Type 2 diabetes mellitus (T2DM) is increasingly known as a risk factor of hepatocellular carcinoma (HCC). In this study, we determined the risk factors associated with HCC in T2DM patients. This was a matched case-control study conducted at two hepatobiliary referral centres in a developing country. Patients’ sociodemographic, clinical, and biochemical characteristics between 1 January 2012 and 30 June 2018 were extracted from the electronic medical records and analysed using multivariate logistic regression analysis. A total of 212 case-control pairs were included. Significant risk factors included Chinese and Malay ethnicities that interacted with viral hepatitis (adjusted odds ratio [AOR] = 11.77, 95% confidence interval [CI]: 1.39–99.79) and (AOR = 37.94, 95% CI: 3.92–367.61) respectively, weight loss (AOR = 5.28, 95% CI: 2.29–12.19), abdominal pain/ discomfort (AOR = 6.73, 95% CI: 3.34–13.34), alcohol (AOR = 4.08, 95% CI: 1.81–9.22), fatty liver (AOR = 3.29, 95% CI: 1.40–7.76), low platelet (AOR = 4.03, 95% CI:1.90–8.55), raised alanine transaminase (AOR = 2.11, 95% CI: 1.16–3.86). and alkaline phosphatase (ALP) levels (AOR = 2.17, 95% CI: 1.17–4.00). Statins reduced the risk of HCC by 63% (AOR = 0.37, 95% CI: 0.21–0.65). The identification of these factors aids the risk stratification for HCC among T2DM patients for early detection and decision-making in patient management in the primary care setting.
The increasing involvement of women in the paid-labor market has led to multifactorial exposure towards the development of noncommunicable diseases (NCDs). This review aims to identify the prevalence of NCDs and the associated risk factors among working women. A systematic review was performed using PubMed and Scopus databases. Twelve articles published between 2015 and 2019 satisfied the inclusion and exclusion criteria and were selected for qualitative synthesis. Among working women, the prevalence of NCDs was as follows: coronary heart disease, 0.3%–5.9%; metabolic syndrome, 52.0%; diabetes mellitus, 8.9%–16.0%; hypertension, 16.6%–66.4%; non-skin cancer, 3.7%. The prevalence of NCD risk factors was as follows: overweight/obesity, 33.8%–77.0%; low physical activity, 51.0%; unhealthy diet, 44.9%–69.9%; dyslipidemia, 27.8%–44.0%. The factors associated with NCDs were long working hours, double work burden, and stress. NCD is an important burden of working women that will lead to reduced work quality and affect family well-being. Disease prevention approaches, such as the intervention of common workplace risk factors and specific work schedule design, are among the strategies for improving the situation.
BackgroundWith the rise in prevalence of childhood tuberculosis (TB) globally, contact tracing should be a powerful strategy for early diagnosis and management, especially in children who are household contacts of active TB cases. Here, we aimed to determine the prevalence and factors associated with TB disease in children who are household contacts of TB cases.MethodsWe used a cross-sectional study with data from the Malaysian TB Information System (TBIS) recorded from 1 January 2014 to 31 December 2017. All children aged 0–14 years who were registered in the TBIS with at least one household contact of TB cases were included in the study. Multiple logistic regression analysis was performed to calculate the adjusted odds ratio (adj. OR) and for adjusting the confounding factors.ResultsA total of 2793 children were included in the study. The prevalence of active TB was 1.5% (95% confidence interval [CI]: 1.31, 1.77%). Children aged < 5 years [adj. OR 9.48 (95% CI: 3.41, 26.36) p < 0.001] with positive tuberculin skin test [adj. OR 395.73 (95% CI: 134.17, 1167.13), p < 0.001] and investigation period of > 6 weeks [adj. OR 7.48 (95% CI: 2.88, 19.43), p < 0.001] had significantly higher odds for TB disease.ConclusionsThe prevalence of TB disease in children who were household contacts of TB cases is relatively low. However, contact tracing programmes should not only focus on children aged < 5 years and with positive tuberculin skin test results, but also be empowered to reduce the investigation period.
Background: The insecticides used widely has led to resistance in the vector and impose a challenge to vector control op- eration. Objectives: This review aims to analyse the distribution of insecticide resistance of dengue vectors in South East Asia and to describe the mechanism of insecticide resistance. Methods: Literature search for articles published on 2015 to 2019 from PubMed, Scopus and ProQuest was performed. Total of 37 studies included in the final review from the initial 420 studies. Results: Pyrethroid resistance was concentrated on the west coast of Peninsular Malaysia and Northern Thailand and scat- tered at Java Island, Indonesia while organophosphate resistance was seen across the Java Island (Indonesia), West Sumatera and North Peninsular Malaysia. Organochlorine resistance was seen in Sabah, Malaysia and scattered distribution in Nusa Tenggara, Indonesia. V1016G, S989P, F1269C gene mutation in Aedes Aegypti were associated with Pyrethroid resistance in Singapore and Indonesia. In Malaysia, over-expressed with monooxygenase P450 genes (CYP9J27, CYP6CB1, CYP9J26 and CYP9M4) Glutathione S-transferases, carboxylesterases commonly associated with pyrethroids resistance in Aedes Aegypti and CYP612 overexpressed in Aedes Albopictus. The genetic mutation in A302S in Aedes Albopictus was associated with organochlorine resistance in Malaysia. Conclusions: Rotation of insecticide, integration with synergist and routine assessment of resistance profile are recom- mended strategies in insecticide resistance management. Keywords: Insecticide resistance; vector management; Aedes; pyrethroid; mortality.
The application of artificial intelligence (AI) is on the rise in the healthcare industry. However, the study on the physicians’ perspectives is still lacking. The study aimed to examine physicians’ attitudes, expectations, and concerns regarding the application of AI in medicine. A cross-sectional study was conducted in October 2019 among physicians in a tertiary teaching hospital in Malaysia. The survey used a validated questionnaire from the literature, which covered: (1) socio-demographic profile; (2) attitude towards the application of AI; (3) expected application in medicine; and (4) possible risks of using AI. Comparison of the mean score between the groups using a t-test or one-way analysis of variance (ANOVA). A total of 112 physicians participated in the study: 64.3% from the clinical departments; 35.7% from the non-clinical specialties. The physicians from non-clinical departments had significantly higher mean attitude score (mean = 14.94 ± 3.12) compared to the clinical (person-oriented) departments (mean = 14.13 ± 3.10) and clinical (technique-oriented) departments (mean = 13.06 ± 2.88) (p = 0.033). The tech-savvy participants had a significantly higher mean attitude score (mean = 14.72 ± 3.55) than the non–tech-savvy participants (mean = 13.21 ± 2.46) (p = 0.01). There are differences in the expectations among the respondents and some concerns exist especially on the legal aspect of AI application in medicine. Proper training and orientation should precede its implementation and must be appropriate to the physicians’ needs for its utilization and sustainability.
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