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Introduction: One of the most common problems in endodontic treatments is post-treatment pain, and sealers might be one of the factors influencing the degree of pain following root canal therapy. The purpose of this study is to compare pain following endodontic treatment using an AH-26 resin sealer against the Resil experimental sealer in mandibular molars with irreversible pulpitis. Materials and Methods: One hundred patients with irreversible pulpitis in the mandibular first or second molar were randomly divided into two groups (n=50) based on the type of sealer applied. Two postgraduate students with at least five years of experience treated all patients. All patients had a single root canal treatment. Postoperative pain scores and analgesic consumption were assessed after 6, 12, 24, and 48 hours and 3, 4, 5, 6, and 7 days after the treatment. The data were statistically analyzed by Fisher's exact or Chi-Square test (to compare the distribution of qualitative variables in two groups), repeated measures ANOVA (to compare changes in pain intensity over time in two groups), Boneferronie (for pairwise comparisons), Friedman, Wilcoxon and Mann-Whitney tests (for assessment of the changes in pain scores over time). The generalized estimating equations (GEE) were used for assessing time and group effects. Results: There was no significant difference in postoperative pain between groups at any of the time points studied (P>0.05), and also for patient analgesic consumption between groups (P>0.05). Both groups recorded the maximum pain levels in the first 6 hours. For each subsequent day postoperatively, the odds ratio (OR) of not using analgesics was 2.078. Conclusion: Resil and AH-26 perform similarly in terms of the occurrence and intensity of postoperative pain in mandibular molar teeth with irreversible pulpitis.
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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.
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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.
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Root canal therapy (RCT) is a widely performed procedure in dentistry, with over 25 million individuals undergoing it annually. This procedure is carried out to address inflammation or infection within the root canal system of affected teeth. However, accurately aligning CT scan information with the patient's tooth has posed challenges, leading to errors in tool positioning and potential negative outcomes. To overcome these challenges, a mixed reality application is developed using an optical see-through head-mounted display (OST-HMD). The application incorporates visual cues, an augmented mirror, and dynamically updated multi-view CT slices to address depth perception issues and achieve accurate tooth localization, comprehensive canal exploration, and prevention of perforation during RCT. Through the preliminary experimental assessment, significant improvements in the accuracy of the procedure are observed. Specifically, with the system the accuracy in position was improved from 1.4 to 0.4 mm (more than a 70% gain) using an Optical Tracker (NDI) and from 2.8 to 2.4 mm using an HMD, thereby achieving submillimeter accuracy with NDI. 6 participants were enrolled in the user study. The result of the study suggests that the average displacement on the crown plane of 1.27 ± 0.83 cm, an average depth error of 0.90 ± 0.72 cm and an average angular deviation of 1.83 ± 0.83°. Our error analysis further highlights the impact of HMD spatial localization and head motion on the registration and calibration process. Through seamless integration of CT image information with the patient's tooth, our mixed reality application assists dentists in achieving precise tool placement. This advancement in technology has the potential to elevate the quality of root canal procedures, ensuring better accuracy and enhancing overall treatment outcomes.
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BACKGROUND: This study aimed to assess the accuracy of two different endodontic guides for fiber post removal. METHODS: In this in vitro study, 54 maxillary canine fiber posts were mounted on 36 maxillary stone casts; 18 teeth were mounted unilaterally, and 36 teeth were mounted bilaterally. Static endodontic guides were fabricated according to baseline cone-beam computed tomography (CBCT) and intraoral optical scans using Blue Sky software. In the single-sleeve endodontic guides group (SSG), two anterior and two posterior teeth were included in a 5-unit guide. In the double-sleeve endodontic guides group (DSG) group, the guide was passed through the midline to include both canine teeth and extended by 2 teeth posterior to the canine teeth bilaterally (a 10-unit guide). After drilling, postoperative CBCT scans were taken and superimposed on the virtually designed path, and the maximum coronal deviation (MCD) at the marginal entry point of the tooth, maximum apical deviation (MAD) at 10 mm apical to the tooth margin, and maximum angular deflection (MAnD) of the drill were calculated. RESULTS: The mean MCD, MAD, and MAnD were 0.34 mm, 0.6 mm, and 2.32 degrees, respectively, in the SSG and 0.31 mm, 0.7 mm, and 2.37 degrees, respectively, in the DSG. The two groups were not significantly different from each other in terms of MCD (P = 0.573), MAD (P = 0.290), or MAnD (P = 0.896). CONCLUSIONS: The accuracies of the two techniques, the extended double sleeve guide and the single sleeve guide, were comparable and thus DSG may be used for removal of fiber posts in adjacent or distant teeth.
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Cone-Beam Computed Tomography , Post and Core Technique , Humans , Post and Core Technique/instrumentation , Cuspid/diagnostic imaging , In Vitro TechniquesABSTRACT
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.
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Dental Pulp Cavity , Mandible , Molar , Retreatment , Root Canal Therapy , Humans , Molar/diagnostic imaging , Male , Female , Root Canal Therapy/methods , Retreatment/statistics & numerical data , Dental Pulp Cavity/diagnostic imaging , Adult , Incidence , Middle Aged , Young AdultABSTRACT
INTRODUCTION: This systematic review and meta-analysis aimed to evaluate the clinical and radiographic failure of nonsurgical endodontic treatment and retreatment for mature permanent teeth with or without apical periodontitis using the single-cone (SC) obturation technique with calcium silicate-based bio-ceramic (CSBC) sealers and to compare these failure rates to other sealer materials and obturation techniques. METHODS: A comprehensive search was conducted using MEDLINE (PubMed), Embase, Cochrane Library, Scopus, Web of Science, and gray literature up to March 2023. Two reviewers assessed the eligibility of the included studies. Eligible studies were critically appraised for risk of bias and quality of evidence. Subsequently, a meta-analysis of pooled data was conducted utilizing the RevMan software (P < .05) to evaluate the failure rate of non-surgical root canal therapy using CSBC sealers and SC obturation procedures. Separately, another analysis was conducted to compare those results with the outcome of nonsurgical root canal therapy using alternative obturation materials and methods. RESULTS: Five studies were included. The pooled failure rate for nonsurgical endodontic treatment and retreatment combined using CSBC sealers and SC obturation technique was 6.8% [95% confidence interval (CI) = (3%-12%), I2 = 46%]. A second analysis was conducted on the 3 included clinical trials to compare the outcomes of the intervention (CSBC sealers and SC obturation technique) and control groups (other sealers and other obturation techniques). This analysis found no significant difference between the 2 groups regarding clinical and radiographic failure of endodontic treatment and retreatment [Risk ratio = 0.71, 95% CI = (0.33, 1.51), I2 = 0]. This difference was also not statistically significant when the failure rate of primary root canal treatment and retreatment were separately analyzed [Combined Risk ratio of primary root canal treatment = 0.94, 95% CI = (0.46, 1.93), I2 = 0%; Combined Risk ratio of retreatment = 0.21, 95% CI = (0.001, 75.46), I2 = 0%]. CONCLUSIONS: The overall results of this systematic review and meta-analysis demonstrate that the SC obturation technique with CSBC sealer provides similar results compared to other obturation materials and techniques in facilitating the healing of apical periodontitis.
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Calcium Compounds , Root Canal Filling Materials , Root Canal Obturation , Root Canal Therapy , Silicates , Humans , Calcium Compounds/therapeutic use , Dental Restoration Failure , Periapical Periodontitis/therapy , Periapical Periodontitis/diagnostic imaging , Retreatment , Root Canal Filling Materials/therapeutic use , Root Canal Obturation/methods , Root Canal Therapy/methods , Silicates/therapeutic use , Treatment FailureABSTRACT
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.
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Artificial Intelligence , Curriculum , Education, Dental , Endodontics , Endodontics/education , Humans , Education, Dental/methods , Clinical CompetenceABSTRACT
Invasive cervical root resorption (ICRR) is a dental pathology, marked by unexpected destruction originating in the cervical region of the tooth. This comprehensive literature review provides a holistic view into the pathogenesis, clinical manifestation, and precise management of ICRR, aiming to guide endodontists and enhance patient care and treatment outcomes. The review delves into the potential etiology of ICRR, covering contributing factors such as trauma, orthodontic treatment, and other pertinent conditions. It outlines the clinical and radiographic indicators, underscoring the crucial role of early detection and precise diagnosis in effectively managing and halting ICRR progression. The exploration of treatment approaches is thorough, ranging from non-surgical methods like vital pulp therapy or root canal treatment to surgical interventions. This review accentuates the essential role of interdisciplinary collaboration among diverse dental specialties in enhancing ICRR management. It highlights the importance of a consolidated strategy in enhancing treatment outcomes and preserving tooth structure and function. Moreover, it investigates prevention methods, risk evaluation, and identifies prospective research pathways to address the existing knowledge gaps.
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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.
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Dental Caries , Tooth , Humans , Cone-Beam Computed Tomography/methods , Artificial Intelligence , Tomography, X-Ray Computed/methods , Supervised Machine LearningABSTRACT
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.
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Artificial Intelligence , Endodontics , Reproducibility of Results , Software , Information SourcesABSTRACT
OBJECTIVES: To evaluate a modified two-step buccal infiltration (MBI) of 1.7 mL 4% articaine as primary or supplemental anesthesia in mandibular first and second molars diagnosed with symptomatic irreversible pulpitis (SIP). MATERIALS AND METHODS: One hundred and eight patients with SIP were randomly assigned to one of three groups (n = 36). They were given an inferior alveolar nerve block (IANB) of 2% lidocaine with 1:80.000 epinephrine or a primary MBI of 4% articaine with 1:100.000 epinephrine in the IANB and MBI groups, respectively. Patients in the IANB + MBI group received an IANB followed by an MBI. Pain levels during the injection, access cavity preparation, and initial filing were recorded on the Heft-Parker visual analog scale (HP-VAS). No or mild pain (HP-VAS ≤ 54) upon access cavity preparation and initial filing was considered a success. Chi-square and Kruskal-Wallis tests were used to analyze the data. RESULTS: MBI (77.8%) and IANB + MBI (94.4%) had both significantly higher success rates than IANB (50.0%) (P < .001). However, when the Bonferroni adjustment was applied, there was no statistically significant difference between the MBI and IANB + MBI techniques (P = .041 > .017). MBI was associated with significantly less injection pain than IANB (P < .001). CONCLUSIONS: Both primary and supplemental MBI with 4% articaine were superior to IANB with 2% lidocaine in mandibular first and second molars diagnosed with SIP. Further research may be needed to confirm the findings of this study. CLINICAL RELEVANCE: The findings of this study suggest that supplemental or primary MBI can be a clinically viable alternative to IANB, which has a relatively low success rate when managing mandibular molars diagnosed with SIP.
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Anesthesia, Dental , Anesthetics , Pulpitis , Humans , Carticaine , Pulpitis/surgery , Lidocaine , Pain , Molar/surgery , EpinephrineABSTRACT
INTRODUCTION: This study aimed to assess the fracture resistance of mandibular first molars after preparation with 3 different access cavity designs and 2 rotary systems using finite element analysis. METHODS: Six 3-dimensionally printed mandibular first molars simulating natural teeth received traditional, conservative, and ultraconservative (truss) access cavity preparations. The root canals in each group were instrumented with either XP-Endo Shaper (FKG Dentaire, La Chaux-de-Fonds, Switzerland) or TruNatomy (Dentsply Sirona, Ballaigues, Switzerland) rotary files. The models were individually digitized, and micro-computed tomographic scans were transferred to Mimics software (Materialise NV, Leuven, Belgium) to create a geometric model of the tooth. The designed model was exported to 3-matic software (Materialise NV), and STL files were transferred to Geomagic Design X (3D Systems, Rock Hill, SC). Point cloud data were used for surfacing and transferred to ANSYS software (Ansys, Canonsburg, PA). A 200-N superficial force was applied vertically to the buccal cusps and central fossa, and the maximum and minimum equivalent von Mises stress values were calculated and reported. RESULTS: The traditional and ultraconservative access cavity designs yielded the highest and the lowest von Mises stress values, respectively. In the ultraconservative cavity design, the stress values in pericervical dentin were lower in canal preparation with TruNatomy compared with XP-Endo Shaper. In the traditional and conservative cavity designs, stress was lower in the first 2 mm from the cementoenamel junction in the XP-Endo Shaper group and in the next 3 mm in the TruNatomy group. CONCLUSIONS: Stress was lower in the ultraconservative and conservative cavity designs compared with the traditional design. Also, root canal preparation with TruNatomy yielded lower stress values in general compared with XP-Endo Shaper.
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Dental Pulp Cavity , Molar , Dental Pulp Cavity/diagnostic imaging , Finite Element Analysis , X-Ray Microtomography , Molar/diagnostic imaging , Root Canal Preparation/methodsABSTRACT
Removing a fiber post from a root canal that requires endodontic retreatment is often very challenging. Conventional freehand techniques for removing fiber posts are time-consuming, sometimes result in iatrogenic errors, and heavily rely on the practitioner's experience. The endodontic static guide can be an alternative method. While the use of an endodontic 3D-printed static guide for fiber post removal has been reported as highly successful, it can also cause complications. Skipping any critical steps during the guide construction or its clinical application can lead to errors. This case report presents the saving of a compromised tooth with a fractured fiber post and a periapical lesion around the apex through the use of an endodontic static guide for fiber post removal. This study describes possible sources of error that may happen during construction and clinical use of the guide.
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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 (â¼4%) 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.
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Diabetes Mellitus , Hypertension , Humans , Incidence , Pain, Postoperative/epidemiology , Toothache/etiology , Diabetes Mellitus/etiology , Hypertension/etiology , Root Canal Therapy/methodsABSTRACT
OBJECTIVE: The management of postoperative endodontic pain (PEP) is essential to contemporary endodontic practice. Diclofenac and ibuprofen (IBU) are two of the most widely-used non-steroidal anti-inflammatory analgesics. However, their comparative data are neither sufficient nor conclusive. This prospective randomised clinical trial aimed to compare the analgesic efficacy of diclofenac potassium (DFK) with IBU on PEP in maxillary and mandibular first molars diagnosed with irreversible pulpitis after single-visit non-surgical root canal treatment. METHODS: Sixty-four patients were randomised into two groups of DFK (n=32) and IBU (n=32), using the stratified permuted randomisation method, and 61 participants completed the trial. After root canal treatment, patients randomly received IBU 400 mg every 6 hours (n=31) or DFK 50 mg every 8 hours (n=30) for 24 hours. Patients recorded their pain level on 0-100 mm visual analogue scales (VAS) at 2, 4, 6, 12, and 24 hours after the treatment. Recorded VAS scores and the number of pain-free patients (VAS<5) were compared between the two groups. A generalised linear estimation equation model, Chi-Square test, and Mann-Whitney U test were used to analyse the data. RESULTS: The mean overall PEP score was statistically significantly lower in the DFK group than the IBU group with a p value of 0.030. Pain scores at 2 (p=0.034), 4 (p=0.021), and 24 hours (p=0.042) after the treatment were also significantly lower for DFK than IBU. The number of pain-free patients was also significantly higher in the DFK group at 2-hour (p=0.015) and 4-hour (p=0.048) time points and overall (p=0.013) compared to the IBU group. There was no adverse effect observed in either group. CONCLUSION: Based on the results, taking multi-dose DFK 50 mg by the clock had better analgesic outcomes than multi-dose IBU 400 mg for PEP management. (EEJ-2022-01-07).
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Ibuprofen , Pulpitis , Humans , Ibuprofen/therapeutic use , Diclofenac/therapeutic use , Pulpitis/therapy , Prospective Studies , Analgesics/therapeutic use , Pain, Postoperative/drug therapy , Pain, Postoperative/etiology , Molar/surgeryABSTRACT
INTRODUCTION: This systematic review evaluated the effect of periapical lesion (PL) size on the success rate of different endodontic treatments, including root canal treatment (RCT), non-surgical retreatment (NSR), and apical surgery (AS). METHODS: Cohorts and randomized controlled trials investigating the outcomes of endodontic treatment of permanent teeth with PL and its size were identified electronically through Web of Science, MEDLINE, Scopus, and Embase databases. Two reviewers independently conducted the study selection, data extraction, and critical appraisal process. The quality of the included studies was evaluated using the Newcastle-Ottawa Scale and the 11-item Critical Appraisal Skills Program checklist for randomized controlled trials. The success rates of the endodontic treatments (small lesions and large lesions) were estimated using the rate ratios (RRs) with an associated 95% confidence interval (CI). RESULTS: Out of 44 included studies, 42 were cohort, and 2 were randomized controlled trials. Thirty-two studies had poor quality. For the meta-analysis, five studies in RCT, 4 in NSR, and 3 in AS were considered. The RR of the endodontic treatment success in PLs was 1.04 in RCT (95% CI, 0.99-1.07), 1.11 in NSR (95% CI, 0.99-1.24), and 1.06 in AS (95% CI, 0.97-1.16). Only sub-group analysis of long-term follow-up of RCT showed a significantly higher success rate in small lesions than in large lesions. CONCLUSIONS: Considering the quality of studies and variation in outcomes and size classification, our meta-analysis demonstrated that the PL size had no significant effect on the success rate of different endodontic treatments.
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Dental Care , Root Canal Therapy , Humans , Treatment Outcome , Retreatment , Dentition, PermanentABSTRACT
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.
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Deep Learning , Cone-Beam Computed Tomography/methods , Radiography, Panoramic , Diagnostic Tests, Routine , Sensitivity and SpecificityABSTRACT
This systematic review (PROSPERO-CRD42020147333) aimed to compare the effects of conservative, ultraconservative and truss access cavities with traditional access cavities on the load capacity of root-canal-treated teeth. Online databases were searched until December 2021, and 25 ex vivo studies in which the effects of different access cavities on load capacity of permanent teeth had been investigated were included. Quality assessment was completed using a modified risk of bias tool for in vitro studies adapted from previous studies. Meta-analysis was performed using the maximum-likelihood-based random-effects model with similar groups. Conservative access cavities significantly improved the load capacity of maxillary premolars (p < 0.01 [-1.32, -0.028]) and molars (p < 0.05 [-0.89, -0.02]) compared to traditional access cavities. Additionally, truss access cavities significantly improved the load capacity of mandibular molars with (p < 0.05, [-1.18, -0.02]) mesio-occluso-distal cavity preparations. Higher levels of evidence are needed to determine the long-term implications of minimal preparations for treatment outcomes.