Background: COVID-19 disease first appeared in 2019 and quickly spread worldwide, causing a global pandemic. The oral cavity represents a target of SARS-CoV-2, and oral lesions are observed in both non-hospitalized and hospitalized patients. This systematic review aims to investigate the frequency of oral manifestations in COVID-19 hospitalized patients. Methods: An electronic search was conducted in PubMed, Scopus, and Web of Science databases, including articles published up to September 2021. The review protocol was based on PRISMA-P. The risk of bias of the studies was assessed using the Joana Briggs Institute. The certainty of evidence was assessed using the GRADE instrument. Results: Fifty-nine articles were included: 19 case reports, 17 case series, 2 case-control studies, 13 cross-sectional studies, 4 observational studies, and 4 retrospective studies. Oral ulcers, cheilitis, and tongue lesions were more common in patients before hospitalization, while perioral pressure ulcers, macroglossia, blisters, and oral candidiasis were more recurrent in patients during hospitalization. The first could be related directly to COVID-19, while the latter could be caused by medical devices, treatments, prone position, and immunological impairment. Conclusions: An accurate oral examination during the hospital admission of all confirmed COVID-19 cases is encouraged to recognize oral early manifestations and to apply appropriate treatments.
This study aimed to compare two different bulk-filling techniques, evaluating the internal and external adaptation of class II resin-composite restorations, by analysing the gap formation using microcomputed tomography (µ-CT) and scanning electronic microscopy (SEM) coupled with energy-dispersive X-ray spectroscopy (EDS). Two standardized mesio/disto-occlusal (MO/DO) cavities were prepared in eight extracted human third molars that were divided, according to the filling technique used, in the following two groups (n = 4): BG (Bulk&Go group) and BT (Bulk Traditional group). After universal bonding application, followed by the light curing, all teeth were restored using a bulk-fill composite. Specimens were scanned with µ-CT to evaluate 3D interfacial gaps. Acquired µ-CT data were analysed to quantify the gap formation. Complementary information to the µ-CT analysis were obtained by SEM. Thereafter, the chemical composition of tooth–restoration interface was analysed using EDS. The µ-CT analysis revealed gaps formation at the tooth–restoration interface for both the BG and BT groups, while within the restoration, only in the BT group there was evidence of microleakage formation. The scanning electron micrographs of both groups showed that the external marginal integrity of the restoration was preserved, while EDS showed the three different structures (tooth surface, adhesive layer and resin composite) of the tooth–restoration interface, highlighting the absence of gap formation. In both BG and BT, the two filling techniques did not show significant differences regarding the internal and external marginal adaptation of the restoration. To achieve a successful restoration, the clinician could be advised to restore a class II cavity using a single increment bulk-filling technique (BG), thus treating it as a class I cavity.
The recent advancements in digital technologies have led to exponential progress in dentistry. This narrative review aims to summarize the applications of Augmented Reality, Virtual Reality and Mixed Reality in dentistry and describes future challenges in digitalization, such as Artificial Intelligence and Robotics. Augmented Reality, Virtual Reality and Mixed Reality represent effective tools in the educational technology, as they can enhance students’ learning and clinical training. Augmented Reality and Virtual Reality and can also be useful aids during clinical practice. Augmented Reality can be used to add digital data to real life clinical data. Clinicians can apply Virtual Reality for a digital wax-up that provides a pre-visualization of the final post treatment result. In addition, both these technologies may also be employed to eradicate dental phobia in patients and further enhance patient’s education. Similarly, they can be used to enhance communication between the dentist, patient, and technician. Artificial Intelligence and Robotics can also improve clinical practice. Artificial Intelligence is currently developed to improve dental diagnosis and provide more precise prognoses of dental diseases, whereas Robotics may be used to assist in daily practice.
Dental remineralization represents the process of depositing calcium and phosphate ions into crystal voids in demineralized enamel, producing net mineral gain and preventing early enamel lesions progression. The aim of the present study was to qualitatively and quantitatively compare the remineralizing effectiveness of four commercially available agents on enamel artificial lesions using Scanning Electron Microscopy (SEM) combined with Energy Dispersive Spectroscopy (EDS) techniques. Thirty-six extracted third molars were collected and randomly assigned to six groups (n = 6), five of which were suspended in demineralizing solution for 72 h to create enamel artificial lesions, and one serving as control: G1, treated with a mousse of casein phosphopeptide and amorphous calcium–phosphate (CPP-ACP); G2, treated with a gel containing nano-hydroxyapatite; G3, treated with a 5% SF varnish; G4, treated with a toothpaste containing ACP functionalized with fluoride and carbonate-coated with citrate; G5, not-treated artificial enamel lesions; G6, not demineralized and not treated sound enamel. G1–G4 were subjected to pH cycling over a period of seven days. Analyses of the specimens’ enamel surfaces morphology were performed by SEM and EDS. Data were statistically analyzed for multiple group comparison by one-way ANOVA/Tukey’s test (p < 0.05). The results show that the Ca/P ratio of the G5 (2.00 ± 0.07) was statistically different (p < 0.05) from G1 (1.73 ± 0.05), G2 (1.76 ± 0.01), G3 (1.88 ± 0.06) and G6 (1.74 ± 0.04), while there were no differences (p > 0.05) between G1, G2 and G6 and between G4 (2.01 ± 0.06) and G5. We concluded that G1 and G2 showed better surface remineralization than G3 and G4, after 7 days of treatment.
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