Management Strategies for Immature Teeth with Pulp Necrosis: An Umbrella Review of Systematic Reviews.

Introduction: This review evaluates the effectiveness of treatment modalities for immature teeth with pulp necrosis, focusing on calcium hydroxide (CH) and mineral trioxide aggregate (MTA) apexification, as well as regenerative endodontic treatments (RETs). Recent advancements and clinical outcomes are highlighted. Materials and Methods: A comprehensive search of MEDLINE (PubMed), Embase, Cochrane Library, Scopus, and grey literature was conducted from inception to July 2024. Systematic reviews and meta-analyses (SR/MAs) assessing apexification and RET outcomes in immature teeth with pulp necrosis were included. Studies were selected based on predefined criteria, and data on study design, interventions, and outcomes were extracted. Methodological quality was evaluated using the AMSTAR-2 tool. Results: 31 SR/MAs were included. The quality ranged from critically low to low, except one rated as high. MTA apexification was more effective than CH for faster apical barrier formation, though overall success rates were similar. MTA is preferred for its efficiency, but standardized protocols are needed, and tooth discoloration was noted as a potential complication. RET generally outperforms apexification in root maturation, with platelet concentrates like platelet-rich plasma (PRP) and platelet-rich fibrin (PRF) showing promising results; PRP was associated with greater root length, while PRF showed superior apical healing. Variability in RET outcomes was noted due to the lack of standardized protocols. Comparative studies of RET versus apexification showed no significant differences in survival or overall success rates. RET often provides better apical closure and root development, though results vary. Both approaches are viable, but more research with standardized protocols and larger samples is needed to establish definitive clinical advantages. Conclusions: MTA apexification and RET are viable alternatives to CH apexification, with RET showing greater potential for root development and apical healing. Future research should focus on developing standardized protocols and uniform RET guidelines, and evaluating long-term outcomes to establish efficacy and safety.

Artificial intelligence in endodontics: Data preparation, clinical applications, ethical considerations, limitations, and future directions.

Artificial intelligence (AI) is emerging as a transformative technology in healthcare, including endodontics. A gap in knowledge exists in understanding AI's applications and limitations among endodontic experts. This comprehensive review aims to (A) elaborate on technical and ethical aspects of using data to implement AI models in endodontics; (B) elaborate on evaluation metrics; (C) review the current applications of AI in endodontics; and (D) review the limitations and barriers to real-world implementation of AI in the field of endodontics and its future potentials/directions. The article shows that AI techniques have been applied in endodontics for critical tasks such as detection of radiolucent lesions, analysis of root canal morphology, prediction of treatment outcome and post-operative pain and more. Deep learning models like convolutional neural networks demonstrate high accuracy in these applications. However, challenges remain regarding model interpretability, generalizability, and adoption into clinical practice. When thoughtfully implemented, AI has great potential to aid with diagnostics, treatment planning, clinical interventions, and education in the field of endodontics. However, concerted efforts are still needed to address limitations and to facilitate integration into clinical workflows.

Artificial intelligence in endodontics: Fundamental principles, workflow, and tasks.

The integration of artificial intelligence (AI) in healthcare has seen significant advancements, particularly in areas requiring image interpretation. Endodontics, a specialty within dentistry, stands to benefit immensely from AI applications, especially in interpreting radiographic images. However, there is a knowledge gap among endodontists regarding the fundamentals of machine learning and deep learning, hindering the full utilization of AI in this field. This narrative review aims to: (A) elaborate on the basic principles of machine learning and deep learning and present the basics of neural network architectures; (B) explain the workflow for developing AI solutions, from data collection through clinical integration; (C) discuss specific AI tasks and applications relevant to endodontic diagnosis and treatment. The article shows that AI offers diverse practical applications in endodontics. Computer vision methods help analyse images while natural language processing extracts insights from text. With robust validation, these techniques can enhance diagnosis, treatment planning, education, and patient care. In conclusion, AI holds significant potential to benefit endodontic research, practice, and education. Successful integration requires an evolving partnership between clinicians, computer scientists, and industry.

Tooth Loss is a Risk Factor for Cardiovascular Disease Mortality: A Systematic Review with Meta-analyses.

INTRODUCTION: The current evidence linking tooth loss and cardiovascular disease mortality is inconclusive. Thus, the aim of this systematic review was to explore the association between tooth loss and cardiovascular disease (CVD) mortality. METHODS: A comprehensive literature search of databases and gray literature included: Web of Science, Scopus, PubMed, Cochrane Central Register of Controlled Trials, Google Scholar, various digital repositories. The included studies reported on CVD mortality and tooth loss. The Newcastle-Ottawa scale was used to assess the quality of included studies. Random-effects meta-analysis method, sub-group analysis (based on the tooth loss categories (edentulous and fewer than 10 teeth present), meta-regression (based on the number. of confounders), publication bias, and sensitivity analysis were performed. RESULTS: Twelve articles met the eligibility criteria with an overall "Good" quality. A significant association between tooth loss (edentulous or less than 10 teeth present) and CVD mortality was found in the primary meta-analysis, which compiled data from 12 studies. The estimated hazard ratio was 1.66 (95% CI: 1.32-2.09), and there was high heterogeneity (I2 = 82.42). Subgroup analysis revealed that the edentulous subgroup showed a higher risk with no significant heterogeneity, while the subgroup with fewer than 10 teeth showed a higher risk with substantial heterogeneity. Meta-regression analysis did not reveal any significant impact (P = .626) on whether variations in the number of confounders across studies would substantially affect the overall findings. No publication bias was detected and the sensitivity analysis based on the critical confounders also confirmed that tooth loss as a risk factor for CVD mortality (hazard ratio = 1.52, 95% CI: 1.28-1.80), (I2 51.82%). CONCLUSION: The present systematic review reported that being edentulous or having lesser than 10 teeth is a predictive indicator of CVD mortality.

Surface plasmon resonance biosensors for early troponin detection.

Acute myocardial infarction (AMI) is one of the life-threatening causes that decrease blood flow to the heart, leading to increased mortality and related complications. Recently, the measure of blood concentration of cardiac biomarkers has been suggested to overcome the limitations of electrocardiography (ECG) analyses for early diagnosis of this disease. Troponins, especially cardiac troponin I and cardiac troponin T, with high sensitivity and specificity, are considered the gold standards in myocardial diagnosis. Recently, the use of new biosensors such as surface plasmon resonance (SPR) for early detection of these biomarkers has been greatly appreciated. Due to the rapid, sensitive, real-time, and label-free detection of SPR-based biosensors, they can be applied for selective and nonspecific absorption that is intended to be used as an in situ cardiac biosensor. Here, we exclusively discussed the updated developments of these valuable predictors for the possible occurrence of AMI detected by SPR.

Incidence of Middle Mesial Canals in Mandibular Molars during Root Canal Treatment and Nonsurgical Retreatment.

INTRODUCTION: Large-scale clinical studies on the incidence of middle mesial canals (MMCs) in nonsurgical root canal treatment (RCT) and retreatment of mandibular molars are lacking. The primary aim of this observational study was to determine the incidence of MMCs in mandibular first and second molars that received RCT or nonsurgical retreatment (NSRetx). The secondary aim was to determine factors associated with incidence of MMCs. METHODS: Included were 3018 mandibular molars that received RCT (n = 1624) or NSRetx (n = 1394) by 3 endodontists in a private practice. Demographic and procedural data were collected. Bivariate and multivariable (Poisson regression model) analyses were performed. RESULTS: Incidence of MMCs was 8.8% (n = 267). Although the bivariate analysis showed that NSRetx was significantly associated with incidence of MMCs, this association did not reach the threshold for statistical significance after controlling for all covariates (P = .07). Multivariable analysis on the entire cohort showed that incidence of MMCs was significantly associated with younger age (risk ratio [RR] = 1.62; 95% confidence interval [CI], 1.28-2.06), male gender (RR = 1.48; 95% CI, 1.18-1.85), preoperative cone-beam computed tomography (CBCT) (RR = 1.48; 95% CI, 1.17-1.89), and first molar (RR = 2.30; 95% CI:1.74-3.05). Subgroup multivariable analyses revealed that incidence of MMCs was associated with male gender only in the RCT group (RR = 2.26; 95% CI, 1.55-3.30) but not in the NSRetx group (RR = 1.11; 95% CI, 0.82, 1.50); and with preoperative CBCT only in the NSRetx group (RR = 1.78; 95% CI, 1.28, 2.50) but not in the RCT group (RR = 1.10; 95% CI, 0.71, 1.69). Associations with younger age and first molar remained unchanged. CONCLUSIONS: Overall incidence of MMCs was 8.8%. Incidence of MMCs was significantly higher in younger patients and in mandibular first molars but was not associated with the type of treatment.

Artificial Intelligence in Endodontic Education.

AIMS: The future dental and endodontic education must adapt to the current digitalized healthcare system in a hyper-connected world. The purpose of this scoping review was to investigate the ways an endodontic education curriculum could benefit from the implementation of artificial intelligence (AI) and overcome the limitations of this technology in the delivery of healthcare to patients. METHODS: An electronic search was carried out up to December 2023 using MEDLINE, Web of Science, Cochrane Library, and a manual search of reference literature. Grey literature, ongoing clinical trials were also searched using ClinicalTrials.gov. RESULTS: The search identified 251 records, of which 35 were deemed relevant to artificial intelligence (AI) and Endodontic education. Areas in which AI might aid students with their didactic and clinical endodontic education were identified as follows: 1) radiographic interpretation; 2) differential diagnosis; 3) treatment planning and decision-making; 4) case difficulty assessment; 5) preclinical training; 6) advanced clinical simulation and case-based training, 7) real-time clinical guidance; 8) autonomous systems and robotics; 9) progress evaluation and personalized education; 10) calibration and standardization. CONCLUSIONS: AI in endodontic education will support clinical and didactic teaching through individualized feedback; enhanced, augmented, and virtually generated training aids; automated detection and diagnosis; treatment planning and decision support; and AI-based student progress evaluation, and personalized education. Its implementation will inarguably change the current concept of teaching Endodontics. Dental educators would benefit from introducing AI in clinical and didactic pedagogy; however, they must be aware of AI's limitations and challenges to overcome.

Outcomes and predictive factors of vital pulp therapy in a large-scale retrospective cohort study over 10 years.

This cohort study evaluated the long-term success/survival of vital pulp therapies (VPTs) after carious pulp exposure in adult teeth. Additionally, factors influencing long-term success were identified. Teeth treated during 2011-2022 in a private clinic were studied with clinical/radiographic follow-ups. Data included patient demographics, tooth specifics, and treatment details. Outcomes were classified as success/failure based on clinical/radiographic findings, with tooth functionality determining the survival rate. Encompassing 1149 patients and 1257 VPT-treated teeth, the average monitoring period was 42.2 months. Overall VPTs' survival and success rates were 99.1% and 91.6%, respectively. Success rates for 768 direct pulp cappings, 217 miniature pulpotomies, and 272 full pulpotomies were 91.9%, 92.6%, and 90.1%, respectively (P > 0.05). Influencing factors included symptomatic irreversible pulpitis (SIP; HR 1.974, 95% CI 1.242-3.137; P = 0.004), radiographic signs of apical periodontitis (AP; HR 2.983, 95% CI 1.961-4.540; P < 0.001), restoration type (HR 2.263, 95%CI 1.423-3.600; P = 0.001), and restoration surfaces (HR 1.401, 95%CI 1.034-1.899; P = 0.030). This study concludes that VPT techniques consistently exhibit high long-term success/survival rates in treating carious pulp exposures. Critical predictors include initial clinical signs of SIP/AP, caries extent, and use of composite restorations.

Artificial Intelligence for Detection of External Cervical Resorption Using Label-Efficient Self-Supervised Learning Method.

INTRODUCTION: The aim of this study was to leverage label-efficient self-supervised learning (SSL) to train a model that can detect ECR and differentiate it from caries. METHODS: Periapical (PA) radiographs of teeth with ECR defects were collected. Two board-certified endodontists reviewed PA radiographs and cone beam computed tomographic (CBCT) images independently to determine presence of ECR (ground truth). Radiographic data were divided into 3 regions of interest (ROIs): healthy teeth, teeth with ECR, and teeth with caries. Nine contrastive SSL models (SimCLR v2, MoCo v2, BYOL, DINO, NNCLR, SwAV, MSN, Barlow Twins, and SimSiam) were implemented in the assessment alongside 7 baseline deep learning models (ResNet-18, ResNet-50, VGG16, DenseNet, MobileNetV2, ResNeXt-50, and InceptionV3). A 10-fold cross-validation strategy and a hold-out test set were employed for model evaluation. Model performance was assessed via various metrics including classification accuracy, precision, recall, and F1-score. RESULTS: Included were 190 PA radiographs, composed of 470 ROIs. Results from 10-fold cross-validation demonstrated that most SSL models outperformed the transfer learning baseline models, with DINO achieving the highest mean accuracy (85.64 ± 4.56), significantly outperforming 13 other models (P < .05). DINO reached the highest test set (ie, 3 ROIs) accuracy (84.09%) while MoCo v2 exhibited the highest recall and F1-score (77.37% and 82.93%, respectively). CONCLUSIONS: This study showed that AI can assist clinicians in detecting ECR and differentiating it from caries. Additionally, it introduced the application of SSL in detecting ECR, emphasizing that SSL-based models can outperform transfer learning baselines and reduce reliance on large, labeled datasets.

Validity and reliability of artificial intelligence chatbots as public sources of information on endodontics.

AIM: This study aimed to evaluate and compare the validity and reliability of responses provided by GPT-3.5, Google Bard, and Bing to frequently asked questions (FAQs) in the field of endodontics. METHODOLOGY: FAQs were formulated by expert endodontists (n = 10) and collected through GPT-3.5 queries (n = 10), with every question posed to each chatbot three times. Responses (N = 180) were independently evaluated by two board-certified endodontists using a modified Global Quality Score (GQS) on a 5-point Likert scale (5: strongly agree; 4: agree; 3: neutral; 2: disagree; 1: strongly disagree). Disagreements on scoring were resolved through evidence-based discussions. The validity of responses was analysed by categorizing scores into valid or invalid at two thresholds: The low threshold was set at score ≥4 for all three responses whilst the high threshold was set at score 5 for all three responses. Fisher's exact test was conducted to compare the validity of responses between chatbots. Cronbach's alpha was calculated to assess the reliability by assessing the consistency of repeated responses for each chatbot. RESULTS: All three chatbots provided answers to all questions. Using the low-threshold validity test (GPT-3.5: 95%; Google Bard: 85%; Bing: 75%), there was no significant difference between the platforms (p > .05). When using the high-threshold validity test, the chatbot scores were substantially lower (GPT-3.5: 60%; Google Bard: 15%; Bing: 15%). The validity of GPT-3.5 responses was significantly higher than Google Bard and Bing (p = .008). All three chatbots achieved an acceptable level of reliability (Cronbach's alpha >0.7). CONCLUSIONS: GPT-3.5 provided more credible information on topics related to endodontics compared to Google Bard and Bing.

Flare-ups After Nonsurgical Retreatments: Incidence, Associated Factors, and Prediction.

INTRODUCTION: The aims of this study were to determine the incidence, associated factors, and predictability of flare-ups after nonsurgical retreatments (NSRetx). METHODS: All patients (n = 3,666) who received NSRetx by 3 endodontists in 2 endodontic offices during a period of 6 years (2016-2022) were included. Demographic, diagnostic, and procedural data were collected. A flare-up was defined as moderate-severe pain with/without swelling that took place within 14 days of initiation of NSRetx and resulted in an unscheduled appointment. Bivariate analyses on the entire cohort and multivariable analyses on cases with complete dataset (n = 2,846) were performed to identify significant associations. A Random Forest algorithm was used to make a prediction model. RESULTS: Incidence of flare-ups was 3.95% (n = 145). Increased risk of flare-ups was associated with diabetes (adjusted odds ratio [AOR] = 2.01; 95% confidence interval [CI], 1.01-3.97), mandibular teeth (AOR = 1.67; 95% CI, 1.11-2.52), moderate-severe preoperative pain on percussion (AOR = 2.13; 95% CI, 1.31-3.50), and pain on palpation (AOR = 1.63; 95% CI, 1.01-2.64). Lower risk of flare-up was associated with high blood pressure (AOR = 0.44; 95% CI, 0.21-0.82) (P < .05). The prediction model was not able to predict flare-ups with sufficient confidence (precision = 0.13). CONCLUSIONS: Incidence of flare-ups following NSRetx was low (∼4%) and had a weak but significant association with the history of diabetes. Moderate-severe pain on percussion, pain on palpation (any intensity), and mandibular teeth had a significant association with flare-ups. The history of high blood pressure was associated with lower risk of flare-ups. Flare-ups were difficult to predict in this clinical setting.

Deep Learning for Detection of Periapical Radiolucent Lesions: A Systematic Review and Meta-analysis of Diagnostic Test Accuracy.

INTRODUCTION: The aim of this systematic review and meta-analysis was to investigate the overall accuracy of deep learning models in detecting periapical (PA) radiolucent lesions in dental radiographs, when compared to expert clinicians. METHODS: Electronic databases of Medline (via PubMed), Embase (via Ovid), Scopus, Google Scholar, and arXiv were searched. Quality of eligible studies was assessed by using Quality Assessment and Diagnostic Accuracy Tool-2. Quantitative analyses were conducted using hierarchical logistic regression for meta-analyses on diagnostic accuracy. Subgroup analyses on different image modalities (PA radiographs, panoramic radiographs, and cone beam computed tomographic images) and on different deep learning tasks (classification, segmentation, object detection) were conducted. Certainty of evidence was assessed by using Grading of Recommendations Assessment, Development, and Evaluation system. RESULTS: A total of 932 studies were screened. Eighteen studies were included in the systematic review, out of which 6 studies were selected for quantitative analyses. Six studies had low risk of bias. Twelve studies had risk of bias. Pooled sensitivity, specificity, positive likelihood ratio, negative likelihood ratio, and diagnostic odds ratio of included studies (all image modalities; all tasks) were 0.925 (95% confidence interval [CI], 0.862-0.960), 0.852 (95% CI, 0.810-0.885), 6.261 (95% CI, 4.717-8.311), 0.087 (95% CI, 0.045-0.168), and 71.692 (95% CI, 29.957-171.565), respectively. No publication bias was detected (Egger's test, P = .82). Grading of Recommendations Assessment, Development and Evaluationshowed a "high" certainty of evidence for the studies included in the meta-analyses. CONCLUSION: Compared to expert clinicians, deep learning showed highly accurate results in detecting PA radiolucent lesions in dental radiographs. Most studies had risk of bias. There was a lack of prospective studies.

External Cervical Resorption: A Volumetric Analysis on Evolution of Defects over Time.

INTRODUCTION: The aim of this study was to assess the temporal evolution of external cervical resorption (ECR) defects using a volumetric quantification method. METHODS: Cone-beam computed tomographic (CBCT) images of patients diagnosed with ECR who chose not to receive treatment and attended recalls were collected. ECR defects were segmented in CBCT images at baseline and recall, and their volumes were quantified. The volumetric ratio of resorption defects/teeth was calculated. Three-dimensional classification of defects at baseline and recall and the prevalence of root surface perforations ≥1 mm were determined. The Wilcoxon matched pairs signed rank test, chi-square test, and linear regression models were used to analyze the data. RESULTS: Fifteen patients with 20 teeth diagnosed with ECR and an average recall time of 21 months were included. Nine (45%) teeth showed a change in 3-dimensional classification at recall. The volume of resorption defects (P = .0001) and the volumetric ratio of resorption defects/teeth (P = .0001) increased over time. The prevalence of root surface perforations ≥1 mm was higher at recall (n = 17, 85%) compared with baseline (n = 9, 45%) (P = .008). Linear regression models showed significant associations between the resorption defect volume at recall compared with baseline (P < .0001; 95% confidence interval, 0.053-0.081) and the volumetric ratio of resorption defects/teeth at recall compared with baseline (P < .0001; 95% confidence interval, 0.205-0.356). There was no association between the volume of resorption defects at recall with the length of the recall period, sex, or age (P > .05). CONCLUSIONS: When left untreated, ECR defects can increase in size and develop more root surface perforations. ECR has a dynamic nature, and its volumetric increase over time does not result from uniform/linear expansion of the defects.

Was the Coronavirus Disease 2019 Pandemic Associated with an Increased Rate of Cracked Teeth?

INTRODUCTION: There is lack of data on whether the coronavirus disease 2019 (COVID-19) pandemic was associated with changes in the etiology of pathosis in endodontic patients. The aim of this study was to determine the rate of cracks and other etiologic factors during the period of March 16th to May 31st in 2020 (COVID-19 initial outbreak) and 2021 (COVID-19 ongoing pandemic) compared with figures from the same period in 2019 (pre-COVID era) in 2 endodontists' practices. METHODS: The etiologies of patients' chief complaints were determined from records of 2440 teeth (740 in 2019, 651 in 2020, and 1049 in 2021). Changes in the proportion of etiologic factors among all 3 periods were analyzed. The association between the rate of cracked teeth and patients' age and sex was determined using a logistic regression model. RESULTS: The rates of all etiologies collectively during the studied periods showed a significant change (P < .0001). The rate of cracks significantly increased in 2020 (11.8%) (P = .0001) and 2021 (8%) (P = .0018) compared with 2019 (4.3%). The rate of persistent infections decreased in 2020 (22.3%) (P = .0013) and then increased in 2021 (27.5%) (P = .0153) compared with 2019 (30%). Cracked teeth were associated with the age group of 40-60 years (odds ratio [OR] = 1.882; 95% confidence interval [CI], 1.063-3.330) in 2020 and with age ranges of 40-60 years (OR = 2.051; 95% CI, 1.120-3.759) and >60 years (OR = 2.038; 95% CI, 1.050-3.956) and male sex (OR = 1.599; 95% CI, 1.019-2.510) in 2021. CONCLUSIONS: The rate of cracked teeth increased during the initial outbreak of the COVID-19 pandemic and 1 year later. This study provided evidence on the association between the COVID-19 pandemic and changes in the rate and presentation of endodontic etiologic factors.

Cytokine co-stimulation effect on odontogenic differentiation of stem cells.

OBJECTIVE: The study aims to evaluate the effect of bone morphogenetic protein-2 (BMP-2) and transforming growth factor-beta 1 (TGF-ß1) co-stimulation on odontogenic differentiation of human dental pulp stem cells (hDPSCs). MATERIALS AND METHODS: The viability/proliferation of hDPSCs treated with BMP-2 (group B), TGF-ß1 (group T), or BMP-2/TGF-ß1 (group BT) were evaluated. The experiments on odontogenic differentiation were done for 14 days. The following subgroups were added to investigate the effect of co-stimulation with different timing: subgroup B1, TGF-ß1 co-stimulation in the first week; subgroup B2, TGF-ß1 co-stimulation in the second week; subgroup T1, BMP-2 co-stimulation in the first week; and subgroup T2, BMP-2 co-stimulation in the second week. The mineralization was assessed using alizarin red staining. The expression of following genes was assessed using quantitative real-time polymerase chain reaction: dentin sialophosphoprotein (DSPP), dentin matrix protein-1 (DMP1), osteopontin (OPN), and alkaline phosphatase. RESULTS: All groups showed viability similar to the control group (P > .05). The greater mineralization was detected in B groups on day 14. The expressions of DSPP, DMP-1, and OPN increased on day 14 (P < .05). In the combination groups, the higher expressions of DSPP and DMP-1 were observed in subgroups B1 and B2 than groups B and T (P < .05). CONCLUSIONS: BMP-2 was the key in odontogenic differentiation of hDPSCs, which was further enhanced by co-stimulation with TGF-ß1. Continuous stimulation with TGFß-1 did not improve the differentiation of hDPSCs. CLINICAL RELEVANCE: Combined use of the BMP-2 and TGFß-1 at the specific sequence can provide a tissue engineering approach for the future guided dentin regeneration.

Endodontic Specialists' Practice During the Coronavirus Disease 2019 Pandemic: 1 Year after the Initial Outbreak.

INTRODUCTION: The aims of this observational study were to determine if endodontists' practices in early 2021 experienced changes in patient characteristics compared with a comparable prepandemic period and to determine whether the changes reported during the initial outbreak of coronavirus disease 2019 (COVID-19) in 2020 were reversed 1 year later. METHODS: Demographic, diagnostic, and procedural data of 2657 patient visits from 2 endodontist private offices from March 16 to May 31 in 2019, 2020, and 2021 were included. Bivariate analyses and multiple logistic regression models were used to examine the impact of ongoing COVID-19 pandemic on patient data. RESULTS: Bivariate analyses showed that patients' self-reported pain levels and the number of visits with irreversible pulpitis in 2021 were higher than 2019 (P < .05). Patients' self-reported pain, percussion pain, and palpation pain levels in 2021 were less than 2020 (P < .05). Multiple logistic regression analyses showed that endodontists' practices in 2021 had an increase in the number of nonsurgical root canal treatments (odds ratio [OR] = 1.482; 95% confidence interval [CI], 1.102-1.992), and apicoectomies (OR = 2.662; 95% CI, 1.416-5.004) compared with 2019. Compared with the initial outbreak in 2020, endodontists' practices in 2021 had visits with older patients (OR = 1.288; 95% CI, 1.045-1.588), less females (OR = 0.781; 95% CI, 0.635-.960), more molars (OR = 1.389; 95% CI, 1.065-1.811), and less pain on percussion (OR = 0.438; 95% CI, 0.339-0.566). CONCLUSIONS: The ongoing COVID-19 pandemic was associated with an increase in the number of nonsurgical root canal treatments. Some of the changes observed during the initial outbreak in 2020, including objective pain parameters, returned to normal levels 1 year later.

Regenerative Endodontic Treatment Using Periapical Blood or Circulating Blood as Scaffold: A Volumetric Analysis.

INTRODUCTION: Circulating blood is a readily available scaffold when enough bleeding cannot be induced from periapical tissues during regenerative endodontic treatments (RETs). The aim of this investigation was to compare the radiographic outcome (ie, linear and 3-dimensional volumetric) of RET using periapical blood or circulating blood as scaffolds in sheep immature mandibular incisors. METHODS: Thirty-two immature sheep mandibular central incisors were randomly assigned to the following groups (n = 8): the positive control groups, the pulps were removed without any treatment; the periapical blood group, RET was performed using periapical blood as the scaffold; the circulating blood group, RET was performed using circulating blood as the scaffold; and the negative control group, intact teeth without any treatment. After 8 months, micro-computed tomographic images of mandibular blocks were taken to assess the following: root length, root thickness at the midroot and cementoenamel junction levels, and the incidence of apical closure. Root structures were segmented, and root volumes were calculated and analyzed statistically. RESULTS: RET using periapical blood and circulating blood resulted in increases in root length and root wall thickness at the midroot and cementoenamel junction levels, the incidence of apical closure, and root volume (P < .05). There were no significant differences between the RET groups and the negative control group regarding linear measurements (ie, root length, root thickness, and apical closure) (P > .05). The root volumes of the 2 RET groups were similar (P > .05) and were less than those observed in the negative control group (P < .05). CONCLUSIONS: There were no significant radiographic differences between the RET groups using periapical blood and circulating blood as scaffolds. RET resulted in less root volume compared with normal root development.

Endodontics Specialists' Practice during the Initial Outbreak of Coronavirus Disease 2019.

INTRODUCTION: The first outbreak of coronavirus disease 2019 (COVID-19) in the United States resulted in a nationwide closure of dental offices that created an oral health crisis. The aim of this observational study was to analyze and compare the characteristics of patients who visited 2 private endodontics offices from March 16 to May 31, 2020, compared with the same period in 2019. METHODS: Demographic, diagnostic, and procedural data of 1520 (693 in 2020 and 827 in 2019) patient visits were collected. Bivariate and multiple logistic regression analyses were used to assess the impact of the COVID-19 outbreak on patient-related variables. RESULTS: Bivariate analyses showed that the number of patient visits decreased in April and May 2020 (P < .0001). In 2020, patients' self-reported pain level was higher, they were more frequently diagnosed with pulp necrosis and acute apical abscess, and they received more incisions for drainage (P < .05). Multiple logistic regression analyses showed that the COVID-19 outbreak was associated with less visits for older patients (>49.5 years) (odds ratio [OR] = 0.720; 95% confidence interval [CI], 0.573-0.906), more patients with kidney diseases (OR = 2.690; 95% CI, 1.143-6.331), higher levels of pain on percussion (OR = 2.277; 95% CI, 1.718-3.016), less cases with previously initiated treatment (OR = 0.242; 95% CI, 0.080-0.731), less periapical diagnoses of asymptomatic apical periodontitis (OR = 0.510; 95% CI, 0.306-0.849), and a higher number of nonsurgical root canal treatments (OR = 2.073; 95% CI, 1.397-3.074) and apicoectomies (OR = 2.799; 95% CI, 1.367-5.729). CONCLUSIONS: These findings show that the public health burden of endodontic infections was more intense during the initial outbreak of COVID-19.

Revitalizing previously treated teeth with open apices: A case report and a literature review.

Revitalizing the root canals of previously treated teeth with open apices is appealing to clinicians and patients. However, there are fundamental differences in the microbiome and the microenvironment between a canal with a primary endodontic infection and a canal with a persistent endodontic infection. The aims of this report are to report a case where a previously treated tooth with an open apex and a large apical radiolucency was treated successfully using regenerative endodontic treatment (RET) and to review and critically appraise the literature on procedures and outcomes of RET that result in revitalization of canal(s) in previously treated teeth with open apices. A maxillary central incisor with poor-quality root filling, a large apical radiolucency and an open apex was retreated using RET using platelet-rich fibrin as the scaffold. After 24 months, there was complete healing of the periapical lesion and obvious radiographic signs of apical root closure. Electronic searches were performed in MEDLINE, Scopus and Embase, and the baseline, procedural and outcome data of qualified articles were collected. An assessment tool was developed to rate the quality of evidence reported in these case report/series. Nine articles, three case series and six case reports, with a total of 17 teeth of all types, were included in the reports identified. The age of patients ranged from 7 to 48 years (mean: 19.4 years). The recall period ranged from 12 to 72 months (mean: 29 months). All 17 teeth survived and were functional with healing/healed outcomes. "Apical closure" was the most common radiographic finding regarding root development. The quality of evidence using the new assessment tool was rated "Excellent" in three case reports but only "Fair" in the other six articles. The present case report, as well as the review of the literature, suggests that revitalizing the root canal system of teeth with open apices and post-treatment disease using RET is a potentially valid treatment option. However, more clinical studies with higher levels of evidence and higher quality of evidence are required to confirm the viability of this treatment approach.