DESIGN: A population-based cross-sectional study.
SETTING: 13 states and 3 Federal Territories in Malaysia.
PARTICIPANTS: A total of 3966 adults aged 60 years and above were extracted from the nationwide National Health and Morbidity Survey (NHMS) 2018 data set.
PRIMARY OUTCOME MEASURES: Multimorbidity was defined as co-occurrence of at least two known chronic non-communicable diseases in the same individual. The chronic diseases included hypertension, type 2 diabetes mellitus, dyslipidaemia and cancer.
RESULTS: The prevalence of multimorbidity among Malaysian older adults was 40.6% (95% CI: 37.9 to 43.3). The factors associated with multimorbidity were those aged 70-79 years (adjusted OR (AOR)=1.30; 95% CI=1.04 to 1.63; p=0.019), of Indian (AOR=1.69; 95% CI=1.14 to 2.52; p=0.010) and Bumiputera Sarawak ethnicities (AOR=1.81; 95% CI=1.14 to 2.89; p=0.013), unemployed (AOR=1.53; 95% CI=1.20 to 1.95; p=0.001), with functional limitation from activities of daily livings (AOR=1.66; 95% CI=1.17 to 2.37; p=0.005), physically inactive (AOR=1.28; 95% CI=1.03 to 1.60; p=0.026), being overweight (AOR=1.62; 95% CI=1.11 to 2.36; p=0.014), obese (AOR=1.88; 95% CI=1.27 to 2.77; p=0.002) and with abdominal obesity (AOR=1.52; 95% CI=1.11 to 2.07; p=0.009).
CONCLUSION: This study highlighted that multimorbidity was prevalent among older adults in the community. Thus, there is a need for future studies to evaluate preventive strategies to prevent or delay multimorbidity among older adults in order to promote healthy and productive ageing.
METHODS: We identified all HCWs at Hamad Medical Corporation in Qatar between December 20, 2020 and May 18, 2021 with confirmed SARS-CoV-2 RT-PCR infection >14 days after the second vaccine dose. For each case thus identified, we identified one control with a negative test after December 20, 2020, matched on age, sex, nationality, job family and date of SARS-CoV-2 testing. We excluded those with a prior positive test and temporary workers. We used Cox regression analysis to determine factors associated with breakthrough infection.
RESULTS: Among 22,247 fully vaccinated HCW, we identified 164 HCW who had breakthrough infection and matched them to 164 controls to determine the factors associated with SARS-CoV-2 breakthrough infection. In the breakthrough infection group the nursing and midwifery job family constituted the largest group, spouse was identified as the most common positive contact followed by a patient. Exposure to a confirmed case, presence of symptoms and all other job families except Allied Health Professionals when compared with nursing and Midwifery staff independently predicted infection.
CONCLUSION: Presence of symptoms and contact with a confirmed case are major risk factors for breakthrough SARS-CoV-2 infection after vaccination, and these groups should be prioritized for screening even after full vaccination.
METHODS: A wellness program was conducted to determine the presence of antibodies against Leptospira (seroprevalence) in 11 refugee community schools and centers in the Klang Valley, Malaysia. A total of 433 samples were assessed for IgG and IgM antibodies against Leptospira, using enzyme-linked immunosorbent assays (ELISA).
RESULTS: Overall Leptospira seroprevalence was 24.7%, with 3.0% being seropositive for anti-Leptospira IgG and 21.7% for anti-Leptospira IgM. Factors significantly associated with overall Leptospira seroprevalence included: age, ethnicity, pet ownership, knowledge of disease and awareness of disease fatality. For IgM seroprevalence, significant risk factors included sex, ethnicity, eating habits with hands, pet ownership, the presence of rats, walking in bare feet and water recreation visits.
CONCLUSIONS: These findings highlight the need for improvements in health and well-being among the refugee community through disease awareness programs and provision of healthy behavior programs, particularly in hygiene and sanitation through community engagement activities.
RECENT FINDINGS: Methods of acquisition and analysis of BPV and cognitive measurements and their relationship were extracted from selected articles. Of 656 studies identified, 53 articles were selected. Twenty-five evaluated long-term (LTBPV), nine mid-term (MTBPV), 12 short-term (STBPV) and nine very short-term BPV (VSTBPV) with conflicting findings on the relationship between BPV and cognition. Variations existed in devices, period and procedure for acquisition. The studies also utilized a wide range of methods of BPV calculation. Thirteen cognitive assessment tools were used to measure global cognition or domain functions which were influenced by the population of interest. The interpretation of available studies was hence limited by heterogeneity. There is an urgent need for standardization of BPV assessments to streamline research on BPV and cognition. Future studies should also establish whether BPV could be a potential modifiable risk factor for cognitive decline, as well as a marker for treatment response.
Methods: An analytical cross-sectional study was performed, including 223 patients treated by the Cardiology Department, the Emergency Interventional Cardiology Departments, and the Internal Cardiology Clinic of Thong Nhat Hospital.
Results: In our cohort of 223 patients, the NAFLD was detected in 66% of the population, the mean coronary artery stenosis (CAS) was 44.54% ± 20.23%, and the mean coronary artery calcium score (CACS) was 3569.05 ± 425.99, as assessed using the Agatston method. The proportion of patients with significant atherosclerotic plaque (CAS 50%) >was 32%, whereas the remaining 68% had insignificant stenosis. Among our study population, 16% had no coronary artery calcification, 38% had mild calcification, and 46% had moderate to severe calcification. In the group of NAFLD patients, 33.3% had significant atherosclerotic plaque, which was not significantly different from the rate in individuals without NAFLD (p = 0.51). Mild coronary artery calcification was detected in 37.4% of NAFLD patients, and moderate to severe calcification was detected in 48.3% (p = 0.45).
Conclusions: NAFLD was not found to be strongly associated with coronary atherosclerosis in this study. More studies with larger sample sizes remain necessary to verify whether any correlation exists.
METHODS AND MATERIALS: A retrospective cross-sectional study involving 80 haemodialysis (HD) patients recruited from March 2020 till March 2021. Patients' information and results was retrieved and evaluated. Risk factors affecting the COVID-19 mortality were analysed using a one-way analysis of variance (ANOVA) and binary logistic regression.
RESULTS: The mean age of the patients was 54 years who were predominantly Malays (87.5%) and living in rural areas. Majority of them had comorbidities such as diabetes mellitus (71%) and hypertension (90%). The most common presentations were fever (46%) and cough (54%) with chest radiographs showing bilateral lower zone ground glass opacities (45%). A quarter of the study population were admitted to the intensive care unit, necessitating mechanical ventilation. This study found that 51% of the patients were given steroids and 45% required oxygen supplementation. The COVID-19 infection mortality among the study population was 12.5%. Simple logistic regression analysis showed that albumin, Odd Ratio, OR=0.85 (95% Confidence Interval, 95%CI: 0.73, 0.98)) and absolute lymphocyte count OR=0.08 (95%CI: 0.11, 0.56) have inverse association with COVID-19 mortality. C-reactive protein OR=1.02 (95%CI: 1.01, 1.04), lactate dehydrogenase OR=1.01 (95%CI: 1.00, 1.01), mechanical ventilation OR=17.21 (95%CI: 3.03, 97.67) and high dose steroids OR=15.71 (95%CI: 1.80, 137.42) were directly associated with COVID-19 mortality.
CONCLUSION: The high mortality rate among ESKD patients receiving HD was alarming. This warrants additional infection control measures to prevent the spread of COVID- 19 infection among this vulnerable group of patients. Expediting vaccination efforts in this group of patients should be advocated to reduce the incidence of complications from COVID-19 infection.
Patients and Methods: A total of 253 participants aged 60 years and above participated in this cross-sectional study. The participants were subjected to pure tone audiometric assessment. The hearing threshold was calculated for the better ear and classified into pure-tone average (PTA) for the octave frequencies from 0.5 to 4 kHz and high-frequency pure-tone average (HFA) for the octave from 2 to 8kHz. Then, the risk factors associated with PTA hearing loss (HL) and HFAHL were identified by using multivariate logistic regression analysis.
Results: The prevalence of ARHL based on PTA and HFA among the community-dwelling older adults was 75.5% and 83.0%, respectively. Following multifactorial adjustments, being older (OR: 1.239; 95% CI: 1.062-1.445), having higher waist circumference (OR: 1.158; 95% CI: 1.015-1.322), lower intake of niacin (OR: 0.909; 95% CI: 0.831-0.988) and potassium (OR: 0.998; 95% CI: 0.996-1.000), and scoring lower in RAVLT T5 (OR: 0.905; 95% CI: 0.838-0.978) were identified as the risk factors of PTAHL. Meanwhile, being older (OR: 1.117; 95% CI: 1.003-1.244), higher intake of carbohydrate (OR: 1.018; 95% CI: 1.006-1.030), lower intake of potassium (OR: 0.998; 95% CI: 0.997-0.999), and lower scores on the RAVLT T5 (OR: 0.922; 95% CI: 0.874-0.973) were associated with increased risk of having HFAHL.
Conclusion: Increasing age, having higher waist circumference, lower intake of niacin and potassium, higher intake of carbohydrates and having lower RAVLT T5 score were associated with increased risk of ARHL. Modifying these risk factors may be beneficial in preventive and management strategies of ARHL among older persons.
METHODS: Bedtime was recorded based on self-reported habitual time of going to bed in 112,198 participants from 21 countries in the Prospective Urban Rural Epidemiology (PURE) study. Participants were prospectively followed for 9.2 years. We examined the association between bedtime and the composite outcome of all-cause mortality, non-fatal myocardial infarction, stroke and heart failure. Participants with a usual bedtime earlier than 10PM were categorized as 'earlier' sleepers and those who reported a bedtime after midnight as 'later' sleepers. Cox frailty models were applied with random intercepts to account for the clustering within centers.
RESULTS: A total of 5633 deaths and 5346 major cardiovascular events were reported. A U-shaped association was observed between bedtime and the composite outcome. Using those going to bed between 10PM and midnight as the reference group, after adjustment for age and sex, both earlier and later sleepers had a higher risk of the composite outcome (HR of 1.29 [1.22, 1.35] and 1.11 [1.03, 1.20], respectively). In the fully adjusted model where demographic factors, lifestyle behaviors (including total sleep duration) and history of diseases were included, results were greatly attenuated, but the estimates indicated modestly higher risks in both earlier (HR of 1.09 [1.03-1.16]) and later sleepers (HR of 1.10 [1.02-1.20]).
CONCLUSION: Early (10 PM or earlier) or late (Midnight or later) bedtimes may be an indicator or risk factor of adverse health outcomes.
METHODS: In total, 299 SNPs previously associated with prostate cancer were evaluated for inclusion in a new PHS, using a LASSO-regularized Cox proportional hazards model in a training dataset of 72,181 men from the PRACTICAL Consortium. The PHS model was evaluated in four testing datasets: African ancestry, Asian ancestry, and two of European Ancestry-the Cohort of Swedish Men (COSM) and the ProtecT study. Hazard ratios (HRs) were estimated to compare men with high versus low PHS for association with clinically significant, with any, and with fatal prostate cancer. The impact of genetic risk stratification on the positive predictive value (PPV) of PSA testing for clinically significant prostate cancer was also measured.
RESULTS: The final model (PHS290) had 290 SNPs with non-zero coefficients. Comparing, for example, the highest and lowest quintiles of PHS290, the hazard ratios (HRs) for clinically significant prostate cancer were 13.73 [95% CI: 12.43-15.16] in ProtecT, 7.07 [6.58-7.60] in African ancestry, 10.31 [9.58-11.11] in Asian ancestry, and 11.18 [10.34-12.09] in COSM. Similar results were seen for association with any and fatal prostate cancer. Without PHS stratification, the PPV of PSA testing for clinically significant prostate cancer in ProtecT was 0.12 (0.11-0.14). For the top 20% and top 5% of PHS290, the PPV of PSA testing was 0.19 (0.15-0.22) and 0.26 (0.19-0.33), respectively.
CONCLUSIONS: We demonstrate better genetic risk stratification for clinically significant prostate cancer than prior versions of PHS in multi-ancestry datasets. This is promising for implementing precision-medicine approaches to prostate cancer screening decisions in diverse populations.
METHOD: A systematic review and meta-analysis approach was adopted as per the PRISMA guidelines, targeting articles published in PubMed, Google Scholar and Scopus from January 2021 to March 30, 2021. The screening resulted in 82 papers.
RESULTS: The overall pooled depression prevalence among 201,953 respondents was 34% (95%CI, 29-38, 99.7%), with no significant differences observed between the cohorts, timelines, and regions (p > 0.05). Dominant risk factors found were fear of COVID-19 infection (13%), gender (i.e., females; 12%) and deterioration of underlying medical conditions (8.3%), regardless of the sub-groups. Specifically, fear of COVID-19 infection was the most reported risk factor among general population (k = 14) and healthcare workers (k = 8). Gender (k = 7) and increased workload (k = 7) were reported among healthcare workers whereas education disruption among students (k = 7).
LIMITATION: The review is limited to articles published in three electronic databases. Conclusion The pandemic has caused depression among the populations across Asia Pacific, specifically among the general population, healthcare workers and students. Immediate attention and interventions from the concerned authorities are needed in addressing this issue.
OBJECTIVE: To derive a single algorithm using deep learning and machine learning for the prediction and identification of factors associated with in-hospital mortality in Asian patients with ACS and to compare performance to a conventional risk score.
METHODS: The Malaysian National Cardiovascular Disease Database (NCVD) registry, is a multi-ethnic, heterogeneous database spanning from 2006-2017. It was used for in-hospital mortality model development with 54 variables considered for patients with STEMI and Non-STEMI (NSTEMI). Mortality prediction was analyzed using feature selection methods with machine learning algorithms. Deep learning algorithm using features selected from machine learning was compared to Thrombolysis in Myocardial Infarction (TIMI) score.
RESULTS: A total of 68528 patients were included in the analysis. Deep learning models constructed using all features and selected features from machine learning resulted in higher performance than machine learning and TIMI risk score (p < 0.0001 for all). The best model in this study is the combination of features selected from the SVM algorithm with a deep learning classifier. The DL (SVM selected var) algorithm demonstrated the highest predictive performance with the least number of predictors (14 predictors) for in-hospital prediction of STEMI patients (AUC = 0.96, 95% CI: 0.95-0.96). In NSTEMI in-hospital prediction, DL (RF selected var) (AUC = 0.96, 95% CI: 0.95-0.96, reported slightly higher AUC compared to DL (SVM selected var) (AUC = 0.95, 95% CI: 0.94-0.95). There was no significant difference between DL (SVM selected var) algorithm and DL (RF selected var) algorithm (p = 0.5). When compared to the DL (SVM selected var) model, the TIMI score underestimates patients' risk of mortality. TIMI risk score correctly identified 13.08% of the high-risk patient's non-survival vs 24.7% for the DL model and 4.65% vs 19.7% of the high-risk patient's non-survival for NSTEMI. Age, heart rate, Killip class, cardiac catheterization, oral hypoglycemia use and antiarrhythmic agent were found to be common predictors of in-hospital mortality across all ML feature selection models in this study. The final algorithm was converted into an online tool with a database for continuous data archiving for prospective validation.
CONCLUSIONS: ACS patients were better classified using a combination of machine learning and deep learning in a multi-ethnic Asian population when compared to TIMI scoring. Machine learning enables the identification of distinct factors in individual Asian populations to improve mortality prediction. Continuous testing and validation will allow for better risk stratification in the future, potentially altering management and outcomes.
MATERIALS AND METHODS: This cross-sectional study involved 410 randomly selected respondents among nurses in a government hospital in Penang, Malaysia. Data were gathered through a self-administered questionnaire consisting of a standardised questionnaire regarding WPV.
RESULTS: The prevalence of reported WPV was 43.9%. The most common forms of WPV were verbal abuse (82.2%), followed by psychological violence (8.9%), physical violence (8.3%), and sexual violence (0.6%). The perpetrators were primarily among relatives of patients (51.7%), followed by patients (30%). Multiple logistic regression demonstrated that nurses working in the emergency department (ED) were six times more likely to experience WPV than in other departments (adjusted odds ratio (AOR) 6.139, 95% CI: 1.28 - 4.03). In addition, nurses in the age group of ≤30 years old were twice more likely to experience WPV (AOR 2.275, 95% CI: 3.4-11.08).
CONCLUSION: This study indicates that the prevalence of WPV among nurses is high and most common among young nurses and those working in ED. Hence, hospital management should develop guidelines and comprehensive policies to prevent WPV. In addition, education and training, especially among young nurses and those working in the ED, are needed to increase their knowledge in the management and prevention of WPV and counselling sessions for nurses who have experienced WPV.