Profilometric, esthetic, and patient-reported outcomes of the L-shape technique combined with delayed connective tissue grafting in the maxillary anterior region: A 3-year case series study.

OBJECTIVE: To evaluate the profilometric, esthetic, and patient-reported outcomes of peri-implant tissues in the maxillary anterior esthetic zone following guided bone regeneration (GBR) using the L-shape technique combined with delayed connective tissue grafting (CTG). MATERIALS AND METHODS: Profilometric and pink esthetic score (PES) measurements were performed at the time of implant surgery with GBR (T0) and at the 1- (T1), 2- (T2), and 3-year (T3) follow-up. Patient-reported outcomes were also assessed using the Oral Health Impact Profile-14 (OHIP-14) questionnaire. Statistical analysis over 3 years of follow-up assessed changes at time points (T0, T1, T2, and T3) and time periods (T0-T1, T0-T2, and T0-T3) using the Wilcoxon signed-rank test. RESULTS: A total of 12 patients (57.5 ± 12.3 years) were included in this study. The mean profilometric change in peri-implant tissues over the 3-year follow-up period was 3.49 ± 1.11 mm, and the buccal contours were not significantly different between the comparison periods. The PES remained stable, while all OHIP-14 domain scores improved significantly. CONCLUSION: Simultaneous implant placement and GBR using the L-shape technique combined with delayed CTG in the maxillary anterior region provides stable buccal profiles and consistent esthetics and improves patient-reported quality of life over a 3-year period. CLINICAL SIGNIFICANCE: This study demonstrated that GBR using the L-shape technique combined with delayed CTG in the maxillary anterior region improved the buccal profile, esthetics, and patient-reported quality of life.

Long-term results of regenerative treatment of intrabony defects: a cohort study with 5-year follow-up.

BACKGROUND: The aim of this retrospective cohort study was to evaluate the long-term clinical and radiographic outcomes and survival of teeth in periodontal regenerative treatment of intrabony defects using combined enamel matrix protein derivative (EMD) and deproteinized porcine bone mineral (DPBM) compared to EMD alone. METHODS: A total of 333 intrabony defects in 176 patients (mean age: 54.7 ± 8.9 years) were followed-up for 58.6 ± 11.2 (range, 25-78) months after periodontal regenerative treatment. Changes in clinical (pocket probing depth and clinical attachment level) and radiographic (defect depth and defect width) parameters were analyzed using serial periapical radiographs. Kaplan-Meier and multivariate Cox proportional-hazards regression analyses for tooth loss were also performed. RESULTS: Compared to periodontal surgery with EMD alone with a mean follow-up of 5 years, combined EMD and DPBM showed significantly better gain in clinical attachment level (EMD and DPBM: 2.8 ± 2.3 mm vs. EMD alone: 2.2 ± 2.2 mm) and reduction in probing pocket depth (EMD and DPBM: 2.8 ± 1.8 mm vs. EMD alone: 2.3 ± 1.8 mm), defect depth (EMD and DPBM: 2.5 ± 2.4 mm vs. EMD alone: 2.0 ± 2.4 mm) and defect width (EMD and DPBM: 0.6 ± 1.0 mm vs. EMD alone: 0.2 ± 1.3 mm). The overall survival rates of the teeth were 91.48% and 95.20% in the patient- and tooth-based analyses, respectively, showing no statistically significant difference. CONCLUSIONS: Within the limitations of the current study, combined EMD and DPBM offered additional clinical and radiographic benefits over a mean of 5 years compared to EMD alone. However, tooth loss did not differ significantly between the two groups. CLINICAL RELEVANCE: Compared to EMD alone, combined EMD and DPBM for intrabony defects has additional clinical advantages; however, patient- and tooth-related risk factors must be considered when performing periodontal regenerative surgery.

Deep learning in periodontology and oral implantology: A scoping review.

Deep learning (DL) has been employed for a wide range of tasks in dentistry. We aimed to systematically review studies employing DL for periodontal and implantological purposes. A systematic electronic search was conducted on four databases (Medline via PubMed, Google Scholar, Scopus, and Embase) and a repository (ArXiv) for publications after 2010, without any limitation on language. In the present review, we included studies that reported deep learning models' performance on periodontal or oral implantological tasks. Given the heterogeneities in the included studies, no meta-analysis was performed. The risk of bias was assessed using the QUADAS-2 tool. We included 47 studies: focusing on imaging data (n = 20) and non-imaging data in periodontology (n = 12), or dental implantology (n = 15). The detection of periodontitis and gingivitis or periodontal bone loss, the classification of dental implant systems, or the prediction of treatment outcomes in periodontology and implantology were major use cases. The performance of the models was generally high. However, it varied given the employed methods (which includes various types of convolutional neural networks (CNN) and multi-layered perceptron (MLP)), the variety in specific modeling tasks, as well as the chosen and reported outcomes, outcome measures and outcome level. Only a few studies (n = 7) showed a low risk of bias across all assessed domains. A growing number of studies evaluated DL for periodontal or implantological objectives. Heterogeneity in study design, poor reporting and a high risk of bias severely limit the comparability of studies and the robustness of the overall evidence.

Augmentation stability and early wound healing outcomes of guided bone regeneration in peri-implant dehiscence defects with L- and I-shaped soft block bone substitutes: A clinical and radiographic study.

OBJECTIVES: To retrospectively evaluate whether guided bone regeneration (GBR) with L- and I-shaped demineralized bovine bone mineral with 10% collagen (DBBM-C) differs from GBR with DBBM in terms of augmentation stability and early wound healing outcomes in peri-implant dehiscence defects. METHODS: A total of 91 peri-implant defects were grafted with 24 L- (GBR-L), 22 I (GBR-I)-shaped DBBM-C, and 45 DBBM (GBR-P). Cone-beam computed tomography images were obtained after surgery and at 5 months follow-up. The horizontal thickness (HT0, HT2, HT4), vertical thickness (VT), and VT at 45° angle (45-VT) of the augmented hard tissue were measured. Early postoperative discomfort and wound healing outcomes were assessed 2 weeks after surgery, and periotest values were also measured at 5 months in all groups. RESULTS: At 5 months follow-up, the change at HT0 and VT of the GBR-L (HT0: -0.63 ± 0.55 mm, VT: -0.77 ± 0.60 mm) and GBR-I (HT0: -0.68 ± 0.53 mm, VT: -0.91 ± 0.73 mm) groups was significantly more stable than that of the GBR-P (HT0: -1.30 ± 0.77 mm, VT: -1.57 ± 0.67 mm) group (p < .05). The GBR-L group (-0.74 ± 0.54 mm) showed better augmentation stability than the other two groups at the change at 45-VT. Early postoperative discomfort, wound healing outcomes, and periotest values did not differ significantly between the three groups. CONCLUSION: Within the limitations of this study, L- and I-shaped DBBM-Cs used for GBR were more beneficial in terms of horizontal augmentation stability than DBBM after a 5-month healing period.

Comparative assessment of anterior maxillary alveolar ridge preservation with and without adjunctive use of enamel matrix derivative: A randomized clinical trial.

OBJECTIVES: The aim of this randomized, controlled, parallel-arm study was to evaluate the (a) radiographic bone dimensional changes, (b) postoperative discomfort, and (c) early soft tissue wound healing outcomes, following extraction of maxillary anterior teeth (central and lateral incisors) and treatment with alveolar ridge preservation (ARP) with and without the adjunctive use of enamel matrix derivative (EMD). METHODS: Thirty extraction sockets were randomly assigned to two groups: deproteinized bovine bone mineral with 10% collagen covered with collagen membrane with the adjunctive use of EMD (test group) and without EMD (control group). Bone dimensional changes were measured using cone beam computed tomography at 3 and 5 months after ARP. The severity and duration of pain and swelling were evaluated using self-reported questionnaires, and soft tissue wound healing outcomes were assessed clinically. Chi-square tests and t tests were conducted to compare differences between the two groups. RESULTS: Radiographic and clinical analyses showed no significant differences in horizontal and vertical bone dimensional changes and soft tissue wound healing outcomes (including spontaneous bleeding, persistent swelling, and ulceration) between the two groups. There were no significant differences in the severity of pain and swelling between the two groups, but the durations of pain (difference [df] = 1.20, 95% CI = 0.33-2.06; p = .008) and swelling (df = 1.06, 95% CI = 0.11-2.01; p = .029) were significantly reduced in the test group. CONCLUSION: Alveolar ridge preservation with the adjunctive use of EMD reduced the durations of postoperative pain and swelling following maxillary anterior teeth extraction.

Diagnosis of cystic lesions using panoramic and cone beam computed tomographic images based on deep learning neural network.

OBJECTIVES: The aim of the current study was to evaluate the detection and diagnosis of three types of odontogenic cystic lesions (OCLs)-odontogenic keratocysts, dentigerous cysts, and periapical cysts-using dental panoramic radiography and cone beam computed tomographic (CBCT) images based on a deep convolutional neural network (CNN). METHODS: The GoogLeNet Inception-v3 architecture was used to enhance the overall performance of the detection and diagnosis of OCLs based on transfer learning. Diagnostic indices (area under the ROC curve [AUC], sensitivity, specificity, and confusion matrix with and without normalization) were calculated and compared between pretrained models using panoramic and CBCT images. RESULTS: The pretrained model using CBCT images showed good diagnostic performance (AUC = 0.914, sensitivity = 96.1%, specificity = 77.1%), which was significantly greater than that achieved by other models using panoramic images (AUC = 0.847, sensitivity = 88.2%, specificity = 77.0%) (p = .014). CONCLUSIONS: This study demonstrated that panoramic and CBCT image datasets, comprising three types of odontogenic OCLs, are effectively detected and diagnosed based on the deep CNN architecture. In particular, we found that the deep CNN architecture trained with CBCT images achieved higher diagnostic performance than that trained with panoramic images.

Assessment of early discomfort and wound healing outcomes after periodontal surgery with and without enamel matrix derivative: an observational retrospective case-control study.

OBJECTIVE: The aim of this study was to evaluate and compare early postoperative discomfort and wound healing outcomes between patients who underwent periodontal surgery with and without enamel matrix derivative (EMD), using retrospective questionnaires and postoperative clinical examinations. MATERIALS AND METHODS: All enrolled patients filled out the self-report questionnaire after suture removal. The severity and duration of subjective pain and swelling were evaluated using visual analog scale (VAS) scores and wound healing parameters (dehiscence/fenestration, spontaneous bleeding, persistent swelling, and ulceration). Chi-squared tests, two-tailed independent t tests, analysis of variance, and multiple logistic regression analysis were performed to identify significant differences between the two groups (surgery with EMD and surgery without EMD). RESULTS: The severity of pain and swelling did not differ between patients who underwent surgery with and without EMD, but the durations of pain (P < 0.001) and swelling (P = 0.019) were significantly lower in patients who underwent surgery with EMD. Multivariate analysis with adjustment for confounding variables showed that wound healing outcomes including dehiscence/fenestration, spontaneous bleeding, and ulceration did not differ significantly between the two groups, and only persistent swelling showed significant differences (odds ratio 4.03, 95% CI 1.17-13.78; P = 0.026). CONCLUSIONS: No difference was observed in the severity of early postoperative discomfort and wound healing outcomes between patients who underwent surgery with and without EMD, but shorter durations of postoperative pain and swelling were evident in patients who underwent surgery with EMD. CLINICAL RELEVANCE: Adjunctive EMD used in periodontal surgery has clinical advantages for reducing the durations of postoperative pain and swelling.

A Population-Based Study on the Association between Periodontal Disease and Major Lifestyle-Related Comorbidities in South Korea: An Elderly Cohort Study from 2002-2015.

This study determined the association between periodontal disease (PD) and major lifestyle-related comorbidities (LCs) using the database of the nationwide population-based National Health Insurance Service-Elderly Cohort 2002-2015. A nationwide representative sample comprising 558,147 participants, aged 60 years, was analyzed. Univariate and multivariate logistic regression analyses adjusted for sociodemographic and economic factors (sex, age, household income, insurance status, health status, and living area) and major LCs (hypertension, diabetes mellitus, rheumatoid arthritis, osteoporosis, cerebral infarction, angina pectoris, myocardial infarction, erectile dysfunction, lipoprotein disorder, and obesity) were used to determine the association between PD and major LCs. Elderly participants with PD had a higher risk of major LCs (hypertension: odds ratio (OR) = 1.40, diabetes mellitus: OR = 1.22, rheumatoid arthritis: OR = 1.16, osteoporosis: OR = 1.37, erectile dysfunction: OR = 1.73, lipoprotein disorder: OR = 1.50, and obesity: OR = 1.59). Our longitudinal cohort study provided evidence that PD was significantly associated with major LCs in elderly participants. In particular, the association between PD and erectile dysfunction had the highest OR in the multivariate analyses.

Implant fracture failure rate and potential associated risk indicators: An up to 12-year retrospective study of implants in 5,124 patients.

OBJECTIVES: This study investigated fracture rates and risk indicators for fractures in internal connection dental implants. MATERIAL AND METHODS: We performed a retrospective analysis of 19,006 internal connection implants used in fixed restoration in 5,124 patients (4,570 males, 554 females) at the Dental Hospital of Veterans Health Service Medical Center between 2006 and 2015. Patients were followed through June 2018 (0.03-12.39 years post-installation). Clinical factors (age, sex, implant diameter, implant length, placement site, bone graft, fixture material, cervical feature, abutment connection, microthread, and platform switching) were recorded. Kaplan-Meier survival analysis identified risk indicators associated with an implant fracture. Cox regression models elucidated potential fracture risks. RESULTS: One hundred and seventy-four implants fractured in 135 patients, for an incidence rate of 0.92% after an average of 4.95 ± 2.14 years of use. Kaplan-Meier estimates showed that the 3-, 5-, and 10-year survival rates of implants were 99.8%, 99.2%, and 97.7%, respectively. In the multivariable Cox regression model, the diameter, location, history of bone graft, and microthread presence were significantly correlated with implant fractures. Wide-diameter implants had a reduced fracture risk within 90 months, after which the diameter did not correlate with fractures. Implants placed in the anterior mandible had a lower fracture risk within 90 months; mandibular premolar implants corresponded with a lower risk after 90 months. Implants without a history of bone graft or microthreads were more likely to fracture throughout the follow-up time. CONCLUSIONS: These results elucidate risk indicators for implant fractures and facilitate their reduction in clinical practice.

Interdisciplinary treatment of a patient with multiple missing teeth and periodontitis.

A 49-year-old woman with several missing and periodontically compromised teeth was referred to the orthodontic department of National Health Insurance Service Ilsan Hospital by the periodontic department for interdisciplinary treatment. Multiple posterior teeth had been extracted 10 days earlier. Her chief complaint was crowding of the anterior teeth, and she wanted to improve both esthetics and function. Orthodontic, periodontic, and prosthodontic treatments were undertaken in the proper timing and sequence with an interdisciplinary approach. As a result, improved periodontal health and a stable occlusion and vertical dimension were achieved. Although there were limited teeth and alveolar bone for anchorage, good esthetic and functional treatment results were obtained through the application of temporary anchorage devices and proper biomechanics.

Effect of periodontitis on the development of osteoporosis: results from a nationwide population-based cohort study (2003-2013).

BACKGROUND: The prevalence of osteoporosis associated with the aging process is anticipated to increase along with the rising aging population. Periodontitis that the most common chronic infections of humankind is considered the risk factor for osteoporosis. The aim of this study was to identify the association between osteoporosis and periodontitis using a population-based cohort. METHODS: The case group was defined as patients diagnosed with periodontitis and treated with subgingival curettage, root conditioning, periodontal flap operation, bone grafting for alveolar bone defects, and guided tissue regeneration. Case and control groups matched for gender, age, household income, type of social security, disability, and residential area were generated. A Cox proportional hazard model was constructed to examine the difference in the development of osteoporosis between the case and control groups. The final sample included 13,464 participants. RESULTS: The incidence of osteoporosis was 1.1% in males and 15.8% in females during a 10-year period. The risk factors for osteoporosis in males were increasing age and Charlson Comorbidity Index score. Periodontitis was not associated with the development of osteoporosis in males. The risk factors for osteoporosis in females were increasing age, body mass index, Charlson Comorbidity Index score, diabetes, and periodontitis. Women with periodontitis were more likely to also develop osteoporosis (HR: 1.22, 95% CI: 1.01-1.48). CONCLUSIONS: Periodontitis has an effect on the development of osteoporosis in females. Managing good teeth is required for the prevention and delay of osteoporosis. This includes dental examinations, regular cleanings and gum treatment.

National dental policies and socio-demographic factors affecting changes in the incidence of periodontal treatments in Korean: A nationwide population-based retrospective cohort study from 2002-2013.

BACKGROUND: Dental insurance coverage has recently expanded in Korea. The number of patients diagnosed with periodontal disease (PD), and the actual number of periodontally compromised patients has increased. However, few studies have investigated the relationships between the prevalence of periodontal disease and the incidence of PD treatment, dental insurance policies, and socio-demographic factors. To determine the incidence of periodontal treatments required, the comprehensive longitudinal data of the National Health Insurance Service were used. This study evaluated changes in the incidence of periodontal treatments, using data from the Korean National Health Insurance Cohort Database. METHODS: A random stratified sample of 1,025,340 Korean patients was selected from National Health Insurance database, using 1,476 multistage samplings (of sex, age, and income level) for 12 years from 2002 to 2013. Chi-square analysis, and univariate, and multivariate logistic regression were used to evaluate the association of socio-demographic factors with the prevalence of PD and the incidence of periodontal treatment. RESULTS: The incidence of periodontal treatment steadily and significantly increased, in both male and female participants, from 2002 to 2013. The increase was associated with socio-demographic factors and changes in national dental insurance policies. The incidence of periodontal treatment evaluated by age is influenced by the changes in national dental policies. These results suggest that the increase in patients diagnosed with PD reflects changes in dental policies and insurance benefits. CONCLUSIONS: This study confirms that national dental policies and socio-demographic factors are related to the incidence of periodontal treatments. The incidence of periodontal treatment is significantly related to the expansion of insurance coverage in South Korea.

Mechanical Complication Rates and Optimal Horizontal Distance of the Most Distally Positioned Implant-Supported Single Crowns in the Posterior Region: A Study with a Mean Follow-Up of 3 Years.

PURPOSE: The purpose of this retrospective study was to determine the 3-year mechanical complication rates of the most distally positioned implant-supported single crowns (ISSCs) in the posterior region, and how these complication rates are affected by several clinical factors (i.e., gender, mean age, horizontal distance [HD], position in the jaw, placement location, duration of functional loading, clinical crown-to-implant length ratio [C/I ratio], and crown height space of the implant). MATERIALS AND METHODS: The mechanical complications (i.e., abutment screw loosening [ASL], abutment screw fracture [ASF], and ceramic fracture [CF]) associated with the implants were identified by examining the patients' treatment records, clinical photographs, and intraoral periapical radiographs. Statistical analyses were performed using chi-square and Student's t-test to identify the relationship between various clinical factors and the mechanical complication rates. Receiver operating characteristics analysis was conducted to determine the optimal cut-off value for the HD between the most distally positioned ISSCs and the mesially adjacent natural tooth beyond which complications occur. RESULTS: The study inclusion criteria were met by 183 patients who had undergone implant surgery in the period 2004 to 2011, involving a total of 221 implant treatments. Mechanical complications were present in 40 (18.1%) of the 221 investigated ISSCs. ASL was the most common complication (n = 28, 12.7%), followed in order by CF (n = 9, 4.1%) and ASF (n = 3, 1.4%). Repeated ASL and CF occurred in four (1.8%) and two (0.9%) implants, respectively. The mechanical complication rates differed significantly between implants with different HDs (p = 0.009) and clinical C/I ratios (p = 0.019); however, there was no significant association between the other clinical factors and the mechanical complication rates. CONCLUSION: Within the limitations of this study, it appears that the incidence of mechanical complications is higher for the most distally positioned ISSCs in the posterior region than for those positioned at other sites. Furthermore, since the rate of mechanical complications increases with increasing HD, an HD of 3.7 mm or less is recommended.

Identification of dental implant systems from low-quality and distorted dental radiographs using AI trained on a large multi-center dataset.

Most artificial intelligence (AI) studies have attempted to identify dental implant systems (DISs) while excluding low-quality and distorted dental radiographs, limiting their actual clinical use. This study aimed to evaluate the effectiveness of an AI model, trained on a large and multi-center dataset, in identifying different types of DIS in low-quality and distorted dental radiographs. Based on the fine-tuned pre-trained ResNet-50 algorithm, 156,965 panoramic and periapical radiological images were used as training and validation datasets, and 530 low-quality and distorted images of four types (including those not perpendicular to the axis of the fixture, radiation overexposure, cut off the apex of the fixture, and containing foreign bodies) were used as test datasets. Moreover, the accuracy performance of low-quality and distorted DIS classification was compared using AI and five periodontists. Based on a test dataset, the performance evaluation of the AI model achieved accuracy, precision, recall, and F1 score metrics of 95.05%, 95.91%, 92.49%, and 94.17%, respectively. However, five periodontists performed the classification of nine types of DISs based on four different types of low-quality and distorted radiographs, achieving a mean overall accuracy of 37.2 ± 29.0%. Within the limitations of this study, AI demonstrated superior accuracy in identifying DIS from low-quality or distorted radiographs, outperforming dental professionals in classification tasks. However, for actual clinical application of AI, extensive standardization research on low-quality and distorted radiographic images is essential.

Deep learning to assess bone quality from panoramic radiographs: the feasibility of clinical application through comparison with an implant surgeon and cone-beam computed tomography.

PURPOSE: Bone quality is one of the most important clinical factors for the primary stability and successful osseointegration of dental implants. This preliminary pilot study aimed to evaluate the clinical applicability of deep learning (DL) for assessing bone quality using panoramic (PA) radiographs compared with an implant surgeon's subjective tactile sense and cone-beam computed tomography (CBCT) values. METHODS: In total, PA images of 2,270 edentulous sites for implant placement were selected, and the corresponding CBCT relative gray value measurements and bone quality classification were performed using 3-dimensional dental image analysis software. Based on the pre-trained and fine-tuned ResNet-50 architecture, the bone quality classification of PA images was classified into 4 levels, from D1 to D4, and Spearman correlation analyses were performed with the implant surgeon's tactile sense and CBCT values. RESULTS: The classification accuracy of DL was evaluated using a test dataset comprising 454 cropped PA images, and it achieved an area under the receiving characteristic curve of 0.762 (95% confidence interval [CI], 0.714-0.810). Spearman correlation analysis of bone quality showed significant positive correlations with the CBCT classification (r=0.702; 95% CI, 0.651-0.747; P<0.001) and the surgeon's tactile sense (r=0.658; 95% CI, 0.600-0.708, P<0.001) versus the DL classification. CONCLUSIONS: DL classification using PA images showed a significant and consistent correlation with CBCT classification and the surgeon's tactile sense in classifying the bone quality at the implant placement site. Further research based on high-quality quantitative datasets is essential to increase the reliability and validity of this method for actual clinical applications.

Deep-learning performance in identifying and classifying dental implant systems from dental imaging: a systematic review and meta-analysis.

Deep learning (DL) offers promising performance in computer vision tasks and is highly suitable for dental image recognition and analysis. We evaluated the accuracy of DL algorithms in identifying and classifying dental implant systems (DISs) using dental imaging. In this systematic review and meta-analysis, we explored the MEDLINE/PubMed, Scopus, Embase, and Google Scholar databases and identified studies published between January 2011 and March 2022. Studies conducted on DL approaches for DIS identification or classification were included, and the accuracy of the DL models was evaluated using panoramic and periapical radiographic images. The quality of the selected studies was assessed using QUADAS-2. This review was registered with PROSPERO (CRDCRD42022309624). From 1,293 identified records, 9 studies were included in this systematic review and meta-analysis. The DL-based implant classification accuracy was no less than 70.75% (95% confidence interval [CI], 65.6%-75.9%) and no higher than 98.19 (95% CI, 97.8%-98.5%). The weighted accuracy was calculated, and the pooled sample size was 46,645, with an overall accuracy of 92.16% (95% CI, 90.8%-93.5%). The risk of bias and applicability concerns were judged as high for most studies, mainly regarding data selection and reference standards. DL models showed high accuracy in identifying and classifying DISs using panoramic and periapical radiographic images. Therefore, DL models are promising prospects for use as decision aids and decision-making tools; however, there are limitations with respect to their application in actual clinical practice.

Alveolar ridge preservation of damaged or periodontally compromised extraction sockets with bovine- and porcine-derived block bone substitutes: A retrospective case-control study.

PURPOSE: Alveolar ridge preservation (ARP) was introduced to minimize postextraction alveolar bone loss and extraction socket remodeling; however, current knowledge of the ARP procedure for nonintact extraction sockets is still limited and inconclusive. This retrospective study aimed to evaluate the difference between using deproteinized bovine bone mineral with 10% collagen (DBBM-C) and deproteinized porcine bone mineral with 10% collagen (DPBM-C) when performing ARP procedures in damaged or periodontally compromised extraction sockets based on clinical, radiographic, and profilometric outcomes. METHODS: In total, 108 extraction sockets were grafted with 67 DBBM-C and 41 DPBM-C. Changes in radiographic (horizontal width and vertical height) and profilometric outcomes were measured after the ARP procedure and before the implant surgery. Postoperative discomfort (including the severity and duration of pain and swelling), early wound healing outcomes (including spontaneous bleeding and persistent swelling), implant stability, and treatment modalities for implant placement were also assessed. RESULTS: Radiographically, the DBBM-C group decreased by -1.70 ± 2.26 mm (-21.50%) and - 1.39 ± 1.85 mm (-30.47%) horizontally and vertically, and the corresponding DPBM-C group decreased by -1.66 ± 1.80 mm (-20.82%) and -1.44 ± 1.97 mm (-27.89%) horizontally and vertically at an average of 5.6 months. There were no serious or adverse complications in any of the cases, and none of the measured parameters differed significantly between the groups. CONCLUSION: Within the limitations of this study, ARP with DBBM-C and DPBM-C showed similar clinical, radiographic, and profilometric outcomes in nonintact extraction sockets.

A retrospective epidemiological investigation of periodontitis risk and current smoking status based on the number of cigarettes per day and the Fagerström Test for Nicotine Dependence: a preliminary pilot study.

PURPOSE: The aim of this study was to investigate the risk of periodontitis according to current smoking status based on the number of cigarettes smoked per day (CPD) and the Fagerström Test for Nicotine Dependence (FTND). METHODS: All enrolled patients were diagnosed and classified according to the new periodontal classification scheme, and current smoking status was investigated via a self-reported questionnaire. The correlation between smoking status (CPD and FTND) and periodontitis risk (severity of periodontitis and tooth loss due to periodontal reasons) was statistically assessed using Spearman correlation coefficients. Moreover, partial correlation analyses between smoking and periodontal status were performed after adjusting for age, sex, and diabetes mellitus. RESULTS: Overall, data from 74 men and 16 women (mean age: 48.1±10.8 years) were evaluated. The mean number of missing teeth, CPD, and FTND score were 3.5±5.2, 24.6±15.5, and 3.5±2, respectively. CPD and the FTND were significantly positively correlated with each other (r=0.741, P<0.001). CPD and the FTND were also significantly correlated with the severity of periodontitis (CPD: r=0.457, P<0.05 and FTND: r=0.326, P<0.05) and the number of missing teeth due to periodontal reasons (CPD: r=0.525, P<0.05 and FTND: r=0.480, P<0.05), respectively. CONCLUSIONS: Within the limitations of this study, both CPD and the FTND were significantly correlated with the severity of periodontitis and the number of periodontally compromised extracted teeth.

Porcine-derived soft block bone substitutes for the treatment of severe class II furcation-involved mandibular molars: a prospective controlled follow-up study.

PURPOSE: No evidence exists regarding the advantages of periodontal regeneration treatment for furcation defects using soft block bone substitutes. Therefore, this randomized controlled trial aimed to assess the clinical and radiographic outcomes of regenerative therapy using porcine-derived soft block bone substitutes (DPBM-C, test group) compared with porcine-derived particulate bone substitutes (DPBM, control group) for the treatment of severe class II furcation defects in the mandibular molar regions. METHODS: Thirty-five enrolled patients (test group, n=17; control group, n=18) were available for a 12-month follow-up assessment. Clinical (probing pocket depth [PPD] and clinical attachment level [CAL]) and radiographic (vertical furcation defect; VFD) parameters were evaluated at baseline and 6 and 12 months after regenerative treatment. Early postoperative discomfort (severity and duration of pain and swelling) and wound healing outcomes (dehiscence, suppuration, abscess formation, and swelling) were also assessed 2 weeks after surgery. RESULTS: For both treatment modalities, significant improvements in PPD, CAL, and VFD were found in the test group (PPD reduction of 4.1±3.0 mm, CAL gain of 4.4±2.9 mm, and VFD reduction of 4.1±2.5 mm) and control group (PPD reduction of 2.7±2.0 mm, CAL gain of 2.0±2.8 mm, and VFD reduction of 2.4±2.5 mm) 12 months after the regenerative treatment of furcation defects (P<0.05). However, no statistically significant differences were found in any of the measured clinical and radiographic parameters, and no significant differences were observed in any early postoperative discomfort and wound healing outcomes between the 2 groups. CONCLUSIONS: Similar to DPBM, DPBM-C showed favorable clinical and radiographic outcomes for periodontal regeneration of severe class II furcation defects in a 12-month follow-up period. TRIAL REGISTRATION: Clinical Research Information Service Identifier: KCT0007305.

Automated deep learning for classification of dental implant radiographs using a large multi-center dataset.

This study aimed to evaluate the accuracy of automated deep learning (DL) algorithm for identifying and classifying various types of dental implant systems (DIS) using a large-scale multicenter dataset. Dental implant radiographs of pos-implant surgery were collected from five college dental hospitals and 10 private dental clinics, and validated by the National Information Society Agency and the Korean Academy of Oral and Maxillofacial Implantology. The dataset contained a total of 156,965 panoramic and periapical radiographic images and comprised 10 manufacturers and 27 different types of DIS. The accuracy, precision, recall, F1 score, and confusion matrix were calculated to evaluate the classification performance of the automated DL algorithm. The performance metrics of the automated DL based on accuracy, precision, recall, and F1 score for 116,756 panoramic and 40,209 periapical radiographic images were 88.53%, 85.70%, 82.30%, and 84.00%, respectively. Using only panoramic images, the DL algorithm achieved 87.89% accuracy, 85.20% precision, 81.10% recall, and 83.10% F1 score, whereas the corresponding values using only periapical images achieved 86.87% accuracy, 84.40% precision, 81.70% recall, and 83.00% F1 score, respectively. Within the study limitations, automated DL shows a reliable classification accuracy based on large-scale and comprehensive datasets. Moreover, we observed no statistically significant difference in accuracy performance between the panoramic and periapical images. The clinical feasibility of the automated DL algorithm requires further confirmation using additional clinical datasets.