Silver diamine fluoride (SDF) is used in minimally invasive dentistry for arresting dental caries. However, discoloration of teeth is a significant side effect that has limited the use of SDF. Hence, ...the application of potassium iodide (KI) following SDF has been proposed to ameliorate the staining. Although antimicrobial activity is one of the major mechanisms of the caries-arresting effect of SDF, the antimicrobial potency of SDF/KI combination is unclear. Thus, the primary objective of this systematic review was to appraise the studies on the antimicrobial efficacy of SDF/KI combination on cariogenic microbes. The secondary objective was to summarize the evidence on the potential of KI in reducing the discoloration associated with the application of SDF. Electronic databases of Medline via PubMed, Cochrane Library, Web of Science, and EBSCO host were searched for English language manuscripts from January 2005 to 15th November 2020. The reference lists of these manuscripts were manually searched for additional studies. Twelve studies were included in the final analysis, seven of which have investigated the antimicrobial efficacy of SDF/KI, and the rest have examined the anti-staining potential of KI. The exploratory findings from the reviewed articles revealed the promising antimicrobial potential of SDF/KI on cariogenic microbes associated with dentine caries. There is, however, contradictory evidence on the effect of SDF/KI on tooth color. The reviewed in-vitro studies indicated significant effectiveness of KI in preventing staining. A clinical trial on primary dentition showed 25% reduction in the incidence of staining by SDF after applying KI, while a clinical study on root caries in adults showed no significant effect. Within the methodological limitations of this review, we conclude that for arresting dental caries, SDF could be combined with KI, as there may be a lower likelihood of staining. Further, well-designed clinical trials on the antimicrobial and anti-staining effect of SDF/KI are needed to obtain more robust evidence.
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DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Deep learning (DL) has been employed for a wide range of tasks in dentistry. We aimed to systematically review studies employing DL for periodontal and implantological purposes. A systematic ...electronic search was conducted on four databases (Medline via PubMed, Google Scholar, Scopus, and Embase) and a repository (ArXiv) for publications after 2010, without any limitation on language. In the present review, we included studies that reported deep learning models' performance on periodontal or oral implantological tasks. Given the heterogeneities in the included studies, no meta‐analysis was performed. The risk of bias was assessed using the QUADAS‐2 tool. We included 47 studies: focusing on imaging data (n = 20) and non‐imaging data in periodontology (n = 12), or dental implantology (n = 15). The detection of periodontitis and gingivitis or periodontal bone loss, the classification of dental implant systems, or the prediction of treatment outcomes in periodontology and implantology were major use cases. The performance of the models was generally high. However, it varied given the employed methods (which includes various types of convolutional neural networks (CNN) and multi‐layered perceptron (MLP)), the variety in specific modeling tasks, as well as the chosen and reported outcomes, outcome measures and outcome level. Only a few studies (n = 7) showed a low risk of bias across all assessed domains. A growing number of studies evaluated DL for periodontal or implantological objectives. Heterogeneity in study design, poor reporting and a high risk of bias severely limit the comparability of studies and the robustness of the overall evidence.
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CMK, FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SBCE, SBMB, UL, UM, UPUK
The accuracy of cephalometric landmark identification for malocclusion classification is essential for diagnosis and treatment planning. Identifying these landmarks is often complex and ...time-consuming for orthodontists. An AI model for classification was recently developed. This model was investigated based on current regulatory considerations as a result of the strict regulations on software systems and the lack of information on artificial intelligence (AI) requirements in this publication. The platform developed by the ITU/WHO for AI is used to assess the models of the application. The auditing procedure assessed the development process concerning medical device regulations, data protection regulations, and ethical considerations. Upon that, the major tasks during the development were evaluated, such as qualification, annotation procedure, and data set attributes. The AI models were investigated under consideration of technical, clinical, regulatory, and ethical considerations. The risk to the patient and user’s health can be considered low according to the International Medical Device Regulators Forum (IMDRF) definition. This application facilitates the decision and planning of malocclusion treatment based on lateral cephalograms without cephalometric landmarks. It is comparable with common standards in orthodontic diagnosis.
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EMUNI, FIS, FZAB, GEOZS, GIS, IJS, IMTLJ, KILJ, KISLJ, MFDPS, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, SBMB, SBNM, UKNU, UL, UM, UPUK, VKSCE, ZAGLJ
The coronavirus disease 2019 (COVID-19) due to the severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) can present either as an asymptomatic carrier state or an acute respiratory disease, ...with or without severe pneumonia. The asymptomatic carriers are a challenge for the dental profession as the infection could be transmitted via virus-laden, and saliva in dental settings through aerosol-generating procedures (AGPSs). The aim of this review was to perform a systematic review of SARS-CoV-2 in the saliva of asymptomatic individuals.
PubMed, Google scholar, and MedRxiv databases were searched between and a systematic review and meta-analysis of the available data were performed to assess the viral burden in the saliva of asymptomatic carriers of SARS-CoV-2. All investigators of the included studies used qRT-PCR to detect SARS-CoV-2 and yield quantitative data (the Ct values) appertaining to the viral load.
A total of 322 records in the English literature were identified, and eight studies with 2642 SARS-CoV-2-positive and asymptomatic individuals were included in the final analysis. Of these, 16.7% (95% CI: 11-23%) yielded SARS-CoV-2-positive saliva samples in comparison to 13.1% (95% CI: 12-17%) of the respiratory specimens (nasopharyngeal or nose-throat swabs).
As approximately 1 in 5 to 1 in 10 asymptomatic individuals harbour SARS-CoV-2 in either saliva or respiratory secretions, our results highlight the need for continued vigilance and the critical importance of maintaining strict, additional infection control regimens for the foreseeable future to mitigate the potential risks of COVID-19 transmission in dentistry.
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