Background: The integration of digital technologies into prosthodontics has significantly improved clinical workflows, from intraoral data acquisition to restoration design and fabrication. Accurate tooth shade selection remains a critical step in achieving optimal aesthetic outcomes, with spectrophotometry considered the gold standard. However, alternative digital methods such as intraoral scanners and digital photography are increasingly used in clinical practice. Objective: This study aimed to evaluate the accuracy of intraoral scanning and standardized digital photography for tooth shade selection within a digital prosthodontic workflow, using spectrophotometric measurements as reference. Methods: Twenty participants were included in this clinical study. Tooth color was recorded using a spectrophotometer (reference method), an intraoral scanner (Medit i700), and standardized digital photography, which was analyzed with a Digital Color Meter. Color differences (ΔE) were calculated using the CIELAB formula. Statistical analysis included one-sample and independent-samples t-tests, as well as Bland–Altman analysis to assess agreement between methods. Results: Digital photography showed significantly higher ΔE values (19.37 ± 2.45) compared to the clinical acceptability threshold (ΔE = 3.3; p < 0.001), indicating poor accuracy. The intraoral scanner demonstrated lower ΔE values (5.53 ± 0.62; p < 0.001) but still exceeded the acceptable limit. Bland–Altman analysis confirmed poor agreement for digital photography and a reduced, though still suboptimal, agreement for the intraoral scanner relative to spectrophotometry. Nonetheless, the intraoral scanner demonstrated significantly better agreement than digital photography, supporting its preferential use in digital prosthodontic workflows. Conclusions: Within the context of digital prosthodontics, digital photography cannot be considered a reliable method for shade matching. Intraoral scanners provide improved consistency but do not achieve clinically acceptable accuracy compared to spectrophotometry. Spectrophotometry remains the gold standard, while intraoral scanning may serve as a complementary tool in digital workflows. Future studies with larger samples are needed to confirm these findings.

Background/Objectives: Metabolic syndrome (MetS), defined by abdominal obesity, dysglycemia, dyslipidemia, hypertension, and insulin resistance, markedly increases the risk of type 2 diabetes mellitus and cardiovascular disease. Affecting an estimated 25–30% of the global adult population, MetS represents a major and growing public health challenge. A growing body of evidence supports a significant bidirectional relationship between MetS and oral health, particularly periodontitis. The present study aimed to synthesize current evidence on the pathophysiological mechanisms, epidemiological associations, interventional outcomes, and clinical implications of the bidirectional relationship between metabolic syndrome (MetS) and periodontitis. Methods: A narrative review following the SANRA framework was performed. PubMed, Scopus, and Web of Science were searched for articles published in January 2021–March 2026 using MeSH and free-text terms including “metabolic syndrome”, “periodontal disease”, “insulin resistance”, and “oral microbiota”. Eligible studies included original research and systematic reviews in English with full-text availability; animal and in vitro studies were included if directly informative of mechanistic pathways. Results: A total of 64 references were selected for inclusion. Shared mechanisms include chronic systemic inflammation, insulin resistance, oxidative stress, adipokine imbalance, endothelial dysfunction, and oral–gut microbiome dysbiosis. Cross-sectional and longitudinal studies show that MetS components are independently associated with higher prevalence and severity of periodontitis; meta-analyses report pooled odds ratios of 1.7–1.9 compared with metabolically healthy controls. Non-surgical periodontal therapy produces modest but significant reductions in glycated hemoglobin (HbA1c) and systemic inflammatory markers. Sodium–glucose cotransporter-2 (SGLT2) inhibitors may alter oral microbiota composition and cause mucosal changes, while glucagon-like peptide-1 (GLP-1) receptor agonists may increase caries risk through gastrointestinal side effects and xerostomia; both drug classes warrant proactive dental monitoring. Conclusions: The bidirectional relationship between MetS and oral health supports integrated screening and interdisciplinary management. Routine periodontal assessment should be integrated into the metabolic risk management pathway, and dental professionals should screen patients with severe periodontitis for metabolic risk factors. The oral microbiome emerges as a promising target for future mechanistic research and therapeutic intervention. Recognition of oral health as an integral component of metabolic health may improve risk stratification, prevention, and long-term patient outcomes. Large-scale randomized controlled trials with standardized endpoints are needed to establish causal directionality and optimize combined therapeutic strategies.