Clinical Oral Investigations最新文献

Objectives: "The objective of this randomized control trial is to compare the marginal bone loss (MBL) in single implant-retained mandibular overdentures (SIRMO) retained by two different types of attachments using two healing protocols after a 2-year follow-up.

Materials & methods: SIRMOs were constructed for eighty completely edentulous patients. The latters were randomized based on the healing protocol and the used attachments into 4 equal groups: Submerged healing with ball attachment (BS), submerged with CM-LOC attachment (CS), non-submerged with ball attachment (BN), and non-submerged with CM-LOC (CN). Standardized peri-apical radiographs at baseline, 12 and 24 months were recorded to measure MBL. Comparisons for numerical data were performed using either Mann Whitney-U or Kruskal Wallis tests. Binary and categorical data were compared using chi square test. Significance level was set at p < .05.

Results: During the healing period, 6 implants failed, and 4 drop-outs were recorded. At the second year, 27/34 ball groups and 28/36 CM-LOC groups were recalled, no significant difference between B (0.28 ± 0.44) and C (0.38 ± 0.46) favoring B group (p = .3), and N (0.27 ± 0.39) and S (0.43 ± 0.51) favoring N group (P = .6). MBL revealed no significant difference neither between B and C groups nor between N and S groups.

Conclusion: Both attachments showed physiologically accepted limits of MBL, favoring the non-submerged healing protocol after a 2-year follow-up period.

Clinical relevance: Submerged (S) and Non-submerged (N) protocols could be used for a SIMOR, favoring the N protocol after a 2-year follow-up.

Trial registration number: PACTR20183003085193.

Aim: This in vitro study aimed to compare the direct (visual exam) versus indirect (3D-colored digital images exam) assessments of ICDAS (dental caries), BEWE (erosive tooth wear), and TF (enamel fluorosis lesions) indices performed on the occlusal surfaces of extracted human teeth for the detection and severity differentiation of dental caries, erosive tooth wear, and enamel fluorosis lesions.

Materials and methods: A total of 453 occlusal surfaces from extracted human teeth were mounted on 28 typodont models. Surfaces were examined directly (visual) and indirectly using 3D-coloured intraoral scans (TRIOS 4, 3Shape). Three indices were assessed: International Caries Detection and Assessment System (ICDAS; caries), Basic Erosive Wear Examination (BEWE; erosive tooth wear), and Thylstrup-Fejerskov (TF; fluorosis). Agreement between methods was analysed using weighted kappa statistics and percentage agreement.

Results: Substantial agreement was observed between direct and indirect methods: ICDAS (κ = 0.72, 64%), BEWE (κ = 0.70, 73%), and TF (κ = 0.75, 86%). Early lesions (ICDAS 1-2, BEWE 1) were more frequently misclassified.

Conclusions: 3D-coloured intraoral scanner imaging shows substantial agreement with visual examination for detecting and grading caries, erosive tooth wear, and fluorosis.

Clinical significance: This study supports the use of intraoral scanners as a practical adjunct to visual examination for documentation, education, and potentially remote consultations. Further clinical validation is warranted.

Objectives: This study aims to propose an iterative finite element method to simulate and analyze the long-term biomechanical responses during space closure in clear aligner therapy (CAT) extraction treatment.

Materials and methods: A patient-specific FE model was reconstructed from cone beam computed tomography and intraoral scanning. An innovative algorithm has been developed to automate the generation of CA model sequences for subsequent force loading and to enable dynamic simulation through real-time updates of teeth and periodontal ligament (PDL) positions. Each aligner was simulated in 10 iterations ("micro-cycle"), and the full treatment consisted of 30 aligners with 0.25 mm/step ("macro-cycle").

Results: The algorithm achieved complete space closure. In the macro-cycle, torque control gradually escalated as the extraction gap narrowed, leading to a reversal in the direction of root movement of anterior teeth in the 16th aligner. In the micro-cycle, the initial displacement of the anterior teeth accounts for 36% to 65% of the cumulative displacement, with the contact stress initially distributed evenly across the labial surface of the dental crown, gradually concentrating on the labial cervix and lingual incisal sites.

Conclusions: Changes in contact stress led to altered tooth movement, initially tipping and later torque movements during space closure. Cumulative displacements, rather than initial responses, should represent tooth movement tendency.

Clinical relevance: The proposed methods can be integrated into existing clinical software platforms and advance precision treatment planning through biomechanical simulation. Based on the biomechanical results, personalized staging strategies and overcorrection can be made to alleviate side effects.

Objectives: The objective of this study is to assess how different annotation methods used during AI model training affect the accuracy of early caries lesion detection, and how the choice of the evaluation reference standard leads to significant differences in assessing AI models' outcomes.

Clinical relevance: AI-based tools for caries detection are becoming common in dentistry. This study shows that how these models are evaluated can significantly impact perceived performance. Clinicians and developers should ensure that evaluation standards are independent and clinically relevant to avoid overestimating AI's diagnostic abilities and to build trust for real-world use and regulatory approval.

Methods: Multiple AI caries lesion segmentation models were trained on the ACTA-DIRECT dataset using annotations from (1) single dentists, (2) aggregated strategies (majority vote, consensus meetings, STAPLE), and (3) micro-CT-based methods. Model accuracy was evaluated using two approaches: (1) comparison against micro-CT-based annotations and (2) comparison against the training-matched annotations. Statistical significance of differences in model diagnostic accuracy across annotation strategies was assessed using the McNemar test.

Results: There was no statistically significant difference in diagnostic accuracy among AI models when compared to micro-CT-based annotations. However, the diagnostic accuracy was considered statistically significantly higher when the results of the AI models were evaluated with the training-matched annotations.

Conclusion: Our findings indicate a strong influence of reference standards on AI model evaluation. While annotation strategies during training did not significantly affect AI accuracy in caries lesion segmentation, evaluation was subject to bias when models were tested against different reference standards. CLINICAL RELEVANCE : AI-based tools for caries detection are becoming common in dentistry. This study shows that how these models are evaluated can significantly impact perceived performance. Clinicians and developers should ensure that evaluation standards are independent and clinically relevant to avoid overestimating AI's diagnostic abilities and to build trust for real-world use and regulatory approval.

Objectives: Although superficial fungal infections of the oral and maxillofacial region are common, deep fungal infections remain unfamiliar. We investigated the prevalence of fungal infections in this location in Thailand from specimens examined in the Department of Oral and Maxillofacial Pathology over a 50-year period.

Materials and methods: Cases diagnosed as fungal infections in our archive were selected. Demographic data, risk factors, clinical and radiographic features, clinical differential diagnoses and treatments were analyzed.

Results: Of 22,070 biopsied specimens, 41 cases (0.19%) were fungal infections in this location. The prevalence increased in the last decade. Approximately 71% were candidiasis, while 29% constituted deep infections including mucormycosis, aspergillosis and histoplasmosis. Fungal infections predominantly affected elderly individuals (mean age: 62.1 years). Both superficial and deep types exhibited a female predominance with a ratio of 1:3.8 and 1:3, respectively. About 60% of patients were associated with risk factors, namely, betel quid chewing, diabetes mellitus and human immunodeficiency virus infection. Clinically misdiagnosed chronic hyperplastic candidiasis as erythroleukoplakia/lichen planus, and deep fungal infections as osteomyelitis/oral squamous cell carcinoma were frequently observed. All candidiasis were treated with topical antifungal drugs, while mucormycosis and histoplasmosis required systemic antifungal therapy.

Conclusions: Fungal infections constituted less than 1% among biopsied specimens. The majority of fungal infections were clinically misdiagnosed. Currently, histopathologic examinations using proper special stains play a vital role to achieve a definite diagnosis.

Clinical relevance: Unfamiliarity with deep fungal infections in the oral and maxillofacial region among oral healthcare personnel may lead to misdiagnosis and inappropriate treatment. Awareness of fungal infections in this area must be encouraged.

Objectives: To explore correlation between ability of dentists and dental students to recognise the clinical presentation of oral cancer and their self-rated confidence.

Methods: A cross-sectional, analytical design was used for this study. A validated oral disease recognition scale (ODRS) encompassing a range of benign, premalignant, and malignant oral conditions was used for data collection. For each of the seven patient cases, the participants were asked to provide a diagnosis and rate their self-perceived confidence. Confidence ratings were used as a predictor in a logistic regression model to determine its value as a predictor of diagnosis accuracy, controlling for other factors.

Results: A total of 252 participants completed the online survey. All correlations between pairs of Cases are positive and statistically significant (p < 0.001). An ordinal logistic regression model predicting Correct vs. Incorrect based on Confidence, Case, participant status, participant gender, and participant age group (and a random effect for participant) suggests that each unit increase in confidence results in a 0.235 unit increase in log-odds of a correct response (an Odds Ratio of 1.265, p < 0.001).

Conclusions: Overall, confidence ratings appear to predict diagnosis accuracy, after controlling for case and participant characteristics. Notwithstanding the limitations of the current study, the oral disease recognition scale may serve as a useful tool to assess clinicians' ability to recognize oral cancer and identify potential cognitive biases in their clinical assessment skills.

Clinical relevance: This study highlights the correlations between diagnostic accuracy and confidence of dentists and dental students in identifying oral cancer, which is crucial for timely referral and improved patient outcomes. By identifying gaps in diagnostic confidence and potential cognitive biases, the findings can inform targeted educational interventions for reliable oral cancer screening in general dental practice.

Objective: Obesity and periodontitis are recognized as a major public health problem. The aim of this study was to investigate the response of different body mass index(BMI) groups to non-surgical periodontal treatment(NSPT).

Methods: We retrospectively reviewed the medical records, including baseline medical information and BMI, of patients with periodontal disease. We also analyzed periodontal indices, including periodontal pocket depth (PD), clinical attachment level (CAL), bleeding on probing (BOP), before and after NSPT to assess the correlation between BMI and the effectiveness of NSPT.

Results: A total of 147 patients participated in this study, including 88 individuals in the normal BMI group with an average age of 49.02 ± 10.05 years and 59 individuals in the high BMI group with an average age of 48.15 ± 8.78 years. The results showed that the periodontal index of the abnormal BMI group was higher than that of the normal BMI group both before and after NSPT. NSPT had significant effects on patients with periodontitis in both the normal and abnormal BMI groups. The abnormal BMI group exhibited a significantly higher change in the percentage of PD ≧ 4 mm compared to the normal BMI group (p = 0.019).

Conclusion: Despite the fact that Taiwan individuals have lower BMI groupings, those with abnormal BMI exhibit less favorable periodontal indices compared to those with normal BMI. However, NSPT has shown promising results in improving periodontal disease among individuals with abnormal BMI. Encouragement should be given to individuals with generalized severe periodontitis and a high BMI to actively consider receiving periodontal treatment.

Clinical relevance: Despite generally lower BMI in Taiwan, individuals with abnormal BMI exhibit less favorable periodontal health. NSPT shows promise in improving their periodontal condition. Tailored interventions may enhance periodontal outcomes.

Objectives: This study aimed to investigate the microbial spectrum and resistance patterns in surgically treated odontogenic infections and to assess the clinical impact of resistance, including systemic complications and hospitalization. Resistance rates were additionally evaluated in relation to reported penicillin hypersensitivity.

Methods: A total of 740 inpatient cases with microbiological testing from surgically treated odontogenic infections at the Jena University Hospital from January 1, 2012, to December 31, 2023, were analyzed. Resistance rates were assessed at infection level. Time trends were analyzed using Poisson regression. Associations between resistance rates and clinical variables were evaluated using binary logistic regression.

Results: Clindamycin resistance was observed in 38.9% of infections, while amoxicillin/clavulanate (6.9%) and moxifloxacin (4.5%) showed lower resistance rates. No statistically significant trends in resistance rates were observed. Moxifloxacin resistance increased the risk of systemic complications (OR: 10.875; 95%-CI: 2.364-50.017; p = 0.002), while no significant associations were found between antibiotic resistance and prolonged hospitalization. A history of penicillin hypersensitivity was associated with increased clindamycin resistance (OR: 2.156; 95%-CI: 1.038-4.480; p = 0.04).

Conclusions: Clindamycin exhibits high resistance rates in odontogenic infections and should be critically re-evaluated as empirical therapy, especially in patients with penicillin hypersensitivity. Given the overall low resistance rates to moxifloxacin, resistance to this agent indicated highly resistant infections and was associated with an increased risk of systemic complications.

Clinical relevance: Continuous resistance surveillance and adaptation of empirical therapy are essential for managing severe odontogenic infections and reducing life-threatening infection-related complications, emphasizing the need for antimicrobial stewardship.