Association and Predictive Value of C-Reactive Protein, Fibrinogen and Periodontal Indices in Periodontitis Severity : A Retrospective study

Association and Predictive Value of C-Reactive Protein, Fibrinogen and Periodontal Indices in Periodontitis Severity : A Retrospective study | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Association and Predictive Value of C-Reactive Protein, Fibrinogen and Periodontal Indices in Periodontitis Severity : A Retrospective study ziyue Yang, jingci Zhu, shuo Sun, tongtong Hu, qin Yu, xiao Can, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8122125/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 13 Mar, 2026 Read the published version in Clinical Oral Investigations → Version 1 posted 9 You are reading this latest preprint version Abstract Objectives : Periodontitis is a chronic inflammatory disease closely linked to systemic conditions. This study evaluated the clinical utility of systemic inflammatory markers and periodontal parameters in assessing periodontitis severity and explored their combined predictive value for identifying advanced disease. Materials and Methods: A total of 215 participants were enrolled in a cross-sectional study and categorized into Stage I (2.3%), Stage II (9.3%), Stage III (63.3%), and Stage IV (25.1%) periodontitis based on clinical assessments. Periodontal parameters, including plaque index (PLI), gingival index (GI), bleeding index (BI), probing depth (PD), and clinical attachment loss (AL), were recorded. Venous blood samples were collected to determine serum C-reactive protein (CRP) and plasma fibrinogen (Fg) levels. Correlation analyses and multivariate binary logistic regression were performed to assess the relationships and predictive value of these parameters. Results : Age differed significantly across disease stages (P 0.05). PD, AL, CRP, and Fg increased progressively with disease severity (P < 0.05), whereas PLI, GI, and BI showed no significant trends. CRP correlated with PD, AL, and Fg (P < 0.05). The predictive model combining CRP, Fg, PD, and AL achieved an AUC of 0.885. Logistic regression identified CRP (OR: 1.97), PD (OR: 1.47), and AL (OR: 1.98) as independent predictors of Stage IV periodontitis (P < 0.05), while Fg lost significance after adjustment (P = 0.107). Conclusion: A composite model integrating CRP, Fg, PD, and AL effectively predicts periodontitis severity, supporting its use for early detection and personalized management. Clinical Relevance: CRP and Fg, widely recognized as inflammatory mediators in systemic disease, are also implicated in periodontal inflammation. By combining CRP, Fg, PD, and AL, we developed a predictive model that provides a comprehensive and clinically meaningful tool for identifying patients at high risk of severe periodontitis. Periodontitis C-Reactive Protein Fibrinogen Probing Depth Clinical Attachment Loss Figures Figure 1 Introduction Periodontitis is a common chronic inflammatory disease affecting the supporting structures of the teeth. It is characterized by progressive gingival inflammation, alveolar bone resorption, and, in severe cases, tooth loss[ 1 ]. Globally, the prevalence of periodontitis ranges from 4% to 76% in developed countries and 50% to 90% in developing countries, with severe forms affecting 3%~18% and 8%~46% of the populations, respectively[ 2 , 3 ]. Beyond its local manifestations, periodontitis is increasingly recognized for its impact on systemic health, as chronic infection and inflammation within the periodontium may contribute to systemic immune activation and inflammatory burden[ 4 ]. Recent studies have revealed that periodontitis is closely linked to various systemic diseases, such as cardiovascular disease, diabetes, and adverse pregnancy outcomes[ 5 ]. Mainas et al. reported that periodontitis is associated with elevated systemic inflammatory markers and may influence the onset and progression of systemic complications[ 6 ]. Among these markers, C-reactive protein (CRP) has drawn significant attention. CRP is an acute-phase protein synthesized primarily by hepatocytes in response to inflammatory stimuli and is widely used in clinical practice to monitor both acute and chronic inflammatory conditions[ 7 , 8 ]. Numerous studies have demonstrated that patients with moderate to severe periodontitis exhibit elevated circulating CRP levels compared to healthy individuals[ 9 , 10 , 11 ]. This suggests a bidirectional relationship in which periodontitis contributes to systemic inflammation, and elevated CRP, in turn, may exacerbate periodontal tissue destruction through inflammatory cascades. Furthermore, elevated CRP levels in periodontitis patients have been linked to increased risk of systemic diseases, reinforcing the importance of oral health in maintaining systemic well-being[ 12 ]. Another inflammatory mediator, fibrinogen (Fg), has also been extensively studied. Fg is a plasma glycoprotein synthesized in the liver and acts as the precursor of fibrin in the coagulation cascade. Under the action of thrombin, it plays a crucial role not only in coagulation but also in systemic inflammation. It promotes platelet aggregation, endothelial and smooth muscle cell proliferation, and increases blood viscosity, thereby contributing to vascular endothelial dysfunction and inflammatory responses[ 13 ]. Recent studies, including those by Wu et al. have reported that serum Fg levels are significantly higher in patients with severe periodontitis compared to healthy individuals, suggesting a potential link between periodontal inflammation and systemic pro-thrombotic conditions[ 14 ]. Elevated Fg levels may reflect the systemic response to periodontal infection and have also been implicated in the development of atherosclerosis and cardiovascular disease. Although numerous studies have established associations between CRP, Fg, and periodontitis, there remains a lack of researches specifically evaluating their value in predicting the severity of periodontitis. Most existing studies have focused on presence or absence of periodontitis or its relationship with systemic diseases, while the ability of CRP and Fg to reflect or predict periodontal disease severity has not been clearly defined. Therefore, this study aims to explore the relationship between CRP and Fg levels and the severity of periodontitis, with the goal of identifying potential biomarkers for clinical screening, disease monitoring, and risk assessment of advanced periodontal destruction. Materials and Methods Study population and ethics statement A total of 215 patients (52.6% male, 47.4% female; mean age: 42.54 ± 12.13 years) who received treatment at the Department of Stomatology, First Affiliated Hospital of Soochow University between January 2022 and August 2023 were included in this study. The diagnosis and staging of periodontitis were based on the classification system jointly developed by the European Federation of Periodontology and the American Academy of Periodontology[15]. According to these criteria, patients were categorized into Stage I, II, III, or IV periodontitis. The distribution of disease stages showed that the majority were classified as Stage III (63.3%), followed by Stage IV (25.1%), Stage II (9.3%), and Stage I (2.3%) (Table S1). This retrospective study was conducted in compliance with the revised Declaration of Helsinki. The study protocol was reviewed and approved by the Ethics Committee of the First Affiliated Hospital of Soochow University (Approval No. 2023 Research Grant 378). All participants provided written informed consent prior to inclusion in the study. Inclusion criteria: (1) Diagnosis of Stage I, II, III, or IV periodontitis based on clinical examination and radiographic findings, in accordance with the classification of periodontal and peri-implant diseases; (2) No use of antibiotics, immunosuppressants, or analgesics within the past three months; (3) Male or female participants aged between 18 and 60 years; (4) Body mass index (BMI) ≤ 40 kg/m². Exclusion criteria: (1) Patients with severe cardiac, liver and renal disease, malignant tumors or autoimmune diseases；(2) Pregnant or lactation. Sample collection and analysis Demographic and clinical characteristics of the study participants, including gender, age, and systemic medical history, were recorded through review of prior medical records, in-person interviews, and structured questionnaires. Blood Sample Collection: A 5 mL sample of fasting venous blood was collected from each participant. For plasma collection, blood was drawn into vacuum anticoagulant tubes containing sodium citrate and centrifuged at 3000 rpm for 15 minutes at 4°C within 30 minutes of collection. For serum preparation, another 5 mL of fasting venous blood was collected in standard serum tubes and similarly centrifuged at 3000 rpm for 15 minutes. The resulting plasma and serum were aliquoted into sterile tubes and stored at –80°C until analysis. All blood sample collection and biochemical analyses were conducted by the Department of Laboratory Medicine. The average CRP concentration was 1.86 ± 0.82 mg/L, and the average fibrinogen level was 2.52 ± 0.47 g/L (Table S1). Assessment of Clinical Periodontal Indices Clinical periodontal parameters were assessed by certified specialists in the Department of Stomatology. The indices evaluated included the plaque index (PLI), gingival index (GI), bleeding index (BI), probing depth (PD), and clinical attachment loss (AL). All measurements were conducted using a Williams periodontal probe. PD and AL were recorded at six sites per tooth: mesiobuccal, distobuccal, mid-buccal, mesiopalatal, distopalatal, and mid-palatal. PD was defined as the distance from the gingival margin to the base of the periodontal pocket, while AL was measured as the distance from the cemento-enamel junction (CEJ) to the base of the pocket. The PLI, GI, and BI scores were recorded from four surfaces of each tooth—mesial, distal, buccal, and palatal. The scoring criteria for PLI, GI, and BI were based on previously published literature[16,17]. Clinical findings showed that the majority of participants presented with moderate to high PLI, with 30.2% scoring level 1, 64.2% level 2, and 5.6% level 3. Gingival inflammation (GI) was predominantly moderate (71.2%), with 14.0% and 14.9% exhibiting mild and severe inflammation, respectively. The most frequently observed BI score was level 4 (81.9%), with fewer cases observed at levels 2, 3, and 5. The mean PD was 6.28 ± 1.95 mm, and the mean AL was 7.41 ± 2.26 mm ( Table S1). Statistical analyses All statistical analyses were performed using SPSS software, version 25.0. For continuous variables, either the rank sum test or the independent-samples t-test was applied, depending on the distribution of the data and the assumption of homogeneity of variances. Categorical variables, including periodontitis stage (I-IV), grade, and demographic characteristics (e.g.,age, hypertension, diabetes), were analyzed using either Pearson’s Chi-squared test or Fisher’s exact test, based on sample size and expected frequencies in contingency tables. To examine the relationships between inflammatory markers (CRP and Fg and clinical periodontal indices, Pearson correlation analyses were conducted. Furthermore, to assess the predictive value of CRP, Fg, PD and AL in distinguishing between advanced stages of disease, a multivariate binary logistic regression model was constructed using data from patients with Stage III and IV periodontitis. In this model, the outcome variable was coded as 1 for Stage IV and 0 for Stage III. Model performance was evaluated through five-fold cross-validation and by fitting the model on the entire dataset. A P -value < 0.05 was considered statistically significant. Results General Patient Characteristics in Relation to Periodontitis Stages and Grades The general characteristics of patients revealed no statistically significant differences in gender, hypertension, or diabetes between groups classified as stage I, II, III and IV periodontitis ( P > 0.05); however, a significant difference was observed in age ( P < 0.05) (Table 1 ). Further analysis focusing on patients with severe periodontitis (stage III and IV) also demonstrated a statistically significant difference in age ( P 0.05) (Table 2 ). Additionally, in a subgroup analysis of patients with severe periodontitis (stage III C and IV C), a significant association with hypertension was identified ( P 0.05) (Table 3 ). Correlation of Clinical and Inflammatory Parameters With Periodontitis Severity An analysis of clinical periodontal indices (PLI, GI, BI, PD, and AL) and inflammatory markers (CRP and Fg) indicated that PLI, GI, and BI were not significantly associated with the four stages of periodontitis ( P > 0.05, Table 1 ). In contrast, both PD and AL exhibited strong correlations with periodontitis staging ( P < 0.0001, Table 1 ). Notably, the inflammatory markers CRP and Fg also demonstrated significant associations with periodontitis stages ( P < 0.05, Table 1 ). Further analysis of patients with severe periodontitis (Stages III and IV) revealed that PD, AL, CRP, and Fg levels progressively increased with advancing disease severity ( P < 0.05, Table 2 ). This trend remained consistent in patients with stage III grade C and stage IV grade C periodontitis, where CRP, Fg, PD, and AL levels were significantly elevated ( P 0.05, Tables 2 and 3 ). Table 1 Comparison of Clinical Features of Periodontitis (n = 215) Features Stage P -value Stage I II III IV Gender (%) Male 3 (2.65) 10 (8.85) 67 (59.29) 33 (29.20) 0.5054 Female 2 (1.96) 10 (9.80) 69 (67.65) 21 (20.59) Age, mean (std) 26.8 (6.6) 33.4 (9.5) 43.8 (12.0) 44.4 (11.3) < 0.0001 Hypertension (%) Yes 0 (0) 0 (0) 8 (47.06) 9 (52.94) 0.0563 No 5 (2.53) 20 (10.10) 128 (64.65 45 (22.73) Diabetes (%) Yes 0 (0) 0 (0) 7 (70.00) 3 (30.00) 0.8283 No 5 (2.44) 20 (9.76) 129 (62.93) 51 (24.88) PLI (%) 1 2 (3.08) 6 (9.23) 43 (66.15) 14 (21.54) 0.8420 2 3 (2.17) 13 (9.42) 87 (63.04) 35 (25.36) 3 0 (0) 1 (8.33) 6 (50.00) 5 (41.67) GI (%) 1 1 (3.33) 7 (23.33) 17 (56.67) 5 (16.67) 0.1203 2 4 (2.61) 11 (7.19) 95 (62.09) 43 (28.10) 3 0 (0) 2 (6.25) 24 (75.00) 6 (18.75) BI (%) 2 0 (0) 0 (0) 3 (100.00) 0 (0) 0.5094 3 2 (6.06) 5 (15.15) 19 (57.58) 7 (21.21) 4 3 (1.70) 15 (8.52) 111 (63.07) 47 (26.70) 5 0 (0) 0 (0) 3 (100.00) 0 (0) PD, mean (std) 3.8 (0.4) 4.5 (0.8) 6.6 (1.6) 8.6 (1.5) < 0.0001 AL, mean (std) 3.0 (0) 4.2 (0.6) 7.2 (1.6) 9.6 (1.8) < 0.0001 CRP, mean (std) 2.0 (0.8) 1.5 (0.4) 1.7 (0.7) 2.3 (1.1) 0.0004 Fg, mean (std) 2.6 (0.2) 2.3 (0.5) 2.5 (0.5) 2.7 (0.5) 0.0268 Table 2 Comparison of Clinical Features of Severe Periodontitis(III、IV)(n = 190) Features Stage P -value Stage III IV Gender (%) Male 67 (67.00) 33 (33.00) 0.1402 Female 69 (76.67) 21 (23.33) Age, mean (std) 43.8 (12.0) 44.4 (11.3) 0.7447 Hypertension (%) Yes 8 (47.06) 9 (52.94) 0.0254 No 128 (73.99) 45 (26.01) Diabetes (%) Yes 7 (70.00) 3 (30.00) 1.0000 No 129 (71.67) 51 (28.33) PLI (%) 1 43 (75.44) 14 (24.56) 0.3448 2 87 (71.31) 35 (28.69) 3 6 (54.55) 5 (45.45) GI (%) 1 17 (77.27) 5 (22.73) 0.3858 2 95 (68.84) 43 (31.16) 3 24 (80.00) 6 (20.00) BI (%) 2 3 (100.00) 0 (0) 0.7094 3 19 (73.08) 7 (26.92) 4 111 (70.25) 47 (29.75) 5 3 (100.00) 0 (0) PD, mean (std) 6.6 (1.6) 8.6 (1.5) < 0.0001 AL, mean (std) 7.2 (1.6) 9.6 (1.8) < 0.0001 CRP, mean (std) 1.7 (0.7) 2.3 (1.1) 0.0001 Fg, mean (std) 2.5 (0.5) 2.7 (0.5) 0.0208 Table 3 Comparison of Clinical Features of Severe Periodontitis(III、IV)grade C (n = 124) Features Stage P -value Stage III C IV C Gender (%) Male 39 (54.17) 33 (45.83) 0.4129 Female 32 (61.54) 20 (38.46) Age, mean (std) 41.7 (10.5) 44.2 (11.3) 0.1366 Hypertension (%) Yes 4 (30.77) 9 (69.23) 0.0413 No 67 (60.36) 44 (39.64) Diabetes (%) Yes 5 (62.50) 3 (37.50) 1.0000 No 66 (56.90) 50 (43.10) PLI (%) 1 19 (59.38) 13 (40.62) 0.5159 2 49 (58.33) 35 (41.67) 3 3 (37.50) 5 (62.50) GI (%) 1 7 (63.64) 4 (36.36) 0.2975 2 49 (53.26) 43 (46.74) 3 15 (71.43) 6 (28.57) BI (%) 2 1 (100.00) 0 (0) 1.0000 3 10 (58.82) 7 (41.18) 4 59 (56.19) 46 (43.81) 5 1 (100.00) 0 (0) PD, mean (std) 7.1 (1.5) 8.6 (1.6) < 0.0001 AL, mean (std) 7.7 (1.4) 9.6 (1.8) < 0.0001 CRP, mean (std) 1.7 (0.7) 2.3 (1.1) 0.0002 Fg, mean (std) 2.4 (0.4) 2.7 (0.5) 0.0034 Correlational findings between CRP, Fg and clinical periodontal parameters Based on the above findings, further correlation analyses were conducted to evaluate the relationships between CRP, Fg, and clinical periodontal parameters. In the overall patient cohort, CRP levels were positively correlated with probing depth (PD) (r = 0.17, P = 0.0129), attachment loss (AL) (r = 0.22, P = 0.0015), and Fg (r = 0.32, P < 0.0001). Although Fg expression was significantly associated with CRP levels (r = 0.32, P 0.05) (Table 4 b). In patients with severe periodontitis (including Stage III, Stage IV, and their corresponding Grade C classifications), CRP remained significantly correlated with PD (r = 0.15/0.22, P = 0.0391/0.0124), AL (r = 0.20/0.24, P = 0.0057/0.0077), and Fg (r = 0.30/0.28, P 0.05), despite its continued strong association with CRP (P < 0.001). Moreover, no statistically significant correlations were observed between either CRP or Fg and the plaque index (PLI), gingival index (GI), or bleeding index (BI) at any stage of periodontitis (P > 0.05) (Tables 4 a– 6 a). Additionally, across all patients and within subgroups of those with severe periodontitis, the correlation between CRP and Fg was stronger than the correlations between CRP and either PD or AL. Among the clinical parameters, the correlation between CRP and AL was consistently higher than that between CRP and PD. Table 4 Correlation Analysis of CRP and Fg with Clinical Parameters of Periodontitis (n = 215) (a) Features CRP Fg Mean (std) P-value Mean (std) P-value PLI 1 1.8 (0.7) 0.7507 2.5 (0.5) 0.9490 2 1.9 (0.9) 2.5 (0.4) 3 2.0 (0.8) 2.5 (0.5) GI 1 1.8 (0.6) 0.8545 2.6 (0.5) 0.5162 2 1.8 (0.8) 2.5 (0.5) 3 2.0 (1.1) 2.5 (0.5) BI 2 1.1 (0.2) 0.0789 1.9 (0.3) 0.1392 3 1.9 (0.9) 2.5 (0.5) 4 1.9 (0.8) 2.5 (0.5) 5 1.2 (0.2) 2.6 (0.2) (b) Features CRP Fg Pearson P-value Pearson P-value PD 0.17 0.0129 0.06 0.3870 95% CI [0.04;0.3] 95% CI [-0.08;0.19] AL 0.22 0.0015 0.06 0.3829 95% CI [0.08;0.34] 95% CI [-0.07;0.19] Fg 0.32 < 0.0001 - - 95% CI [0.19;0.43] CRP - - 0.32 < 0.0001 95% CI [0.19;0.43] Table 5 Correlation Analysis of CRP and Fg with Clinical Parameters of Severe Periodontitis (III、IV) (n = 190) (a) Features CRP Fg Mean (std) P-value Mean (std) P-value PLI 1 1.8 (0.8) 0.5776 2.5 (0.5) 0.8282 2 1.9 (0.9) 2.5 (0.5) 3 2.1 (0.8) 2.6 (0.5) GI 1 1.8 (0.6) 0.9031 2.6 (0.4) 0.3588 2 1.9 (0.8) 2.5 (0.5) 3 2.0 (1.1) 2.5 (0.6) BI 2 1.1 (0.2) 0.0652 1.9 (0.3) 0.1068 3 2.0 (1.0) 2.6 (0.5) 4 1.9 (0.8) 2.5 (0.5) 5 1.2 (0.2) 2.6 (0.2) (b) Features CRP Fg Pearson P-value Pearson P-value PD 0.15 0.0391 0.01 0.8990 95% CI [0.01;0.29] 95% CI [-0.13;0.15] AL 0.20 0.0057 0.02 0.8176 95% CI [0.06;0.33] 95% CI [-0.13;0.16] Fg 0.30 < 0.0001 - - 95% CI [0.17;0.43] CRP - - 0.3 < 0.0001 95% CI [0.17;0.43] Table 6 Correlation Analysis of CRP and Fg with Clinical Parameters of Severe Periodontitis Grade C (IIIC、IVC) (n = 124) (a) CRP Fg Mean (std) P-value Mean (std) P-value PLI 1 2.0 (0.8) 0.2109 2.5 (0.6) 0.6561 2 2.0 (1.0) 2.5 (0.4) 3 2.4 (0.8) 2.7 (0.5) GI 1 1.8 (0.6) 0.8659 2.5 (0.4) 0.4624 2 2.0 (0.9) 2.6 (0.4) 3 2.2 (1.2) 2.4 (0.6) BI 2 1.0 (NA) 0.3595 1.6 (NA) 0.3995 3 2.1 (1.1) 2.5 (0.5) 4 2.0 (0.9) 2.5 (0.5) 5 1.3 (NA) 2.6 (NA) (b) CRP Fg Pearson P-value Pearson P-value PD 0.22 0.0124 0.1 0.2534 95% CI [0.05;0.39] 95% CI [-0.07;0.27] AL 0.24 0.0077 0.07 0.4627 95% CI [0.06;0.40] 95% CI [-0.11;0.24] Fg 0.28 0.0017 - - 95% CI [0.11;0.43] CRP - - 0.28 0.0017 95% CI [0.11;0.43] Predictive Value of CRP, Fg, PD, and AL for Severe Periodontitis The above results demonstrated strong correlations between CRP, Fg, PD, AL, and the stages of periodontitis. To further assess their potential for screening severe cases, receiver operating characteristic (ROC) curve analysis was conducted on these indicators in the severe periodontitis group. A predictive model was constructed, yielding a cross-validated area under the curve (AUC) of 0.87, indicating robust performance across different training/testing splits and suggesting good generalizability to unseen data. When the model was applied to the entire dataset, the AUC increased to 0.885, reflecting enhanced predictive accuracy with the inclusion of all available data points (Fig. 1 ). Multivariate logistic regression analysis further revealed that elevated levels of CRP, PD, and AL were significantly associated with increased odds of being classified as Stage IV compared to Stage III. Specifically, each one-unit increase in CRP (mg/L) nearly doubled the odds of Stage IV classification (odds ratio [OR]: 1.97, 95% confidence interval [CI]: 1.16–3.52, P = 0.016). PD (mm) also showed a significant association (OR: 1.47, 95% CI: 1.06–2.09, P = 0.024), as did AL (mm) (OR: 1.98, 95% CI: 1.40–2.94, P < 0.001). Although higher Fg (g/L) levels were associated with increased odds of Stage IV (OR: 2.19), this association did not reach statistical significance after adjusting for CRP, PD, and AL (95% CI: 0.86–5.91, P = 0.107) (Table 7 ). Table 7 Multivariate logistic regression analysis of stage severity in Stage III and IV Features OR 95% CI P-value CRP 1.97 1.16–3.52 0.016 Fg 2.19 0.86–5.91 0.107 PD 1.47 1.06–2.09 0.024 AL 1.98 1.40–2.94 < 0.001 *OR, odds ratio; CI, confidence interval. The binary outcome was coded as 1 for Stage IV and 0 for Stage III. Discussion Periodontitis is a chronic infectious disease that significantly affects both oral and systemic health[ 18 ]. Accumulating evidence has identified periodontal infections are important risk factors for various systemic conditions, including cardiovascular disease, diabetes mellitus, and osteoporosis[ 19 ]. Among various inflammatory mediators, CRP and Fg have garnered considerable attention due to their involvement in both systemic inflammation and periodontal pathogenesis. Although previous studies have confirmed associations between these markers and periodontitis[ 20 , 21 ], few have systematically evaluated their combined predictive value in assessing disease progression and severity. In the present study, we comprehensively analyzed demographic variables, clinical periodontal indices, and inflammatory biomarkers in relation to periodontitis severity. The results revealed that age was significantly associated with the progression of periodontitis. Patients with more advanced stages (Stage III and IV) tended to be older, suggesting a cumulative effect of age-related immune and inflammatory changes on periodontal tissue destruction. This finding aligns with previous studies indicating that aging is a key risk factor in periodontitis, potentially due to diminished immune regulation and increased production of pro-inflammatory mediators such as prostaglandin E2 (PGE2) in aged macrophages, which contribute to alveolar bone resorption[ 22 , 23 , 24 , 25 ]. Further subgroup analysis revealed that hypertension was significantly associated with the most severe forms of periodontitis (Stage III and IV, Grade C), while no significant association was found in mild or moderate cases. This supports the hypothesis that advanced periodontal inflammation may contribute to systemic vascular changes that influence blood pressure regulation[ 26 , 27 ]. In contrast, despite the well-documented bidirectional relationship between diabetes and periodontitis, our study did not observe a significant association. A plausible explanation lies in the age distribution of diabetic patients in our cohort, most of whom were between 40 and 60 years old, which is below the age range where diabetes prevalence peaks, potentially diluting the strength of association[ 28 , 29 ]. With regard to clinical periodontal parameters, PLI, GI and BI showed no significant association with disease severity. These indices, although indicative of local plaque accumulation and inflammation[ 30 , 31 ], may be confounded by short-term oral hygiene behavior or examiner subjectivity[ 32 , 33 ], thus limiting their value in assessing cumulative disease progression. In contrast, PD and AL, which directly reflect periodontal tissue destruction, demonstrated strong and consistent associations with disease staging. Their objectivity and reproducibility reaffirm their central role in clinical diagnosis and monitoring of periodontitis[ 34 , 35 ]. Importantly, we observed a clear upward trend in the levels of CRP and Fg with increasing periodontitis severity, particularly in the more advanced stages and higher-risk Grade C groups. This pattern underscores the systemic inflammatory response to periodontal pathology and supports the concept of a bidirectional interaction between periodontal and systemic inflammation[ 35 , 36 ]. Notably, CRP was significantly correlated with both PD and AL, while Fg showed a strong association with CRP but not with clinical periodontal indices. This differential pattern suggests that CRP may more directly reflect local inflammatory damage within the periodontium, whereas Fg may serve as a broader indicator of systemic inflammatory burden[ 37 ]. Correlation analysis further revealed that the association between CRP and AL was stronger than that between CRP and PD, reinforcing the utility of AL as a more sensitive marker of cumulative tissue damage. Moreover, the correlation between CRP and Fg exceeded that between CRP and any individual clinical parameter, emphasizing the systemic inflammatory axis in periodontitis progression. To translate these findings into clinical application, we constructed a predictive model incorporating CRP, Fg, PD, and AL. The model demonstrated excellent diagnostic performance, with an area under the curve (AUC) of 0.885, indicating strong discriminatory ability and generalizability which indicates high predictive accuracy and strong generalizability[ 38 ]. This integrative approach represents a novel attempt to combine both systemic and local indicators for risk stratification in periodontitis. Importantly, multivariate logistic regression analysis confirmed that elevated levels of CRP, PD, and AL were independent risk factors for advanced periodontitis, whereas fibrinogen lost statistical significance when adjusted for the other variables. This suggests that while fibrinogen remains an important systemic inflammatory marker, its predictive value may be secondary to more direct indicators of local inflammation and tissue destruction. Collectively, these findings underscore the innovative value of a composite biomarker panel that integrates systemic inflammatory markers with clinical measures of periodontal damage. By incorporating both dimensions, this predictive model offers a comprehensive and clinically meaningful tool for identifying individuals at elevated risk of severe periodontitis. Its implementation may improve early risk stratification, support the development of personalized therapeutic strategies, and enable more precise monitoring of disease progression in both clinical practice and research contexts. Conclusion In conclusion, our study provides evidence that CRP, Fg, PD, and AL together offer a powerful and clinically meaningful model for evaluating periodontitis severity. The strong correlations and predictive performance of these indicators underscore their potential utility in improving diagnostic precision and informing individualized treatment planning. Future longitudinal investigations are necessary to confirm the prognostic relevance of this composite biomarker panel and to validate its applicability across diverse populations. Incorporating these measures into routine periodontal assessment may enhance early detection, optimize risk stratification, and support the implementation of targeted therapeutic interventions. Declarations Author information Ziyue Yang, Jingci Zhu and Shuo Sun contributed equally to this work. Ethics declarations Ethics approval and consent to participate All procedures in this study were conducted in accordance with the ethical standards of the Declaration of Helsinki. The study protocol was reviewed and approved by the Ethics Committee of the First Affiliated Hospital of Soochow University (Approval No. 2023 Research Grant 378). Written informed consent was obtained from all individual participants involved in the study. Consent for publication Not applicable. Competing interests The authors declare no competing interests. Funding This work was supported by the Clinical Research Project of the First Affiliated Hospital of Soochow University under Grant BXLC2024016 and the project of the State Key Laboratory of Radiation Medicine and Protection under Grant GZK12024035. Author Contribution Ziyue Yang, Jingci Zhu, Tongtong Hu and Qin Yu collected the clinical data, Ziyue Yang wrote the manuscript; Shuo Sun contributed to data analysis. Lifang Zhu designed the study, while Lifang Zhu and Can Xiao revised the manuscript. All authors read and approved the final manuscript. Acknowledgments This work was supported by the Clinical Research Project of the First Affiliated Hospital of Soochow University under Grant BXLC2024016 and the project of the State Key Laboratory of Radiation Medicine and Protection under Grant GZK12024035. Data Availability All data generated or analysed during this study are included in this manuscript. References Kinane DF, Stathopoulou PG, Papapanou PN.Periodontal diseases.Nat Rev Dis Primers.2017 Jun 22;3:17038. Kassebaum NJ, Bernabé E, Dahiya M, Bhandari B, Murray CJ, Marcenes W.Global burden of severe periodontitis in 1990-2010: a systematic review and meta-regression.J Dent Res.2014 Nov;93(11):1045-53. Jiao J, Jing W, Si Y, Feng X, Tai B, Hu D, Lin H, Wang B, Wang C, Zheng S, Liu X, Rong W, Wang W, Li W, Meng H, Wang X.The prevalence and severity of periodontal disease in Mainland China: Data from the Fourth National Oral Health Survey (2015-2016).J Clin Periodontol.2021 Feb;48(2):168-179. Esteves-Lima RP, Reis CS, Santirocchi-Júnior F, Abreu LG, Costa FO. Association between periodontitis and serum c-reactive protein levels. J Clin Exp Dent. 2020 Sep 1;12(9):e838-e843. Murray PE, Coffman JA, Garcia-Godoy F. Oral Pathogens' Substantial Burden on Cancer, Cardiovascular Diseases, Alzheimer's, Diabetes, and Other Systemic Diseases: A Public Health Crisis-A Comprehensive Review. Pathogens. 2024 Dec 9;13(12):1084. Mainas G, Ide M, Rizzo M, Magan-Fernandez A, Mesa F, Nibali L.Managing the Systemic Impact of Periodontitis.Medicina (Kaunas).2022 Apr 29;58(5):621. Vanderschueren S, Deeren D, Knockaert DC, Bobbaers H, Bossuyt X, Peetermans W. Extremely elevated C-reactive protein. Eur J Intern Med. 2006 Oct;17(6):430-3. Wetterö J, von Löhneysen S, Cobar F, Kristenson M, Garvin P, Sjöwall C. Pronounced Diurnal Pattern of Salivary C-Reactive Protein (CRP) With Modest Associations to Circulating CRP Levels. Front Immunol. 2021 Jan 8;11:607166. Bansal T, Pandey A, D D, Asthana AK. C-Reactive Protein (CRP) and its Association with Periodontal Disease: A Brief Review. J Clin Diagn Res. 2014 Jul;8(7):ZE21-4. Goyal L, Bey A, Gupta ND, Sharma VK. Comparative evaluation of serum C-reactive protein levels in chronic and aggressive periodontitis patients and association with periodontal disease severity. Contemp Clin Dent. 2014 Oct;5(4):484-8. Chang HY, Kim AR, Pi SH, You HK. A Study on the Correlation between C-Reactive Protein Concentration and Teeth with a ≥5 mm Periodontal Pocket in Chronic Periodontitis Patients. Int J Dent. 2020 Dec 23;2020:8832186. Lee JH, Mun SJ.Relationship between C-reactive protein level and periodontitis and systemic diseases.J Periodontol.2023 Oct 16. Li Min, Lin Zengrong. Correlation analysis of homocysteine, fibrinogen, and D-dimer and the severity of primary acute cerebral infarction [J]. The Chinese Medical Guide, 2023,21(28):95-98. Wu T, Trevisan M, Genco RJ, Falkner KL, Dorn JP, Sempos CT.Examination of the relation between periodontal health status and cardiovascular risk factors: serum total and high density lipoprotein cholesterol, C-reactive protein, and plasma fibrinogen.Am J Epidemiol.2000 Feb 1;151(3):273-82. G Caton J, et al. A new classification scheme for periodontal and peri-implant diseases and conditions -Introduction and key changes from the 1999 classification. J Clin Periodontol. 2018 Jun;45 Suppl 20:S1-S8. SILNESS J, LOE H. PERIODONTAL DISEASE IN PREGNANCY. II. CORRELATION BETWEEN ORAL HYGIENE AND PERIODONTAL CONDTION. Acta Odontol Scand. 1964 Feb;22:121-35. Mazza JE, Newman MG, Sims TN. Clinical and antimicrobial effect of stannous fluoride on periodontitis. J Clin Periodontol. 1981 Jun;8(3):203-12. Chen X, Ye W, Zhan JY, Wang X, Tai BJ, Hu Y, Lin HC, Wang B, Si Y, Wang CX, Zheng SG, Liu XN, Rong WS, Wang WJ, Feng XP.Periodontal Status of Chinese Adolescents: Findings from the 4th National Oral Health Survey.Chin J Dent Res.2018;21(3):195-203. Kim J, Amar S.Periodontal disease and systemic conditions: a bidirectional relationship.Odontology.2006 Sep;94(1):10-21. Chandy S, Joseph K, Sankaranarayanan A, Issac A, Babu G, Wilson B, Joseph J.Evaluation of C-Reactive Protein and Fibrinogen in Patients with Chronic and Aggressive Periodontitis: A Clinico-Biochemical Study.J Clin Diagn Res.2017 Mar;11(3):ZC41-ZC45. Liu Jing. Correlation between the severity of periodontitis and fibrinogen, blood lipids, and hypersensitive C-reactive protein in patients with acute cerebral infarction [D]. Hainan Medical College, 2022. Liang S, Hosur KB, Domon H, Hajishengallis G. Periodontal inflammation and bone loss in aged mice. J Periodontal Res. 2010 Aug;45(4):574-8. Hajishengallis G. Aging and its Impact on Innate Immunity and Inflammation: Implications for Periodontitis. J Oral Biosci. 2014 Feb 1;56(1):30-37. Sczepanik FSC, Grossi ML, Casati M, Goldberg M, Glogauer M, Fine N, Tenenbaum HC. Periodontitis is an inflammatory disease of oxidative stress: We should treat it that way. Periodontol 2000. 2020 Oct;84(1):45-68. Clark D, Kotronia E, Ramsay SE. Frailty, aging, and periodontal disease: Basic biologic considerations. Periodontol 2000. 2021 Oct;87(1):143-156. Xavier I., Botelho J., Machado V., Rua J., Delgado A.S., Mendes J.J.Association between hypertension and chronic periodontitis in a Portuguese population.Ann.Med.2019;51:132. Muñoz Aguilera E, Suvan J, Buti J, Czesnikiewicz-Guzik M, Barbosa Ribeiro A, Orlandi M, Guzik TJ, Hingorani AD, Nart J, D'Aiuto F. Periodontitis is associated with hypertension: a systematic review and meta-analysis. Cardiovasc Res. 2020 Jan 1;116(1):28-39. GBD 2021 Diabetes Collaborators.Global, regional, and national burden of diabetes from 1990 to 2021, with projections of prevalence to 2050: a systematic analysis for the Global Burden of Disease Study 2021. Lancet.2023 Jul 15;402(10397):203-234. CDC. National Diabetes Statistics Report (2024, May 15). Centers for Disease Control and Prevention. Retrieved from https://www.cdc.gov/diabetes/php/data-research/index.html . Butler A, Targett D, Bosma ML. Maintenance of gingival health--a measure based on clinical indices. Int Dent J. 2011 Aug;61 Suppl 3(Suppl 3):28-32. Carvalho AP, Moura MF, Costa FO, Cota LO. Correlations between different plaque indexes and bleeding on probing: A concurrent validity study. J Clin Exp Dent. 2023 Jan 1;15(1):e9-e16. Wang I-C, Chan H-L, Johnson GK, Elangovan S. Assessment of Negative Gingival Recession: A Critical Component of Periodontal Diagnosis. Applied Sciences. 2022; 12(14):7015. Bosma ML, McGuire JA, DelSasso A, Milleman J, Milleman K. Efficacy of flossing and mouth rinsing regimens on plaque and gingivitis: a randomized clinical trial. BMC Oral Health. 2024 Feb 3;24(1):178. Mdala I, Olsen I, Haffajee AD, Socransky SS, Thoresen M, de Blasio BF. Comparing clinical attachment level and pocket depth for predicting periodontal disease progression in healthy sites of patients with chronic periodontitis using multi-state Markov models. J Clin Periodontol. 2014 Sep;41(9):837-45. Tonetti MS, Greenwell H, Kornman KS. Staging and grading of periodontitis: Framework and proposal of a new classification and case definition. J Periodontol. 2018 Jun;89 Suppl 1:S159-S172. doi: 10.1002/JPER.18-0006. Erratum in: J Periodontol. 2018 Dec;89(12):1475. Rai J., Shah V., Shah M. Periodontitis Severity Grading Scale and C-Reactive Protein: A Possible Relation. Cureus. 2023;15:e41618. Ullah N, Ma FR, Han J, Liu XL, Fu Y, Liu YT, Liang YL, Ouyang H, Li HY. Monomeric C-reactive protein regulates fibronectin mediated monocyte adhesion. Mol Immunol. 2020 Jan;117:122-130. Fischer JE, Bachmann LM, Jaeschke R. A readers' guide to the interpretation of diagnostic test properties: clinical example of sepsis. Intensive Care Med. 2003 Jul;29(7):1043-51. Additional Declarations No competing interests reported. Supplementary Files TableS1.docx Cite Share Download PDF Status: Published Journal Publication published 13 Mar, 2026 Read the published version in Clinical Oral Investigations → Version 1 posted Editorial decision: Revision requested 09 Dec, 2025 Reviews received at journal 08 Dec, 2025 Reviews received at journal 06 Dec, 2025 Reviewers agreed at journal 01 Dec, 2025 Reviewers agreed at journal 25 Nov, 2025 Reviewers invited by journal 25 Nov, 2025 Editor assigned by journal 18 Nov, 2025 Submission checks completed at journal 18 Nov, 2025 First submitted to journal 15 Nov, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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1","display":"","copyAsset":false,"role":"figure","size":36122,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eReceiver Operating Characteristic (ROC) curve and area under the curve (AUC) for the multivariate binomial logistic regression model using patients in Stage III and IV\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"Figure1.png","url":"https://assets-eu.researchsquare.com/files/rs-8122125/v1/8c40f418474df78dace49cc1.png"},{"id":104739414,"identity":"747e367d-611b-49ce-97e1-877c8432a355","added_by":"auto","created_at":"2026-03-16 16:06:33","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1344356,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8122125/v1/b430f53c-f260-4a01-8caa-8e4a65123b69.pdf"},{"id":97257520,"identity":"7c715010-0100-46a3-8a1e-66f472780531","added_by":"auto","created_at":"2025-12-02 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It is characterized by progressive gingival inflammation, alveolar bone resorption, and, in severe cases, tooth loss[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. Globally, the prevalence of periodontitis ranges from 4% to 76% in developed countries and 50% to 90% in developing countries, with severe forms affecting 3%~18% and 8%~46% of the populations, respectively[\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. Beyond its local manifestations, periodontitis is increasingly recognized for its impact on systemic health, as chronic infection and inflammation within the periodontium may contribute to systemic immune activation and inflammatory burden[\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eRecent studies have revealed that periodontitis is closely linked to various systemic diseases, such as cardiovascular disease, diabetes, and adverse pregnancy outcomes[\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. Mainas et al. reported that periodontitis is associated with elevated systemic inflammatory markers and may influence the onset and progression of systemic complications[\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. Among these markers, C-reactive protein (CRP) has drawn significant attention. CRP is an acute-phase protein synthesized primarily by hepatocytes in response to inflammatory stimuli and is widely used in clinical practice to monitor both acute and chronic inflammatory conditions[\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. Numerous studies have demonstrated that patients with moderate to severe periodontitis exhibit elevated circulating CRP levels compared to healthy individuals[\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. This suggests a bidirectional relationship in which periodontitis contributes to systemic inflammation, and elevated CRP, in turn, may exacerbate periodontal tissue destruction through inflammatory cascades. Furthermore, elevated CRP levels in periodontitis patients have been linked to increased risk of systemic diseases, reinforcing the importance of oral health in maintaining systemic well-being[\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eAnother inflammatory mediator, fibrinogen (Fg), has also been extensively studied. Fg is a plasma glycoprotein synthesized in the liver and acts as the precursor of fibrin in the coagulation cascade. Under the action of thrombin, it plays a crucial role not only in coagulation but also in systemic inflammation. It promotes platelet aggregation, endothelial and smooth muscle cell proliferation, and increases blood viscosity, thereby contributing to vascular endothelial dysfunction and inflammatory responses[\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. Recent studies, including those by Wu et al. have reported that serum Fg levels are significantly higher in patients with severe periodontitis compared to healthy individuals, suggesting a potential link between periodontal inflammation and systemic pro-thrombotic conditions[\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. Elevated Fg levels may reflect the systemic response to periodontal infection and have also been implicated in the development of atherosclerosis and cardiovascular disease.\u003c/p\u003e\u003cp\u003eAlthough numerous studies have established associations between CRP, Fg, and periodontitis, there remains a lack of researches specifically evaluating their value in predicting the severity of periodontitis. Most existing studies have focused on presence or absence of periodontitis or its relationship with systemic diseases, while the ability of CRP and Fg to reflect or predict periodontal disease severity has not been clearly defined. Therefore, this study aims to explore the relationship between CRP and Fg levels and the severity of periodontitis, with the goal of identifying potential biomarkers for clinical screening, disease monitoring, and risk assessment of advanced periodontal destruction.\u003c/p\u003e"},{"header":"Materials and Methods","content":"\u003cp\u003e\u003cstrong\u003eStudy population and ethics statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA total of 215 patients (52.6% male, 47.4% female; mean age: 42.54 \u0026plusmn; 12.13 years) who received treatment at the Department of Stomatology, First Affiliated Hospital of Soochow University between January 2022 and August 2023 were included in this study. The diagnosis and staging of periodontitis were based on the classification system jointly developed by the European Federation of Periodontology and the American Academy of Periodontology[15]. According to these criteria, patients were categorized into Stage I, II, III, or IV periodontitis. The distribution of disease stages showed that the majority were classified as Stage III (63.3%), followed by Stage IV (25.1%), Stage II (9.3%), and Stage I (2.3%) (Table S1).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThis retrospective study was conducted in compliance with the revised Declaration of Helsinki. The study protocol was reviewed and approved by the Ethics Committee of the First Affiliated Hospital of Soochow University (Approval No. 2023 Research Grant 378). All participants provided written informed consent prior to inclusion in the study.\u003c/p\u003e\n\u003cp\u003eInclusion criteria: (1) Diagnosis of Stage I, II, III, or IV periodontitis based on clinical examination and radiographic findings, in accordance with the classification of periodontal and peri-implant diseases; (2) No use of antibiotics, immunosuppressants, or analgesics within the past three months; (3) Male or female participants aged between 18 and 60 years; (4) Body mass index (BMI) \u0026le; 40 kg/m\u0026sup2;. Exclusion criteria: (1) Patients with severe cardiac, liver and renal disease, malignant tumors or autoimmune diseases；(2) Pregnant or lactation.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSample collection and analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eDemographic and clinical characteristics of the study participants, including gender, age, and systemic medical history, were recorded through review of prior medical records, in-person interviews, and structured questionnaires. Blood Sample Collection: A 5 mL sample of fasting venous blood was collected from each participant. For plasma collection, blood was drawn into vacuum anticoagulant tubes containing sodium citrate and centrifuged at 3000 rpm for 15 minutes at 4\u0026deg;C within 30 minutes of collection. For serum preparation, another 5 mL of fasting venous blood was collected in standard serum tubes and similarly centrifuged at 3000 rpm for 15 minutes. The resulting plasma and serum were aliquoted into sterile tubes and stored at \u0026ndash;80\u0026deg;C until analysis. All blood sample collection and biochemical analyses were conducted by the Department of Laboratory Medicine. The average CRP concentration was 1.86 \u0026plusmn; 0.82 mg/L, and the average fibrinogen level was 2.52 \u0026plusmn; 0.47 g/L (Table S1).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAssessment of Clinical Periodontal Indices\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eClinical periodontal parameters were assessed by certified specialists in the Department of Stomatology. The indices evaluated included the plaque index (PLI), gingival index (GI), bleeding index (BI), probing depth (PD), and clinical attachment loss (AL). All measurements were conducted using a Williams periodontal probe. \u0026nbsp;\u003c/p\u003e\n\u003cp\u003ePD and AL were recorded at six sites per tooth: mesiobuccal, distobuccal, mid-buccal, mesiopalatal, distopalatal, and mid-palatal. PD was defined as the distance from the gingival margin to the base of the periodontal pocket, while AL was measured as the distance from the cemento-enamel junction (CEJ) to the base of the pocket. The PLI, GI, and BI scores were recorded from four surfaces of each tooth\u0026mdash;mesial, distal, buccal, and palatal. The scoring criteria for PLI, GI, and BI were based on previously published literature[16,17].\u003c/p\u003e\n\u003cp\u003eClinical findings showed that the majority of participants presented with moderate to high PLI, with 30.2% scoring level 1, 64.2% level 2, and 5.6% level 3. Gingival inflammation (GI) was predominantly moderate (71.2%), with 14.0% and 14.9% exhibiting mild and severe inflammation, respectively. The most frequently observed BI score was level 4 (81.9%), with fewer cases observed at levels 2, 3, and 5. The mean PD was 6.28 \u0026plusmn; 1.95 mm, and the mean AL was 7.41 \u0026plusmn; 2.26 mm ( Table S1).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStatistical analyses\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll statistical analyses were performed using SPSS software, version 25.0. For continuous variables, either the rank sum test or the independent-samples t-test was applied, depending on the distribution of the data and the assumption of homogeneity of variances. Categorical variables, including periodontitis stage (I-IV), grade, and demographic characteristics (e.g.,age, hypertension, diabetes), were analyzed using either Pearson\u0026rsquo;s Chi-squared test or Fisher\u0026rsquo;s exact test, based on sample size and expected frequencies in contingency tables.\u003c/p\u003e\n\u003cp\u003eTo examine the relationships between inflammatory markers (CRP and\u0026nbsp;Fg\u0026nbsp;and clinical periodontal indices, Pearson correlation analyses were conducted. Furthermore, to assess the predictive value of CRP, Fg, PD and AL in distinguishing between advanced stages of disease, a multivariate binary logistic regression model was constructed using data from patients with Stage III and IV periodontitis. In this model, the outcome variable was coded as 1 for Stage IV and 0 for Stage III. Model performance was evaluated through five-fold cross-validation and by fitting the model on the entire dataset. A \u003cem\u003eP\u003c/em\u003e-value \u0026lt; 0.05 was considered statistically significant.\u003c/p\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\n \u003ch2\u003eGeneral Patient Characteristics in Relation to Periodontitis Stages and Grades\u003c/h2\u003e\n \u003cp\u003eThe general characteristics of patients revealed no statistically significant differences in gender, hypertension, or diabetes between groups classified as stage I, II, III and IV periodontitis (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026gt;\u0026thinsp;0.05); however, a significant difference was observed in age (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05) (Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e). Further analysis focusing on patients with severe periodontitis (stage III and IV) also demonstrated a statistically significant difference in age (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05), while no significant differences were found in gender, hypertension, or diabetes (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026gt;\u0026thinsp;0.05) (Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e). Additionally, in a subgroup analysis of patients with severe periodontitis (stage III C and IV C), a significant association with hypertension was identified (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05), whereas age, gender, and diabetes showed no statistically significant differences (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026gt;\u0026thinsp;0.05) (Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e\n\u003c/div\u003e\n\u003ch3\u003eCorrelation of Clinical and Inflammatory Parameters With Periodontitis Severity\u003c/h3\u003e\n\u003cp\u003eAn analysis of clinical periodontal indices (PLI, GI, BI, PD, and AL) and inflammatory markers (CRP and Fg) indicated that PLI, GI, and BI were not significantly associated with the four stages of periodontitis (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026gt;\u0026thinsp;0.05, Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e). In contrast, both PD and AL exhibited strong correlations with periodontitis staging (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.0001, Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e). Notably, the inflammatory markers CRP and Fg also demonstrated significant associations with periodontitis stages (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05, Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e\n\u003cp\u003eFurther analysis of patients with severe periodontitis (Stages III and IV) revealed that PD, AL, CRP, and Fg levels progressively increased with advancing disease severity (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05, Table \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e). This trend remained consistent in patients with stage III grade C and stage IV grade C periodontitis, where CRP, Fg, PD, and AL levels were significantly elevated (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05, Table \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e). In contrast, PLI, GI, and BI did not show significant differences across the severe stages of periodontitis (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026gt;\u0026thinsp;0.05, Tables \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e and \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e\n\u003cp\u003e\u003c/p\u003e\n\u003ctable id=\"Tab1\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eComparison of Clinical Features of Periodontitis (n\u0026thinsp;=\u0026thinsp;215)\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eFeatures\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"4\"\u003e\n \u003cp\u003eStage\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eP\u003c/em\u003e-value\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eStage\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eII\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eIII\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eIV\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGender (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3 (2.65)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e10 (8.85)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e67 (59.29)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e33 (29.20)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" rowspan=\"2\"\u003e\n \u003cp\u003e0.5054\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eFemale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2 (1.96)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e10 (9.80)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e69 (67.65)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e21 (20.59)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAge, mean (std)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e26.8 (6.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e33.4 (9.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e43.8 (12.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e44.4 (11.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;\u0026thinsp;0.0001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHypertension (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0 (0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0 (0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8 (47.06)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e9 (52.94)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" rowspan=\"2\"\u003e\n \u003cp\u003e0.0563\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5 (2.53)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e20 (10.10)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e128 (64.65\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e45 (22.73)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDiabetes (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0 (0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0 (0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7 (70.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3 (30.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" rowspan=\"2\"\u003e\n \u003cp\u003e0.8283\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5 (2.44)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e20 (9.76)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e129 (62.93)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e51 (24.88)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePLI (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2 (3.08)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6 (9.23)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e43 (66.15)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e14 (21.54)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" rowspan=\"3\"\u003e\n \u003cp\u003e0.8420\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3 (2.17)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e13 (9.42)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e87 (63.04)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e35 (25.36)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0 (0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1 (8.33)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6 (50.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5 (41.67)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGI (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1 (3.33)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7 (23.33)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e17 (56.67)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5 (16.67)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" rowspan=\"3\"\u003e\n \u003cp\u003e0.1203\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4 (2.61)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e11 (7.19)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e95 (62.09)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e43 (28.10)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0 (0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2 (6.25)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e24 (75.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6 (18.75)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBI (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0 (0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0 (0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3 (100.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0 (0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" rowspan=\"4\"\u003e\n \u003cp\u003e0.5094\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2 (6.06)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5 (15.15)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e19 (57.58)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7 (21.21)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3 (1.70)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e15 (8.52)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e111 (63.07)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e47 (26.70)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0 (0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0 (0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3 (100.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0 (0)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePD, mean (std)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3.8 (0.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4.5 (0.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6.6 (1.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8.6 (1.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;\u0026thinsp;0.0001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAL, mean (std)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3.0 (0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4.2 (0.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7.2 (1.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e9.6 (1.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;\u0026thinsp;0.0001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCRP, mean (std)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.0 (0.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.5 (0.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.7 (0.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.3 (1.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.0004\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eFg, mean (std)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.6 (0.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.3 (0.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.5 (0.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.7 (0.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.0268\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003c/p\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n\u003cp\u003e\u003c/p\u003e\n\u003ctable id=\"Tab2\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eComparison of Clinical Features of Severe Periodontitis(III、IV)(n\u0026thinsp;=\u0026thinsp;190)\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eFeatures\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eStage\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eP\u003c/em\u003e-value\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eStage\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eIII\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eIV\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGender (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e67 (67.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e33 (33.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" rowspan=\"2\"\u003e\n \u003cp\u003e0.1402\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eFemale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e69 (76.67)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e21 (23.33)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAge, mean (std)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e43.8 (12.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e44.4 (11.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.7447\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHypertension (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8 (47.06)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e9 (52.94)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" rowspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.0254\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e128 (73.99)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e45 (26.01)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDiabetes (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7 (70.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3 (30.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" rowspan=\"2\"\u003e\n \u003cp\u003e1.0000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e129 (71.67)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e51 (28.33)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePLI (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e43 (75.44)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e14 (24.56)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" rowspan=\"3\"\u003e\n \u003cp\u003e0.3448\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e87 (71.31)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e35 (28.69)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6 (54.55)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5 (45.45)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGI (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e17 (77.27)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5 (22.73)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" rowspan=\"3\"\u003e\n \u003cp\u003e0.3858\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e95 (68.84)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e43 (31.16)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e24 (80.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6 (20.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBI (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3 (100.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0 (0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" rowspan=\"4\"\u003e\n \u003cp\u003e0.7094\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e19 (73.08)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7 (26.92)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e111 (70.25)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e47 (29.75)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3 (100.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0 (0)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePD, mean (std)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6.6 (1.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8.6 (1.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;\u0026thinsp;0.0001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAL, mean (std)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7.2 (1.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e9.6 (1.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;\u0026thinsp;0.0001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCRP, mean (std)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.7 (0.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.3 (1.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.0001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eFg, mean (std)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.5 (0.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.7 (0.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.0208\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003c/p\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n\u003cp\u003e\u003c/p\u003e\n\u003ctable id=\"Tab3\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eComparison of Clinical Features of Severe Periodontitis(III、IV)grade C (n\u0026thinsp;=\u0026thinsp;124)\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eFeatures\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eStage\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eP\u003c/em\u003e-value\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eStage\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eIII C\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eIV C\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGender (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e39 (54.17)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e33 (45.83)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" rowspan=\"2\"\u003e\n \u003cp\u003e0.4129\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eFemale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e32 (61.54)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e20 (38.46)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAge, mean (std)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e41.7 (10.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e44.2 (11.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.1366\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHypertension (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4 (30.77)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e9 (69.23)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" rowspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.0413\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e67 (60.36)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e44 (39.64)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDiabetes (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5 (62.50)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3 (37.50)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" rowspan=\"2\"\u003e\n \u003cp\u003e1.0000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e66 (56.90)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e50 (43.10)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePLI (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e19 (59.38)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e13 (40.62)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" rowspan=\"3\"\u003e\n \u003cp\u003e0.5159\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e49 (58.33)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e35 (41.67)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3 (37.50)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5 (62.50)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGI (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7 (63.64)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4 (36.36)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" rowspan=\"3\"\u003e\n \u003cp\u003e0.2975\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e49 (53.26)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e43 (46.74)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e15 (71.43)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6 (28.57)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBI (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1 (100.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0 (0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" rowspan=\"4\"\u003e\n \u003cp\u003e1.0000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e10 (58.82)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7 (41.18)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e59 (56.19)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e46 (43.81)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1 (100.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0 (0)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePD, mean (std)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7.1 (1.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8.6 (1.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;\u0026thinsp;0.0001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAL, mean (std)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7.7 (1.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e9.6 (1.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;\u0026thinsp;0.0001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCRP, mean (std)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.7 (0.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.3 (1.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.0002\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eFg, mean (std)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.4 (0.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.7 (0.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.0034\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003c/p\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n\u003ch3\u003eCorrelational findings between CRP, Fg and clinical periodontal parameters\u003c/h3\u003e\n\u003cp\u003eBased on the above findings, further correlation analyses were conducted to evaluate the relationships between CRP, Fg, and clinical periodontal parameters. In the overall patient cohort, CRP levels were positively correlated with probing depth (PD) (r\u0026thinsp;=\u0026thinsp;0.17, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.0129), attachment loss (AL) (r\u0026thinsp;=\u0026thinsp;0.22, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.0015), and Fg (r\u0026thinsp;=\u0026thinsp;0.32, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.0001). Although Fg expression was significantly associated with CRP levels (r\u0026thinsp;=\u0026thinsp;0.32, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.0001), no statistically significant correlations were found between Fg and either PD or AL (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026gt;\u0026thinsp;0.05) (Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003eb).\u003c/p\u003e\n\u003cp\u003eIn patients with severe periodontitis (including Stage III, Stage IV, and their corresponding Grade C classifications), CRP remained significantly correlated with PD (r\u0026thinsp;=\u0026thinsp;0.15/0.22, P\u0026thinsp;=\u0026thinsp;0.0391/0.0124), AL (r\u0026thinsp;=\u0026thinsp;0.20/0.24, P\u0026thinsp;=\u0026thinsp;0.0057/0.0077), and Fg (r\u0026thinsp;=\u0026thinsp;0.30/0.28, P\u0026thinsp;\u0026lt;\u0026thinsp;0.0001/0.0017) (Tables\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e5\u003c/span\u003eb and \u003cspan class=\"InternalRef\"\u003e6\u003c/span\u003eb). However, consistent with findings in the overall cohort, Fg showed no statistically significant correlation with PD or AL in any subgroup (P\u0026thinsp;\u0026gt;\u0026thinsp;0.05), despite its continued strong association with CRP (P\u0026thinsp;\u0026lt;\u0026thinsp;0.001).\u003c/p\u003e\n\u003cp\u003eMoreover, no statistically significant correlations were observed between either CRP or Fg and the plaque index (PLI), gingival index (GI), or bleeding index (BI) at any stage of periodontitis (P\u0026thinsp;\u0026gt;\u0026thinsp;0.05) (Tables\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003ea\u0026ndash;\u003cspan class=\"InternalRef\"\u003e6\u003c/span\u003ea).\u003c/p\u003e\n\u003cp\u003eAdditionally, across all patients and within subgroups of those with severe periodontitis, the correlation between CRP and Fg was stronger than the correlations between CRP and either PD or AL. Among the clinical parameters, the correlation between CRP and AL was consistently higher than that between CRP and PD.\u003c/p\u003e\n\u003cp\u003e\u003c/p\u003e\n\u003ctable id=\"Tab4\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eCorrelation Analysis of CRP and Fg with Clinical Parameters of Periodontitis (n\u0026thinsp;=\u0026thinsp;215)\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e(a)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eFeatures\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eCRP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eFg\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMean (std)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eP-value\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMean (std)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eP-value\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePLI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.8 (0.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"3\"\u003e\n \u003cp\u003e0.7507\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.5 (0.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"3\"\u003e\n \u003cp\u003e0.9490\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.9 (0.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.5 (0.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.0 (0.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.5 (0.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.8 (0.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"3\"\u003e\n \u003cp\u003e0.8545\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.6 (0.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"3\"\u003e\n \u003cp\u003e0.5162\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.8 (0.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.5 (0.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.0 (1.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.5 (0.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.1 (0.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"4\"\u003e\n \u003cp\u003e0.0789\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.9 (0.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"4\"\u003e\n \u003cp\u003e0.1392\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.9 (0.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.5 (0.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.9 (0.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.5 (0.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.2 (0.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.6 (0.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e(b)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eFeatures\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eCRP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eFg\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePearson\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eP-value\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePearson\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eP-value\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003ePD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.0129\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e0.3870\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e95% CI [0.04;0.3]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e95% CI [-0.08;0.19]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eAL\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.0015\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e0.3829\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e95% CI [0.08;0.34]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e95% CI [-0.07;0.19]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eFg\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.32\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;\u0026thinsp;0.0001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e95% CI [0.19;0.43]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eCRP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.32\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;\u0026thinsp;0.0001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e95% CI [0.19;0.43]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003c/p\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n\u003cp\u003e\u003c/p\u003e\n\u003ctable id=\"Tab5\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eCorrelation Analysis of CRP and Fg with Clinical Parameters of Severe Periodontitis (III、IV) (n\u0026thinsp;=\u0026thinsp;190)\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e(a)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eFeatures\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eCRP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eFg\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMean (std)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eP-value\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMean (std)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eP-value\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePLI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.8 (0.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"3\"\u003e\n \u003cp\u003e0.5776\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.5 (0.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"3\"\u003e\n \u003cp\u003e0.8282\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.9 (0.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.5 (0.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.1 (0.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.6 (0.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.8 (0.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"3\"\u003e\n \u003cp\u003e0.9031\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.6 (0.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"3\"\u003e\n \u003cp\u003e0.3588\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.9 (0.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.5 (0.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.0 (1.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.5 (0.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.1 (0.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"4\"\u003e\n \u003cp\u003e0.0652\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.9 (0.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"4\"\u003e\n \u003cp\u003e0.1068\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.0 (1.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.6 (0.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.9 (0.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.5 (0.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.2 (0.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.6 (0.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e(b)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eFeatures\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eCRP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eFg\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePearson\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eP-value\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePearson\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eP-value\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003ePD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.0391\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e0.8990\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e95% CI [0.01;0.29]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e95% CI [-0.13;0.15]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eAL\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.0057\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e0.8176\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e95% CI [0.06;0.33]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e95% CI [-0.13;0.16]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eFg\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;\u0026thinsp;0.0001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e95% CI [0.17;0.43]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eCRP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;\u0026thinsp;0.0001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e95% CI [0.17;0.43]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003c/p\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n\u003cp\u003e\u003c/p\u003e\n\u003ctable id=\"Tab6\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 6\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eCorrelation Analysis of CRP and Fg with Clinical Parameters of Severe Periodontitis Grade C (IIIC、IVC) (n\u0026thinsp;=\u0026thinsp;124)\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e(a)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eCRP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eFg\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMean (std)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eP-value\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMean (std)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eP-value\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePLI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.0 (0.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"3\"\u003e\n \u003cp\u003e0.2109\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.5 (0.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"3\"\u003e\n \u003cp\u003e0.6561\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.0 (1.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.5 (0.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.4 (0.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.7 (0.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.8 (0.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"3\"\u003e\n \u003cp\u003e0.8659\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.5 (0.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"3\"\u003e\n \u003cp\u003e0.4624\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.0 (0.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.6 (0.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.2 (1.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.4 (0.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.0 (NA)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"4\"\u003e\n \u003cp\u003e0.3595\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.6 (NA)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"4\"\u003e\n \u003cp\u003e0.3995\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.1 (1.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.5 (0.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.0 (0.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.5 (0.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.3 (NA)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.6 (NA)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e(b)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eCRP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eFg\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePearson\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eP-value\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePearson\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eP-value\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003ePD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.0124\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e0.2534\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e95% CI [0.05;0.39]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e95% CI [-0.07;0.27]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eAL\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.0077\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e0.4627\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e95% CI [0.06;0.40]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e95% CI [-0.11;0.24]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eFg\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.0017\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e95% CI [0.11;0.43]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eCRP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e0.0017\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e95% CI [0.11;0.43]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003c/p\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\n \u003ch2\u003ePredictive Value of CRP, Fg, PD, and AL for Severe Periodontitis\u003c/h2\u003e\n \u003cp\u003eThe above results demonstrated strong correlations between CRP, Fg, PD, AL, and the stages of periodontitis. To further assess their potential for screening severe cases, receiver operating characteristic (ROC) curve analysis was conducted on these indicators in the severe periodontitis group. A predictive model was constructed, yielding a cross-validated area under the curve (AUC) of 0.87, indicating robust performance across different training/testing splits and suggesting good generalizability to unseen data. When the model was applied to the entire dataset, the AUC increased to 0.885, reflecting enhanced predictive accuracy with the inclusion of all available data points (Fig. \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e\n \u003cp\u003eMultivariate logistic regression analysis further revealed that elevated levels of CRP, PD, and AL were significantly associated with increased odds of being classified as Stage IV compared to Stage III. Specifically, each one-unit increase in CRP (mg/L) nearly doubled the odds of Stage IV classification (odds ratio [OR]: 1.97, 95% confidence interval [CI]: 1.16\u0026ndash;3.52, P\u0026thinsp;=\u0026thinsp;0.016). PD (mm) also showed a significant association (OR: 1.47, 95% CI: 1.06\u0026ndash;2.09, P\u0026thinsp;=\u0026thinsp;0.024), as did AL (mm) (OR: 1.98, 95% CI: 1.40\u0026ndash;2.94, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Although higher Fg (g/L) levels were associated with increased odds of Stage IV (OR: 2.19), this association did not reach statistical significance after adjusting for CRP, PD, and AL (95% CI: 0.86\u0026ndash;5.91, P\u0026thinsp;=\u0026thinsp;0.107) (Table \u003cspan class=\"InternalRef\"\u003e7\u003c/span\u003e).\u003c/p\u003e\n \u003cp\u003e\u003c/p\u003e\n \u003ctable id=\"Tab8\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 7\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eMultivariate logistic regression analysis of stage severity in Stage III and IV\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eFeatures\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eOR\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e95% CI\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eP-value\u003c/em\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCRP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.97\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.16\u0026ndash;3.52\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.016\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eFg\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2.19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.86\u0026ndash;5.91\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.107\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.47\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.06\u0026ndash;2.09\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.024\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAL\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.98\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.40\u0026ndash;2.94\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003cp\u003e\u003c/p\u003e\n \u003cp\u003e*OR, odds ratio; CI, confidence interval. The binary outcome was coded as 1 for Stage IV and 0 for Stage III.\u003c/p\u003e\n\u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003ePeriodontitis is a chronic infectious disease that significantly affects both oral and systemic health[\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. Accumulating evidence has identified periodontal infections are important risk factors for various systemic conditions, including cardiovascular disease, diabetes mellitus, and osteoporosis[\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. Among various inflammatory mediators, CRP and Fg have garnered considerable attention due to their involvement in both systemic inflammation and periodontal pathogenesis. Although previous studies have confirmed associations between these markers and periodontitis[\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e], few have systematically evaluated their combined predictive value in assessing disease progression and severity.\u003c/p\u003e\u003cp\u003eIn the present study, we comprehensively analyzed demographic variables, clinical periodontal indices, and inflammatory biomarkers in relation to periodontitis severity. The results revealed that age was significantly associated with the progression of periodontitis. Patients with more advanced stages (Stage III and IV) tended to be older, suggesting a cumulative effect of age-related immune and inflammatory changes on periodontal tissue destruction. This finding aligns with previous studies indicating that aging is a key risk factor in periodontitis, potentially due to diminished immune regulation and increased production of pro-inflammatory mediators such as prostaglandin E2 (PGE2) in aged macrophages, which contribute to alveolar bone resorption[\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eFurther subgroup analysis revealed that hypertension was significantly associated with the most severe forms of periodontitis (Stage III and IV, Grade C), while no significant association was found in mild or moderate cases. This supports the hypothesis that advanced periodontal inflammation may contribute to systemic vascular changes that influence blood pressure regulation[\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. In contrast, despite the well-documented bidirectional relationship between diabetes and periodontitis, our study did not observe a significant association. A plausible explanation lies in the age distribution of diabetic patients in our cohort, most of whom were between 40 and 60 years old, which is below the age range where diabetes prevalence peaks, potentially diluting the strength of association[\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e, \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eWith regard to clinical periodontal parameters, PLI, GI and BI showed no significant association with disease severity. These indices, although indicative of local plaque accumulation and inflammation[\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e, \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e], may be confounded by short-term oral hygiene behavior or examiner subjectivity[\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e, \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e], thus limiting their value in assessing cumulative disease progression. In contrast, PD and AL, which directly reflect periodontal tissue destruction, demonstrated strong and consistent associations with disease staging. Their objectivity and reproducibility reaffirm their central role in clinical diagnosis and monitoring of periodontitis[\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e, \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eImportantly, we observed a clear upward trend in the levels of CRP and Fg with increasing periodontitis severity, particularly in the more advanced stages and higher-risk Grade C groups. This pattern underscores the systemic inflammatory response to periodontal pathology and supports the concept of a bidirectional interaction between periodontal and systemic inflammation[\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e, \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e]. Notably, CRP was significantly correlated with both PD and AL, while Fg showed a strong association with CRP but not with clinical periodontal indices. This differential pattern suggests that CRP may more directly reflect local inflammatory damage within the periodontium, whereas Fg may serve as a broader indicator of systemic inflammatory burden[\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eCorrelation analysis further revealed that the association between CRP and AL was stronger than that between CRP and PD, reinforcing the utility of AL as a more sensitive marker of cumulative tissue damage. Moreover, the correlation between CRP and Fg exceeded that between CRP and any individual clinical parameter, emphasizing the systemic inflammatory axis in periodontitis progression.\u003c/p\u003e\u003cp\u003eTo translate these findings into clinical application, we constructed a predictive model incorporating CRP, Fg, PD, and AL. The model demonstrated excellent diagnostic performance, with an area under the curve (AUC) of 0.885, indicating strong discriminatory ability and generalizability which indicates high predictive accuracy and strong generalizability[\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e]. This integrative approach represents a novel attempt to combine both systemic and local indicators for risk stratification in periodontitis. Importantly, multivariate logistic regression analysis confirmed that elevated levels of CRP, PD, and AL were independent risk factors for advanced periodontitis, whereas fibrinogen lost statistical significance when adjusted for the other variables. This suggests that while fibrinogen remains an important systemic inflammatory marker, its predictive value may be secondary to more direct indicators of local inflammation and tissue destruction.\u003c/p\u003e\u003cp\u003eCollectively, these findings underscore the innovative value of a composite biomarker panel that integrates systemic inflammatory markers with clinical measures of periodontal damage. By incorporating both dimensions, this predictive model offers a comprehensive and clinically meaningful tool for identifying individuals at elevated risk of severe periodontitis. Its implementation may improve early risk stratification, support the development of personalized therapeutic strategies, and enable more precise monitoring of disease progression in both clinical practice and research contexts.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eIn conclusion, our study provides evidence that CRP, Fg, PD, and AL together offer a powerful and clinically meaningful model for evaluating periodontitis severity. The strong correlations and predictive performance of these indicators underscore their potential utility in improving diagnostic precision and informing individualized treatment planning. Future longitudinal investigations are necessary to confirm the prognostic relevance of this composite biomarker panel and to validate its applicability across diverse populations. Incorporating these measures into routine periodontal assessment may enhance early detection, optimize risk stratification, and support the implementation of targeted therapeutic interventions.\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003eAuthor information\u003c/h2\u003e\n\u003cp\u003eZiyue Yang, Jingci Zhu and Shuo Sun contributed equally to this work.\u003c/p\u003e\n\u003ch2\u003eEthics declarations\u003c/h2\u003e\n\u003ch2\u003eEthics approval and consent to participate\u003c/h2\u003e\n\u003cp\u003eAll procedures in this study were conducted in accordance with the ethical standards of the Declaration of Helsinki. The study protocol was reviewed and approved by the Ethics Committee of the First Affiliated Hospital of Soochow University (Approval No. 2023 Research Grant 378). Written informed consent was obtained from all individual participants involved in the study.\u003c/p\u003e\n\u003ch2\u003eConsent for publication\u003c/h2\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003ch2\u003eCompeting interests\u003c/h2\u003e\n\u003cp\u003eThe authors declare no competing interests.\u003c/p\u003e\n\u003ch2\u003eFunding\u003c/h2\u003e\n\u003cp\u003eThis work was supported by the Clinical Research Project of the First Affiliated Hospital of Soochow University under Grant BXLC2024016 and the project of the State Key Laboratory of Radiation Medicine and Protection under Grant GZK12024035.\u003c/p\u003e\n\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\n\u003cp\u003eZiyue Yang, Jingci Zhu, Tongtong Hu and Qin Yu collected the clinical data, Ziyue Yang wrote the manuscript; Shuo Sun contributed to data analysis. Lifang Zhu designed the study, while Lifang Zhu and Can Xiao revised the manuscript. All authors read and approved the final manuscript.\u003c/p\u003e\n\u003ch2\u003eAcknowledgments\u003c/h2\u003e\n\u003cp\u003eThis work was supported by the Clinical Research Project of the First Affiliated Hospital of Soochow University under Grant BXLC2024016 and the project of the State Key Laboratory of Radiation Medicine and Protection under Grant GZK12024035.\u003c/p\u003e\n\u003ch2\u003eData Availability\u003c/h2\u003e\n\u003cp\u003eAll data generated or analysed during this study are included in this manuscript.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eKinane DF, Stathopoulou PG, Papapanou PN.Periodontal diseases.Nat Rev Dis Primers.2017 Jun 22;3:17038.\u003c/li\u003e\n\u003cli\u003eKassebaum NJ, Bernab\u0026eacute; E, Dahiya M, Bhandari B, Murray CJ, Marcenes W.Global burden of severe periodontitis in 1990-2010: a systematic review and meta-regression.J Dent Res.2014 Nov;93(11):1045-53.\u003c/li\u003e\n\u003cli\u003eJiao J, Jing W, Si Y, Feng X, Tai B, Hu D, Lin H, Wang B, Wang C, Zheng S, Liu X, Rong W, Wang W, Li W, Meng H, Wang X.The prevalence and severity of periodontal disease in Mainland China: Data from the Fourth National Oral Health Survey (2015-2016).J Clin Periodontol.2021 Feb;48(2):168-179. \u003c/li\u003e\n\u003cli\u003eEsteves-Lima RP, Reis CS, Santirocchi-J\u0026uacute;nior F, Abreu LG, Costa FO. 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J Clin Periodontol. 2018 Jun;45 Suppl 20:S1-S8.\u003c/li\u003e\n\u003cli\u003eSILNESS J, LOE H. PERIODONTAL DISEASE IN PREGNANCY. II. CORRELATION BETWEEN ORAL HYGIENE AND PERIODONTAL CONDTION. Acta Odontol Scand. 1964 Feb;22:121-35. \u003c/li\u003e\n\u003cli\u003eMazza JE, Newman MG, Sims TN. Clinical and antimicrobial effect of stannous fluoride on periodontitis. 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Retrieved from https://www.cdc.gov/diabetes/php/data-research/index.html .\u003c/li\u003e\n\u003cli\u003eButler A, Targett D, Bosma ML. Maintenance of gingival health--a measure based on clinical indices. Int Dent J. 2011 Aug;61 Suppl 3(Suppl 3):28-32. \u003c/li\u003e\n\u003cli\u003eCarvalho AP, Moura MF, Costa FO, Cota LO. Correlations between different plaque indexes and bleeding on probing: A concurrent validity study. J Clin Exp Dent. 2023 Jan 1;15(1):e9-e16. \u003c/li\u003e\n\u003cli\u003eWang I-C, Chan H-L, Johnson GK, Elangovan S. Assessment of Negative Gingival Recession: A Critical Component of Periodontal Diagnosis. Applied Sciences. 2022; 12(14):7015. \u003c/li\u003e\n\u003cli\u003eBosma ML, McGuire JA, DelSasso A, Milleman J, Milleman K. Efficacy of flossing and mouth rinsing regimens on plaque and gingivitis: a randomized clinical trial. BMC Oral Health. 2024 Feb 3;24(1):178. \u003c/li\u003e\n\u003cli\u003eMdala I, Olsen I, Haffajee AD, Socransky SS, Thoresen M, de Blasio BF. Comparing clinical attachment level and pocket depth for predicting periodontal disease progression in healthy sites of patients with chronic periodontitis using multi-state Markov models. J Clin Periodontol. 2014 Sep;41(9):837-45. \u003c/li\u003e\n\u003cli\u003eTonetti MS, Greenwell H, Kornman KS. Staging and grading of periodontitis: Framework and proposal of a new classification and case definition. J Periodontol. 2018 Jun;89 Suppl 1:S159-S172. doi: 10.1002/JPER.18-0006. Erratum in: J Periodontol. 2018 Dec;89(12):1475.\u003c/li\u003e\n\u003cli\u003eRai J., Shah V., Shah M. Periodontitis Severity Grading Scale and C-Reactive Protein: A Possible Relation. Cureus. 2023;15:e41618. \u003c/li\u003e\n\u003cli\u003eUllah N, Ma FR, Han J, Liu XL, Fu Y, Liu YT, Liang YL, Ouyang H, Li HY. Monomeric C-reactive protein regulates fibronectin mediated monocyte adhesion. Mol Immunol. 2020 Jan;117:122-130. \u003c/li\u003e\n\u003cli\u003eFischer JE, Bachmann LM, Jaeschke R. A readers\u0026apos; guide to the interpretation of diagnostic test properties: clinical example of sepsis. Intensive Care Med. 2003 Jul;29(7):1043-51. \u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"clinical-oral-investigations","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"cloi","sideBox":"Learn more about [Clinical Oral Investigations](http://link.springer.com/journal/784)","snPcode":"784","submissionUrl":"https://submission.nature.com/new-submission/784/3","title":"Clinical Oral Investigations","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"Periodontitis, C-Reactive Protein,Fibrinogen,Probing Depth,Clinical Attachment Loss","lastPublishedDoi":"10.21203/rs.3.rs-8122125/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8122125/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eObjectives\u003c/strong\u003e: Periodontitis is a chronic inflammatory disease closely linked to systemic conditions. This study evaluated the clinical utility of systemic inflammatory markers and periodontal parameters in assessing periodontitis severity and explored their combined predictive value for identifying advanced disease.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMaterials and Methods:\u003c/strong\u003e A total of 215 participants were enrolled in a cross-sectional study and categorized into Stage I (2.3%), Stage II (9.3%), Stage III (63.3%), and Stage IV (25.1%) periodontitis based on clinical assessments. Periodontal parameters, including plaque index (PLI), gingival index (GI), bleeding index (BI), probing depth (PD), and clinical attachment loss (AL), were recorded. Venous blood samples were collected to determine serum C-reactive protein (CRP) and plasma fibrinogen (Fg) levels. Correlation analyses and multivariate binary logistic regression were performed to assess the relationships and predictive value of these parameters.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults\u003c/strong\u003e: Age differed significantly across disease stages (P \u0026lt; 0.05), while gender, hypertension, and diabetes did not (P \u0026gt; 0.05). PD, AL, CRP, and Fg increased progressively with disease severity (P \u0026lt; 0.05), whereas PLI, GI, and BI showed no significant trends. CRP correlated with PD, AL, and Fg (P \u0026lt; 0.05). The predictive model combining CRP, Fg, PD, and AL achieved an AUC of 0.885. Logistic regression identified CRP (OR: 1.97), PD (OR: 1.47), and AL (OR: 1.98) as independent predictors of Stage IV periodontitis (P \u0026lt; 0.05), while Fg lost significance after adjustment (P = 0.107).\u003c/p\u003e\n\u003cp\u003eConclusion: A composite model integrating CRP, Fg, PD, and AL effectively predicts periodontitis severity, supporting its use for early detection and personalized management.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eClinical Relevance: \u003c/strong\u003eCRP and Fg, widely recognized as inflammatory mediators in systemic disease, are also implicated in periodontal inflammation. By combining CRP, Fg, PD, and AL, we developed a predictive model that provides a comprehensive and clinically meaningful tool for identifying patients at high risk of severe periodontitis.\u003c/p\u003e","manuscriptTitle":"Association and Predictive Value of C-Reactive Protein, Fibrinogen and Periodontal Indices in Periodontitis Severity : A Retrospective study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-12-02 13:40:31","doi":"10.21203/rs.3.rs-8122125/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-12-09T10:30:45+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-12-08T07:41:34+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-12-06T10:58:52+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"337340498130567565789995920039314819423","date":"2025-12-01T20:04:49+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"191971189521875482272278226093930661962","date":"2025-11-25T11:16:39+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-11-25T11:04:26+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-11-18T08:57:00+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-11-18T08:54:54+00:00","index":"","fulltext":""},{"type":"submitted","content":"Clinical Oral Investigations","date":"2025-11-15T12:41:46+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"clinical-oral-investigations","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"cloi","sideBox":"Learn more about [Clinical Oral Investigations](http://link.springer.com/journal/784)","snPcode":"784","submissionUrl":"https://submission.nature.com/new-submission/784/3","title":"Clinical Oral Investigations","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"4fc38062-fde9-4644-b1f2-d8e0664071e6","owner":[],"postedDate":"December 2nd, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2026-03-16T16:02:42+00:00","versionOfRecord":{"articleIdentity":"rs-8122125","link":"https://doi.org/10.1007/s00784-026-06775-1","journal":{"identity":"clinical-oral-investigations","isVorOnly":false,"title":"Clinical Oral Investigations"},"publishedOn":"2026-03-13 15:59:16","publishedOnDateReadable":"March 13th, 2026"},"versionCreatedAt":"2025-12-02 13:40:31","video":"","vorDoi":"10.1007/s00784-026-06775-1","vorDoiUrl":"https://doi.org/10.1007/s00784-026-06775-1","workflowStages":[]},"version":"v1","identity":"rs-8122125","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8122125","identity":"rs-8122125","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}