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Salivary E‐cadherin as a biomarker for diagnosis and predicting grade of periodontitis
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Abstract<sec><title>Objectives

To determine the abilities of salivary E‐cadherin to differentiate between periodontal health and periodontitis and to discriminate grades of periodontitis.

Background

E‐cadherin is the main protein responsible for maintaining the integrity of epithelial‐barrier function. Disintegration of this protein is one of the events associated with the destructive forms of periodontal disease leading to increase concentration of E‐cadherin in the oral biofluids.

Materials and Methods

A total of 63 patients with periodontitis (case) and 35 periodontally healthy subjects (control) were included. For each patient, periodontal parameters including bleeding on probing (BOP), probing pocket depth (PPD), and clinical attachment level (CAL) were recorded. Concentration of salivary E‐cadherin was determined by ELISA. Receiver operating characteristic (ROC) curve and area under the curve (AUC) were used to determine the diagnostic potentials of E‐cadherin.

Results

Level of salivary E‐cadherin was significantly higher in periodontitis cases than controls. The ROC analysis showed that salivary E‐cadherin exhibits excellent sensitivity and specificity (AUC 1.000) to differentiate periodontal health from periodontitis with a cutoff concentration equal to 1.325 ng/mL. The AUCs of E‐cadherin to differentiate grade A from grade B and C periodontitis were 0.731 (cutoff point = 1.754 ng/mL) and 0.746 (cutoff point = 1.722 ng/mL), respectively. However, the AUC of salivary E‐cadherin to differentiate grade B from grade C periodontitis was lower (0.541). Additionally, BOP and PPD were significantly and positively correlated with the concentration of salivary E‐cadherin.

Conclusion

Salivary E‐cadherin exhibited excellent sensitivity and specificity to differentiate periodontitis from a healthy periodontium. The level of accuracy of E‐cadherin was also sufficient to recognize grade A periodontitis from grade B and C periodontitis.

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. مجلة العلوم الزراعية العراقية 26 (1), 84-87
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Proposing Robust IRWs Technique to Estimate Segmented Regression Model for the Bed load Transport of Tigris River with Change Point of Water Discharge Amount at Baghdad City
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