Journal of Clinical Periodontology最新文献

Aim

Oral dysbiosis and periodontal inflammation might play a role in oesophageal carcinogenesis via the translocation of periodontal pathogens. We aimed to assess whether poor oral health is associated with oesophageal cancer.

Methods

We conducted a population-based case–control study using the Korean National Health Insurance Service database to evaluate poor oral health as the exposure and oesophageal cancer as the outcome. Two study designs were employed: (1) oral health analysis using screening data, and (2) periodontal disease analysis using claims data. Oesophageal cancer cases were matched to cancer-free controls at a 1:4 ratio using extensive propensity score matching.

Results

After matching, 4238 cases and 16,904 controls were included in the oral health analysis, and 18,905 cases and 75,604 controls were included in the claims-based analysis. In the multivariable analysis, missing teeth (adjusted OR [aOR], 1.16; 95% confidence interval [CI]: 1.08–1.25) and periodontal disease (aOR, 1.05; 95% CI: 1.01–1.09) were both significantly associated with increased odds of oesophageal cancer. Poor oral hygiene practices including infrequent brushing, irregular bedtime brushing, lack of interdental cleaning and dental visits also showed positive associations. Subgroup analyses showed consistent associations across obesity and smoking status, whereas the associations were less consistent in women, the elderly and non-drinkers.

Conclusion

Poor oral health indicators including inadequate oral hygiene behaviours were associated with elevated odds of oesophageal cancer, suggesting the potential utility of oral health status in risk stratification.

Aim

To evaluate the 3-year clinical and radiographic outcomes of implant-supported restorations with different emergence profiles (CONVEX vs. CONCAVE).

Materials and Methods

A total of 47 patients received a single implant in the aesthetic zone and were allocated to one of three groups: (1) CONVEX: customized provisional with a convex emergence profile (n = 15); (2) CONCAVE: customized provisional with a concave profile (n = 16); (3) Control: no provisional restoration (n = 16). Final crowns in groups CONVEX and CONCAVE were fabricated to replicate the emergence profile of the respective provisional restorations. Follow-ups were performed at baseline, 6 months, 1 year and 3 years. The primary outcome was mid-facial mucosal recession and secondary outcomes included clinical, radiographic and aesthetic outcomes as well as profilometric measurements. Multivariable logistic regressions and mixed-effects models were used to compare the groups.

Results

Out of the 47 patients originally included, 42 were available for re-examination at 3 years follow-up. At 3 years, the frequency of mucosal recession amounted to 46.7% in group CONVEX, 13.3% in group CONCAVE and 40.0% in group Control. Adjusted logistic regression models revealed that the CONVEX group was significantly more likely to show recessions at 3 years (odds ratios [ORs]: 7.3, 95% CI: 1.02–52.14, p = 0.048) when compared with the CONCAVE group. No statistically significant difference in recession frequency was observed between the CONVEX and CONCAVE groups between the 1- and 3-year follow-ups (OR: 3.7, 95% CI: 0.30–46.09, p = 0.303).

Conclusion

The emergence profile design significantly influences soft tissue stability predominantly within the first year after crown insertion. Whenever clinically feasible, a CONCAVE profile is preferable in the aesthetic zone to maintain the level of the mid-facial mucosal margin and reduce the frequency of recessions.

Trial Registration: German Clinical Trials Register: DRKS00009420

Aim

The oral microbiota, a complex and dynamic ecosystem, plays a crucial role in human health, yet systematic studies across the lifespan remain limited. This study aimed to investigate variations in the oral microbiota and the effects of key influencing factors on the oral microbiota at different age groups.

Materials and Methods

In this study, we analysed the oral microbiota of 9662 individuals aged 14–69 years from the US National Health and Nutrition Examination Survey (NHANES) to explore the impact of demographic, lifestyle and environmental factors on microbial diversity and composition. Microbiological characterisation was done using the participants' oral rinses by 16S ribosomal RNA gene sequencing.

Results

Our findings revealed a clear age-related trend in microbial diversity, with Shannon diversity peaking in middle-aged and declining in older adults. The composition of the oral microbiota also varied significantly with age, as different genera exhibited distinct abundance patterns across the lifespan. Gender and race emerged as key influencing factors, with males showing greater Shannon diversity and greater relative abundances of Atopobium, Megasphaera and Porphyromonas spp., and Whites were enriched in Rothia and Veillonella. Socioeconomic factors and lifestyle, particularly smoking, were strongly associated with shifts in microbial communities.

Conclusions

These findings provide a comprehensive overview of the dynamic changes in the oral microbiota throughout life and underscore the intricate interplay between host and environmental factors in shaping microbial composition, offering a foundation for future research on microbiota-related health interventions.

Aim

Periodontitis proxy variables enable an expansion of periodontal research. The study aimed to estimate the validity of questionnaire items and registry data in relation to Stage III–IV periodontitis and having 50% bone loss.

Methods

Malmö Offspring Dental Study (MODS) participants (995) filled out questionnaires and underwent periodontal and panoramic radiography examinations. The questionnaire items, number of periodontal treatment procedures (PTP) in the Dental Health Register (DHR), and number of teeth with ≥ 6 mm probing depth in the Swedish Quality Register for Caries and Periodontal Disease (SKaPa) were evaluated as proxies for severe periodontitis. Stage III–IV periodontitis was the primary reference standard.

Results

For PTP-based severe periodontitis proxy in DHR, positive predictive value (PPV) was 88% and negative predictive value (NPV) 87% for Stage III–IV. The SKaPa-based proxy showed poor positive predictive values (PPVs, < 70%), but similar area under the curve (AUC), 0.74, compared with the DHR data (AUC 0.76). Sensitivity was < 70%, and specificity > 90% for the DHR and SKaPa proxies. Identification of cases with periodontitis by questionnaire combined with the demographic variables age, sex, smoking habits and education yielded good discriminatory ability (AUC > 0.75).

Conclusion

Register-based data can effectively identify individuals with severe periodontitis in large cohort studies, thereby advancing periodontal research.

Aim

To construct predictive models of periodontitis progression by applying Machine Learning (ML) to baseline data from a study of periodontitis progression.

Materials and Methods

Logistic regression (LR), multi-layer perceptron (MLP) and probabilistic graphic model (PGM) were utilised on data from a multi-centre longitudinal study in which periodontally healthy (n = 113) and periodontitis participants (n = 302) were examined bi-monthly for 12 months without treatment. Periodontal examination was performed, and salivary levels of 10 analytes were determined. Clinical and demographic parameters and analytes levels were input into the model. The performance of 14 models was compared using the area under the receiver operating characteristic curve (AUROC), and feature importance was assessed using SHapley Additive exPlanations (SHAP).

Results

The PGM model (Clinical measures, saliva IL-1β, age, sex) demonstrated the best overall performance (AUROC = 0.88), compared to LR (AUROC = 0.72) and MLP (AUROC = 0.58). Although MLP had a lower Brier score (0.12), its sensitivity was 0, limiting its clinical utility. In contrast, PGM achieved a balanced sensitivity (0.55) and specificity (0.81). Feature importance analyses highlighted the number of deep periodontal pockets as a key driver of model predictions in both PGM and MLP.

Conclusions

ML models can predict periodontitis progression, supporting early detection strategies. Our integrative approach, combining clinical data with salivary biomarkers such as IL-1β, improved predictive accuracy.

Aim

Saliva is a diagnostic surrogate for microbial and host biomarkers in periodontitis, but whether it reflects subgingival plaque, gingival crevicular fluid (GCF) or serum remains debated. This study profiled GCF and subgingival plaque from all sites of periodontitis patients, comparing them to saliva and serum.

Materials and Methods

Saliva, serum, subgingival plaque and GCF were obtained from three patients with stage III, grade C periodontitis, having 23, 25 and 27 teeth, respectively, with six sites sampled per tooth. All plaque and GCF samples were pooled per patient. Shotgun sequencing and mass spectrometry proteomics were used for microbiome and proteome analysis, respectively.

Results

Totally 277 microbial taxa were collectively identified in saliva and plaque, 93 of which were differentially abundant between the two. Saliva exhibited higher overall species diversity, but lower periodontal pathogen abundance. A total of 1153 host proteins were identified (saliva: 803; GCF: 932; serum: 195) across the three biological fluids, with 685 shared among saliva and GCF and 109 among all three. Saliva contained slightly fewer proteins than GCF, but shared several common immune, metabolic and enzyme regulation pathways.

Conclusion

Saliva is effective for broad microbiome and proteome screening; whereas plaque delivers greater precision in identifying specific periodontal pathogens directly associated with a periodontal pocket.

Aim

To assess the efficacy of repeated submarginal mechanical instrumentation, as an adjunct to oral hygiene instruction, in the treatment of peri-implant mucositis.

Material and Methods

Patients with peri-implant mucositis were allocated to a control group receiving oral hygiene instructions only, or a test group with adjunctive repeated ultrasonic instrumentation with a polyetheretherketone tip. Bleeding on probing reduction was the primary outcome. A blinded examiner recorded clinical variables, and intraoral scans were obtained at baseline, 12 weeks and 24 weeks.

Results

In total, 58 patients were recruited, and 50 completed the study. Clinical parameters improved from baseline in both groups. There were no significant differences in the reduction of the extent nor the severity of bleeding on probing between the control and the test group at the 12- and 24-week follow-ups, but a significantly higher reduction in the peri-implant mucosa volume was observed in the test group from 12 to 24 weeks.

Conclusions

Ultrasonic instrumentation with a polyetheretherketone tip adjunctive to oral hygiene instructions did not render a higher reduction in bleeding on probing or lead to improved clinical outcomes. Still, it resulted in a higher reduction of the peri-implant mucosa volume as compared to oral hygiene instructions alone.

Background and Aim

Patients' disease perception plays a fundamental role in adherence to therapy and participation in long-term maintenance programmes. This cross-sectional study aimed to assess the cognitive and emotional representation of peri-implant diseases (PIDs) in a cohort of patients with periodontitis.

Methods

Patients diagnosed with both periodontitis and PIDs were enrolled. Psychometric evaluation was conducted using the Brief Illness Perception Questionnaire (Brief-IPQ) and the Oral Health Impact Profile-14. Differences were analysed based on disease severity, and a multivariate logistic regression model was applied to explore associations between patient and implant-level variables and illness perception.

Results

A total of 148 patients (459 implants) were included. Patients exhibited low perception of PIDs, with no differences between peri-implant mucositis and peri-implantitis. However, participants with both peri-implantitis and stage III/IV periodontitis presented with significantly higher Brief-IPQ scores. Having ≥ 3 implants and a history of periodontitis treatment were associated with a 4.16-fold and 6.58-fold increase, respectively, in the odds of a higher Brief-IPQ score.

Conclusions

The cognitive and emotional representation of PIDs was found to be low among patients with both periodontitis and PIDs, but appeared to increase in more advanced clinical profiles. A higher number of implants and prior periodontal treatment were associated with greater disease representation.

Trial Registration: The study protocol was approved by the University Hospital of Siena Ethics Committee (Siena, Italy) (Sezione Area vasta Toscana Sud Est, no. 25906), and it was registered on Clinicaltrials.gov (registration number: NCT06383351)

Aim

To evaluate bone level changes in implants with 1-mm- or 3-mm-high abutments over a 7-year period and to investigate the role of abutment height upon peri-implant status.

Materials and Methods

Two-piece implants were placed 1.5 mm subcrestally with either 1-mm (control) or 3-mm (test) high definitive abutments. Marginal bone level change from the first to seventh year was the primary outcome. Peri-implant status and other patient and peri-implant clinical variables (smoking, peri-implant maintenance therapy compliance, interproximal hygiene, vertical soft tissue thickness and keratinised mucosa width) were also assessed.

Results

After 7 years, 37 subjects (63 implants) were analysed: 17 subjects with 32 implants in the 1-mm abutment group, and 20 subjects with 31 implants in the 3-mm abutment group. Significant differences in marginal bone level changes were observed at 7 years. The 3-mm abutment group showed smaller changes compared to the 1-mm abutment group at mesial sites (−0.27 ± 1.32 mm vs. −0.42 ± 0.50 mm, respectively) and distal sites (−0.33 ± 1.39 mm vs. −0.35 ± 0.38 mm), with both differences being statistically significant (p < 0.001). In the control group, 18 implants (54.6%) presented peri-implant mucositis and 6 implants (18.2%) showed peri-implantitis. In the test group, 23 implants (74.2%) presented peri-implant mucositis and 1 implant (3.2%) showed peri-implantitis. No statistically significant differences were found (p = 0.158).

Conclusions

Subcrestally inserted implants with 3-mm definitive abutments experienced minimal bone loss over long-term follow-up compared to 1-mm abutments. However, since the differences were not statistically significant, no conclusions could be drawn on the protective effect against peri-implantitis.

Aim

The humoral immune system is implicated in the link between periodontitis and atherosclerosis. This study aims to explore how interactions between the oral microbiota and humoral immune responses may contribute to this association.

Materials and Methods

We analysed data from the Northern Finland Birth Cohort 1966, which included 1560 participants who underwent comprehensive health and oral examinations. Serum antibodies against phosphorylcholine (PCho) and malondialdehyde acetaldehyde (MAA) adducts were measured using chemiluminescence immunoassays. In a sub-cohort (n = 868), the oral microbiome from saliva samples was characterised using 16S rRNA gene sequencing.

Results

Higher serum levels of IgA and IgG to PCho, as well as IgA to MAA, were associated with an increased number of teeth with probing pocket depths (PPD) ≥ 4 mm. Several oral bacterial species, including Prevotella dentalis , Filifactor alocis and Treponema denticola , correlated with both PPD ≥ 4 mm and IgA/IgG responses to PCho. Mediation analysis, adjusted for periodontitis risk factors, identified F. alocis as a mediator linking elevated plasma IgG to PCho with the number of teeth with PPD ≥ 4 mm. Additionally, individuals harbouring F. alocis exhibited increased carotid intima-media thickness.

Conclusions

Our findings suggest that F. alocis may serve as a microbial link between periodontitis and atherosclerosis. Future mechanistic studies should investigate how F. alocis induces systemic IgG responses and contributes to atherosclerosis.