Assessment of Oral Health Status and Pregnancy Outcomes Among Women in Saudi Arabia.

Purpose: Pregnant women witness many changes in the body as well as in the oral cavity with many factors influencing these changes. This study evaluated the relationship between oral health status, perceptions, and pregnancy outcomes. Methods: A cross sectional study design was implemented to recruit a convenience sample of women attending Obstetrics and gynecology department in public hospitals in East and capital city of Saudi Arabia. To collect data, a validated self-administered questionnaire in English and Arabic was used. The questionnaire covered background information, perceived oral health status, and dental visits. Results: About 64.4% of the 481 women recruited had dental problems, 49.7% reported deterioration in their oral health during pregnancy, and 17.5% reported adverse pregnancy outcomes. Only 40.7% of pregnant women rated their oral health as good, and only 22% visited a dentist during their pregnancy. Dentists were the most common source of oral health information (44.1%), followed by social media (38.9%). Dental problems during pregnancy were significantly associated with adverse outcomes (P=0.007). Oral health perceptions of pregnant women, not visiting the dentist during pregnancy, and gingival problems were also significantly associated with adverse pregnancy outcomes (P=0.001). Those with fair to poor oral health were twice as likely to experience adverse pregnancy outcome. Those who intended to visit the dentist during their pregnancy but did not do so, as well as those who did not visit the dentist at all were 12 and 9 times more likely to experience adverse pregnancy outcomes respectively. Conclusion: Dental complaints during pregnancy, oral health perceptions, and a lack of dental visits were all linked to increased likelihood of adverse pregnancy outcomes. There is a need for interprofessional collaboration to dispel myths and encourage oral health care and regular dental visits during pregnancy.

Accuracy of Al Algorithms in Diagnosing Periodontal Disease Using Intraoral Images.

Background: Periodontal disease, characterized by inflammation and damage to tooth-supporting structures, poses a prevalent oral health concern. Early detection is crucial for effective management. Materials and Methods: This study comprised of 60 patients with varying degrees of periodontal disease. Intraoral images were captured using digital cameras, and AI algorithms were trained to analyze these images for signs of periodontal disease. Clinical diagnoses, conducted by experienced periodontal specialists, were used as the reference standard. Results: The AI algorithms achieved an overall accuracy of 87% in diagnosing periodontal disease. Sensitivity was 90%, indicating the AI's ability to correctly identify 90% of true cases, while specificity stood at 84%, demonstrating its capability to accurately classify 84% of non-diseased cases. In comparison, clinical diagnosis yielded an overall accuracy of 86%. Statistical analysis showed no significant difference between AI-based diagnosis and clinical examination (P > 0.05). Conclusion: This study underscores the promising potential of AI algorithms in diagnosing periodontal disease through intraoral image analysis.

Comparison of Digital Planimetry and Ruler Methods for the Measurement of Extraction Socket Wounds.

Background and objectives: The purpose of the study was to evaluate and compare ruler and digital planimetry methods to measure extraction socket wounds. Materials and Methods: In total, 41 extraction socket wounds were selected for assessment of wound area by ruler and digital planimetry methods. In the simple ruler method, the periodontal probe was utilized to measure the length and breadth of the extraction wound, whereas in the digital planimetry technique, Pictzar software was used. Data were analyzed using R software version 4.1.1 and Excel. For intergroup comparisons of wound surface area, Welch t-tests were used, and paired t-tests were used for intragroup comparisons. Intra-class correlation coefficients (ICC) and 95% confidence intervals (CIs) were used to evaluate the inter-method reliabilities of surface area. Results: Both ruler and digital planimetry techniques showed post-operative reductions in surface area. A significant difference was reported between the two techniques; however, the ruler method measurements were overestimated compared to those obtained with digital planimetry. Conclusions: This study concludes that digital planimetry techniques provide more accurate results when compared with the simple ruler method.