Association of interleukin-1, interleukin-6, collagen type I alpha 1, and osteocalcin gene polymorphisms with early crestal bone loss around submerged dental implants: A nested case control study

STATEMENT OF PROBLEM

The reason for variations in peri-implant early crestal bone loss is unclear but may be due to genetic differences among individuals.

PURPOSE

The purpose of this nested case control study was to investigate the association of single-nucleotide polymorphisms of interleukin-1, interleukin-6, collagen type I alpha1, and osteocalcin genes to early crestal bone loss around submerged dental implants.

MATERIAL AND METHODS

Dental implants were placed in the mandibular posterior region (single edentulous space) of 135 participants selected according to predetermined selection criteria. Bone mineral density measurement by using dual energy X-ray absorptiometry, cone beam computed tomography scans at the baseline and after 6 months, and interleukin-1A-889 A/G (rs1800587), interleukin-1B-511 G/A (rs16944), interleukin-1B+3954 (rs1143634), interleukin-6-572 C/G (rs1800796), collagen type I alpha1 A/C (rs1800012), and osteocalcin C/T (rs1800247) genotyping were performed in all participants. Early crestal bone loss measured around dental implants was used to group participants into clinically significant bone loss (BL)>0.5 mm and clinically nonsignificant bone loss (NBL)≤0.5 mm. Early crestal bone loss was calculated as the mean of the difference of bone levels at the baseline and bone levels after 6 months as measured with cone beam computed tomography scans. The obtained data for basic characteristics, early crestal bone loss, and genotyping were tabulated and compared by using a statistical software program (α=.05).

RESULTS

AA genotype and the A allele frequency of interleukin-1B-511 and GG genotype and the G allele frequency of interleukin-6-572 were significantly higher in BL than in NBL (P<.05). Multiple logistic analysis suggested that interleukin-1B-511 AA/GG+AG and interleukin-6-572 GG/CC+CG genotype expression were significantly associated with early crestal bone loss (AA/GG+AG; P=.014, GG/CC+CG; P=.047) around dental implants. Other risk factors were not significantly different (P>.05).

CONCLUSIONS

Of the genes studied, individuals with interleukin-1B-511 AA (rs16944) or interleukin-6-572 GG (rs1800796) genotype had higher susceptibility to early crestal bone loss around dental implants.

PGPR: the treasure of multifarious beneficial microorganisms for nutrient mobilization, pest biocontrol and plant growth promotion in field crops

Plant growth-promoting rhizobacteria (PGPR) have multifarious beneficial activities for plant growth promotion; act as source of metabolites, enzymes, nutrient mobilization, biological control of pests, induction of disease resistance vis-a-vis bioremediation potentials by phytoextraction and detoxification of heavy metals, pollutants and pesticides. Agrochemicals and synthetic pesticides are currently being utilized widely in all major field crops, thereby adversely affecting human and animal health, and posing serious threats to the environments. Beneficial microorganisms like PGPR could potentially substitute and supplement the toxic chemicals and pesticides with promising application in organic farming leading to sustainable agriculture practices and bioremediation of heavy metal contaminated sites. Among field crops limited bio-formulations have been prepared till now by utilization of PGPR strains having plant growth promotion, metabolites, enzymes, nutrient mobilization and biocontrol activities. The present review contributes comprehensive description of PGPR applications in field crops including commercial, oilseeds, leguminous and cereal crops to further extend the utilization of these potent groups of beneficial microorganisms so that even higher level of crop productivity and quality produce of field crops could be achieved. PGPR and bacteria based commercialized bio-formulations available worldwide for its application in the field crops have been compiled in this review which can be a substitute for the harmful synthetic chemicals. The current knowledge gap and potential target areas for future research have also been projected.

Radiographic findings of space-occupying lesions in sialo-CBCT of the major salivary glands

OBJECTIVES

When performing CBCT sialography (sialo-CBCT), space-occupying lesions may be identified incidentally. The objective was to describe their radiologic-clinical-histopathologic correlations.

METHOD AND MATERIALS

The archive of sialo-CBCT scans was retrospectively searched for suspected space-occupying lesions. Based on the scan and clinical-histopathologic data, the cases were divided into "pathologic" vs "normal," "intra-parenchymal" vs "extra-parenchymal," and "benign" vs "malignant." Two precalibrated, blinded radiologists performed a survey of the radiographic features of each scan. Cohen kappa, chi-square, Kruskal-Wallis, and Mann-Whitney tests assessed inter-observer agreement and radiologic-clinical-histopathologic correlations.

RESULTS

In total, 27 (1.5%) suspected space-occupying lesions were found in 1,758 reports. Full follow-up data were available for 15 cases: four were "malignant," six were "benign," and the remaining five were "normal." Kappa showed substantial inter-observer agreement (0.8 to 1.0). Constant swelling correlated with "pathologic" cases (P = .003). Lesion diameter was greater in "pathologic" than "normal" (P < .001) cases, with a cut-off of 12.6 mm. Clinical and radiographic features were similar in "benign" and "malignant" lesions. "Intra-parenchymal" and "extra-parenchymal" space-occupying lesions correlated with "no-fill-region" (P = .01) and "main-duct-displacement" (P = .002), respectively.

CONCLUSIONS

Suspected space-occupying lesions in sialo-CBCT with a diameter greater than 12.6 mm are likely to be "pathologic." No radiographic features were able to differentiate between "malignant" and "benign" space-occupying lesions.

Artificial intelligence for oral and dental healthcare: Core education curriculum

OBJECTIVES

Artificial intelligence (AI) is swiftly entering oral health services and dentistry, while most providers show limited knowledge and skills to appraise dental AI applications. We aimed to define a core curriculum for both undergraduate and postgraduate education, establishing a minimum set of outcomes learners should acquire when taught about oral and dental AI.

METHODS

Existing curricula and other documents focusing on literacy of medical professionals around AI were screened and relevant items extracted. Items were scoped and adapted using expert interviews with members of the IADR's e-oral health group, the ITU/WHO's Focus Group AI for Health and the Association for Dental Education in Europe. Learning outcome levels were defined and each item assigned to a level. Items were systematized into domains and a curricular structure defined. The resulting curriculum was consented using an online Delphi process.

RESULTS

Four domains of learning outcomes emerged, with most outcomes being on the "knowledge" level: (1) Basic definitions and terms, the reasoning behind AI and the principle of machine learning, the idea of training, validating and testing models, the definition of reference tests, the contrast between dynamic and static AI, and the problem of AI being a black box and requiring explainability should be known. (2) Use cases, the required types of AI to address them, and the typical setup of AI software for dental purposes should be taught. (3) Evaluation metrics, their interpretation, the relevant impact of AI on patient or societal health outcomes and associated examples should be considered. (4) Issues around generalizability and representativeness, explainability, autonomy and accountability and the need for governance should be highlighted.

CONCLUSION

Both educators and learners should consider this core curriculum during planning, conducting and evaluating oral and dental AI education.

CLINICAL SIGNIFICANCE

A core curriculum on oral and dental AI may help to increase oral and dental healthcare providers' literacy around AI, allowing them to critically appraise AI applications and to use them consciously and on an informed basis.

Global prevalence of edentulism and dental caries in middle-aged and elderly persons: A systematic review and meta-analysis

OBJECTIVE

The aim of the study was to analyze data collected from studies worldwide on the prevalence of edentulism and dental caries, in community-dwellers aged ≥ 45 years.

DATA

Inclusion criteria; participants aged ≥ 45 years, community-dwellers. Exclusion criteria; participants aged < 45 years, in nursing homes, data obtained from dental clinics or pre-2005. The quality assessment tool by The National Heart, Lung and Blood Institute for Observational Cohort and Cross-sectional studies was used. Meta-analysis using the random-effects model (95% confidence interval) was done with data on participants who were edentulous and/or had active dental caries and stratified by regions of the world, age and Gross National Income per capita. Limitations in the data arose from several factors such as design of the studies included differences in socioeconomic status and access to health care among different countries.

SOURCES

Embase, MEDLINE via Pubmed and Scopus, manual searches, from January 2016, restricted to English. Experts from different countries were contacted to identify National oral health surveys (NOHS) conducted from 2010 onwards.

STUDY SELECTION

Eighty-six papers and seventeen NOHS were selected for data extraction. Majority of the studies (n = 69) were cross-sectional and of fair quality. 1.1%-70%, 4.9% - 98% prevalence of edentulism and dental caries, respectively. 22%, 45% estimated random-effects pooled prevalence of edentulism and dental caries, respectively.

CONCLUSIONS

Within the limitations of this study, the findings indicate that untreated dental caries and tooth loss are prevalent on a global level with wide variations among different countries, age groups and socioeconomic status.

CLINICAL SIGNIFICANCE

The findings demonstrate the reality of the new cohort of older adults, with higher tooth retention implying more dental caries incidence and the need for different care strategies to ensure better oral health. Large variations and difficulty in making comparisons among different countries highlight the need for more standardized, regular research.

Artificial Intelligence for Caries Detection: Value of Data and Information

If increasing practitioners’ diagnostic accuracy, medical artificial intelligence (AI) may lead to better treatment decisions at lower costs, while uncertainty remains around the resulting cost-effectiveness. In the present study, we assessed how enlarging the data set used for training an AI for caries detection on bitewings affects cost-effectiveness and also determined the value of information by reducing the uncertainty around other input parameters (namely, the costs of AI and the population’s caries risk profile). We employed a convolutional neural network and trained it on 10%, 25%, 50%, or 100% of a labeled data set containing 29,011 teeth without and 19,760 teeth with caries lesions stemming from bitewing radiographs. We employed an established health economic modeling and analytical framework to quantify cost-effectiveness and value of information. We adopted a mixed public–private payer perspective in German health care; the health outcome was tooth retention years. A Markov model, allowing to follow posterior teeth over the lifetime of an initially 12-y-old individual, and Monte Carlo microsimulations were employed. With an increasing amount of data used to train the AI sensitivity and specificity increased nonlinearly, increasing the data set from 10% to 25% had the largest impact on accuracy and, consequently, cost-effectiveness. In the base-case scenario, AI was more effective (tooth retention for a mean [2.5%–97.5%] 62.8 [59.2–65.5] y) and less costly (378 [284–499] euros) than dentists without AI (60.4 [55.8–64.4] y; 419 [270–593] euros), with considerable uncertainty. The economic value of reducing the uncertainty around AI’s accuracy or costs was limited, while information on the population’s risk profile was more relevant. When developing dental AI, informed choices about the data set size may be recommended, and research toward individualized application of AI for caries detection seems warranted to optimize cost-effectiveness.

Emulating Clinical Diagnostic Reasoning for Jaw Cysts with Machine Learning

The detection and classification of cystic lesions of the jaw is of high clinical relevance and represents a topic of interest in medical artificial intelligence research. The human clinical diagnostic reasoning process uses contextual information, including the spatial relation of the detected lesion to other anatomical structures, to establish a preliminary classification. Here, we aimed to emulate clinical diagnostic reasoning step by step by using a combined object detection and image segmentation approach on panoramic radiographs (OPGs). We used a multicenter training dataset of 855 OPGs (all positives) and an evaluation set of 384 OPGs (240 negatives). We further compared our models to an international human control group of ten dental professionals from seven countries. The object detection model achieved an average precision of 0.42 (intersection over union (IoU): 0.50, maximal detections: 100) and an average recall of 0.394 (IoU: 0.50–0.95, maximal detections: 100). The classification model achieved a sensitivity of 0.84 for odontogenic cysts and 0.56 for non-odontogenic cysts as well as a specificity of 0.59 for odontogenic cysts and 0.84 for non-odontogenic cysts (IoU: 0.30). The human control group achieved a sensitivity of 0.70 for odontogenic cysts, 0.44 for non-odontogenic cysts, and 0.56 for OPGs without cysts as well as a specificity of 0.62 for odontogenic cysts, 0.95 for non-odontogenic cysts, and 0.76 for OPGs without cysts. Taken together, our results show that a combined object detection and image segmentation approach is feasible in emulating the human clinical diagnostic reasoning process in classifying cystic lesions of the jaw.

Population-level risks of alcohol consumption by amount, geography, age, sex, and year: a systematic analysis for the Global Burden of Disease Study 2020

BACKGROUND

The health risks associated with moderate alcohol consumption continue to be debated. Small amounts of alcohol might lower the risk of some health outcomes but increase the risk of others, suggesting that the overall risk depends, in part, on background disease rates, which vary by region, age, sex, and year.

METHODS

For this analysis, we constructed burden-weighted dose-response relative risk curves across 22 health outcomes to estimate the theoretical minimum risk exposure level (TMREL) and non-drinker equivalence (NDE), the consumption level at which the health risk is equivalent to that of a non-drinker, using disease rates from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2020 for 21 regions, including 204 countries and territories, by 5-year age group, sex, and year for individuals aged 15-95 years and older from 1990 to 2020. Based on the NDE, we quantified the population consuming harmful amounts of alcohol.

FINDINGS

The burden-weighted relative risk curves for alcohol use varied by region and age. Among individuals aged 15-39 years in 2020, the TMREL varied between 0 (95% uncertainty interval 0-0) and 0·603 (0·400-1·00) standard drinks per day, and the NDE varied between 0·002 (0-0) and 1·75 (0·698-4·30) standard drinks per day. Among individuals aged 40 years and older, the burden-weighted relative risk curve was J-shaped for all regions, with a 2020 TMREL that ranged from 0·114 (0-0·403) to 1·87 (0·500-3·30) standard drinks per day and an NDE that ranged between 0·193 (0-0·900) and 6·94 (3·40-8·30) standard drinks per day. Among individuals consuming harmful amounts of alcohol in 2020, 59·1% (54·3-65·4) were aged 15-39 years and 76·9% (73·0-81·3) were male.

INTERPRETATION

There is strong evidence to support recommendations on alcohol consumption varying by age and location. Stronger interventions, particularly those tailored towards younger individuals, are needed to reduce the substantial global health loss attributable to alcohol.

FUNDING

Bill & Melinda Gates Foundation.

Impact of Laser Therapy on Periodontal and Peri-Implant Diseases

Objective: In the last few decades, lasers in dentistry have encompassed all branches in dentistry, with more focus in periodontology. In recent years, the use of lasers against periodontitis and peri-implantitis has undergone a decisive development that has involved various operational areas. The broadest applications were probably found in the clinical approach to soft tissues. Methods: Laser therapy is a novel technique that may provide further beneficial effects to conventional periodontal and peri-implant therapies. However, clinical evidence for the improvement of periodontal wound healing and tissue regeneration through laser treatment is still limited. Results: This review is aimed at assessing the advantages and disadvantages of the use of lasers in dental procedures and pathologies, focusing more on protocols for the management of periodontal and peri-implant diseases. Conclusions: The adjuvant action of laser therapy, in addition to conventional therapies for the management of periodontal and peri-implant disease, could induce benefits, but further investigation would be necessary to standardize better the protocols applied and to understand the actual tissue response to laser therapy.

Cost-effectiveness of AI for Caries Detection: Randomized Trial

OBJECTIVES

We assessed the cost-effectiveness of AI-supported detection of proximal caries in a randomized controlled clustered cross-over superiority trial.

METHODS

Twenty-three dentists were sampled to assess 20 bitewings; 10 were randomly evaluated supported by an AI-based software (dentalXrai Pro 1.0.4, dentalXrai Ltd, Berlin, Germany) and the other 10 without AI support. The reference test had been established by four independent experts and an additional review. We evaluated the proportion of true and false positive and negative detections and the treatment decisions assigned to each detection (non-invasive, micro-invasive, invasive). Cost-effectiveness was assessed using a mixed public-private-payer perspective in German healthcare. Using the accuracy and treatment decision data from the trial, a Markov simulation model was populated and posterior permanent teeth in initially 31-years old individuals followed over their lifetime. The model allowed extrapolation from the initial detection and therapy to treatment success, re-treatments and, eventually, tooth loss and replacement, capturing long-term effectiveness (tooth retention) and costs (cumulative in Euro). Costs were estimated using the German public and private fee catalogues. Monte-Carlo microsimulations were used and incremental cost-effectiveness at different willingness-to-pay ceiling thresholds assessed.

RESULTS

In the trial, AI-supported detection was significantly more sensitive than detection without AI. However, in the AI group, lesions were more often treated invasively. As a result, AI and no AI showed identical effectiveness (tooth retention for a mean (2.5-97.5%) 49 (48-51)) and nearly identical costs (AI: 330 (250-409) Euro, no AI: 330 (248-410) Euro). 41% simulations found AI and 43% no AI to be more cost-effective. The resulting cost-effectiveness remained uncertain regardless of a payer's willingness-to-pay.

CONCLUSIONS

Higher accuracy of AI did not lead to higher cost-effectiveness, as more invasive treatment approaches generated costs and diminished possible effectiveness advantages.

CLINICAL SIGNIFICANCE

The cost-effectiveness of AI could be improved by supporting not only caries detection, but also subsequent management.

The global burden of adolescent and young adult cancer in 2019: a systematic analysis for the Global Burden of Disease Study 2019

BACKGROUND

In estimating the global burden of cancer, adolescents and young adults with cancer are often overlooked, despite being a distinct subgroup with unique epidemiology, clinical care needs, and societal impact. Comprehensive estimates of the global cancer burden in adolescents and young adults (aged 15-39 years) are lacking. To address this gap, we analysed results from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2019, with a focus on the outcome of disability-adjusted life-years (DALYs), to inform global cancer control measures in adolescents and young adults.

METHODS

Using the GBD 2019 methodology, international mortality data were collected from vital registration systems, verbal autopsies, and population-based cancer registry inputs modelled with mortality-to-incidence ratios (MIRs). Incidence was computed with mortality estimates and corresponding MIRs. Prevalence estimates were calculated using modelled survival and multiplied by disability weights to obtain years lived with disability (YLDs). Years of life lost (YLLs) were calculated as age-specific cancer deaths multiplied by the standard life expectancy at the age of death. The main outcome was DALYs (the sum of YLLs and YLDs). Estimates were presented globally and by Socio-demographic Index (SDI) quintiles (countries ranked and divided into five equal SDI groups), and all estimates were presented with corresponding 95% uncertainty intervals (UIs). For this analysis, we used the age range of 15-39 years to define adolescents and young adults.

FINDINGS

There were 1·19 million (95% UI 1·11-1·28) incident cancer cases and 396 000 (370 000-425 000) deaths due to cancer among people aged 15-39 years worldwide in 2019. The highest age-standardised incidence rates occurred in high SDI (59·6 [54·5-65·7] per 100 000 person-years) and high-middle SDI countries (53·2 [48·8-57·9] per 100 000 person-years), while the highest age-standardised mortality rates were in low-middle SDI (14·2 [12·9-15·6] per 100 000 person-years) and middle SDI (13·6 [12·6-14·8] per 100 000 person-years) countries. In 2019, adolescent and young adult cancers contributed 23·5 million (21·9-25·2) DALYs to the global burden of disease, of which 2·7% (1·9-3·6) came from YLDs and 97·3% (96·4-98·1) from YLLs. Cancer was the fourth leading cause of death and tenth leading cause of DALYs in adolescents and young adults globally.

INTERPRETATION

Adolescent and young adult cancers contributed substantially to the overall adolescent and young adult disease burden globally in 2019. These results provide new insights into the distribution and magnitude of the adolescent and young adult cancer burden around the world. With notable differences observed across SDI settings, these estimates can inform global and country-level cancer control efforts.

FUNDING

Bill & Melinda Gates Foundation, American Lebanese Syrian Associated Charities, St Baldrick's Foundation, and the National Cancer Institute.

A randomized controlled trial for evaluation of bone density changes around immediate functionally and nonfunctionally loaded implants using three-dimensional cone-beam computed tomography

Aim

The aim of this study was to compare and assess bone density changes around immediate functionally and nonfunctionally loaded implants.

Settings and design

In vivo comparative study.

Materials and Methods

Sixty participants selected based on the predetermined inclusion and exclusion criteria received single tooth implants in mandible under two implant loading protocols: Immediate functionally loaded (IFL) and immediate nonfunctionally loaded (INFL). Randomization was done by computer-aided simple randomization procedure. Self-tapering, aggressive SLA implants were placed in the single tooth edentulous sites of mandible in both the groups. Three-dimensional cone-beam computed tomography (3D CBCT) was taken at baseline, 3 and 6 months postimplant placement. Quantitative analysis of the bone density was performed using 3D CBCT in three areas around the implants at crestal, middle, and apical regions of implants.

Statistical Analysis Used

Quantitative data were summarized as mean ± standard deviation. Statistical analyses were performed using the SPSS software version 21.0 (SPSS Inc., Chicago, IL, USA) by unpaired t-test.

Results

Bone density changes after implant placement in IFL group from baseline to 3 months were; crestal region (314.18 ± 71.69), middle (278.23 ± 70.17), apical (274.70 ± 59.79) and changes from 3 to 6 months were; crestal (-105.55 ± 39.60), middle (-114.80 ± 41.46), apical (-141.88 ± 69.58). Bone density changes after implant placement in INFL group from baseline to 3 months were crestal region (199.42 ± 47.97), middle (56.91 ± 10.39), apical (200.98 ± 67.43) and changes from 3 to 6 months were; crestal (-194.38 ± 75.30), middle (-204.40 ± 63.75), apical (-191.28 ± 62.33).

Conclusions

It was concluded that INFL implant group showed better bone density when compared to IFL implant group.

Effectiveness of mouthwash against viruses: 2020 perspective. A systematic review

INTRODUCTION

Antiseptic mouthwash is widely recommended to treat various oral diseases as well as to improve oral health. Most of the dental procedures lead to the generation of aerosols. These aerosols have a high potential to transmit disease. Preprocedural oral rinse with antimicrobial agents in the form of mouthwashes reduces the bacterial and viral load many folds. The purpose of this review was to summarize the effectiveness of mouthwash against viruses affecting human beings.

EVIDENCE ACQUISITION

Search engines like PubMed, Google Scholar, and others were used to search the electronic database. Articles were identified in which the effectiveness of antiseptic mouth rinse against the virus was tested. A comprehensive search strategy was designed to select the articles and then independently screened for eligibility.

EVIDENCE SYNTHESIS

A total of 9624 articles out of the 13 titles met the eligibility criteria. The selected papers were included in the present manuscript according to their relevance to the topic. Authors searched the most used chemicals as mouthwashes but records of three types of mouthwash tested against various types of viruses i.e. chlorhexidine gluconate, Povidone-iodine and essential oil containing mouthwash (Listerine) were found.

CONCLUSIONS

Povidone-iodine mouth rinse is effective in reducing viral load either in-vitro or in-vivo conditions. Chlorhexidine gluconate mouthwash and essential oils have shown its effectiveness in a few studies. Insufficient evidence is available to support the claim that oral antiseptics can reduce the risk of developing viral loads in humans or the rate of progression of diseases caused by viruses.

Oral cancer diagnostics: An overview

Cancer was first mentioned in medicine texts by Egyptians. Ancient Indians studied oral cancer in great detail under Susruta. Cancer has continued to be a challenge to physicians from ancient times to the present. Over the years, cancer underwent a shift in management from radical surgeries toward a more preventive approach. Early diagnosis is vital in reducing cancer-associated mortality especially with oral cancer. Even though the mainstay of oral cancer diagnosis still continues to be a trained clinician and histopathologic examination of malignant tissues. Translating innovation in technological advancements in diagnostic aids for oral cancer will require both improved decision-making and a commitment toward optimizing cost, skills, turnover time between capturing data and obtaining a useful result. The present review describes the conventional to most advanced diagnostic modalities used as oral cancer diagnostics. It also includes the new technologies available and the future trends in oral cancer diagnostics.

Gabapentin for cessation of smoking and non-smoking tobacco habits in Indian population

BACKGROUND

The effectiveness of gabapentin in tobacco dependence has been evaluated by many researchers. The randomized control trials, testing the efficacy of gabapentin in quitting the habit in smokers and users of smokeless tobacco, have not been published yet. We attempted to address this lacuna in knowledge in reducing dependence on tobacco use by gabapentin.

METHODS

Our study involves 150 study subjects, 75 of whom were identified as chronic users of tobacco and assigned randomly to one of the three groups consisting of 25 subjects each. Gabapentin in tablet form was prescribed thrice a day for 8 weeks wherein group 1 received a dose of 300mg, group 2 received 600 mg, and group 3 was prescribed 900 mg. An age and sex matched control group have received calcium tablets as placebo in three times daily dose for a period of 8 weeks.

RESULTS

Among the three doses of gabapentin, stoppage of habit was reported to be highest in the group-2 followed by group 1 and group 3 respectively. In our study, we found differences in response to quitting tobacco use between duration of habit prior to pharmacologic intervention amongst both smokers and the users of smokeless tobacco.

CONCLUSIONS

Gabapentin at dose of 600 mg TDS has optimum effect. Smokers having smoking for more than ten years showed notable benefit with gabapentin. Among smokeless tobacco users who quit tobacco dependence was better having history of habit less than 2 years.

Classification of Dental Radiographs Using Deep Learning

OBJECTIVES

To retrospectively assess radiographic data and to prospectively classify radiographs (namely, panoramic, bitewing, periapical, and cephalometric images), we compared three deep learning architectures for their classification performance.

METHODS

Our dataset consisted of 31,288 panoramic, 43,598 periapical, 14,326 bitewing, and 1176 cephalometric radiographs from two centers (Berlin/Germany; Lucknow/India). For a subset of images L (32,381 images), image classifications were available and manually validated by an expert. The remaining subset of images U was iteratively annotated using active learning, with ResNet-34 being trained on L, least confidence informative sampling being performed on U, and the most uncertain image classifications from U being reviewed by a human expert and iteratively used for re-training. We then employed a baseline convolutional neural networks (CNN), a residual network (another ResNet-34, pretrained on ImageNet), and a capsule network (CapsNet) for classification. Early stopping was used to prevent overfitting. Evaluation of the model performances followed stratified k-fold cross-validation. Gradient-weighted Class Activation Mapping (Grad-CAM) was used to provide visualizations of the weighted activations maps.

RESULTS

All three models showed high accuracy (>98%) with significantly higher accuracy, F1-score, precision, and sensitivity of ResNet than baseline CNN and CapsNet (p < 0.05). Specificity was not significantly different. ResNet achieved the best performance at small variance and fastest convergence. Misclassification was most common between bitewings and periapicals. For bitewings, model activation was most notable in the inter-arch space for periapicals interdentally, for panoramics on bony structures of maxilla and mandible, and for cephalometrics on the viscerocranium.

CONCLUSIONS

Regardless of the models, high classification accuracies were achieved. Image features considered for classification were consistent with expert reasoning.

Generalizability of deep learning models for dental image analysis

We assessed the generalizability of deep learning models and how to improve it. Our exemplary use-case was the detection of apical lesions on panoramic radiographs. We employed two datasets of panoramic radiographs from two centers, one in Germany (Charité, Berlin, n = 650) and one in India (KGMU, Lucknow, n = 650): First, U-Net type models were trained on images from Charité (n = 500) and assessed on test sets from Charité and KGMU (each n = 150). Second, the relevance of image characteristics was explored using pixel-value transformations, aligning the image characteristics in the datasets. Third, cross-center training effects on generalizability were evaluated by stepwise replacing Charite with KGMU images. Last, we assessed the impact of the dental status (presence of root-canal fillings or restorations). Models trained only on Charité images showed a (mean ± SD) F1-score of 54.1 ± 0.8% on Charité and 32.7 ± 0.8% on KGMU data (p < 0.001/t-test). Alignment of image data characteristics between the centers did not improve generalizability. However, by gradually increasing the fraction of KGMU images in the training set (from 0 to 100%) the F1-score on KGMU images improved (46.1 ± 0.9%) at a moderate decrease on Charité images (50.9 ± 0.9%, p < 0.01). Model performance was good on KGMU images showing root-canal fillings and/or restorations, but much lower on KGMU images without root-canal fillings and/or restorations. Our deep learning models were not generalizable across centers. Cross-center training improved generalizability. Noteworthy, the dental status, but not image characteristics were relevant. Understanding the reasons behind limits in generalizability helps to mitigate generalizability problems.

Artificial intelligence in dental research: Checklist for authors, reviewers, readers

OBJECTIVES

The number of studies employing artificial intelligence (AI), specifically machine and deep learning, is growing fast. The majority of studies suffer from limitations in planning, conduct and reporting, resulting in low robustness, reproducibility and applicability. We here present a consented checklist on planning, conducting and reporting of AI studies for authors, reviewers and readers in dental research.

METHODS

Lending from existing reviews, standards and other guidance documents, an initial draft of the checklist and an explanatory document were derived and discussed among the members of IADR's e-oral network and the ITU/WHO focus group "Artificial Intelligence for Health (AI4H)". The checklist was consented by 27 group members via an e-Delphi process.

RESULTS

Thirty-one items on planning, conducting and reporting of AI studies were agreed on. These involve items on the studies' wider goal, focus, design and specific aims, data sampling and reporting, sample estimation, reference test construction, model parameters, training and evaluation, uncertainty and explainability, performance metrics and data partitions.

CONCLUSION

Authors, reviewers and readers should consider this checklist when planning, conducting, reporting and evaluating studies on AI in dentistry.

CLINICAL SIGNIFICANCE

Current studies on AI in dentistry show considerable weaknesses, hampering their replication and application. This checklist may help to overcome this issue and advance AI research as well as facilitate a debate on standards in this fields.

Clinical outcomes of flap versus flapless immediately loaded single dental implants in the mandibular posterior region: One-year follow-up results from a randomized controlled trial

STATEMENT OF PROBLEM

Flapless implant placement with immediate functional loading has been reported in anterior locations. However, data on posterior locations are lacking.

PURPOSE

The purpose of this randomized controlled trial was to determine and compare clinical outcomes of flap versus flapless surgically placed single posterior mandibular dental implants subjected to immediate functional loading.

MATERIAL AND METHODS

Participants with missing mandibular first molar teeth were recruited and randomized into 2 groups (n=51): flapped and flapless. Dental implants were surgically placed and loaded immediately with interim restorations following implant protective occlusion. Outcome measures were implant failure, crestal bone loss, and periodontal parameters: modified plaque index, modified sulcus bleeding index, and pocket depths. Outcome data were recorded at baseline, 6-month, and 12-month follow-up visits. Cone beam computed tomography scans were used to calculate crestal bone loss, and periodontal outcomes were recorded by using a resin covered periodontal probe (α=.05).

RESULTS

After 12 months, similar implant failure rates (P>.05) were found between the groups. Crestal bone loss in the flapped group was statistically higher than in the flapless group at 6 months (0.83 ±0.21 mm versus 0.75 ±0.23 mm) and at 12 months (1.04 ±0.27 mm versus 0.90 ±0.24 mm) from the baseline. The modified plaque index, modified sulcus bleeding index, and peri-implant probing depths (PDs) in both groups increased from the baseline to 6-month follow-ups (Baseline modified plaque index: 0.82 ±0.54 versus 0.79 ±0.21; Baseline modified sulcus bleeding index: 0.74 ±0.21 versus 0.70 ±0.43; Baseline PD: 1.25 ±0.37 mm versus 1.20 ±0.22 mm; 6 months modified plaque index: 1.54 ±0.70 versus 1.21 ±0.45; 6 months modified sulcus bleeding index: 1.93 ±0.54 versus 1.51 ±0.61; 6 months PD: 3.20 ±0.73 mm versus 2.80 ±0.43 mm). At 12-month follow-ups after repeated oral hygiene reinforcements, periodontal parameters had improved (decreased) significantly.

CONCLUSIONS

Flapless implant insertion with immediate functional loading could be considered as an appropriate treatment option for providing functional restorations on the day of implant placement with minimal surgical intervention, reducing crestal bone loss, and periodontal complications.

Cost-effectiveness of Artificial Intelligence for Proximal Caries Detection

Artificial intelligence (AI) can assist dentists in image assessment, for example, caries detection. The wider health and cost impact of employing AI for dental diagnostics has not yet been evaluated. We compared the cost-effectiveness of proximal caries detection on bitewing radiographs with versus without AI. U-Net, a fully convolutional neural network, had been trained, validated, and tested on 3,293, 252, and 141 bitewing radiographs, respectively, on which 4 experienced dentists had marked carious lesions (reference test). Lesions were stratified for initial lesions (E1/E2/D1, presumed noncavitated, receiving caries infiltration if detected) and advanced lesions (D2/D3, presumed cavitated, receiving restorative care if detected). A Markov model was used to simulate the consequences of true- and false-positive and true- and false-negative detections, as well as the subsequent decisions over the lifetime of patients. A German mixed-payers perspective was adopted. Our health outcome was tooth retention years. Costs were measured in 2020 euro. Monte-Carlo microsimulations and univariate and probabilistic sensitivity analyses were conducted. The incremental cost-effectiveness ratio (ICER) and the cost-effectiveness acceptability at different willingness-to-pay thresholds were quantified. AI showed an accuracy of 0.80; dentists’ mean accuracy was significantly lower at 0.71 (minimum–maximum: 0.61–0.78, P < 0.05). AI was significantly more sensitive than dentists (0.75 vs. 0.36 [0.19–0.65]; P = 0.006), while its specificity was not significantly lower (0.83 vs. 0.91 [0.69–0.98]; P > 0.05). In the base-case scenario, AI was more effective (tooth retention for a mean 64 [2.5%–97.5%: 61–65] y) and less costly (298 [244–367] euro) than assessment without AI (62 [59–64] y; 322 [257–394] euro). The ICER was −13.9 euro/y (i.e., AI saved money at higher effectiveness). In the majority (>77%) of all cases, AI was less costly and more effective. Applying AI for caries detection is likely to be cost-effective, mainly as fewer lesions remain undetected. Notably, this cost-effectiveness requires dentists to manage detected early lesions nonrestoratively.

Gabapentin for cessation of smoking and non-smoking tobacco habits in Indian population

BACKGROUND

The effectiveness of gabapentin in tobacco dependence has been evaluated by many researchers. The randomized control trials, testing the efficacy of gabapentin in quitting the habit in smokers and users of smokeless tobacco, have not been published yet. We attempted to address this lacuna in knowledge in reducing dependence on tobacco use by gabapentin.

METHODS

Our study involves 150 study subjects, 75 of whom were identified as chronic users of tobacco and assigned randomly to one of the three groups consisting of 25 subjects each. Gabapentin in tablet form was prescribed thrice a day for 8 weeks wherein group 1 received a dose of 300mg, group 2 received 600 mg, and group 3 was prescribed 900 mg. An age and sex matched control group have received calcium tablets as placebo in three times daily dose for a period of 8 weeks.

RESULTS

Among the three doses of gabapentin, stoppage of habit was reported to be highest in the group-2 followed by group 1 and group 3 respectively. In our study, we found differences in response to quitting tobacco use between duration of habit prior to pharmacologic intervention amongst both smokers and the users of smokeless tobacco.

CONCLUSIONS

Gabapentin at dose of 600 mg TDS has optimum effect. Smokers having smoking for more than ten years showed notable benefit with gabapentin. Among smokeless tobacco users who quit tobacco dependence was better having history of habit less than 2 years.

Temporomandibular disorders in North Indian population visiting a tertiary care dental hospital

Background:

The terminology “temporomandibular disorders” (TMDs) encompasses a wide spectrum of conditions. Several hypothesized causes are occlusal disharmony, muscle hyperactivity, central pain mechanisms, psychological distress, and trauma. In day-to-day practice, TMDs had become more prevalent in Indian population due to changed dietary pattern and food habits, excessive stress of modern life, and other environmental causes. This study is an attempt to find the prevalence of TMDs in North Indian population.

Aims:

The present study is taken into account to determine the prevalence of TMDs on the basis of signs and symptoms based on the Research Diagnostic Criteria for Temporomandibular Disorders (RDC/TMD).

Materials and Methods:

The present cross-sectional study was conducted in the Department of Oral Medicine and Radiology. A total of 1009 patients aged between 6 and 80 years with a mean age of 42.04 ± 16.8 years seeking dental treatment from January 2016 to June 2017 were included in the study. All the patients were screened for TMD sign and symptoms. The demographic data and the signs and symptoms of TMDs were recorded in designed structured questionnaires which were based on the RDC/TMD criteria.

Results:

The study population consisted of 1009 patients aged between 6 and 80 years. In the present study population, based on RDC/TMD criteria, the incidence of clicking sound (42.5%) was highest in TMD joint followed by deviation of mandible on mouth opening (40.8%), internal derangement (36.8%), myofacial pain dysfunction syndrome (33.7%), osteoarthritis (29.5%), crepitus (25.8%), joint tenderness (5.8%), and pain on mouth opening (4.8%).

Conclusion:

Clicking sound was the most common sign of TMD disorders in Indian population.

Prevalence of trigeminal neuralgia in Indian population visiting a higher dental care center in North India

Objectives:

The present study aims to determine the incidence and prevalence of trigeminal neuralgia (TN) in study population and difference in prevalence of TN in urban and rural population.

Materials and Methods:

This retrospective study includes 1215 study participants with typical idiopathic TN. Data regarding the age of onset, gender, site of involvement, and clinical presentations were retrieved from clinical records of patients reported from January 2011 to January 2018.

Results:

The study population consists of 1215 study participants aged between 21 and 87 years, with a mean age of 50.62 ± 15.872 years. The mandibular nerve is involved in most of the cases (56.9%), followed by maxillary nerve (42%). The right side of the face (57.1%) is more involved than the left side (38.8%). TN was more prevalent (52.4%) in rural population than urban population (47.6%).

Conclusion:

TN is more common in females than males, the right side of the face is more involved than the left side, and it is more commonly found in rural population than urban population.