Performance of ChatGPT in classifying periodontitis according to the 2018 classification of periodontal diseases.

OBJECTIVES: This study assessed the ability of ChatGPT, an artificial intelligence(AI) language model, to determine the stage, grade, and extent of periodontitis based on the 2018 classification. MATERIALS AND METHODS: This study used baseline digital data of 200 untreated periodontitis patients to compare standardized reference diagnoses (RDs) with ChatGPT findings and determine the best criteria for assessing stage and grade. RDs were provided by four experts who examined each case. Standardized texts containing the relevant information for each situation were constructed to query ChatGPT. RDs were compared to ChatGPT's responses. Variables influencing the responses of ChatGPT were evaluated. RESULTS: ChatGPT successfully identified the periodontitis stage, grade, and extent in 59.5%, 50.5%, and 84.0% of cases, respectively. Cohen's kappa values for stage, grade and extent were respectively 0.447, 0.284, and 0.652. A multiple correspondence analysis showed high variance between ChatGPT's staging and the variables affecting the stage (64.08%) and low variance between ChatGPT's grading and the variables affecting the grade (42.71%). CONCLUSIONS: The present performance of ChatGPT in the classification of periodontitis exhibited a reasonable level. However, it is expected that additional improvements would increase its effectiveness and broaden its range of functionalities (NCT05926999). CLINICAL RELEVANCE: Despite ChatGPT's current limitations in accurately classifying periodontitis, it is important to note that the model has not been specifically trained for this task. However, it is expected that with additional improvements, the effectiveness and capabilities of ChatGPT might be enhanced.

Association of Peri-Implant Keratinized Mucosa Width and Mucosal Thickness with Early Bone Loss: A Cross-Sectional Study.

Objective: The objective of this study was to evaluate the effects of keratinized mucosa width (KMW) and mucosal thickness (MT) around dental implants on marginal bone loss (MBL). The evaluation was performed one year after loading by comparing clinical, radiographic, and biochemical parameters. Methods: The study included 87 implants in 87 patients undergoing regular follow-ups without hard or soft tissue augmentation one year after loading. Clinical measurements included plaque index (PI), gingival index (GI), bleeding on probing (BoP), probing depth (PD), KMW, and MT. MBL was assessed with periapical radiography. The peri-implant crevicular fluid (PICF) was analyzed for tumor necrosis factor-alpha (TNF-α), receptor activator of nuclear factor-kB ligand (RANKL), osteoprotegerin (OPG), and microRNA-27a. Results: The MBL of implants with thin MT (<2 mm) was higher than that of implants with thick MT (≥2 mm) (p < 0.05). A significant negative correlation (r: -0.217) was established between MT and MBL. No significant association was found between KMW and MBL (p > 0.05). No significant associations was found between KMW and MT with TNF-α, RANKL, OPG and RANKL/OPG (p > 0.05), with the exception of increased microRNA-27a levels in implants with KMW ≥ 2 mm (p < 0.05). Conclusions: Implants with a thick MT had a lower MBL. There may be an association between adequate KMW and high miRNA-27a levels. The relationship between MBL and miRNA-27a remains unclear.

Potential Use of ChatGPT for Patient Information in Periodontology: A Descriptive Pilot Study.

Objectives The aim of this study is to evaluate the accuracy and completeness of the answers given by Chat Generative Pre-trained Transformer (ChatGPT) (OpenAI OpCo, LLC, San Francisco, CA), to the most frequently asked questions on different topics in the field of periodontology. Methods The 10 most frequently asked questions by patients about seven different topics (periodontal diseases, peri-implant diseases, tooth sensitivity, gingival recessions, halitosis, dental implants, and periodontal surgery) in periodontology were created by ChatGPT. To obtain responses, a set of 70 questions was submitted to ChatGPT, with an allocation of 10 questions per subject. The responses that were documented were assessed using two distinct Likert scales by professionals specializing in the subject of periodontology. The accuracy of the responses was rated on a Likert scale ranging from one to six, while the completeness of the responses was rated on a scale ranging from one to three. Results The median accuracy score for all responses was six, while the completeness score was two. The mean scores for accuracy and completeness were 5.50 ± 0.23 and 2.34 ± 0.24, respectively. It was observed that ChatGPT's responses to the most frequently asked questions by patients for information purposes in periodontology were at least "nearly completely correct" in terms of accuracy and "adequate" in terms of completeness. There was a statistically significant difference between subjects in terms of accuracy and completeness (P<0.05). The highest and lowest accuracy scores were peri-implant diseases and gingival recession, respectively, while the highest and lowest completeness scores were gingival recession and dental implants, respectively. Conclusions The utilization of large language models has become increasingly prevalent, extending its applicability to patients within the healthcare domain. While ChatGPT may not offer absolute precision and comprehensive results without expert supervision, it is apparent that those within the field of periodontology can utilize it as an informational resource, albeit acknowledging the potential for inaccuracies.

Splith mouth randomized control trial comparison of T-PRF and subepithelial connective tissue graft in the treatment of maxillar multiple gingival recessions.

AIM: The aim of this study is to compare the treatment efficacy of the bilateral multiple gingival recession areas with a titanium-platelet-rich-fibrin (T-PRF) and subepithelial connective tissue graft (SCTG) combined with a modified coronal advanced flap (MCAF) and the clinical results. METHOD: In the study, 118 maxillary bilateral multiple Miller I recessions were treated. Gingival index, plaque index, probing pocket depth, gingival thickness, recession height, recession width, keratinized gingival width and open root surface area were measured at baseline and at 6 months. Postoperative pain levels Visual Analog Scale, healing status, wound healing index evaluated with. The results of both groups pre and postoperative were compared. RESULTS: The initial recession height was 2.15 ± 1.0 mm in the T-PRF group; 2.04 ± 0.80 mm in the SCTG group. After 6 months, the mean root closure rate was 61.77%, 75.31% in T-PRF and SCTG group, respectively. Clinical attachment gain was achieved in both groups compared to baseline. When the results were compared, the gains achieved in the SCTG group were statistically significantly higher. It was determined that patient satisfaction was higher in T-PRF group and wound healing was faster. CONCLUSION: Considering the advantages of T-PRF such as providing effective results in the treatment of defects, patient satisfaction and rapid recovery; It can be applied as an alternative to SCTG. CLINICAL SIGNIFICANCE: T-PRF can be an alternative to SCTG in the treatment of gingival recessions.

Peritoneal tuberculosis: A case report on a rare cause of tumor marker elevation.

Peritoneal tuberculosis (TB) is a rare extrapulmonary manifestation of TB with non-specific clinical characteristics which can produce test results mimicking malignancy and granulomatous peritonitis. This case describes a Filipino 59-year-old, nulliparous woman who was admitted with abdominal pain, ascites, and an elevated CA-125 level. Radiographically, peritoneal nodules were visualized and initial suspicion was high for malignancy. Following a bilateral salpingo-oophorectomy and peritoneal biopsy, histology was negative for malignancy but revealed non-caseating granulomas. She was discharged then readmitted with progressive abdominal pain, and a repeat laparoscopic biopsy yielded specimens with growth of acid-fast bacilli (AFB). A delay in diagnosis and treatment of tuberculous peritonitis increases mortality rates, making early diagnosis with laparoscopic biopsy of paramount importance in prompt diagnosis and initiation of therapy. This patient was initiated on standard anti-TB therapy and experienced no complications.

Utilization of Wilms' tumor 1 antigen in a panel for differential diagnosis of ovarian carcinomas.

OBJECTIVE: Ovarian metasteses are often mistaken for primary adenocarcinoma. Studies conducted in recent years have focused on a search for an immunohistochemical marker to aid the differential diagnosis primary and metastatic ovarian carcinoma. Our study objective was to study the usefulness of Wilms tumor 1 (WT 1) antigen in this context. MATERIALS AND METHODS: The study was conducted at the pathology clinic of Lütfi Kirdar Training and Research Hospital. Deparaffinated blocks of 40 epithelial ovarian tumors, 40 colon adenocarcinomas, and 35 cases of omentum metastases were studied. Cytokeratin 7 (CK 7), cytokeratin 20 (CK 20), and WT 1 were applied to all specimens. RESULTS: All ovarian adenocarcinomas were stained with CK 7 (100%). Colorectal adenocarcinomas were stained positive with CK 20 in 87.5% of cases. Primary ovarian adenocarcinomas stained positive with WT 1 in 82.5% of the cases and none of the colorectal adenocarcinomas showed staining with WT 1 (0%). CONCLUSION: WT 1 can be used in conjuction with CK 7 in the differential diagnosis of ovarian carcinomas.