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Purpose: To assess possible correlations between clinical outcomes and SEM marginal analysis in a prospective long-term clinical study using two adhesives in incisors and canines.
Materials And Methods: Thirty-five patients received class III and IV restorations with two different adhesives, either the one-step self-etch adhesive iBond Gluma inside (1-SE) or the two-step etch-and-rinse adhesive Gluma Comfort Bond (2-ER) combined with the fine particle hybrid composite Venus. The restorations were clinically evaluated (modified USPHS criteria) over 90 months. Based on resin replicas, a quantitative marginal SEM analysis was performed using the criteria "gap", "perfect margin", "overhang", and "underfilled". The results of the quantitative marginal analysis were statistically compared and related to clinical evaluations. The SEM data were analyzed statistically using the Kolmogorov-Smirnov test, Wilcoxon test, and mixed models test.
Results: Of the 35 subjects at baseline, 16 (1-SE) and 17 (2-ER) were clinically re-examined after 90 months. 13 patients were included in the SEM analysis due to uninterrupted documentation over 90 months or until restoration loss. SEM analysis showed larger discriminative power between groups than did the clinical examination, but the trend was the same. Marginal analysis ("gap", "perfect margin") showed significant differences between the materials after 12 months, which clinically began to show a trend from 12 months, and were statistically verified after 48 and 90 months. "Overhang" and "underfilled" did not reveal significant differences between the systems or over time.
Conclusion: SEM marginal analysis using the replication technique is a powerful tool to reveal differences between adhesives. Compared to clinical evaluation, group differences can be detected earlier, with both outcome parameters confirming each other over long observation periods.
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http://dx.doi.org/10.3290/j.jad.b916821 | DOI Listing |
Bayesian Anal
January 2025
Department of Statistics, University of Washington, Seattle, USA.
We introduce the BREASE framework for the Bayesian analysis of randomized controlled trials with binary treatment and outcome. Approaching the problem from a causal inference perspective, we propose parameterizing the likelihood in terms of the aseline isk, fficacy, and dverse ide ffects of the treatment, along with a flexible, yet intuitive and tractable jointly independent beta prior distribution on these parameters, which we show to be a generalization of the Dirichlet prior for the joint distribution of potential outcomes. Our approach has a number of desirable characteristics when compared to current mainstream alternatives: (i) it naturally induces prior dependence between expected outcomes in the treatment and control groups; (ii) as the baseline risk, efficacy and risk of adverse side effects are quantities commonly present in the clinicians' vocabulary, the hyperparameters of the prior are directly interpretable, thus facilitating the elicitation of prior knowledge and sensitivity analysis; and (iii) we provide analytical formulae for the marginal likelihood, Bayes factor, and other posterior quantities, as well as an exact posterior sampling algorithm and an accurate and fast data-augmented Gibbs sampler in cases where traditional MCMC fails.
View Article and Find Full Text PDFFront Public Health
September 2025
Department of Personnel Strategies, Institute of Management, Collegium of Management and Finance, SGH Warsaw School of Economics, Warsaw, Poland.
Introduction: Organizational resilience is of paramount importance for coping with adversity, particularly in the healthcare sector during crises. The objective of the present study was to evaluate the impact of resilience-based interventions on the well-being of healthcare employees during the pandemic. In this study, resilience-based interventions are defined as organizational actions that strengthen a healthcare institution's capacity to cope with crises-such as ensuring adequate personal protective equipment and staff testing, clear risk-communication, alternative care pathways (e.
View Article and Find Full Text PDFAsia Pac J Clin Oncol
September 2025
Faculty of Medicine, Department of Radiation Oncology, Dokuz Eylul University, Izmir, Türkiye.
Purpose: We aimed to analyze our radiotherapy protocol by evaluating its effect on recurrence patterns and survival outcomes.
Methods: We assessed 69 patients diagnosed with IDH-wild-type glioblastoma who underwent chemoradiotherapy at our institution from January 2014 to January 2021. A high-risk clinical target volume (CTV) was created with a 1 cm margin in all directions from the GTV, while a low-risk clinical target volume (CTV) was established with a 2 cm margin.
PLoS One
September 2025
Faculty of Environment, University of Tehran, Tehran, Iran.
Designing sustainable Flood Control Systems (FCSs) requires considering both the resiliency of the system and the long-term viability of investments. In this regard, our research aimed at integrating concepts of hydrological resiliency and cost-benefit analysis to design the most effective flood control network. To do so, first, the Storm Water Management Model (SWMM) was developed for simulating flood condition.
View Article and Find Full Text PDFIEEE Trans Neural Netw Learn Syst
September 2025
Unsupervised visible-infrared person reidentification (UVI-ReID) has recently gained great attention due to its potential for enhancing human detection in diverse environments without labeling. Previous methods utilize intramodality clustering and cross-modality feature matching to achieve UVI-ReID. However, there exist two challenges: 1) noisy pseudo-labels might be generated in the clustering process and 2) the cross-modality feature alignment via matching the marginal distribution of visible and infrared modalities may misalign the different identities from the two modalities.
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