MATERIALS AND METHODS: This research used observational analytic methods with cross-sectional design. The sample in this study was young women (9th class students), totaling 39 people. This study used the IPAQ Questionnaire Sheet and pain scale rate to confirm dysmenorrhoea. Analysis of this study used chi square.
RESULTS: We found that most respondents (61.5%) had dysmenorrhoea, and more than half of respondents (61.5%) rarely did Physical Activity. Bivariate test results found that there is a relationship between Physical Activity level and dysmenorrhoea (p value = 0.044, α = 0.05, df = 3). From the analysis results, the value of OR = 4.500 was also obtained, meaning that respondents who did not exercise regularly had a 4.5 times chance of experiencing dysmenorrhea compared to respondents who did regular exercise.
CONCLUSION: Respondents who rarely do physical activity often experience dysmenorrhoea. Therefore, good education is needed for young women, which is one of the things that can be done to prevent and reduce the event of dysmenorrhoea is to exercise regularly.
METHODS: A cross-sectional study was conducted among students from 13 dental schools across Malaysia using online questionnaires.
RESULTS: From 355 respondents, 93.5% obtained a high score of knowledge of COVID-19. Female respondents scored higher than males in perceived risks and preventive behaviors. Chinese respondents scored highest in knowledge, while Malay respondents had the highest perceived risk score. The mean preventive behavior score did not vary across ethnicity. On-campus students scored higher in knowledge and perceived risk whereas off-campus students practiced more preventive behaviors. Clinical students' knowledge score was higher than preclinical students. Final year students scored higher in knowledge and perceived risk compared to their juniors.
CONCLUSION: The majority of dental students have good knowledge and a high perceived risk of COVID-19, and they practiced most of the preventive behaviors. However, the latest information on this disease should be incorporated into dental schools' curriculums and updated periodically.
METHODS: ML algorithms logistic regression (LR), decision tree (DT), random forest (RF), and support vector machine (SVM) models were applied. Academic performance prediction in pre-clinical years was made using three input parameters: age during admission, pre-university Cumulative Grade Point Average (CGPA), and total matriculation semester. PCC was deployed to identify the correlation between pre-university CGPA and dental school grades. The proposed models' classification accuracy ranged from 29% to 57%, ranked from highest to lowest as follows: RF, SVM, DT, and LR. Pre-university CGPA was shown to be predictive of dental students' academic performance; however, alone they did not yield optimal outcomes. RF was the most precise algorithm for predicting grades A, B, and C, followed by LR, DT, and SVM. In forecasting failure, LR predicted three grades with the highest recall, SVM predicted two grades, and DT predicted one. RF performance was insignificant.
CONCLUSION: The findings demonstrated the application of ML algorithms and PCC to predict dental students' academic performance. However, it was limited by several factors. Each algorithm has unique performance qualities, and trade-offs between different performance metrics may be necessary. No definitive model stood out as the best algorithm for predicting student academic success in this study.
METHODS: In the current study, we performed quantitative real-time PCR to measure salivary levels of C-reactive protein (CRP) and interleukin-6 (IL-6) in saliva obtained from patients diagnosed with mild COVID-19, in a diabetic group (DG; n = 10) and a non-diabetic group (NDG; n = 13). All participants were diagnosed with periodontitis, while six participants with periodontitis but not diagnosed with COVID-19 were included as controls.
RESULTS: We found increases in salivary total protein levels in both the DG and NDG compared to control patients. In both groups, salivary CRP and IL-6 levels were comparable. Additionally, the levels of salivary CRP were significantly correlated with total proteins, in which a strong and moderate positive correlation was found between DG and NDG, respectively. A linear positive correlation was also noted in the relationship between salivary IL-6 level and total proteins, but the correlation was not significant. Interestingly, the association between salivary CRP and IL-6 levels was positive. However, a moderately significant correlation was only found in COVID-19 patients with diabetes, through which the association was validated by a receiver operating curve.
CONCLUSIONS: These finding suggest that salivary CRP and IL-6 are particularly relevant as potential non-invasive biomarker for predicting diabetes risk in mild cases of COVID-19 accompanied with periodontitis.