Objective: The aim of this study was to review the selection criteria of resin cements for different types of partial coverage restorations (PCRs) and investigate if the type of restorations or restorative materials affect the type of selected resin cement.Materials and Methods: An electronic search (1991–2023) was performed in PubMed, Medline, Scopus, and Google Scholar databases by combinations of related keywords.Results: A total of 68 articles were included to review the selection criteria based on the advantages, disadvantages, indications, and performance of resin cements for different types of PCRs.Conclusions: The survival and success of PCRs are largely affected by appropriate cement selection. Self‐curing and dual‐curing resin cements have been recommended for the cementation of metallic PCRs. The PCRs fabricated from thin, translucent, and low‐strength ceramics could be adhesively bonded by light‐cure conventional resin cements. Self‐etching and self‐adhesive cements, especially dual‐cure types, are not generally indicated for laminate veneers.

Proper cement selection in fixed prosthesis plays a determinative role in providing long-term serviceability, retention, caries prevention, and patient satisfaction. This study, reviews different luting agent characteristics and their application based on different clinical situations and different types of full coverage restorations. An electronic search was conducted through PubMed, Medline, and Google scholar using following keywords or combinations: restoration, full coverage, PFM, porcelain fused to metal, all ceramic, zirconia, ceramic, casting, fixed partial denture, cement*, dental cement, cement selection, and retention. The most related articles were selected for review. Choosing a proper luting agent is highly dependent on scientific knowledge regarding the characteristics of restorative materials and luting agents. Conventional cements could be indicated in various situations; however, some restorative materials or clinical situations call for resin-cements to provide predictable retention, support, and durability. Conscious selection of retentive cement for each type of restoration/material is necessary to provide predictable successful treatment and reduce the potential complications. Key words:Adhesive cement, dental bridgework, dental cements, dental crowns, dental porcelain, prostheses and implants.

The objective of this systematic review was to systematically collect and analyze multiple published systematic reviews to address the following research question “Are artificial intelligence (AI) algorithms effective for the detection of dental caries?”. A systematic search of five electronic databases, including the Cochrane Library, Embase, PubMed, Scopus, and Web of Science, was conducted until October 15, 2024, with a language restriction to English. All fourteen systematic reviews which assessed the performance of AI algorithms for the detection of dental caries were included. From 137 primary original research studies within the systematic reviews, only 20 reported the data necessary for inclusion in the meta-analysis. Pooled sensitivity was 0.85 (95% Confidence Interval (CI): 0.83 to 0.93), specificity was 0.90 (95% CI: 0.85 to 0.95), and log diagnostic odds ratio was 4.37 (95% CI: 3.16 to 6.27). Area under the summary ROC curve was 0.86. Positive post-test probability was 79% and negative post-test probability was 6%. In conclusion, this meta-analysis has revealed that caries diagnosis using AI is accurate and its use in clinical practice is justified. Future studies should focus on specific subpopulations, depth of caries, and real-world performance validation to further improve the accuracy of AI in caries diagnosis.

Carotid artery calcifications are important markers of cardiovascular health, often associated with atherosclerosis and a higher risk of stroke. Recent research shows that dental radiographs can help identify these calcifications, allowing for earlier detection of vascular diseases. Advances in artificial intelligence (AI) have improved the ability to detect carotid calcifications in dental images, making it a useful screening tool. This systematic review and meta-analysis aimed to evaluate how accurately AI methods can identify carotid calcifications in dental radiographs. A systematic search in databases including PubMed, Scopus, Embase, and Web of Science for studies on AI algorithms used to detect carotid calcifications in dental radiographs was conducted. Two independent reviewers collected data on study aims, imaging techniques, and statistical measures such as sensitivity and specificity. A meta-analysis using random effects was performed, and the risk of bias was evaluated with the QUADAS-2 tool. Nine studies were suitable for qualitative analysis, while five provided data for quantitative analysis. These studies assessed AI algorithms using cone beam computed tomography (n = 3) and panoramic radiographs (n = 6). The sensitivity of the included studies ranged from 0.67 to 0.98 and specificity varied between 0.85 and 0.99. The overall effect size, by considering only one AI method in each study, resulted in a sensitivity of 0.92 [95% CI 0.81 to 0.97] and a specificity of 0.96 [95% CI 0.92 to 0.97]. The high sensitivity and specificity indicate that AI methods could be effective screening tools, enhancing the early detection of stroke and related cardiovascular risks. Not applicable.

Objective: To systematically compare the bond strength of denture teeth and reline materials to additively manufactured (AM) versus subtractively milled (SM) denture base resins and to identify the material‐ and process‐related factors influencing bonding performance.Materials and Methods: A systematic electronic search of PubMed, Scopus, Embase, Web of Science, the Cochrane Library, and Google Scholar was conducted up to December 10, 2024. Eligible in vitro studies comparing bond strength at either the tooth–base or reline–base interface using AM and SM denture bases were included. Studies that lacked direct comparison, involved conventional heat‐polymerized bases, or did not report quantitative bond strength data were excluded. Meta‐analyses were performed using random‐effects models, calculating mean differences (MD) for tooth bonding and standardized mean differences (SMD) for reline bonding. Subgroup, sensitivity, and publication bias analyses (Egger's regression and Begg's rank tests) were included. Risk of bias was evaluated using QUIN tools.Results: Out of 2985 screened records, 20 studies comprising 156 independent comparisons were included; 41 for tooth bonding and 115 for reline bonding. Initial tooth‐bonding meta‐analysis revealed no significant difference; however, after exclusion of two outlier comparisons identified through sensitivity analysis (n = 39), milled bases demonstrated significantly higher bond strength (MD = −2.43 MPa, 95% CI–3.90 to −0.96; p = 0.001). For reline bonding, AM bases consistently underperformed across all studies, with the pooled estimate favoring milled bases (SMD = −2.62, 95% CI–3.22 to −2.03; p = 0.001).Conclusion: Within the limitations of this review, milled denture bases demonstrate consistently stronger and more reliable bonding to both teeth and reline materials than current printable photopolymer bases.