Autor: |
Gamil, Omar Khaled, Ahmed, Dina Fahim, Keraa, Khaled Mohamed, Ghallab, Noha Ayman, Elbattawy, Weam |
Předmět: |
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Zdroj: |
Archives of Orofacial Science; Dec2021, Vol. 16 Issue 2, p223-239, 17p |
Abstrakt: |
This hospital-based cross-sectional study aimed at determining frequency and risk indicators/predictors of periodontitis in a sample of Egyptian adult population and to develop a prediction equation for classifying periodontal diseases. Seven hundred and fifty subjects were consecutively recruited from outpatient Diagnostic Center, Faculty of Dentistry, Cairo University. Validated oral health questionnaire for adults and oral health impact profile-14 (OHIP-14) questionnaire were filled by all patients. Diagnosis was made based on measurements of clinical periodontal parameters including plaque index, bleeding on probing, pocket depth, clinical attachment level and gingival recession. Radiographic examination was performed using digital periapical radiographs. Ordinal logistic regression analysis was used to determine significant predictors of periodontal diseases and discriminant analysis was performed to predict periodontal disease classification. Gingivitis was the most frequent periodontal disease (39.6%) followed by periodontitis stage I (38%), stage II (20.4%), stage III (1.6%) and stage IV (0.4%). The lowest OHIP-14 scores were in patients with periodontitis stages III and IV. Multivariate analysis showed that education (p < 0.001), OHIP-14 score (p = 0.003), non-smoking (p = 0.001) and non-alcohol drinking (p = 0.021) were significant negative predictors, while never to clean the teeth (p <0.001) and cleaning the teeth once a month (p < 0.001) were significant positive predictors of periodontal disease. Periodontitis stages III and IV were the least frequent on a sample of Egyptian adult patients. Education, frequency of teeth cleaning, smoking, alcohol drinking and OHIP-14 scores were significant predictors of periodontal disease. Through discriminant analysis this study could classify patients into different periodontal diseases with an overall correct prediction of 99.2%. [ABSTRACT FROM AUTHOR] |
Databáze: |
Complementary Index |
Externí odkaz: |
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