Faculty Publications (HBMCDM)

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Complications Due to Medicaments
(Springer Nature Switzerland, 2025) Alkhatib, Zuhair; Abed, Rashid El
Introduction: Medicaments used in the root canal system are of numerous varieties and have effects on both pulpal tissues and microbial flora, not just inside the root canal system, but also on the periodontium. That is why, when choosing any medicament, the clinician must make the right choice. Choose a medicament that has an effect on the microorganisms, as this is the most important factor in root canal failures, and it should have the least effect on the tissues surrounding the root. The medicament should be confined in the root canal system during its use, and care should be taken not to expel it beyond the root apex into the periapical tissues. In case this happens, damage to the periapical tissues ensues, leading to inflammation, swelling and probably tooth loss. In this chapter, we will discuss the most common intracanal irrigation solutions and interim medicament used by endodontist, referring to literature and case reports that provide scientifically based evidence.
Power arms as adjuncts for root control in lower incisor extraction treatment with clear aligners: A case report
(2025-09) Alyammahi, Bayan; Mohammad, Abrar; Syed Gyasudeen, Kabir; Youssef, Yasmin; Prasad, Sabarinath
Background: Clear aligner therapy (CAT) has become a popular choice among patients seeking orthodontic treatment. However, CAT is not optimal for certain types of tooth movements. This case report illustrates a hybrid approach combining CAT with power arms to achieve controlled space closure after lower incisor extraction.
Large Language Models in peri-implant disease: How well do they perform?
(Elsevier BV, 2025-03) Kaklamanos, Eleftherios G
Statement of problem: Artificial intelligence (AI) has gained significant recent attention and several AI applications, such as the Large Language Models (LLMs) are promising for use in clinical medicine and dentistry. Nevertheless, assessing the performance of LLMs is essential to identify potential inaccuracies or even prevent harmful outcomes. Purpose. Purpose: The purpose of this study was to evaluate and compare the evidence-based potential of answers provided by 4 LLMs to clinical questions in the field of implant dentistry. Material and methods: A total of 10 open-ended questions pertinent to prevention and treatment of peri-implant disease were posed to 4 distinct LLMs including ChatGPT 4.0, Google Gemini, Google Gemini Advanced, and Microsoft Copilot. The answers were evaluated independently by 2 periodontists against scientific evidence for comprehensiveness, scientific accuracy, clarity, and relevance. The LLMs responses received scores ranging from 0 (minimum) to 10 (maximum) points. To assess the intra-evaluator reliability, a re-evaluation of the LLM responses was performed after 2 weeks and Cronbach α and interclass correlation coefficient (ICC) was used (α=.05). Results: The scores assigned by the examiners on the 2 occasions were not statistically different and each LLM received an average score. Google Gemini Advanced ranked higher than the rest of the LLMs, while Google Gemini scored worst. The difference between Google Gemini Advanced and Google Gemini was statistically significantly different (P=.005). Conclusions: Dental professionals need to be cautious when using LLMs to access content related to peri-implant diseases. LLMs cannot currently replace dental professionals and caution should be exercised when used in patient care.
Evaluating the evidence-based potential of six large language models in paediatric dentistry: a comparative study on generative artificial intelligence
(Springer Science and Business Media LLC, 2025-02-22) Kaklamanos, Eleftherios G.
Purpose: The use of large language models (LLMs) in generative artificial intelligence (AI) is rapidly increasing in dentistry. However, their reliability is yet to be fully founded. This study aims to evaluate the diagnostic accuracy, clinical applicability, and patient education potential of LLMs in paediatric dentistry, by evaluating the responses of six LLMs: Google AI’s Gemini and Gemini Advanced, OpenAI’s ChatGPT-3.5, -4o and -4, and Microsoft’s Copilot. Methods: Ten open-type clinical questions, relevant to paediatric dentistry were posed to the LLMs. The responses were graded by two independent evaluators from 0 to 10 using a detailed rubric. After 4 weeks, answers were reevaluated to assess intra-evaluator reliability. Statistical comparisons used Friedman’s and Wilcoxon’s and Kruskal–Wallis tests to assess the model that provided the most comprehensive, accurate, explicit and relevant answers. Results: Variations of results were noted. Chat GPT 4 answers were scored as the best (average score 8.08), followed by the answers of Gemini Advanced (8.06), ChatGPT 4o (8.01), ChatGPT 3.5 (7.61), Gemini (7,32) and Copilot (5.41). Statistical analysis revealed that Chat GPT 4 outperformed all other LLMs, and the difference was statistically significant. Despite variations and different responses to the same queries, remarkable similarities were observed. Except for Copilot, all chatbots managed to achieve a score level above 6.5 on all queries. Conclusion: This study demonstrates the potential use of language models (LLMs) in supporting evidence-based paediatric dentistry. Nevertheless, they cannot be regarded as completely trustworthy. Dental professionals should critically use AI models as supportive tools and not as a substitute of overall scientific knowledge and critical thinking.
Challenges faced when masking a single discoloured tooth - Part 2: indirect restoration procedures
(2025-07) Aljanahi, May; Alhussin, Argwan; Elbishari, Haitham
Purpose: The use of large language models (LLMs) in generative artificial intelligence (AI) is rapidly increasing in dentistry. However, their reliability is yet to be fully founded. This study aims to evaluate the diagnostic accuracy, clinical applicability, and patient education potential of LLMs in paediatric dentistry, by evaluating the responses of six LLMs: Google AI’s Gemini and Gemini Advanced, OpenAI’s ChatGPT-3.5, -4o and -4, and Microsoft’s Copilot. Methods: Ten open-type clinical questions, relevant to paediatric dentistry were posed to the LLMs. The responses were graded by two independent evaluators from 0 to 10 using a detailed rubric. After 4 weeks, answers were reevaluated to assess intra-evaluator reliability. Statistical comparisons used Friedman’s and Wilcoxon’s and Kruskal–Wallis tests to assess the model that provided the most comprehensive, accurate, explicit and relevant answers. Results: Variations of results were noted. Chat GPT 4 answers were scored as the best (average score 8.08), followed by the answers of Gemini Advanced (8.06), ChatGPT 4o (8.01), ChatGPT 3.5 (7.61), Gemini (7,32) and Copilot (5.41). Statistical analysis revealed that Chat GPT 4 outperformed all other LLMs, and the difference was statistically significant. Despite variations and different responses to the same queries, remarkable similarities were observed. Except for Copilot, all chatbots managed to achieve a score level above 6.5 on all queries. Conclusion: This study demonstrates the potential use of language models (LLMs) in supporting evidence-based paediatric dentistry. Nevertheless, they cannot be regarded as completely trustworthy. Dental professionals should critically use AI models as supportive tools and not as a substitute of overall scientific knowledge and critical thinking.
The Prevalence of Supernumerary Teeth in a Sample of Non-Syndromic Young Patients from Greece
(MDPI AG, 2025-07-14) Kaklamanos, Eleftherios G.
Background/Objectives: Supernumerary teeth, or hyperdontia, refer to a developmental anomaly defined by the presence of additional teeth beyond the normal dentition. Hyperdontia may result in clinical complications including delayed eruption, crowding, and malocclusion. Despite its prevalence having been studied in various populations, data from geographically isolated or peripheral groups remain limited. This study aimed to investigate the prevalence and distribution of supernumerary teeth in a sample of children and adolescents from the island of Lesvos, Greece. Methods: A retrospective cross-sectional study was conducted using panoramic radiographs from 621 Caucasian children aged 9–16 years who attended orthodontic or general/pediatric dental clinics in Mytilini, Lesvos island, Greece. Radiographs were examined for the presence, number, type, and location of supernumerary teeth. The analysis included data to explore gender and arch distribution. Results: Supernumerary teeth were identified in 15 individuals, corresponding to a prevalence of 2.4%. A slightly higher occurrence was observed in males (1.4%) than in females (1%). The majority of supernumerary teeth were situated in the maxillary arch (1.9%). Mesiodens represented the most frequently observed type, followed by supernumerary lateral incisors, paramolars, and a single supernumerary central incisor. Conclusions: The prevalence of supernumerary teeth in this population is consistent with reported findings. Mesiodens was the most frequently observed type, with a predominance in the maxillary arch. Early detection of supernumerary teeth is crucial for accurate diagnosis and effective management.
Effects of mouthwashes on the morphology, structure, and mechanical properties of orthodontic materials: a systematic review of randomized clinical studies
(2025-06-12) Kaklamanos, Eleftherios G
Background: Therapeutic mouthwashes are commonly used in dentistry to support mechanical plaque removal. Their interaction with orthodontic materials is increasingly studied due to potential effects on biocompatibility and biomechanics.
Clinical Applications of Artificial Intelligence in Periodontology: A Scoping Review
(2025-06-10) Kaklamanos, Eleftherios G
Abstract: Background and Objectives: This scoping review aimed to identify and synthesize current evidence on the clinical applications of artificial intelligence (AI) in periodontology, focusing on its potential to improve diagnosis, treatment planning, and patient care. Materials and Methods: A comprehensive literature search was conducted using electronic databases including PubMed-MEDLINE, Cochrane Central Register of Controlled Trials, Cochrane Database of Systematic Reviews, Scopus, and Web of Science™ Core Collection. Studies were included if they met predefined PICO criteria relating to AI applications in periodontology. Due to the heterogeneity of study designs, imaging modalities, and outcome measures, a scoping review approach was employed rather than a systematic review. Results: A total of 6394 articles were initially identified and screened. The review revealed a significant interest in utilizing AI, particularly convolutional neural networks (CNNs), for various periodontal applications. Studies demonstrated the potential of AI models to accurately detect and classify alveolar bone loss, intrabony defects, furcation involvements, gingivitis, dental biofilm, and calculus from dental radiographs and intraoral images. AI systems often achieved diagnostic accuracy, sensitivity, and specificity comparable to or exceeding that of dental professionals. Various CNN architectures and methodologies, including ensemble models and task-specific designs, showed promise in enhancing periodontal disease assessment and management. Conclusions: AI, especially deep learning techniques, holds considerable potential to revolutionize periodontology by improving the accuracy and efficiency of diagnostic and treatment planning processes. While challenges remain, including the need for further research with larger and more diverse datasets, the reviewed evidence supports the integration of AI technologies into dental practice to aid clinicians and ultimately improve patient outcomes
Evaluation of Large Language Model Performance in Answering Clinical Questions on Periodontal Furcation Defect Management
(2025-06-18) Kaklamanos, Eleftherios G
Background/Objectives: Large Language Models (LLMs) are artificial intelligence (AI) systems with the capacity to process vast amounts of text and generate humanlike language, offering the potential for improved information retrieval in healthcare. This study aimed to assess and compare the evidence-based potential of answers provided by four LLMs to common clinical questions concerning the management and treatment of periodontal furcation defects. Methods: Four LLMs—ChatGPT 4.0, Google Gemini, Google Gemini Advanced, and Microsoft Copilot—were used to answer ten clinical questions related to periodontal furcation defects. The LLM-generated responses were compared against a “gold standard” derived from the European Federation of Periodontology (EFP) S3 guidelines and recent systematic reviews. Two board-certified periodontists independently evaluated the answers for comprehensiveness, scientific accuracy, clarity, and relevance using a predefined rubric and a scoring system of 0–10. Results: The study found variability in LLM performance across the evaluation criteria. Google Gemini Advanced generally achieved the highest average scores, particularly in comprehensiveness and clarity, while Google Gemini and Microsoft Copilot tended to score lower, especially in relevance. However, the Kruskal–Wallis test revealed no statistically significant differences in the overall average scores among the LLMs. Evaluator agreement and intra-evaluator reliability were high. Conclusions: While LLMs demonstrate the potential to answer clinical questions related to furcation defect management, their performance varies. LLMs showed different comprehensiveness, scientific accuracy, clarity, and relevance degrees. Dental professionals should be aware of LLMs’ capabilities and limitations when seeking clinical information
Diagnostic accuracy of an artificial intelligence-based software in detecting supernumerary and congenitally missing teeth in panoramic radiographs
(2025-06-12) Kaklamanos, Eleftherios G
Background/Objectives: Recent advances in AI have enabled its application in dentistry. This study assessed the diagnostic accuracy of an AI-based model (Diagnocat™) in detecting congenitally missing and supernumerary teeth on panoramic radiographs. Materials/Methods: Three groups of 50 orthopantomograms each—control, congenitally missing, and supernumerary teeth—were evaluated by two human observers and Diagnocat™. Diagnostic performance was compared using the Wilcoxon Signed Rank and McNemar’s tests. Agreement was measured using Cohen’s Kappa, and diagnostic metrics (sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV)) were computed using IBM SPSS 29.0. Results: For congenitally missing teeth, Cohen’s Kappa indicated strong agreement (0.91); however, significant differences were found in the diagnostic performance (p < 0.01). The model exhibited 84.7% sensitivity, 100.0% specificity, 100.0% PPV, and 99.4% NPV. For supernumerary teeth, the agreement was moderate (Kappa = 0.60), with significant differences in the diagnostic performance (p < 0.001). Sensitivity was 43.9%, while specificity, PPV, and NPV were 100.0%, 100.0%, and 98.9%, respectively. Limitations: Using convenience sampling and a retrospective design may affect generalizability and applicability. Conclusions/Implications: Although the AI-based model shows promise, it is not yet able to replace human assessment as the standard for detecting missing and supernumerary teeth in panoramic radiographs
Changes in clinical crown length and the development of gingival recession associated with orthodontic treatment-induced incisor inclination changes: a retrospective cohort study
(2025-06-12) Athanasiou, Athanasios E; Kaklamanos, Eleftherios G
Background/Objectives: Gingival recession results from the displacement of the gingival margin apically to the cementoenamel junction. There is unclear evidence regarding the impact of orthodontic treatment on the development of gingival recessions. The aim of this study was to investigate the changes in clinical crown length and the development of gingival recession on the labial aspect of the maxillary and mandibular incisors associated with orthodontic treatment and relate these changes to the observed variations in their sagittal inclination.
Accuracy of One-Piece vs. Segmented Three-Dimensional Printed Transfer Trays for Indirect Bracket Placement
(MDPI AG, 2024-10-31) Alyammahi, Bayan; Khamis, Amar Hassan; Ghoneima, Ahmed
Objective: To assess the accuracy of three-dimensional (3D) printed one-piece vs. multiple segmented transfer trays for indirect bonding techniques in moderate and severe crowding cases. Methods: Eighty digital maxillary dental models were produced by an extraoral scanner. 3D-printed one-piece and segmented trays were virtually designed utilizing Maestro 3D Ortho Studio® v4 and printed using a NextDent printer. The sample was classified into two groups: Group 1 (moderate crowding) included 40 digital models with a space deficiency of 6–7 mm, and Group 2 (severe crowding) included 40 digital models with a space deficiency of 10 mm. Ortho classic brackets were then placed into the 3D printed models with the aid of the transfer trays, and the models with the final bracket positioning were scanned using iTero scanner. Four measurements were selected on each tooth to perform the analysis. Mann–Whitney and Kruskal–Wallis tests were used for comparisons. Ap-value of ≤ 0.05 was considered statistically significant. Results: In the moderate crowding group, statistically significant differences were detected between the one-piece, segmented, and control groups for three measurements (p < 0.001), while the rest of the measurements showed no significant differences (p > 0.05). In the severe crowding group, no significant differences were detected for any of the measurements. Conclusions: One-piece and segmented 3D-printed transfer trays are considered accurate tools for indirect bonding in moderate and severe malocclusion cases. The severity of crowding did not affect the accuracy of bracket transfer in indirect bonding.
Evaluation of the Root and Canal Morphology of Maxillary and Mandibular Premolars in an Emirati Sub-Population
(Elsevier BV, 2025-02) Almehrzi, Hanadi; Khawajah, Summaya; El Abed, Rashid; Jamal, Mohamed
Introduction and aims: Numerous studies have reported that maxillary and mandibular premolars have a complex internal canal configuration, which can vary according to the race and geographic origin. Therefore, a thorough knowledge and understanding of the root and canal morphology is crucial to ensure successful outcome of root canal treatment. This retrospective study aims to describe the root and canal morphology of the maxillary and mandibular first and second premolars in the Emirati subpopulation using cone-beam computed tomography(CBCT). Methods: This retrospective study analyzed 360 CBCT scans that were randomly selected and met the inclusion and exclusion criteria. The scans were reviewed by two evaluators who recorded the number and shape of roots and categorized the canal morphology based on the Vertucci classification (VC). The data were analyzed statistically using SPSS software. Results: A total of 1795 premolars were examined. Most maxillary first premolars had one root (52.1%), while only 0.9% had three roots. Type I VC was the most common canal configuration (53.8%). The majority of maxillary second premolars had one root (91%). Type I VC was the most common canal configuration (47.4%), followed by type III (32.4%). Most of the mandibular f irst and second premolars had one root (77.3% and 97%, respectively), and Type I VC was the most common canal configuration (70.4% and 94.9%, respectively). C-shaped canals were most observed in the mandibular first premolars, with a prevalence of 22.7%. Conclusion: Our results showed great variations in the canal configuration. In addition, Cshaped canals in mandibular first premolar is relatively high (22.7%). Clinical relevance: Premolars in Emirati population exhibit complex anatomy. Therefore, clinicians might consider advanced diagnostic and treatment techniques when treating premolars in this population.
Periodontitis: Grade Modifiers Revisited
(Wiley, 2025-02-27) Saleh, Obada; Abdulmunim, Anas; Aboushakra, Ibrahim; Shah, Maanas; Hakam, Abeer; Atieh, Momen A
Objective: This review aimed to propose new grade modifiers for the risk assessment of periodontitis. Materials and Methods: Literature on the known risk factors, current, and potential grade modifiers was reviewed. Results: The transition to a staging and grading system for periodontitis was driven by the need for consistent and comprehensive classification that facilitates diagnosis and personalized treatment planning. The new system assesses severity and complexity based on clinical attachment loss, radiographic bone loss, and patient history, and integrates risk factors into the grading scheme as grade modifiers. The two commonly used grade modifiers are smoking and diabetes mellitus. The changes to grade B or C are based on the number of cigarettes smoked per day and the level of glycemic levels, which are known thresholds used in association studies of risk factors for periodontitis. New grade modifiers such as systemic inflammatory response, rheumatoid arthritis, osteoporosis, obesity, and neurodegenerative disease were identified. Conclusion: While adding grade modifiers may increase complexity, they could improve the prognostic accuracy of the current classification, enabling more precise assessment, personalized treatment, and better management of periodontitis, especially in patients with systemic risk factors.
Changes in clinical crown length and the development of gingival recession associated with orthodontic treatment-induced incisor inclination changes: a retrospective cohort study
(2025-06-12) Athanasiou, Athanasios E; Kaklamanos, Eleftherios G
Background/Objectives: Gingival recession results from the displacement of the gingival margin apically to the cementoenamel junction. There is unclear evidence regarding the impact of orthodontic treatment on the development of gingival recessions. The aim of this study was to investigate the changes in clinical crown length and the development of gingival recession on the labial aspect of the maxillary and mandibular incisors associated with orthodontic treatment and relate these changes to the observed variations in their sagittal inclination.
Complications Due to Medicaments
(Springer Nature Switzerland, 2025) Alkhatib, Zuhair; El Abed, Rashid
Medicaments used in the root canal system are of numerous varieties and have effects on both pulpal tissues and microbial flora, not just inside the root canal system, but also on the periodontium. That is why, when choosing any medicament, the clinician must make the right choice. Choose a medicament that has an effect on the microorganisms, as this is the most important factor in root canal failures, and it should have the least effect on the tissues surrounding the root. The medicament should be confined in the root canal system during its use, and care should be taken not to expel it beyond the root apex into the periapical tissues. In case this happens, damage to the periapical tissues ensues, leading to inflammation, swelling and probably tooth loss. In this chapter, we will discuss the most common intracanal irrigation solutions and interim medicament used by endodontist, referring to literature and case reports that provide scientifically based evidence.
Large language models in periodontology: Assessing their performance in clinically relevant questions.
(2024-11-18) Kaklamanos, Eleftherios G
Statement of problem: Although the use of artificial intelligence (AI) seems promising and may assist dentists in clinical practice, the consequences of inaccurate or even harmful responses are paramount. Research is required to examine whether large language models (LLMs) can be used in accessing periodontal content reliably.
Understanding Residents' and Supervisors' Views on Developing Support-Autonomy Balance Through Supervision Methods in Postgraduate Dental Training: A Qualitative Study.
(2024-11) Amir-Rad, Fatemeh
Background: Supervisors continuously need to decide when to provide clinical opportunities for unsupervised patient care to facilitate residents' development in the complex clinical learning context. The aim of this study is to explore residents' and supervisors' views and understanding of the influence of clinical supervision on affording a balanced support-autonomy from the cognitive apprenticeship (CA) theoretical lens.
Comparative Assessment of Pharyngeal Airway Dimensions in Skeletal Class I, II, and III Emirati Subjects: A Cone Beam Computed Tomography Study.
(2024-09-25) AlAskar, Sara; Jamal, Mohamed; Khamis, Amar Hassan; Ghoneima, Ahmed
The aim of the current study was to evaluate the pharyngeal airway dimensions of individuals with different skeletal patterns in a cohort of the Emirati population. The specific aim was to assess the relationship between pharyngeal airway dimensions and anterior facial height in relation to different skeletal patterns. This retrospective study was conducted on a sample of 103 CBCT scans of adult Emirati subjects categorized into three groups according to their skeletal classification as indicated by the ANB angle: Class I (n = 35), Class II (n = 46), and Class III (n = 22). All CBCT scans were taken using an i-CAT CBCT imaging machine (Imaging Sciences, Hatfield, PA, USA). The age range of the patients was 19 to 68 years (62 women and 41 men). ANOVA, -tests, Kruskal-Wallis, and Mann-Whitney tests were employed for comparing means among groups. The correlation coefficient was used to evaluate the association between variables. A -value of less than 0.05 was considered statistically significant. This study revealed significant associations between various airway parameters and cephalometric measurements. Positive correlations were observed between nasal cavity volume and nasopharynx volume, as well as anterior facial height. Oropharynx volume exhibited positive correlations with hypopharynx volume and total airway volume, and negative correlations with overjet, ANB angle, and patient age. Hypopharynx volume correlated positively with total airway volume and the most constricted area of the airway (MCA). Total airway volume showed positive correlations with MCA and anterior facial height. MCA had negative correlations with ANB angle and patient age. Nasopharynx volume was significantly larger in the skeletal Class I group than in the Class II or Class III groups, while the other airway parameters showed no significant differences among the groups ( > 0.05). Several airway parameters showed a correlation with anterior facial height among the different skeletal patterns. Nasopharyngeal airway volume was significantly larger in the skeletal Class I group than in Class II and III groups in the studied sample.
Barriers and Facilitators to Dental Care Services Utilization Among Children With Disabilities: A Systematic Review and Thematic Synthesis.
(2024-10) Alsalami, Anas; Al Mashhadani, Shiamaa
Background: This systematic review investigates barriers and enablers to dental care utilization by disabled children. Given the high global prevalence of disabilities in children, coupled with poor oral hygiene and a 45% rate of dental caries in this group, developing inclusive oral health strategies is critical. The review aims to synthesize literature on factors affecting oral healthcare improvement for disabled children, identifying barriers, facilitators and knowledge gaps.

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