MATERIALS AND METHODS: A prospective observational study was conducted between 1st October 2021 till September 2022 in the state of Johor, Malaysia. 300 patients with confirmed SARS-CoV-2 infection were randomly selected and followed up for six months. Data were analysed by using Chi-square test, Fisher's Exact test, Paired t test and Multiple logistic regression.
RESULTS: The prevalence of short-term neuropsychiatric symptoms was 78%, with anosmia being the most prevalent symptom. Long-term symptoms were found in 22.75% of patients, with headache being the most prevalent (p= 0.001). COVID-19 Stage 2 and 3 infections were associated with a higher risk of short-term neuropsychiatric symptoms, OR for Stage 2 infection was 5.18 (95% CI: 1.48-16.97; p=0.009) and for Stage 3 infection was 4.52 (95% CI: 1.76-11.59; p=0.002). Complete vaccination was a significant predictor of longterm symptoms with adjusted OR 3.65 (95% CI 1.22-10.91; p=0.021).
CONCLUSION: This study demonstrated that neuropsychiatric symptoms were common among COVID-19 patients in Johor, Malaysia and the risk of these symptoms was associated with the severity of the infection. Additionally, complete vaccination does not completely protect against long-term neuropsychiatric deficits. This is crucial for continuous monitoring and addressing neuropsychiatric symptoms in COVID-19 survivors.
METHODS: This systematic review was registered prospectively on Prospero (CRD42020188715). It was designed using the COSMIN guidelines and reported in line with the PRISMA checklist. Two reviewers independently searched Medline, Embase, SportDiscus, and CINAHL Plus databases from inception to the 24th July 2022 with an update of the search conducted until 14th of October 2023. The COSMIN risk of bias checklist was used to assess the risk of bias in each study. The updated criteria for good measurement properties were used to rate individual studies and then the overall pooled results. The level of evidence was rated by two reviewers independently using a modified GRADE approach.
RESULTS: Fifteen studies were included in this review, 13 reporting absolute JPE and 2 reporting constant JPE. The measurement properties assessed were reliability, measurement error, and validity. The measurement of JPE showed sufficient reliability and validity, however, the level of evidence was low/very low for both measurement properties, apart from convergent validity of the constant JPE, which was high.
CONCLUSION: The measure of cervical JPE showed sufficient reliability and validity but with low/very low levels of evidence. Further studies are required to investigate the reliability and validity of this test as well as the responsiveness of the measure.
RESULTS: Thus, this study presents comprehensive robustness evaluations of seven widely used pathway activity inference methods using six cancer datasets based on two assessments. The first assessment seeks to investigate the robustness of pathway activity in pathway activity inference methods, while the second assessment aims to assess the robustness of risk-active pathways and genes predicted by these methods. The mean reproducibility power and total number of identified informative pathways and genes were evaluated. Based on the first assessment, the mean reproducibility power of pathway activity inference methods generally decreased as the number of pathway selections increased. Entropy-based Directed Random Walk (e-DRW) distinctly outperformed other methods in exhibiting the greatest reproducibility power across all cancer datasets. On the other hand, the second assessment shows that no methods provide satisfactory results across datasets.
CONCLUSION: However, PTB methods generally appear to perform better in producing greater reproducibility power and identifying potential cancer markers compared to non-TB methods.
METHODS: A total of 255 dental students in Universiti Malaya completed the modified Index of Learning Styles (m-ILS) questionnaire containing 44 items which classified them into their respective LS. The collected data, referred to as dataset, was used in a decision tree supervised learning to automate the mapping of students' learning styles with the most suitable IS. The accuracy of the ML-empowered IS recommender tool was then evaluated.
RESULTS: The application of a decision tree model in the automation process of the mapping between LS (input) and IS (target output) was able to instantly generate the list of suitable instructional strategies for each dental student. The IS recommender tool demonstrated perfect precision and recall for overall model accuracy, suggesting a good sensitivity and specificity in mapping LS with IS.
CONCLUSION: The decision tree ML empowered IS recommender tool was proven to be accurate at matching dental students' learning styles with the relevant instructional strategies. This tool provides a workable path to planning student-centered lessons or modules that potentially will enhance the learning experience of the students.
METHODS: This cross-sectional study employed qualitative and quantitative methods and used an inductive approach and thematic content analysis to analyze online commentaries on news articles published on popular online news portals from November 2018 to August 2019. Data was collected by downloading the commentaries onto Microsoft Word and importing them into NVivo.
RESULTS: Of the commentaries analyzed, 60.9% rejected the SSBs tax, and 39.1% favored it. No association was found between the online news articles and the slants of the commentaries.
CONCLUSION: The results of this study demonstrate a clear divide in public opinion regarding the SSBs tax in Malaysia, with many online readers expressing opposition to the tax despite evidence of the harmful effects of sugar presented in the articles they are commenting on. These findings have implications for policymakers and public health advocates seeking to implement similar taxes in the future.
METHODOLOGY: We conducted a retrospective data retrieval from the medical records of 254 paediatric patients who had been diagnosed with confirmed cases of dengue fever. The clinical characteristics were compared between severe and non-severe dengue. Multiple logistic regression analysis was utilised to elucidate the variables that exhibited associations with severe dengue.
RESULTS: A total of 254 paediatric patients were included, among whom 15.4% (n = 39) were diagnosed with severe dengue. Multiple logistic regression analysis identified lethargy, systolic blood pressure (SBP) below 90 mmHg, capillary refilled time (CRT) longer than 2 seconds, ascites, and hepatomegaly were independently associated with severe dengue.
CONCLUSION: In paediatric patients, severe dengue is associated with specific clinical indicators, including lethargy, low systolic blood pressure, prolonged capillary refill time (CRT), and the presence of ascites and hepatomegaly. Identifying these clinical features early is crucial for primary care physicians, as it enables accurate diagnosis and timely intervention to manage severe dengue effectively.