Search

Sporadic studies have reported the occurrence of nasopalatine duct cysts after maxillary anterior implant surgery, and the treatment methods still have clinical uncertainty. We report a potential therapy method that successfully treated a nasopalatine duct cyst that developed and expanded 1 year after maxillary anterior implant placement following periodontally hopeless teeth extraction. The nasopalatine cyst was treated surgically without removing implants. During flap surgery, the cyst was removed intact, and the exposed implant's surface was debrided thoroughly by hydrogen peroxide (H2O2) rinsing, glycine air polishing, and saline rinsing. To deal with the significant bone defect caused by the cyst, a bovine porous bone mineral injected platelet-rich fibrin (BPBM-i-PRF) complex was applied to fill the defect, following a resorbable collagen membrane to cover. Seven years after surgery, no cyst recurrence was observed, and bone regeneration in the bone graft area was stable. The implants functioned well without mobility. For nasopalatine duct cysts associated with dental implant placement, complete surgical debridement and longitudinal stable bone regeneration are possibly accessible by regenerative surgery without implant removal. [ABSTRACT FROM AUTHOR]

Aim: To develop a nomogram‐based predictive model of tooth survival by comprehensively analysing clinical and radiographic risk factors of tooth loss (TL). Materials and Methods: In this study, 3447 teeth of 131 subjects who underwent non‐surgical periodontal treatment were examined retrospectively within a mean follow‐up period of 11.6 years. The association of risk factors including clinical and radiographic parameters with TL was assessed using univariate and multivariate Cox regression analyses. A nomogram‐based predictive model was developed, and its validation and discriminatory ability were analysed. Results: In all, 313 teeth were lost in 94 patients in this study (overall tooth loss [OTL] 9.08%; 0.21 teeth/patient/year). Male, heavy smoking, molar teeth, probing depth (PD), attachment loss (AL), tooth mobility and radiographic bone loss were significantly associated with TL (p <.05). A gradient effect of tooth mobility on TL increased from degree I to III versus none (p <.0001). The area under the curve (AUC) of the model was 0.865. Calibration curve and decision curve analysis demonstrated good performance and high net benefit, respectively. Conclusions: Adopting a specific nomogram could facilitate the prediction of tooth survival and the development of tailored treatment plans in Chinese patients with advanced periodontitis. [ABSTRACT FROM AUTHOR]

Background: Periodontitis is characterized by local inflammatory conditions in the periodontium, its severe form has been associated with elevated systemic inflammatory markers. However, the long‐term effects of periodontal inflammation control on systemic inflammatory markers are unclear. Objective: This study aimed to investigate the long‐term effects of periodontal therapy on the levels of peripheral venous blood inflammatory markers in patients with generalized aggressive periodontitis (GAgP), all of whom were now diagnosed as Stage III or IV Grade C periodontitis. Methods: Patients with GAgP were consecutively recruited from April 2013 to August 2014 (T0). Active periodontal treatment (APT) was provided, and follow‐ups were conducted over a 3‐ to 5‐year period (T1). Clinical parameters were assessed and fasting venous blood was collected at T0 and T1. Complete blood cell counts were obtained, and biochemical analyses were performed to evaluate the levels of serum components. The correlations between probing depth (PD) and hematological parameters were analyzed. Results: A total of 49 patients with GAgP completed APT and follow‐ups. Probing depth (PD) reduced from 5.10 ± 1.07 mm at T0 to 3.15 ± 0.65 mm at T1. For every 1‐mm reduction in PD after treatment, the neutrophil count, neutrophil‐lymphocyte ratio, and total protein concentration were reduced by 0.33 × 109/L, 0.26, and 1.18 g/L, respectively. In contrast, the albumin/globulin ratio increased by 0.10. Conclusion: This study indicated that periodontal therapy may have beneficial effects on peripheral venous blood inflammatory markers in patients with GAgP during long‐term observation. [ABSTRACT FROM AUTHOR]

Objective: To assess the effects of amoxicillin and metronidazole with scaling and root planing (SRP) on periodontal parameters and glycemic control in patients with severe periodontitis and diabetes mellitus. Background: Adjunctive antibiotics use is advantageous for treating periodontitis in patients with severe periodontitis and diabetes. However, the effects of adjunctive antibiotic use on hemoglobin A1c (HbA1c) levels remain unclear. Methods: This short‐term, randomized controlled trial enrolled patients with severe periodontitis and type 2 diabetes. The patients were randomly allocated to SPR only (i.e., control) or SPR + antibiotics (500 mg of amoxicillin and 200 mg of metronidazole, three times daily for 7 days) groups. Periodontal and hematological parameters were assessed at baseline and 3 months after treatment. Inter‐ and intra‐group analyses were performed using Student's t‐tests, Mann–Whitney U tests, and the binary logistic regression models. p‐values of <.05 were considered statistically significant. Results: This study enrolled 49 patients, with 23 and 26 patients in the SRP‐only and SRP + antibiotics groups, respectively. The periodontal parameters improved significantly and similarly in both groups after treatment (p <.05). The SRP + antibiotics group had more sites of improvement than the SRP‐only group when the initial probing depth was >6 mm. (698 [78.96%] vs. 545 [73.35%], p =.008). The HbA1c levels decreased in the SRP‐only and SRP + antibiotics groups after treatment (0.39% and 0.53%, respectively). The multivariable binary logistic regression model demonstrated that antibiotics administration and a high baseline HbA1c level were associated with a greater reduction in the HbA1c level (odds ratio = 4.551, 95% confidence interval: 1.012–20.463; odds ratio = 7.162, 95% confidence interval: 1.359–37.753, respectively). Conclusions: SRP and SRP plus systemic antibiotics were beneficial for glycemic control. Adjunctive antibiotic use slightly improved the outcome for patients with severe periodontitis and poorly controlled diabetes. [ABSTRACT FROM AUTHOR]

Background: To investigate the relation of established glucose and lipid metabolism indexes and blood inflammatory biomarkers with severe periodontitis in systemically healthy patients.Methods: Systemically healthy stage III/IV periodontitis patients (case group) (n = 397), stage II periodontitis patients (n = 36), and periodontally healthy subjects (control group) (n = 285) were recruited. A periodontal examination, complete blood cell examination, and blood biochemical examination were conducted for all participants. Full-mouth apical films were taken for the case group. Both the case and control groups were divided by age into younger (≤35 years) and elder subjects. Multiple logistic regression analysis and Pearson correlation analysis were conducted. A logistic least absolute shrinkage and selection operator (LASSO) model was constructed for the younger subgroups.Results: Various glucose and lipid metabolism indexes and blood inflammatory biomarkers significantly differed between severe periodontitis patients and healthy controls, and the younger subgroups presented a greater degree of statistical differences than the elder ones. More pairs of periodontal parameters and blood indexes with significantly fair linear correlations were found in the younger patient subgroup. A logistic LASSO regression model containing eight blood indexes to assess a severe periodontitis outcome in younger subgroups showed satisfactory predictive ability.Conclusion: The present study revealed various glucose and lipid metabolism indexes and blood inflammatory biomarkers significantly differ between severe periodontitis patients and healthy controls, especially in the younger subgroups. A LASSO regression model could be a viable option to assess severe periodontitis risk for younger patients.Summary: The present study revealed significant differences in glucose and lipid metabolism indexes and blood inflammatory biomarkers between patients with severe periodontitis and periodontally healthy individuals, especially in younger subjects. This article is protected by copyright. All rights reserved. [ABSTRACT FROM AUTHOR]

Aim: To develop and validate models based on logistic regression and artificial intelligence for prognostic prediction of molar survival in periodontally affected patients. Materials and Methods: Clinical and radiographic data from four different centres across four continents (two in Europe, one in the United States, and one in China) including 515 patients and 3157 molars were collected and used to train and test different types of machine‐learning algorithms for their prognostic ability of molar loss over 10 years. The following models were trained: logistic regression, support vector machine, K‐nearest neighbours, decision tree, random forest, artificial neural network, gradient boosting, and naive Bayes. In addition, different models were aggregated by means of the ensembled stacking method. The primary outcome of the study was related to the prediction of overall molar loss (MLO) in patients after active periodontal treatment. Results: The general performance in the external validation settings (aggregating three cohorts) revealed that the ensembled model, which combined neural network and logistic regression, showed the best performance among the different models for the prediction of MLO with an area under the curve (AUC) = 0.726. The neural network model showed the best AUC of 0.724 for the prediction of periodontitis‐related molar loss. In addition, the ensembled model showed the best calibration performance. Conclusions: Through a multi‐centre collaboration, both prognostic models for the prediction of molar loss were developed and externally validated. The ensembled model showed the best performance in terms of both discrimination and validation, and it is made freely available to clinicians for widespread use in clinical practice. [ABSTRACT FROM AUTHOR]