 TL implants. The crown contours were evaluated as an angle <40° and ≥40° and concave, convex, and straight crown profiles. The bone level around implant margins (MBL) were measured using radiographs at three time periods: 1-2 years, > 2 up to 5 years, and > 5 years post-restoration. Generalized estimating equation models were used to determine potential factors influencing MBL changes. A negative relationship was observed between MBL and implant angle (p < 0.001). After adjusting for confounders, implants with angles ≥40° had 0.43 mm less MBL change compared with angles <40°. The crown profile did not significantly impact MBL differences between groups. TL implants with over-contoured crowns with angles of ≥40° did not negatively impact the MBL, and this finding was statistically significant. The risk indicators of a 30° crown angle threshold and a convex profile did not apply to TL implants.
Periodontal disease is characterized in part by a host immune-inflammatory response that releases proteolytic enzymes, which damage periodontal tissue. Nonsteroidal anti-inflammatory drugs (NSAIDs) modulate host immune-inflammatory responses. We investigated cross-sectional and prospective relationships between NSAID use and indicators of periodontal disease, for which there is limited epidemiologic evidence. Data were from the Buffalo OsteoPerio Study of 1342 postmenopausal women ages 53-81 years. Periodontal assessments included measurements of alveolar crestal height (ACH), probing pocket depth (PPD), clinical attachment level (CAL), and gingival bleeding, taken at baseline (1997-2001) and 5 years later. Prospective outcomes included measures of periodontal disease progression defined by ACH loss, incident tooth loss, and gingival bleeding. NSAID use was assessed via medication inventory at baseline. Demographic, lifestyle, dental hygiene, and medical history information were collected. Multivariable linear and logistic regression modeling was used to examine associations between NSAID use and periodontal health outcomes. At baseline, 45.8% of participants used NSAIDs, half of whom exclusively used aspirin. No significant cross-sectional differences in periodontal measures were found between NSAID users and nonusers. Prospectively, NSAID users had 37% lower odds of periodontal disease progression defined by ACH loss (odds ratio [OR] 0.63, 95% confidence interval; [CI]: 0.45-0.88), after controlling for demographic variables, lifestyle factors, comorbidities, and dental hygiene behaviors. Prospective associations with PPD, CAL, gingival bleeding, and tooth loss were of variable magnitude and did not achieve statistical significance. In a cohort of postmenopausal women with well-characterized clinical periodontal measurements, use of NSAIDs at baseline was associated with lower odds of periodontal disease progression defined by ACH loss over 5 years of follow-up. NSAID use was not associated with changes to PPD, CAL, gingival bleeding, or tooth loss. Periodontal disease, a common condition characterizing poor oral health, can worsen over time due to the body's inflammatory response, which damages the tissues supporting teeth. Nonsteroidal anti-inflammatory drugs (NSAIDs), like aspirin, can reduce inflammation, but whether they have any role in preventing periodontal disease has not been well-studied. We explored this connection in more than 1,300 postmenopausal women from the Buffalo OsteoPerio Study, tracking their oral health over 5 years. At the start, nearly half of the women reported using NSAIDs, mostly aspirin. While NSAID users and nonusers had similar gum health at the beginning, we found that women who used NSAIDs had a 37% lower odds of losing the bone that supports their teeth over the next 5 years. This protective association remained even after accounting for age, lifestyle, medical conditions, and dental care habits. However, NSAID use was not associated with other measures of oral health, like gum bleeding, pocket depth around teeth, or tooth loss. These findings suggest that NSAIDs may help slow some aspects of periodontal disease progression, but their overall effects on oral health remain unclear. Understanding how common medications like NSAIDs affect oral health could guide strategies to protect against gum disease in older adults.
Periodontal disease (PD) is associated with type 2 diabetes mellitus (T2DM), while periodontal treatment (PT) improves glycemic control in T2DM patients. Leptin and adiponectin belong to the adipokines family and have almost antagonistic functions in inflammatory processes and insulin sensitivity modulation. Hence, these hormones have been linked with both PD severity and glycemic control. This systematic review aims to assess the effect of PT on serum levels of leptin and adiponectin in patients with T2DM. PubMed, Cochrane Library, and Google Scholar databases and ClinicalTrials.gov website were searched up to January 5th, 2025. Randomized and non-randomized controlled clinical trials (RCTs and CCTs) including patients with T2DM and PD who underwent PT and evaluated serum levels of leptin and adiponectin were included. Assessments of risk of bias and of certainty of evidence were performed. Seven trials were eligible for qualitative synthesis. A statistically significant increase in serum adiponectin levels was observed across most studies, while no such consistency was observed for leptin. The overall level of certainty of evidence was judged low in the RCTs and very low in the CCTs. Meta-analysis could not be performed due to significant methodological heterogeneity. Preliminary findings suggest a potential increase in adiponectin levels in T2DM patients, with possible implications for glycemic control. However, these results should be interpreted with caution due to the small number of studies and important methodological limitations. Well-designed studies with larger sample sizes and adequate adjustment for confounders are necessary to verify this observation. People with type 2 diabetes often also have periodontitis, an inflammatory gum disease, which may affect their overall health. The aim of this study was to investigate whether treating periodontitis could help improve certain substances in the blood-called adiponectin and leptin-that are linked to blood sugar control and inflammation. Several studies that tested this in people with both diabetes and periodontitis were included and most of them showed that, after periodontal treatment, levels of adiponectin (which helps reduce inflammation and improve insulin sensitivity) increased. However, results for leptin were less clear. This suggests that taking care of gum health might support better diabetes management. The overall strength of evidence was low due to methodological limitations and heterogeneity among studies. Current findings should be interpreted cautiously, as available data remain preliminary. Still, more high-quality research is needed to fully understand how treating periodontitis may benefit people with diabetes.
Periodontitis is an inflammatory disease of the oral cavity driven by bacterial dysbiosis that progressively breaks down the tooth-supporting structures. This study leverages a uniquely large dataset of up to 34,000 patient records in the United States analyzed using standardized real-time polymerase chain reaction-based molecular testing to quantify bacterial profiles associated with periodontitis. Our analysis focused on 11 bacterial taxa from the red, orange, and green complexes. We assessed bacterial abundance, expressed as genome copies per milliliter, across periodontitis stages and associations with age and systemic conditions. Across stages 1-4 (according to the American Academy of Periodontology classification), the concentration of the three red complex bacteria, Porphyromonas gingivalis, Tannerella forsythia, and Treponema denticola increased up to 11-fold, the highest increase observed among all studied bacteria. A substantial microbial shift in younger patients was observed, while older individuals exhibited a higher prevalence of red complex pathogens. The relative abundance of P. gingivalis increased significantly, from 4% in stage 1 periodontitis to 17% in stage 4. Cumulative bacterial load analysis based on the presence or absence of red complex bacteria revealed that the median bacterial load was 5-fold higher in samples where red complex bacteria were present. The inter-bacterial correlations increased with demographic and clinical variables as periodontitis advanced. The findings revealed a significant positive association between increased bacterial loads, particularly red complex bacteria and higher periodontitis stages, positioning them as a key indicator of dysbiosis and a potential biomarker for disease advancement. Periodontitis is a serious gum disease that damages the tissues supporting the teeth. It is caused by harmful bacteria in the mouth and becomes worse over time if not treated. In this study, we analyzed oral rinse samples collected from more than 34,000 people using a DNA-based method to measure the levels of different bacteria. We focused on 11 bacteria known to be involved in gum disease and compared their presence in healthy versus mild to severe cases. We found that three bacteria, Porphyromonas gingivalis, Tannerella forsythia, and Treponema denticola, became much more common as the disease got worse, with one of them, P. gingivalis, increasing 4-fold in severe cases compared with mild ones. Older adults were more likely to have these harmful bacteria, but younger patients showed notable shifts in their bacterial makeup as well. These results suggest that certain bacteria, especially P. gingivalis, may serve as warning signs for more advanced gum disease. Our findings could help to improve how gum disease is diagnosed and tracked, leading to better care and prevention. This is the largest study of its kind and offers new insight into the role of bacteria in oral health.
To identify novel periodontal phenotypes using unsupervised machine learning on a large-scale, multicenter cohort, specifically characterizing disease patterns based on the "periodontal architecture" of localized structural failures (tooth mobility and molar furcation defects) rather than global severity averages alone. This cross-sectional study analyzed electronic health records from 15,723 adult patients with periodontitis. A high-dimensional feature vector (D = 72) was constructed for each patient, integrating tooth-specific ordinal grades for mobility and furcation, mean probing depths (PPD), clinical attachment loss (CAL), and systemic health variables. Unsupervised phenotyping was performed using principal component analysis (PCA), t-SNE visualization, and K-means clustering. Cluster validity was assessed via Silhouette Analysis, and phenotypes were compared using ANOVA and Chi-square (X2) tests. Four distinct architectural phenotypes were identified: (1) Maintenance/Healthy, representing stability; (2) Anterior-Mobility dominant, defined by high-grade anterior mobility (52.4% prevalence), and the highest diabetes prevalence (12.2%); (3) Molar-Furcation Dominant, a male-dominated group (61%) characterized by advanced posterior furcation defects (93.8% prevalence) despite lower anterior mobility; and (4) Generalized severe, exhibiting global architectural collapse. The phenotypes demonstrated statistically significant separation across all clinical metrics (p < 0.001). Periodontitis manifests as distinct architectural archetypes-specifically "Anterior-Mobility" and "Molar-Furcation" phenotypes-that are often aggregated into a single severity category by traditional staging. These data-driven clusters have unique systemic risk profiles, suggesting that diagnosis and treatment planning should incorporate the specific localization of structural failure. Severe gum disease (periodontitis) is traditionally classified by overall severity, often grouping different types of tooth damage into the same broad category. To uncover hidden patterns, we used an artificial intelligence technique to analyze the detailed dental and medical records of more than 15,000 patients. Instead of simply grouping patients by how advanced their disease was, the computer identified four distinct patient profiles based on specific patterns of tooth damage and overall health. Interestingly, two of the most severe profiles were fundamentally different. One featured loose front teeth and was strongly linked to diabetes and systemic health issues. The other featured damage between the roots of back teeth (molars) and was primarily driven by local anatomical problems rather than general health. These findings demonstrate that severe gum disease is not a single condition, but rather develops through completely distinct biological pathways. Recognizing these unique patterns allows dental professionals to move beyond a "one-size-fits-all" approach, paving the way for personalized treatments-such as medical screening for patients with loose front teeth and targeted surgical repairs for molar damage.
This post hoc analysis of the Periodontitis and Coronary Heart Disease study (ClinicalTrials.gov Identifier: NCT01045070) aimed to determine the association between diabetes and recurrent cardiovascular events (CVEs) in patients with cardiovascular disease (CVD) and severe periodontitis. Another objective was to examine the link between diabetes and severe periodontitis. A cohort of 1,002 stationary patients with angiographically proven CVD was included. The patients were examined for the prevalence of diabetes (severity levels: diet, oral antidiabetic drugs, and insulin) and severe periodontitis (≥30% of teeth with ≥5 mm of proximal attachment loss). Recurrent CVEs were summarized as a combined endpoint (myocardial infarction, stroke/transient ischemic attack, cardiovascular death, and stroke-related death). After a 10-year follow-up period, survival analyses were carried out. Hazard ratios (HRs) were adjusted for known cardiac risk factors using Cox regression. A total of 792 patients completed follow-up. The overall incidence of the combined endpoint was 42.8%. The highest HR for CVEs was observed in patients with both diabetes and severe periodontitis (HR = 2.19, 95% confidence interval [CI] 1.59-3.02). HRs were lower in subjects with only periodontitis (HR = 1.52, 95% CI = 1.14-2.04) or only diabetes (HR = 1.88, 95% CI = ∖1.35-2.63). Patients with diabetes who took drugs or required insulin were more likely to have severe periodontitis than patients without diabetes. Patients with diabetes or severe periodontitis were at an increased risk of recurrent CVEs. An association was also found between diabetes and severe periodontitis prevalence. Periodontitis is a serious gum disease that damages the tissue that supports teeth. In its final stage, it can result in tooth loss. Furthermore, studies have shown an association between periodontitis and cardiovascular disease (CVD) and diabetes mellitus. The objective of this study was to investigate the relationship between diabetes and recurrent cardiovascular events (CVEs) in patients with CVD and severe periodontitis. Another objective was to examine the link between diabetes and severe periodontitis. Thus, 1,002 inpatients with CVD were examined for periodontal disease and other medical conditions, such as diabetes mellitus, at the time of the baseline examination. Ten years later, questionnaires and patient records were used to determine whether new CVEs had occurred. CVEs include myocardial infarction, stroke/transient ischemic attack, cardiovascular death, and death caused by stroke. The results showed that severe periodontitis and diabetes mellitus, especially when the two conditions occurred together, increased the risk of CVEs. Furthermore, a higher percentage of patients with diabetes also suffered from severe periodontitis. Further studies should clarify whether periodontal and antidiabetic therapies reduce the risk of CVEs.
This study aims to investigate the transcriptional characteristics and differentiation microenvironment of the CD169+ macrophages in periodontal tissues, and to explore their impact on periodontitis. Single-cell RNA sequencing landscape of periodontal tissues from healthy controls (n = 8) and periodontitis patients (n = 10) were constructed. Immunohistochemical staining was used to detect the percentage of CD169+ macrophages in periodontitis tissues of different severity to explore the potential links between them and periodontitis. Anti-IFNAR1 antibodies were used to block the IFNAR1 receptor in mice to validate the role of type I interferon signaling in CD169+ macrophage differentiation and its impact on the progression of periodontitis. SCENIC analysis, immunohistochemical staining, immunofluorescence staining, flow cytometry, and in vitro experiments were used to identify the surface markers, differentiation microenvironment, and regulatory mechanisms of CD169+ macrophages. The phenotypes of CD169+ macrophages are characterized by CD169+, MERTK+, CX3CR1-, and CCR2-. The CD169+ macrophages could maintain immune homeostasis by producing CCL18 and IL10. The percentage of CD169+ cells in periodontal tissues was found to be negatively correlated with the severity of periodontitis. Type I interferons produced by gingival fibroblasts and keratinocytes are essential for the differentiation of CD169+ macrophages, which in turn orchestrate immunomodulation and tissue homeostasis restoration during the recovery phase of periodontitis. Our findings indicate that type I interferons produced by fibroblasts in periodontal tissues induce monocytes to differentiate into macrophages with a CD169+MERTK+ phenotype. These cells play a role in negative immune regulation and may provide a positive contribution to the recovery of periodontitis. Periodontitis is one of the major diseases that threaten human health. CD169+ macrophages may play a key role in immune homeostasis by producing IL10 and CCL18. The type I interferon-IRF7 axis may induce the differentiation of macrophages into CD169+ macrophages, which in turn orchestrates immunomodulation and tissue homeostasis restoration during the recovery phase of periodontitis. Studying the functions and differentiation mechanisms of CD169+ macrophages in periodontal tissue may offer new therapeutic targets for periodontitis and provide broader benefits for overall human health.
No longitudinal evidence exists linking the trabecular bone score (TBS), a novel index of bone quality, to periodontitis. This 5-year retrospective cohort study explored the relationship between TBS and periodontitis progression in the Electrical Generating Authority of Thailand (EGAT) population, with a focus on postmenopausal women. Baseline mean TBS values of 617 participants aged 30-80 years were assessed from dual-energy x-ray absorptiometry (DXA) images of L1-L4 lumbar spines and classified as normal, partially degraded, or degraded TBS groups. At baseline and at 5-year follow-up surveys, the participants received full-mouth periodontal examinations. Periodontitis progression was defined as an additional ≥3 mm loss of proximal clinical attachment level (CAL) or the loss of a tooth with a baseline proximal CAL of ≥5 mm. Changes in periodontal parameters among the TBS groups were analyzed using the Kruskal-Wallis and Mann-Whitney U tests. The effects of TBS status on periodontitis progression were analyzed using multivariate Poisson regression. Compared with the normal TBS group, participants with degraded TBS had a higher median number of teeth with periodontitis progression-approximately one additional tooth in the entire study population and two additional teeth in postmenopausal women. In the postmenopausal subgroup, degraded TBS was associated with a higher number of teeth with periodontitis progression, with an adjusted risk ratio of 1.85 (95% CI: 1.22-2.81). Degraded TBS is associated with an increased number of teeth with periodontitis progression in postmenopausal women. Early diagnosis and interdisciplinary collaboration between dental and medical professionals may help to mitigate progression in this population. Gum disease (also called periodontitis) is a long-term condition that damages the tissues and bone supporting the teeth. Poor bone quality may be associated with an increased risk of gum disease progression. Bone quality can be measured using the trabecular bone score (TBS), which reflects the structural characteristics of bone rather than bone density. This study followed 617 Thai adults over 5 years to assess the link between bone quality and worsening gum disease. Disease progression was defined as a major loss of tooth support or the loss of a tooth that was already severely affected. Individuals with poor bone quality (degraded TBS) had, on average, one additional tooth with disease progression compared with those with normal bone quality. Among women after menopause, about two additional teeth were affected, and these women were nearly twice as likely to have more teeth with worsening gum disease. These findings suggest an association between decreased skeletal bone quality and a higher risk of gum disease. Early detection of weak bone quality, combined with proper oral care, may help to slow disease progression and to improve quality of life.
Survival analysis is commonly used to identify factors affecting dental implant longevity. While conventional studies typically employ the Cox proportional hazards model, the potential benefits of modern machine-learning algorithms remain unclear. In this study, we aimed to compare Cox regression with three machine-learning approaches-Random Survival Forest (RSF), DeepSurv, and TabNet-to evaluate their predictive performance and the risk factors they identify. Clinical records of 543 implants placed in 256 patients were reviewed, with 32 failures observed over a mean follow-up of 8.0 ± 2.5  years. Cox models incorporating a patient-level frailty term were subjected to an exhaustive subset search. RSF, DeepSurv, and TabNet were tuned using 50 Optuna Bayesian trials, with the best settings refitted on a 90% training split and evaluated on the remaining 10%. Variable importance was assessed using hazard ratios for Cox regression and Shapley Additive Explanations for the machine-learning models. The optimal Cox model achieved a concordance index (C-index) of 0.81 but demonstrated a limited area under the curve (AUC) performance. Among the machine-learning methods, RSF performed best (C-index, 0.72; AUC, 0.79; Integrated Brier Score, 0.044), outperforming DeepSurv and TabNet across all metrics. Both Cox regression and RSF identified anterior placement and periodontitis-related tooth loss as the primary risk factors for implant failure. RSF showed good, but not superior, predictive accuracy compared with the best-performing Cox model. The choice of analytical method for implant survival studies should consider model complexity in relation to the dataset's sample size and event rate. Dental implants are a well-established treatment for replacing missing teeth; however, reports of associated complications are increasing. Identifying risk factors and estimating the likelihood of failure can assist clinicians in treatment planning and follow-up care. In this study, we analyzed 543 implants placed in 256 patients with disabilities, monitored over an average of 8 years, during which 32 implant failures occurred. We first developed traditional statistical models using Cox regression, a well-established method for survival analysis. Then, we evaluated three modern machine-learning models capable of handling time-to-event outcomes: RSF, DeepSurv, and TabNet. Among the machine-learning approaches, the tree-based RSF demonstrated the highest predictive performance; however, it did not outperform the best Cox model after adjusting for several patient- and implant-related characteristics. Both RSF and Cox models consistently identified anterior implant placement and replacement of periodontitis-related tooth loss as the strongest predictors of failure. Our findings suggest that newer machine-learning tools do not inherently outperform conventional models, particularly in datasets with few events. The selection of analytical methods should be guided by dataset size and event frequency rather than the novelty of the algorithm.
This study aimed to evaluate the predictability of the dental implant prognosis system proposed by Kwok et al. in 2023 by assessing implant survival rates across different initial prognosis categories over a 5-year period. Data were retrospectively collected from patients who received at least one dental implant from 2013-2022 at a single university-affiliated dental center. Eligible participants received baseline examinations at the time of implant-supported prosthesis delivery, with follow-up examinations at least 12 months after. Implants were categorized into favorable, questionable, unfavorable, and hopeless, based upon the prognosis categories proposed by Kwok et al. in 2023. Recorded measurements included: age, sex, follow-up duration, initial and latest implant prognoses, supportive care, history of grade C periodontitis, smoking, diabetes, and the use of intravenous bone sparing agents. Descriptive analysis was employed for data interpretation. This study included 651 implants placed in 291 patients. Implants initially classified as having a favorable prognosis exhibited excellent long-term survivability, while those deemed unfavorable at baseline showed the greatest likelihood of deteriorating to a hopeless prognosis. At the latest follow-up, survival rates for implants initially categorized as favorable, questionable, and unfavorable were 100%, 93.5%, and 33.3%, respectively. Cox regression analysis identified initial prognosis, uncontrolled diabetes, and a history of grade C periodontitis as statistically significant risk factors for implant failure, with hazard ratios of 9.70, 35.14, and 66.48, respectively. The dental implant prognosis system proposed by Kwok et al. is a reliable tool in assessing implant survivability within 5 years. Future research should investigate its long-term performance and the relationship between various influencing factors and implant prognosis. This study explored how well a new system developed by Kwok and colleagues in 2023 can predict the long‐term success of dental implants. We reviewed the records of 291 patients who received a total of 651 implants at a university‐affiliated dental center between 2013 and 2022. Each implant was classified into one of four categories—favorable, questionable, unfavorable, or hopeless—at the time the prosthesis was delivered, and patients were followed for up to 5 years. The findings showed clear differences in survival between the groups. Implants with a favorable prognosis had excellent outcomes, with all surviving after 5 years. Those with a questionable prognosis also performed well, with 93.5% still in place. By contrast, only one in three implants in the unfavorable group survived to the 5‐year mark. Additional analysis showed that the initial prognosis, along with uncontrolled diabetes and a history of severe gum disease, were strong risk factors for implant failure. These results suggest that the proposed prognosis system is a valuable tool to help dentists and patients understand the likelihood of implant survival over time. More research is needed to confirm how well it works in the longer term.
A study was made to assess the diagnostic and predictive value of bleeding on probing (BoP) and the modified Bleeding Index (mBI) for identifying progressive peri-implant bone loss over a 24-month period in patients enrolled in supportive peri-implant care. A prospective cohort study was carried out of 59 patients with screw-retained implant-supported prostheses followed-up on for 24 months. Clinical parameters, including BoP, mBI, probing depth and plaque index, were recorded at six sites per implant across five follow-up visits. Progressive peri-implant bone loss was defined as ≥ 0.5 mm of marginal bone loss as assessed radiographically. The longitudinal diagnostic performance of the bleeding indices was evaluated using sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and receiver operating characteristic (ROC) analyses. After 24 months, 9 of 59 implants (15.3%) demonstrated progressive bone loss. Both BoP and mBI showed high sensitivity (88.9%-100%) but low specificity (0%-26%) for detecting bone loss. PPV was low (16%-18%), whereas NPV remained high (91%-100%). Recurrent low-grade bleeding (mBI = 1) observed across multiple visits was more strongly associated with progressive bone loss than isolated episodes of severe bleeding. Consistent absence of bleeding was associated with peri-implant stability. In patients receiving supportive peri-implant care, the absence of bleeding is a reliable indicator of peri-implant health. While bleeding assessed at a single timepoint has limited specificity, longitudinal patterns of mild bleeding are of greater value in predicting disease progression, highlighting the importance of regular monitoring and of standardized clinical assessment protocols. This prospective cohort study was not registered prior to participant recruitment and randomization.
Medication-related osteonecrosis of the jaw (MRONJ) represents a major clinical challenge for oral and maxillofacial surgery departments as well as dental practices. With increasing life expectancy and the more frequent use of medications associated with osteonecrosis, the incidence of MRONJ continues to rise. To date, there are no uniform treatment standards with scientifically proven effectiveness for this condition. To evaluate the impact of platelet-rich fibrin (PRF) on the outcomes of MRONJ treatment and to identify factors that may influence the effectiveness of PRF therapy, we conducted a comparative prospective study including 22 patients divided into two groups: patients treated with PRF and patients treated without PRF. PRF was prepared according to the PRF Duo Quattro Process protocol for PRF (Nice, France). The study was registered at ClinicalTrials.gov (NCT07464678). The following parameters were assessed: age, smoking status, gender, lesion location, body mass index (BMI), C-reactive protein (CRP) concentration, pain intensity, presence or absence of fistulas, soft tissue healing and radiological findings. Patients were evaluated preoperatively and postoperatively at 14 days, 6 weeks, and 6 months. The study demonstrated a reduction in pain after surgery among patients treated with PRF. In addition, the use of PRF resulted in improved healing outcomes in patients with elevated CRP. Higher BMI was associated with poorer therapeutic response to PRF. Improvements in soft tissue healing and disease stage were observed in the PRF group; however, these differences did not reach statistical significance. All findings should be interpreted with caution due to the limited sample size. There is still no standardized treatment for MRONJ. The use of platelet-rich fibrin as an inexpensive and safe adjunctive therapy may provide clinical benefits for patients, particularly through a significant reduction in pain. Further large-scale, multicenter studies are required to confirm these findings.
The present study aimed at gaining insight on patients´ perception of peri-implantitis and its treatment and also to explore the effect of treatment outcome on patients´ perception and satisfaction. Patients who had received peri-implantitis treatment were contacted and invited to participate in the questionnaire-based survey. Overall, 30 items were surveyed, including demographics, data concerning implant placement, diagnosis and signs/symptoms of peri-implantitis, level of education of disease, risk factors, knowledge of factors implicated in disease recurrence, and treatment delivered along with its self-perceived outcomes. Moreover, the treatment outcome was further recorded. Descriptive analyses and correlation tests were applied to explore association. Based on an a priori sample size calculation, 100 patients with 258 implants subjected to peri-implantitis treatment were included. In total, 63% of the patients successfully responded to therapy displaying arrest in progressive bone loss, 26% demonstrated progressive bone loss (≥ 1 mm) and 11% were subjected to implant removal. The overall level of knowledge about peri-implantitis was moderately low, where ∼ 60% of the patients surveyed reported null knowledge about diagnosis, prevalence, or risk factors associated with disease occurrence, despite having received treatment of this disease. Compliers with supportive care demonstrated greater level of concern and knowledge regarding peri-implantitis and its recurrence. Patients were overall satisfied immediately (following therapy), at early (re-evaluation), and at late stages (during follow-up) with therapeutic outcomes of peri-implantitis, despite the therapeutic outcome achieved. In addition, patients accepted the possibility of disease recurrence and their role in minimizing it. Patient-reported information on factors related to peri-implantitis occurrence and recurrence is suboptimal. Nearly 60% of the patients are unaware of factors related to peri-implantitis ocurrence. However, peri-implantitis therapy does not seem to negatively interfere in the patients´ quality of life or satisfaction, despite the treatment outcomes. This study examined how patients understand peri-implantitis and how they feel about its treatment. One hundred patients who received peri-implantitis therapy completed a questionnaire, and treatment outcomes were evaluated using x-rays. Most patients had limited knowledge about peri-implantitis, its causes, and risk factors, even after treatment. Patients who attended regular follow-up care showed greater awareness of the disease. Despite differences in treatment outcomes, including ongoing bone loss or implant removal, patients were generally satisfied with their treatment and accepted the possibility of disease recurrence. These findings highlight the need for better patient education, while showing that peri-implantitis treatment does not negatively affect patient satisfaction.
The accurate assessment of infraosseous periodontal defects is crucial for effective diagnosis and treatment planning. Cone-beam computed tomography (CBCT) enables detailed imaging of these defects; however, to leverage their full potential, CBCT images must be reconstructed in 3 dimensions (3D). Manual and semi-automatic (SA) segmentation methods are time-consuming and prone to human error. This study aimed to evaluate the performance of a deep learning (DL) model in segmenting mandibular infraosseous periodontal defects on CBCT scans. A multi-stage Segmentation Residual Network (SegResNet)-based DL model was used to segment CBCT scans from patients with stages III to IV periodontitis. Linear and volumetric measurements of infraosseous defects from DL-generated 3D models were compared to those obtained using SA segmentation. The depth (INFRA), width (WIDTH), angle (ANGLE), and volume of 48 infraosseous defects were assessed on both DL and SA segmentations. Measurements made on the DL and SA segmentations correlated strongly. The intraclass correlation coefficient (ICC) was 0.941 (p < 0.0001) for INFRA, 0.943 (p < 0.0001) for WIDTH, 0.889 (p < 0.0001) for ANGLE, and 0.948 (p < 0.0001) for defect volume. These results indicate high reliability of the DL model in capturing key characteristics of infraosseous periodontal defects. These findings support the use of DL-based CBCT segmentation as a valuable tool for enhancing periodontal diagnosis. However, as this study was limited to mandibular defects, applicability to maxillary cases remains to be validated. Periodontitis can cause severe bone loss around teeth, leading to the formation of complex defects that are challenging to diagnose and to treat. Cone‐beam computed tomography (CBCT) provides detailed 3D imaging of these defects, but current methods for segmenting CBCT scans and acquiring 3D models are time‐consuming and prone to human error. This study evaluated the ability of artificial intelligence (AI) to automatically segment infraosseous periodontal defects on CBCT images. Using a SegResNet‐based deep learning model, the manuscript compared AI‐generated 3D models to the results of traditional semi‐automatic segmentation methods. The depth, width, angle, and volume of 48 infraosseous defects were measured, assessing whether AI could match human accuracy. The AI model performed exceptionally well, with strong statistical agreement between AI and human‐generated measurements. By improving the way periodontal defects are visualized and measured, AI‐powered CBCT analysis could help dentists make better treatment decisions, reduce variability in diagnosis, and reduce the complication rates.
Although periodontal disease (PD) has been linked to an increased risk of several gastrointestinal diseases such as inflammatory bowel disease and celiac disease, research on the association between PD and irritable bowel syndrome (IBS) is still insufficiently explored, with conflicting results. We aimed to investigate the potential association between self-reported oral symptoms and IBS based on the UK Biobank cohort. Oral symptoms were assessed via questionnaire. Participants reporting at least one of gum pain, gum bleeding, or loose teeth were classified as being at high risk of PD. The primary outcome was incident IBS. Cox proportional hazards regression, incorporating multiple covariates, was applied to calculate hazard ratios (HRs) and 95% confidence intervals (CIs) in examining the links between oral symptoms, high PD risk, and IBS incidence. Subgroup and sensitivity analyses were conducted. This longitudinal cohort study was conducted among 420,371 participants, 8642 incident cases of IBS (2.1%) were identified. Cox regression analyses showed that several oral symptoms, including mouth ulcers, gum pain, gum bleeding, toothache, and denture use, were significantly associated with an increased risk of IBS. No significant association was observed between loose teeth and IBS in any model. Compared with the low PD risk group, individuals at high risk of PD had an elevated likelihood of IBS onset (HR = 1.19, 95% CI: 1.13-1.25). Subgroup and sensitivity analyses strengthened the validity of these findings. Oral symptoms (mouth ulcers, gum pain, gum bleeding, toothache, and denture use) and high risk of PD were both associated with an increased incidence of IBS. Incorporating oral health management into comprehensive strategies may contribute to the prevention of IBS. There is a close connection between oral health and gut health. This long-term study of more than 420,000 UK adults found that individuals experiencing mouth ulcers, gum pain, gum bleeding, toothache, or denture use had a higher risk of developing irritable bowel syndrome (IBS) later in life. Additionally, participants classified as being at high risk for periodontal disease (PD; those with at least one symptom of gum pain, gum bleeding, or loose teeth) had about a 19% higher risk of developing IBS compared with the low PD risk group. Therefore, incorporating active management of oral problems into personal health practices could offer a new perspective for IBS prevention. Caring for oral health is not just about maintaining local wellness but is a crucial part of overall bodily health.
Information on childhood cancer burden is crucial for effective cancer policy planning. Unfortunately, observed paediatric cancer data are not available in every country, and previous global burden estimates have not discretely reported several common cancers of childhood. We aimed to inform efforts to address childhood cancer burden globally by analysing results from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2023, which now include nine additional cancer causes compared with previous GBD analyses. GBD 2023 data sources for cancer estimation included population-based cancer registries, vital registration systems, and verbal autopsies. For childhood cancers (defined as those occurring at ages 0-19 years), mortality was estimated using cancer-specific ensemble models and incidence was estimated using mortality estimates and modelled mortality-to-incidence ratios (MIRs). Years of life lost (YLLs) were estimated by multiplying age-specific cancer deaths by the standard life expectancy at the age of death. Prevalence was estimated using survival estimates modelled from MIRs and multiplied by sequelae-specific disability weights to estimate years lived with disability (YLDs). Disability-adjusted life-years (DALYs) were estimated as the sum of YLLs and YLDs. Estimates are presented globally and by geographical and resource groupings, and all estimates are presented with 95% uncertainty intervals (UIs). Globally, in 2023, there were an estimated 377 000 incident childhood cancer cases (95% UI 288 000-489 000), 144 000 deaths (131 000-162 000), and 11·7 million (10·7-13·2) DALYs due to childhood cancer. Deaths due to childhood cancer decreased by 27·0% (15·5-36·1) globally, from 197 000 (173 000-218 000) in 1990, but increased in the WHO African region by 55·6% (25·5-92·4), from 31 500 (24 900-38 500) to 49 000 (42 600-58 200) between 1990 and 2023. In 2023, age-standardised YLLs due to childhood cancer were inversely correlated with country-level Socio-demographic Index. Childhood cancer was the eighth-leading cause of childhood deaths and the ninth-leading cause of DALYs among all cancers in 2023. The percentage of DALYs due to uncategorised childhood cancers was reduced from 26·5% (26·5-26·5) in GBD 2017 to 10·5% (8·1-13·1) with the addition of the nine new cancer causes. Target cancers for the WHO Global Initiative for Childhood Cancer (GICC) comprised 47·3% (42·2-52·0) of global childhood cancer deaths in 2023. Global childhood cancer burden remains a substantial contributor to global childhood disease and cancer burden and is disproportionately weighted towards resource-limited settings. The estimation of additional cancer types relevant in childhood provides a step towards alignment with WHO GICC targets. Efforts to decrease global childhood cancer burden should focus on addressing the inequities in burden worldwide and support comprehensive improvements along the childhood cancer diagnosis and care continuum. St Jude Children's Research Hospital, Gates Foundation, and St Baldrick's Foundation.