BMC Oral Health最新文献

Background: There has been a notable increase in artificial intelligence (AI) studies in dentistry. However, the inadequate use of proper validation methods has led to overly optimistic performance metrics of machine learning (ML) models. External validation provides evidence of a ML model's performance with independent datasets and is crucial for generalizability.

Methods: We developed Extreme Gradient Boosting (XGBoost) models to detect dental caries using easy-to-collect questionnaire data. ML model training was conducted using cross-validation nested resampling with a holdout test set, utilizing NHANES datasets (n = 6070). Performance of the trained model was tested using external data from the Northern Finland Birth Cohorts (NFBC1966 and NFBC1986; n = 3616). To enhance interpretability, beeswarm plots were constructed to visualize variable importance.

Results: The ML model demonstrated acceptable performance in predicting dental caries on the internal dataset, with an area under the operating characteristics curve (AUC) of 0.785 (95% CI 0.756-0.813). However, the model encountered difficulties in identifying participants with dental caries, as shown by its poor sensitivity of 0.391, despite achieving a high specificity of 0.919. When applied to the external dataset, the ML model encountered significant challenges, with the AUC dropping to 0.550 (95% CI 0.532-0.569), sensitivity decreasing to 0.053, and specificity slightly improving to 0.974. Important variables identified by the model were self-rated condition of teeth and gums, presence of missing teeth, financial status, and time since last dental visit.

Conclusion: The performance of our ML model during external validation degraded notably compared to the internal validation. However, the XAI methodology exhibited great potential to be used in the future for individualized dental caries risk assessment.

Background: Adenoid hypertrophy is a common cause of pediatric obstructive sleep apnea (OSA), which can impair cognitive development and affect craniofacial development. Given that adenoids typically regress with age and may respond to oral appliance therapy, early identification, clear orthodontic indications, and timely referral are essential for effective management. A major challenge in this process is accurately assessing adenoid volume and quantifying nasopharyngeal obstruction in three dimensions. To address this, we developed a deep learning-based method using cone-beam computed tomography (CBCT) to accurately segment adenoid, and establish a novel quantitative index, the Three-Dimensional Adenoidal-Nasopharyngeal Ratio (3D-AN), for assessing nasopharyngeal airway obstruction.

Methods: This retrospective study included three datasets. Dataset 1 comprised 126 CBCT scans (pre- and post-adenoidectomy) from 63 pediatric OSA patients. Dataset 2 included post-adenoidectomy CBCT scans of 26 pediatric OSA patients. Dataset 3 involved 161 pediatric patients with both polysomnography and CBCT data. A SegResNet-based model was trained on Datasets 1 and 2 (1326 training pairs) to predict postoperative airway morphology following adenoidectomy using preoperative scans. By inputting preoperative airway data, the model predicts postoperative morphology, and the volumetric difference represents the adenoid. 3D-AN ratio was then computed from adenoid-to-nasopharyngeal volume. Dataset 3 was used to investigate the relationship between the 3D-AN and pediatric OSA.

Results: The segmentation model achieved a Dice similarity coefficient of 0.88 and a relative volume error of 0.09. Preliminary analysis showed that a 3D-AN ratio below 0.18 was not significantly correlated with pediatric OSA, while values above 0.18 correlated significantly with OSA (r = 0.56, P < 0.01).

Conclusions: This automated method enables accurate adenoid segmentation. The proposed 3D-AN, based on volumetric ratios, holds potential for early detection of adenoid-related airway obstruction and for supporting future research in adenoid assessment and clinical management.

Background: Endodontic and periodontal diseases are common oral diseases. Traditional treatments, such as root canal disinfection and scaling, are limited by challenges such as microbial residue, tissue damage, and antibiotic resistance. Curcumin, a natural polyphenol derived from turmeric, exhibits antibacterial, anti-inflammatory, and tissue regeneration properties. This scoping review aimed to integrate the research status and application prospects of curcumin in endodontic and periodontal diseases, explore the transformation of basic research into clinical application, and provide guidance for the dual challenges of infection control and tissue repair encountered by clinicians.

Methods: The scoping review was conducted according to the PRISMA extension for scoping reviews. PubMed, EBSCOhost, and SpringerLink were searched for relevant studies. English studies published after 2019 were retrieved. The included studies were manually screened, covering animal experiments, clinical trials, and in vitro experiments. Using a standardized form, two reviewers independently extracted data and resolved disagreements through discussion. The application of curcumin in root canal disinfection, filling materials, and periodontal treatment was comprehensively evaluated.

Results: This review included 31 studies (8 clinical studies). Curcumin, as a photosensitizer for photodynamic therapy in root canal disinfection, showed superior deep bactericidal efficacy and biocompatibility; however, broader clinical application requires further clinical research. In deciduous teeth root canal filling, curcumin formulations have varied therapeutic effects; thus, comparative studies are required to facilitate translation from experimental findings to clinical practice. As periodontal treatment, curcumin demonstrated excellent bactericidal, anti-inflammatory, and tissue repair capabilities; however, more trials are needed to provide clinical evidence for validating its performance and supporting its clinical application.

Conclusion: Preliminary studies show curcumin's potential in antibacterial activity, biocompatibility, and osteogenesis in endodontic and periodontal diseases. However, its practical effects remain inconclusive owing to data heterogeneity and methodological limitations. More clinical studies are warranted to reach definitive conclusions.

Background: Evidence on psychophysiological responses such as heart rate (HR) and electrodermal response (EDR) during long-term supportive periodontal therapy (SPT) is limited. This observational cross-sectional pilot study aimed to explore associations between patient-related factors and physiological stress markers during routine SPT visits, focusing on adherence-related variables.

Methods: A sample of n = 75 patients was examined in a questionnaire-based, cross-sectional survey, indicating sufficient adherence to SPT of ≥ 2 years (a maximum deviation ± 6 months between SPT intervals) at a specialized department for periodontology. At the preliminary last SPT visit, in addition to dental parameters, we assessed socio-demographic, treatment-related (critical attitudes/complaints), psychological variables-such as dental fear, oral health-related quality of life, dental anticipatory trauma symptoms, childhood traumata, depression, and personality functioning-and vital parameters such as HR and EDR. The primary endpoint was the difference in HR and EDR across predefined procedural clusters reflecting varying invasiveness (three clusters: non-invasive (n-iC), minimally invasive (m-iC), and invasive (iC). Analyses were performed using non-parametric tests and exploratory correlation analyses.

Results: The mean (standard deviation) of HR differed significantly across intervention clusters (n-iC/m-iC/iC: 73.06[11.96]/67.66[9.60]/69.46[10.00] bpm; p ≤ 0.001), while EDR revealed no significant differences (n-iC/m-iC/iC: 69.64[156.65]/61.72[172.20]/75.10[154.07] µS; p ≥ 0.075). EDR negatively correlated with the number of teeth m-iC-interventions (r = -0.423; p = 0.003). Moreover, EDR and HR were significantly related to certain variables such as long-term medication and number of general diseases (p < 0.001). Significant correlations included a positive association between Oral Health Impact Profile scores and dental anxiety (r = 0.233; p = 0.040) and a negative correlation with the total number of teeth (r = -0.378; p < 0.001).

Conclusion: Socio-demographic and treatment-related factors were intertwined with patient and dental parameters in SPT and appeared to influence adherence. HR varied across clusters, but no clear link between vital signs and psychological stress could be established.

Trial registration: The clinical trial was prospectively registered in the DRKS-German Clinical Trials Register (https://www.drks.de) with the registration-ID DRKS00031969 (06/05/2023).

Background: Oral health is a critical component of overall well-being, particularly in older hospitalized patients. There is growing interest in how oral conditions and interventions affect oral health-related quality of life (OHRQoL). This study aimed to identify oral-health variables that influence OHRQoL in older hospitalized patients.

Methods: A cross-sectional survey was conducted with 214 older inpatients by using the Oral Health Impact Profile-14 (OHIP-14), Oral Health Assessment Tool (OHAT), and Self-Efficacy Scale for Self-Care (SESS). Data were analyzed using SPSS (version 26.0) and structural equation modeling in AMOS, guided by the Andersen oral-health outcome model. Correlation analyses were also performed to identify factors associated with OHRQoL.

Results: Oral self-care efficacy, the number of remaining teeth, and oral-health status significantly influenced OHRQoL. The mean OHIP score was 10.19 ± 5.96, the mean SESS score was 56.41 ± 9.49, and the mean OHAT score was 3.22 ± 1.02. Oral self-care efficacy exerted both direct (-0.21) and indirect (-0.023) effects on OHRQoL. The number of remaining teeth had a direct effect of -0.26 and an indirect effect of -0.076 on OHRQoL.

Conclusions: Multiple interrelated factors influence OHRQoL in older hospitalized patients. Health education aimed at improving oral-health awareness, beliefs, and self-care efficacy should be prioritized by nurses and physicians. Timely interventions addressing oral-health status, including tooth preservation and treatment, can further enhance quality of life. Further research should examine the social and cultural determinants of OHRQoL in this population.

Background: Injectable platelet-rich fibrin (i-PRF) is often used in maxillofacial surgery in combination with commercially available materials, but until now no study has compared biological and mechanical interactions between i-PRF and different composition biomaterial scaffolds. This study investigated how biomaterials - Collacone® (Biotiss), Bio-Oss® Collagen (90% Geistlich Bio-Oss®/10% porcine collagen, Geistlich), and CeraForm® (65% hydroxyapatite/35% β-tricalcium phosphate, Teknimed) - interact with i-PRF and influence material degradation, growth factor release, osteoblastogenesis, and osteoclastogenesis.

Methods: Blood from three healthy donors was centrifuged at 700 rpm for 5 min to prepare i-PRF. Materials were impregnated with i-PRF and allowed to coagulate for 30 min. Surface properties were examined by scanning electron microscopy, and material degradation was monitored for 50 days. Growth factor release (IL-6, IL-8, EGF, PDGF, TGF-β1) was quantified by ELISA over 14 days. Osteoblastogenesis was evaluated using CellTiter-Blue®, and osteoclastogenesis was assessed through resorption assays on simulated body fluid/collagen type I-coated plates via image analysis and qPCR for differentiation markers. Data was analysed using ANOVA.

Results: i-PRF delays the degradation of collagen-containing biomaterials. Impregnation of studied biomaterials with i-PRF only reduced growth factor release during the first 6 h. TGF-β1 release increased significantly after platelet activation by foreign surfaces, while collagen-based biomaterials triggered rapid IL-6 and IL-8 release. Composites with i-PRF promoted earlier activation of both osteoclasts and osteoblasts.

Conclusion: i-PRF showed different synergetic responses based on collagen and calcium phosphate composition in materials it was combined with. Meaning that these findings provide guidance for optimizing biomaterial and i-PRF combinations in surgical applications and inform the design of next-generation PRF-material composites.