Maternal smoking during pregnancy and early childhood dental caries in children: a systematic review and meta-analysis.

BACKGROUND: Early childhood dental caries, or ECC, is a significant global oral health concern associated with various adverse outcomes. This systematic review and meta-analysis aimed to investigate the potential link between maternal smoking during pregnancy and the occurrence of dental caries in children. METHOD: Through a comprehensive search of PubMed, Scopus, and Google Scholar databases for studies examining the correlation between maternal smoking during pregnancy and childhood caries, we identified 609 relevant articles up to October 2023. Studies were selected, and data extraction was based on the pre-established eligibility criteria and items. Meta-analysis was executed utilizing Comprehensive Meta-analysis (CMA) with a random effects model, ensuring a robust synthesis of the gathered evidence. RESULT: 7 cohorts and five cross-sectional studies, totaling 12 studies, were included in our analysis. The combined results from the studies revealed a significant association between maternal smoking during pregnancy and an increased risk of dental caries in children (OR = 1.78, 95% CI = 1.55-2.05, I2 = 68.53). Sensitivity analyses confirmed the reliability of our results. However, there were indications of publication bias, as suggested by the funnel plot and Egger's test (P = 0.011) concerning the connection between prenatal smoking and childhood caries. CONCLUSION: This review underscores the association between maternal smoking during pregnancy and childhood dental caries. Nevertheless, confounding variables influence this link, necessitating more large-scale, longitudinal studies with adjusted factors. Additional randomized control trials are needed to validate these findings due to the observed heterogeneity. Future research should investigate the precise reasons behind this association. It is essential to raise awareness among pregnant women about the risks of smoking through educational programs.

Medical, dental, and nursing students' attitudes and knowledge towards artificial intelligence: a systematic review and meta-analysis.

BACKGROUND: Nowadays, Artificial intelligence (AI) is one of the most popular topics that can be integrated into healthcare activities. Currently, AI is used in specialized fields such as radiology, pathology, and ophthalmology. Despite the advantages of AI, the fear of human labor being replaced by this technology makes some students reluctant to choose specific fields. This meta-analysis aims to investigate the knowledge and attitude of medical, dental, and nursing students and experts in this field about AI and its application. METHOD: This study was designed based on PRISMA guidelines. PubMed, Scopus, and Google Scholar databases were searched with relevant keywords. After study selection according to inclusion criteria, data of knowledge and attitude were extracted for meta-analysis. RESULT: Twenty-two studies included 8491 participants were included in this meta-analysis. The pooled analysis revealed a proportion of 0.44 (95%CI = [0.34, 0.54], P < 0.01, I2 = 98.95%) for knowledge. Moreover, the proportion of attitude was 0.65 (95%CI = [0.55, 0.75], P < 0.01, I2 = 99.47%). The studies did not show any publication bias with a symmetrical funnel plot. CONCLUSION: Average levels of knowledge indicate the necessity of including relevant educational programs in the student's academic curriculum. The positive attitude of students promises the acceptance of AI technology. However, dealing with ethics education in AI and the aspects of human-AI cooperation are discussed. Future longitudinal studies could follow students to provide more data to guide how AI can be incorporated into education.