Şeyma Çardakcı Bahar

Aims: This study aimed to identify the clinically relevant patient questions about apical root-end resection based on international consensus guidelines, and to systematically evaluate the accuracy, quality, usefulness, and readability of generated responses by four Artificial Intelligence (AI)-powered conversational agents, ChatGPT-4, DeepSeek V3.1, Gemini 3, and Copilot. Methods: A standardized set of 20 clinical questions was developed from the American Association of Endodontists guidelines and international consensus reports. A priori, an evidence-based answer key was established as the reference standard. Queries were submitted to ChatGPT-4, DeepSeek V3.1, Gemini 3, and Copilot, following a standardized interaction protocol designed to minimize personalization and carryover effects, such as incognito mode, newly created accounts, and no response regeneration. The outputs were independently assessed by three experts in periodontics and oral radiology, using validated tools, such as CLEAR criteria, modified Global Quality Score (mGQS), accuracy ratings, DISCERN, readability indices (Flesch reading ease, FRE and Flesch-Kincaid grade level, FKGL) and the patient education materials assessment tool (PEMAT). Results: ChatGPT-4 and Copilot achieved significantly higher CLEAR scores than Gemini 3. Copilot achieved significantly higher mGQS and accuracy than DeepSeek V3.1 and Gemini 3 and received significantly lower, and therefore more favorable, usefulness scores. Gemini 3 scored higher on the FKGL test and lower on the understandability test compared to DeepSeek V3.1. Relationships between evaluation metrics were different between models. Conclusion: The AI models evaluated demonstrated significant variability in clinical accuracy, quality, readability, and patient-centered usability. Copilot had the best overall mGQS and Accuracy scores and the best Usefulness scores, while the models varied in their strengths in readability, understandability, and actionability.

Objective: This study aimed to explore common patient inquiries about Cone-Beam Computed Tomography (CBCT) and systematically assess the accuracy, quality, usefulness, and readability of outputs from four AI-based conversational platforms (ChatGPT-3.5, DeepSeek-V3.1, Gemini 1.5 Flash, and Microsoft Copilot Free).Materials and Methods: Common questions about CBCT were gathered from online sources and expert contributions and submitted to ChatGPT-3.5, DeepSeek, Gemini, and Copilot under standardized conditions. Outputs were independently evaluated by three specialists using CLEAR, mGQS, accuracy, usefulness, DISCERN, and readability metrics (FRE and FKGL).Results: Significant differences were observed among AI platforms regarding CLEAR scores (p < 0.05), with Gemini showing higher values than ChatGPT (p = 0.016). Across all four platforms, strong to a very strong positive correlations were found among CLEAR, mGQS, and Accuracy scores (r ≥ 0.77, p < 0.001), while these measures were strongly to very strongly and inversely correlated with Usefulness (r ≤ −0.77, p < 0.001). Flesch Reading Ease and Flesch-Kincaid Grade Level demonstrated a very strong negative correlations across platforms (r ranging from −0.85 to −0.93, p < 0.05). Within the Gemini group, Flesch-Kincaid Grade Level showed a moderate positive association with DISCERN scores (r = 0.496, p = 0.043).Conclusions: Gemini and DeepSeek produced more accurate and clearer responses. The readability of all AI systems was below the recommended level for patient education. These systems may support patient education but require expert validation.

Periodontitis and chronic respiratory diseases, including chronic obstructive pulmonary disease (COPD) and asthma, are chronic inflammatory conditions that

Although platelet-rich fibrin (PRF) is a biological material with high regenerative potential, its rapid resorption limits its clinical effectiveness. Albumin-platelet-rich fibrin (Alb-PRF), developed in recent years, exhibits prolonged resorption time. The aim of this study was to evaluate the clinical, radiographic, and biochemical effects of Alb-PRF application into periodontal pockets following non-surgical periodontal therapy (NSPT) using a randomized split-mouth design. This study included 23 patients diagnosed with Stage III Grade B periodontitis. Following completion of NSPT, Alb-PRF was applied into periodontal pockets at the test sites. Gingival crevicular fluid (GCF) samples were collected on days 7, 14, and 21. Clinical periodontal parameters were recorded at baseline, 3 and 6 months, and radiographs were obtained at baseline and at 6 months. Levels of vascular endothelial growth factor (VEGF), platelet-derived growth factor-BB (PDGF-BB), transforming growth factor-β (TGF-β), and basic fibroblast growth factor (b-FGF) in GCF were analyzed using enzyme-linked immunosorbent assay (ELISA). Primary outcome measures included changes in probing depth (PD), clinical attachment loss (CAL), and GCF growth factor levels, while secondary outcome measures included changes in plaque index, gingival index (GI), bleeding on probing, gingival recession, and radiographic parameters. GI, PD, and CAL were significantly lower at test sites at 3 months (p < 0.01). However, these differences were not maintained at the 6-month follow-up. Radiographic defect depth and bone loss percentage were significantly lower at test sites at 6 months (p < 0.01). Transforming growth factor-β values were significantly higher at test sites at all subsequent time points (p < 0.01, p < 0.01, and p < 0.05, respectively). Alb-PRF may represent a beneficial adjunctive approach for early periodontal healing following NSPT; however, further studies are needed to clarify the sustainability of these effects over time. ClinicalTrials.gov NCT07363135, registered on 15 January 2026 (retrospectively registered).

Objective: This study compared the clinical and patient-reported outcomes of Er: YAG laser-assisted versus conventional scalpel frenectomy, while evaluating the adjunctive impact of postoperative antimicrobial mouthwashes on wound healing and periodontal parameters. Methods: A total of 102 patients who underwent labial frenectomy were included in this retrospective longitudinal cohort study. Participants were allocated into four groups based on the surgical approach (Er: YAG laser or conventional scalpel) and the postoperative mouthwash protocol (Kloroben^® or Klorhex Plus^®). Clinical assessments were performed at baseline and at 7, 14, and 28 days postoperatively. Wound healing, evaluated using the Wound Healing Index, was defined as the primary outcome. Secondary outcomes included periodontal clinical parameters, epithelialization status, postoperative pain, bleeding, and analgesic consumption. To control potential confounders, multivariable regression analysis was performed alongside standard parametric and nonparametric tests, with p < 0.05 considered statistically significant. Results: All treatment protocols resulted in significant improvements over time (p < 0.001). However, Er: YAG laser–assisted frenectomy was associated with significantly better periodontal indices, superior wound-healing scores, and more favorable patient-reported outcomes than the conventional scalpel technique at all postoperative evaluations (p < 0.001). On day 7, ‘Very Good’ healing was observed in 70.2% of the laser groups, compared with 14.4% in the CS groups (p = 0.001). Group 4 showed the lowest mean VAS scores (0.04 ± 0.20) and the lowest analgesic consumption by day 7. Multivariable analysis confirmed that the surgical technique was the strongest independent predictor of superior wound healing (p < 0.05), regardless of age, gender, smoking, or systemic disease. Notably, frenulum type was not significantly associated with wound healing or pain outcomes (p > 0.05). Conclusions: Within the limitations of this study, Er: YAG laser-assisted frenectomy was observed to provide favorable wound healing outcomes compared to the conventional technique. Furthermore, our findings show that anatomical variations in frenulum type do not significantly influence the quality or speed of recovery. These findings suggest that the choice of surgical modality and postoperative chemical support are more critical determinants of early clinical success than the anatomical variations of the frenulum.

Objective: This study aimed to develop a consensus-based set of patient questions on dental implant failure and to compare the clarity, quality, accuracy, reliability, and readability of responses generated by 4 widely used AI chatbots: ChatGPT-4, DeepSeek-R1, Microsoft Copilot, and Google Gemini. Methods: Twenty-three expert-validated questions were derived from the EAO 2021 and ICOI Pisa Consensus reports and independently submitted to each AI model under standardized, non-personalized conditions. Responses were assessed using CLEAR criteria, mGQS, a 5-point accuracy scale, the first 8 DISCERN items, and Flesch-based readability indices. Nonparametric tests were used for intermodel comparisons. Results: AI models demonstrated significant variability in performance. Gemini achieved the highest accuracy ( P <0.001), whereas ChatGPT-4 exhibited the highest reliability based on DISCERN scores. Copilot generated the most structurally fluent responses, whereas DeepSeek-R1 offered the best readability. Although CLEAR and mGQS scores were high across all systems, readability and linguistic complexity varied markedly. Accuracy, clarity, and reliability were strongly correlated, whereas readability displayed the expected inverse association with grade-level demand. Conclusions: AI chatbots hold potential as adjunct tools for patient education on implant failure; however, their performance characteristics differ substantially. Gemini excels in accuracy, ChatGPT-4 in reliability, Copilot in fluency, and DeepSeek-R1 in readability. Model-specific guidance and continued refinement are needed to enhance the clinical usefulness and accessibility of AI-generated patient information.

Patient safety is a critical component of healthcare quality, including dentistry, where preventable errors can cause serious harm. Despite increasing global attention to safety culture and ethical awareness, research in dental education remains limited. The Patient Safety Attitude Scale in Dentistry (PSASD), a newly validated assessment tool, was used in this study to evaluate patient safety attitudes and ethical awareness among dentistry and dental assisting students. A cross-sectional survey was conductedusing convenience sampling among 323 students (244 dentistry, 79 dental assisting) at the University of Health Sciences, Turkey. Data were collected using the PSASD and analyzed with non-parametric tests. Effect sizes (r) were reported alongside p-values. Students demonstrated generally positive attitudes toward patient safety (mean PSASD score = 61.37 ± 9.01), with effect sizes (r) ranging from 0.12 to 0.14 across significant comparisons. Dental assisting students scored significantly higher than dentistry students in Ethical Attitude (p = 0.024, r = 0.13) and in overall PSASD scores (p = 0.035, r = 0.12). Female students scored higher than males in Risk Management (p = 0.023, r = 0.13). Awareness of the patient safety notification system was associated with higher Ethical Attitude scores (p = 0.011, r = 0.14). Given the small effect sizes, the results should be interpreted with caution. Both dentistry and dental assisting students showed positive safety attitudes, with assisting students consistently achieving higher scores. However, deficiencies in ethical awareness and error reporting highlight the need for targeted educational efforts, particularly for dentistry students, and support the integration of system-based safety and ethics modules into dental curricula.The cross-sectional design and use of convenience sampling limit the generalizability of the findings.

Background and Objectives: This study is aimed at evaluating periodontal health in patients with psoriasis and investigating its impact on dermatology-specific and oral health-related quality of life. Materials and Methods: A total of 226 individuals were enrolled, including 113 patients with clinically diagnosed psoriasis and 113 age- and gender-matched healthy controls. The periodontal parameters recorded included plaque index (PI), gingival index (GI), probing depth (PD), and clinical attachment loss (CAL). Oral health-related quality of life was assessed using the Oral Health Impact Profile-14 (OHIP-14), while dermatology-specific quality of life was evaluated with the Psoriasis Quality of Life Questionnaire (PQLQ). Psoriasis severity was measured by the Psoriasis Area and Severity Index (PASI). Results: Patients with psoriasis demonstrated significantly poorer periodontal parameters compared to controls, with higher PI (p = 0.006), PD (p = 0.001), and CAL (p = 0.041), as well as a lower number of teeth (p = 0.027). No significant differences in GI were observed (p = 0.331). Subdomain analysis of OHIP-14 indicated significantly greater functional limitation in the psoriasis group (p = 0.001), although no differences were detected in other domains. Positive and significant correlations were found among all the OHIP-14 subscales in both groups, and PQLQ scores were strongly correlated with OHIP-14 outcomes in the psoriasis group (p < 0.05). PASI scores tended to be higher among patients with periodontitis than those with gingivitis or periodontal health, but this difference did not reach statistical significance (p = 0.257). Conclusions: Psoriasis patients exhibited poorer periodontal status and reduced oral health-related quality of life compared to healthy individuals. However, differences in oral hygiene habits may also have contributed to these findings. Our findings suggest an association between psoriasis and impaired periodontal health, but due to the cross-sectional design, a causal relationship cannot be established.