This editorial explores the clinical potential of complete blood count-derived inflammation indices (CBC-DIIs) as sensitive and cost-effective measures of systemic inflammation and immune response.

Obesity is a heterogeneous multisystem condition characterized by chronic low-grade inflammation, oxidative stress, adipokine dysregulation, and insulin resistance; its effects on oral microbial homeostasis, tissue regeneration, and disease susceptibility vary with metabolic context and with the outcome examined. This narrative review synthesizes evidence on the mechanisms linking obesity to oral disease and on its implications for dental prevention, periodontal care, implant therapy, and oral surgery. MEDLINE via PubMed, Scopus, and Web of Science Core Collection were searched from January 2000 to 31 August 2026, with the final search performed on 10 September 2026. The strength of evidence differs markedly by outcome. Human epidemiological studies support an association with periodontitis; altered salivary flow and composition are reported mainly in cross-sectional studies. Proposed effects on osseous healing and jawbone remodeling rest substantially on experimental and systemic bone research, and specific marrow alterations remain poorly established. Obesity is associated with selected peri-implant inflammatory outcomes, whereas evidence on implant survival is less consistent; these findings establish neither impaired primary osseointegration nor a contraindication to implant therapy. Associations with caries appear largely attributable to shared determinants. The phenotype-aware framework proposed here is hypothesis-generating and requires prospective interventional validation.

Background: This case report documents selective explantation in advanced peri-implantitis, early clinical healing, and exploratory blood and retrieval observations. Methods: A 71-year-old woman with hypertension had radiographic peri-implant bone defects around six mandibular implants. Implants 35 and 42 had evidence of suppuration, probing depths up to 8 mm, clinical mobility, and bone loss exceeding 66% at one or more surfaces, including full-length mesial defects, and were removed. Treatment combined professional hygiene and mechanical debridement, explantation, curettage, adjunctive Er:YAG irradiation of the post-explantation defect walls, chlorhexidine, systemic amoxicillin, and supportive care. The first blood sample was collected on the day of surgery, 2 weeks after the initial hygiene consultation. A second sample was obtained at 6 weeks, while four implants with radiographic defects remained in situ. Results: Both explantation sites showed uncomplicated soft-tissue healing over 2 months; no osseous healing outcome was assessed. At 4 months, the retained implants showed no bleeding on probing, suppuration, or clinically detectable mobility, without establishing long-term disease control. The blood findings were descriptive observations from one patient and showed no consistent downward inflammatory pattern. Ex vivo scanning electron microscopy with energy-dispersive X-ray spectroscopy (SEM/EDS) was performed on implant 35. Conclusions: SEM/EDS analysis of the retrieved implant revealed surface alterations consistent with mechanical wear and localized variations in elemental composition, providing additional insight into the structural and chemical characteristics of an implant affected by advanced peri-implantitis. Blood-derived inflammatory markers may offer complementary information about the patient’s general systemic inflammatory status and contribute to a more comprehensive clinical assessment. However, their specific diagnostic and prognostic value in peri-implantitis remains to be established through larger prospective clinical studies.

Background: Obesity is now recognized as chronic, low-grade systemic inflammation. The Systemic Immune-Inflammation Index (SII)—derived from routine complete blood counts—captures overall inflammatory activity, yet its adipose-specific relevance is uncertain. Objective: To assess SII as a quantitative marker of inflammatory burden across the obesity spectrum and to introduce the concept of a targeted Systemic Obesity Immune-Inflammation Index (SOI). Methods: Associations between SII and anthropometric measures and supporting clinical datasets were analyzed in two nationally representative NHANES cohorts (2011–2018, n = 11,192; 2017–2020, n = 7,645). Multivariable regression and spline modeling evaluated relationships with body mass index (BMI), waist circumference, and adiposity distribution. Results: SII increased BMI by 3.13 units per kg/m² (95% CI 2.10–4.16) and 7.8 units per centimeter of waist circumference (95% CI 5.50–10.13). A sharp non-linear surge appeared above BMI 30 kg/m² (p < 0.0001). Obese youth showed a higher mean SII (528 ± 285) than non-obese peers (342 ± 10; p < 0.0001). Although SII tracked obesity prevalence, it did not isolate adipose-driven inflammatory signals. Implications: We propose developing the SOI, calibrated to leukocyte shifts characteristic of obesity, for (i) risk stratification beyond BMI, (ii) sensitive monitoring of weight-loss and anti-inflammatory therapies, and (iii) scalable population surveillance. Conclusion: SII is an accessible biomarker of obesity-related systemic inflammation and provides a foundation for constructing the SOI, an index tailored to obesity's distinctive inflammatory phenotype.

Objective: To design and execute preliminary validation of an Integrated Obesity-Economic Framework (IOEF) that synthesizes the Systemic Obesity–Inflammation Index (SOI) with environmental, socioeconomic, and infrastructure data. This undertaking aims to produce a multidimensional assessment of the health and economic burdens linked to obesity, along with the benefits of targeted interventions. Methods: The SOI values were systematically assigned to 250-meter hexagonal grids and integrated with four geospatial layers: (i) the obesogenic environment index, (ii) socioeconomic deprivation, (iii) infrastructure access, and (iv) health-related economic outcomes. Results: Clustering identified urban 'hot zones' where SOI intersected high obesogenic environment exposure and socioeconomic deprivation. Utility: The IOEF facilitates continuous monitoring of the inflammatory obesity burden, provides a comprehensive assessment of both direct and indirect costs, and enables interactive policy testing aimed at optimizing the reduction of the SOI for each specific investment. Conclusion: The deployment of an IOEF digital platform, predicated on passively acquired SOI data, presents a scalable and impartial approach to mapping and mitigating the health-economic impact of obesity, thereby guiding precise public health interventions and optimizing resource allocation.