<p>Periodontitis is a chronic inflammatory disease affecting more than 1&#xa0;billion people worldwide and leading to irreversible alveolar bone loss. Although salivary biomarkers are potentially non-invasive diagnostic targets, the longitudinal changes in osteocalcin (a marker of bone turnover) following periodontal therapy have been poorly described across levels of disease progression. In this prospective longitudinal study, a new multimodal method combining salivary biomarker analysis and Cone-Beam Computed Tomography (CBCT) was employed. A total of 100 patients (25 systemically healthy controls and 75 patients with periodontitis, stratified into Stages I, II, or III according to the World Workshop 2017 classification) received non-surgical periodontal therapy (NSPT). Salivary osteocalcin and clinical parameters (PPD, CAL, PI) were evaluated at baseline, 3 months, and 6 months. The sample size was estimated by G*Power software to achieve reliable power (&gt; 90%) for detecting clinically important correlations. Baseline salivary osteocalcin levels showed a stage-dependent increase, with Stage III patients exhibiting concentrations 4.7-fold higher than those of healthy controls (28.5 ± 4.1 vs. 6.1 ± 1.9 ng/mL; <i>p</i> &lt; 0.001). Temporal trajectory analysis revealed that the greatest therapeutic effect occurred within the first three months post-NSPT, with Stage III patients showing a 30.5% reduction in osteocalcin by six months. Strong correlations were observed between osteocalcin and CAL (<i>r</i> = 0.88, <i>p</i> &lt; 0.001), with treatment-induced changes in osteocalcin significantly predicting clinical improvement (<i>r</i> = 0.75, <i>p</i> &lt; 0.001). Salivary osteocalcin may be a valid, non-invasive biomarker of the metabolism of the periodontal bone. Early post-treatment red detection offers an important therapeutic window to optimize follow-up intervals based on treatment, and it can be incorporated into the personalized periodontal care workflow.</p>

错误:搜索内容不能为空,请输入英文关键词
错误:关键词超出字数限制,请精简
高级检索

Salivary osteocalcin as a biomarker for periodontal disease progression and treatment response: a prospective longitudinal study

  • Zainulabdeen Saad Mahboba,
  • Hussein Jameel Abd Noor,
  • Batool M. Al-fahham,
  • Salah M. Ibrahim

摘要

Periodontitis is a chronic inflammatory disease affecting more than 1 billion people worldwide and leading to irreversible alveolar bone loss. Although salivary biomarkers are potentially non-invasive diagnostic targets, the longitudinal changes in osteocalcin (a marker of bone turnover) following periodontal therapy have been poorly described across levels of disease progression. In this prospective longitudinal study, a new multimodal method combining salivary biomarker analysis and Cone-Beam Computed Tomography (CBCT) was employed. A total of 100 patients (25 systemically healthy controls and 75 patients with periodontitis, stratified into Stages I, II, or III according to the World Workshop 2017 classification) received non-surgical periodontal therapy (NSPT). Salivary osteocalcin and clinical parameters (PPD, CAL, PI) were evaluated at baseline, 3 months, and 6 months. The sample size was estimated by G*Power software to achieve reliable power (> 90%) for detecting clinically important correlations. Baseline salivary osteocalcin levels showed a stage-dependent increase, with Stage III patients exhibiting concentrations 4.7-fold higher than those of healthy controls (28.5 ± 4.1 vs. 6.1 ± 1.9 ng/mL; p < 0.001). Temporal trajectory analysis revealed that the greatest therapeutic effect occurred within the first three months post-NSPT, with Stage III patients showing a 30.5% reduction in osteocalcin by six months. Strong correlations were observed between osteocalcin and CAL (r = 0.88, p < 0.001), with treatment-induced changes in osteocalcin significantly predicting clinical improvement (r = 0.75, p < 0.001). Salivary osteocalcin may be a valid, non-invasive biomarker of the metabolism of the periodontal bone. Early post-treatment red detection offers an important therapeutic window to optimize follow-up intervals based on treatment, and it can be incorporated into the personalized periodontal care workflow.