METHODS: Data were from the Global Burden of Disease Study 2019. We analysed data from Southeast Asia, including Cambodia, Indonesia, Laos, Malaysia, Maldives, Mauritius, Myanmar, Philippines, Seychelles, Sri Lanka, Thailand, Timor-Leste, and Vietnam.
RESULTS: In 2019, there were 728,500 deaths attributable to tobacco in Southeast Asia, with 128,200 deaths attributed to SHS exposure. The leading causes of preventable deaths were ischemic heart disease, stroke, diabetes mellitus, lower respiratory infections, chronic obstructive pulmonary disease, tracheal, bronchus, and lung cancer. Among deaths attributable to tobacco, females had higher proportions of deaths attributable to SHS exposure than males in Southeast Asia.
CONCLUSION: The burden of preventable deaths in a year due to SHS exposure in Southeast Asia is substantial. The implementation and enforcement of smoke-free policies should be prioritized to reduce the disease burden attributed to passive smoking in Southeast Asia.
METHODS: This cross-sectional study of women who underwent DBT and ABUS from December 2019 to March 2022 included opportunistic and targeted screening cases, as well as symptomatic women. Breast density, Breast Imaging Reporting and Data System categories and histopathology reports were collected and compared. The PPV3 (proportion of examinations with abnormal findings that resulted in a tissue diagnosis of cancer), biopsy rate (percentage of biopsies performed) and cancer detection yield (number of malignancies found by the diagnostic test given to the study sample) were calculated.
RESULTS: A total of 1089 ABUS examinations were performed (age range: 29-85 y, mean: 51.9 y). Among these were 909 screening (83.5%) and 180 diagnostic (16.5%) examinations. A total of 579 biopsies were performed on 407 patients, with a biopsy rate of 53.2%. There were 100 (9.2%) malignant lesions, 30 (5.2%) atypical/B3 lesions and 414 (71.5%) benign cases. In 9 cases (0.08%), ABUS alone detected malignancies, and in 19 cases (1.7%), DBT alone detected malignancies. The PPV3 in the screening group was 14.6%.
CONCLUSION: ABUS is useful as an adjunct to DBT in the opportunistic screening and diagnostic setting.
DESIGN: Cross-sectional. Setting, participants, and outcome measures: We used data from the National Health and Morbidity Survey 2018, a nationwide community-based study. This study was conducted using a two-stage stratified cluster sampling design. Older persons were defined as persons aged 60 years and above. SRH was assessed using the question "How do you rate your general health?" and the answers were "very good", "good", "moderate", "not good", and "very bad". SRH was then grouped into two categories; "Good" (very good and good) and "Poor" (moderate, not good, and very bad). Descriptive and logistic regression analyses were conducted using SPSS version 25.0.
RESULTS: The prevalence of poor SRH among older persons was 32.6%. Poor SRH was significantly related to physical inactivity, depression, and limitations in activities of daily living (ADLs). Multiple logistic regression revealed that poor SRH was positively associated with those who had depression (aOR 2.92, 95% CI:2.01,4.24), limitations in ADLs (aOR 1.82, 95% CI: 1.31, 2.54), low individual income (aOR 1.66, 95% CI:1.22, 2.26), physical inactivity (aOR 1.40, 95% CI:1.08, 1.82), and hypertension (aOR 1.23, 95% CI:1.02, 1.49).
CONCLUSIONS: Older persons with depression, limitations in ADLs, low income, physical inactivity, and hypertension were significantly associated with poor SRH. These findings provide information to aid health personnel and policymakers in the development and implementation of health promotion and disease prevention programs, as well as adequate evidence in planning different levels of care for the older population.
METHODS AND FINDINGS: A total of 36603 subjects who were tested for COVID-19 infection via molecular assays at Sunway Medical Centre between Oct 1, 2020 and Jan 31, 2021, and consented to participate in this observation study were included for analysis. Descriptive statistics was used to summarize the study cohort, whereas logistic regression analysis was used to identify risk factors associated with SARS-CoV-2 positivity. Among the reasons listed for COVID-19 screening were those who needed clearance for travelling, clearance to return to work, or clearance prior to hospital admission. They accounted for 67.7% of tested subjects, followed by the self-referred group (27.3%). Most of the confirmed cases were asymptomatic (62.6%), had no travel history (99.6%), and had neither exposure to SARS-CoV-2 confirmed cases (61.9%) nor exposure to patients under investigation (82.7%) and disease clusters (89.2%). Those who presented with loss of smell or taste (OR: 26.91; 95% CI: 14.81-48.92, p<0.001), fever (OR:3.97; 95% CI: 2.54-6.20, p<0.001), running nose (OR: 1.75; 95% CI:1.10-2.79, p = 0.019) or other symptoms (OR: 5.63; 95% CI:1.68-18.91, p = 0.005) were significantly associated with SARS-CoV-2 positivity in the multivariate logistic regression analysis.
CONCLUSION: Our study showed that majority of patients seeking COVID-19 testing in a private healthcare setting were mainly asymptomatic with low epidemiological risk. Consequently, the average positivity rate was 1.2% compared to the national cumulative positivity rate of 4.65%. Consistent with other studies, we found that loss of smell or taste, fever and running nose were associated with SARS-CoV-2 positivity. We believe that strengthening the capacity of private health institutions is important in the national battle against the COVID-19 pandemic, emphasizing the importance of public-private partnership to improve the quality of clinical care.
OBJECTIVES: The objective of this work was to compare quantification techniques for CEST imaging that specifically separate APT and NOE effects for application in the clinical setting. Towards this end a methodological comparison of different CEST quantification techniques was undertaken in healthy subjects, and around clinical endpoints in a cohort of acute stroke patients.
METHODS: MRI data from 12 patients presenting with ischaemic stroke were retrospectively analysed. Six APT quantification techniques, comprising model-based and model-free techniques, were compared for repeatability and ability for APT to distinguish pathological tissue in acute stroke.
RESULTS: Robustness analysis of six quantification techniques indicated that the multi-pool model-based technique had the smallest contrast between grey and white matter (2%), whereas model-free techniques exhibited the highest contrast (>30%). Model-based techniques also exhibited the lowest spatial variability, of which 4-pool APTR∗ was by far the most uniform (10% coefficient of variation, CoV), followed by 3-pool analysis (20%). Four-pool analysis yielded the highest ischaemic core contrast-to-noise ratio (0.74). Four-pool modelling of APT effects was more repeatable (3.2% CoV) than 3-pool modelling (4.6% CoV), but this appears to come at the cost of reduced contrast between infarct growth tissue and normal tissue.
CONCLUSION: The multi-pool measures performed best across the analyses of repeatability, spatial variability, contrast-to-noise ratio, and grey matter-white matter contrast, and might therefore be more suitable for use in clinical imaging of acute stroke. Addition of a fourth pool that separates NOEs and semisolid effects appeared to be more biophysically accurate and provided better separation of the APT signal compared to the 3-pool equivalent, but this improvement appeared be accompanied by reduced contrast between infarct growth tissue and normal tissue.
METHODS: This is an assessor-blinded quasi-experimental study comparing two approaches of physiotherapy, namely pulsed ultrasound-added physiotherapy and conventional physiotherapy. Total number of participants with TKA required for this study will be calculated based on the result of a pilot study. Participants will be alternately allocated into either pulsed ultrasound-added physiotherapy group (low-intensity pulsed ultrasound and conventional physiotherapy) or control group (conventional physiotherapy). Pulsed ultrasound-added physiotherapy group will receive low-intensity pulsed ultrasound starting at post-operative day 2 (4-5 times for the first-week after surgery and 2-3 times a week for a further 2 weeks). Both groups will receive conventional physiotherapy 4 to 5 times for the first-week after surgery and 2 to 3 times a week for a further 11 weeks. This procedure and process will be tested and established in a pilot study. Primary outcomes of interest are pain level, swelling, active range of knee motion, and quadriceps strength. The secondary outcomes are functional performance and quality of life.
DISCUSSION: This study will fill the gaps in knowledge relating the benefits of including low-intensity pulsed ultrasound into conventional physiotherapy for patients with TKA.
TRIAL REGISTRATION: Australian New Zealand Clinical Trials Registry, ACTRN12618001226291.
METHODS: Patients aged 50 years and over hospitalised with a vertebral fragility fracture from 1/2/2016 to 31/1/2017 were identified from radiology and hospital records. Patients sustaining vertebral fractures due to either major trauma or malignancy were excluded. Data was collected on patient demographics, fracture details, hospitalisation details and health outcomes.
RESULTS: 208 patients with acute vertebral fragility fractures were hospitalised over a 12 month period. The mean (SD) age was 80.5 (11) years, of which 68% were female. 94% presented to the Emergency Department (ED) as their first point of contact, of which 70% were subsequently hospitalised. Two-thirds presented with a single level vertebral fracture predominantly around the thoracolumbar region. The majority (87%) were non-operatively managed by general physicians, of which most were under Geriatric Medicine. The median length of stay was 12 (IQR 6-20) days and inpatient mortality was 3%. 52% of patients went on to have a bone health assessment.
CONCLUSION: We have reported on the number of patients presenting to hospital with an acute vertebral fragility fracture over 12 months. This helps identify resources needed to design hospital services to manage them adequately.
PURPOSE: Many countries implemented a lockdown to control the spread of the COVID-19 pandemic. We explored whether outpatient attendances to the Fracture Clinic for non-hip fragility fracture and inpatient admissions for hip fracture declined during lockdown, among adults aged 50 years and older, in a large secondary care hospital.
METHODS: In our observational study, we analysed the records of 6681 outpatients attending the Fracture Clinic, for non-hip fragility fractures, and those of 1752 inpatients, admitted for hip fracture, during the time frames of interest. These were weeks 1st to 12th in 2020 ("prior to lockdown"), weeks 13th to 19th in 2020 ("lockdown") and corresponding periods over 2015 to 2019. We tested for differences in mean numbers (standard deviation (SD)) of outpatients and inpatients, respectively, per week, during the time frames of interest, across the years.
RESULTS: Prior to lockdown, in 2020, 63.1 (SD 12.6) outpatients per week attended the Fracture Clinic, similar to previous years (p value 0.338). During lockdown, 26.0 (SD 7.3) outpatients per week attended the Fracture Clinic, fewer than previous years (p value < 0.001); similar findings were observed in both sexes and age groups (all p values < 0.001). During lockdown, 16.1 (SD 5.6) inpatients per week were admitted for hip fracture, similar to previous years (p value 0.776).
CONCLUSION: During lockdown, fewer outpatients attended the Fracture Clinic, for non-hip fragility fractures, while no change in inpatient admissions for hip fracture was observed. This could reflect fewer non-hip fractures and may inform allocation of resources during pandemic.
METHODS: This study has an ecological design. As a measure of socioeconomic status, we used principal component analysis to construct a socioeconomic index using census data. Districts were ranked according to the standardised median index of households and assigned to each individual in the 5-year mortality data. The mortality indicators of interest were potential years of life lost (PYLL), standardised mortality ratio (SMR), infant mortality rate (IMR) and under-5 mortality rate (U5MR). Both socioeconomic status and mortality outcomes were used compute the concentration index which provided the summary measure of the magnitude of inequality.
RESULTS: Socially disadvantaged districts were found to have worse mortality outcomes compared to more advantaged districts. The values of the concentration index for the overall population of the Peninsula are C = -0.1334 (95% CI: -0.1605 to -0.1063) for the PYLL, C = -0.0685 (95% CI: -0.0928 to -0.0441) for the SMR, C = -0.0997 (95% CI: -0.1343 to -0.0652) for the IMR and C = -0.1207 (95% CI: -0.1523 to -0.0891) for the U5MR. Mortality outcomes within ethnic groups were also found to be less favourable among the poor.
CONCLUSION: The findings of this study suggest that socioeconomic inequalities disfavouring the poor exist in Malaysia.
Settings and Design: This was a cross-sectional study conducted in a Neurological Centre at Hospital Tengku Ampuan Afzan, Kuantan, Pahang, Malaysia, from January 2016 to December 2016.
Subjects and Methods: A total of 209 patients; 133 males and 76 females, in the age range of 16-84 years, were randomly recruited for this study. All the selected patients were subjected to the checklist for diagnosis of PCS as per International Statistical Classification of Diseases and Related Health Problems 10th edition classification at a 2-week interval.
Statistical Analysis Used: Descriptive statistic and Multivariable Logistic Regression Model were used for frequency and percentage analyses of categorical variables, using SPSS version 23.0.
Results: Only 20 patients were identified with PCS. There were more female (70%) patients with PCS than the male (30%) patients. The prevalence of PCS for 2 weeks, 3 and 6 months since injuries were 9.6%, 8.1%, and 8.1% respectively. Majority (80%) of the patients were found to have PCS due to road traffic accidents, while the remaining were attributed to assault (15%), and falls (5%). Among the sample population, 25% were smokers, while 10% of them had either skull fracture or premorbidity.
Conclusion: Less than 10% of patients with MTBI had PCS after 6 months' following trauma. None of the variables tested were significant factors for the development of PCS symptoms.
METHODS: Malaysia was divided into six regions, with each region consisting of 50 clusters. Multistage cluster sampling method was used and each cluster contained 50 residents aged 50 years and above. Eligible subjects were interviewed and pertinent demographic details, barriers to cataract surgery, medical and ocular history was noted. Subjects had visual acuity assessment with tumbling 'E' Snellen optotypes and ocular examination with direct ophthalmoscope. The primary cause of VI was documented. Results were calculated for individual zones and weighted average was used to obtain overall prevalence for the country. Inter-regional and overall prevalence for blindness, severe VI and moderate VI were determined. Causes of VI, cataract surgical coverage and barriers to cataract surgery were assessed.
RESULTS: A total of 15,000 subjects were examined with a response rate of 95.3%. The age and gender-adjusted prevalence of blindness, severe visual impairment and moderate visual impairment were 1.2% (95% Confidence Interval: 1.0-1.4%), 1.0% (95%CI: 0.8-1.2%) and 5.9% (5.3-6.5%) respectively. Untreated cataract (58.6%), diabetic retinopathy (10.4%) and glaucoma (6.6%) were the commonest causes of blindness. Overall, 86.3% of the causes of blindness were avoidable. Cataract surgical coverage (CSC) in persons for blindness, severe visual impairment and moderate visual impairment was 90%, 86% and 66% respectively.
CONCLUSION: Increased patient education and further expansion of ophthalmological services are required to reduce avoidable blindness even further in Malaysia.
METHODS: Stiffness index (SI) was measured and T-scores generated against an Asian database were recorded for 598,757 women and 173,326 men aged over 21 years old using Lunar Achilles (GE Healthcare) heel scanners. The scanners were made available in public centres in Singapore, Vietnam, Malaysia, Taiwan, Thailand, Indonesia and the Philippines.
RESULTS: The mean SI was higher for men than women. In women SI as well as T-scores declined slowly until approximately 45 years of age, then declined rapidly to reach a mean T-score of 80 years.
CONCLUSIONS: The heel scan data shows a high degree of poor bone health in both men and women in Asian countries, raising concern about the possible increase in fractures with ageing and the expected burden on the public health system.
METHODS: After 10 min of supine rest, the subject was tilted at a 70-degree angle on a tilt table for approximately a total of 35 min. 400 µg of glyceryl trinitrate (GTN) was administered sublingually after the first 20 min and monitoring continued for another 15 min. Mean imputation and K-nearest neighbors (KNN) imputation approaches to handle missing values. Next, feature selection techniques were implemented, including genetic algorithm, recursive feature elimination, and feature importance, to determine the crucial features. The Mann-Whitney U test was then performed to determine the statistical difference between two groups. Patients with VVS are categorized via machine learning models including Support Vector Machine (SVM), Gaussian Naïve Bayes (GNB), Multinomial Naïve Bayes (MNB), KNN, Logistic Regression (LR), and Random Forest (RF). The developed model is interpreted using an explainable artificial intelligence (XAI) model known as partial dependence plot.
RESULTS: A total of 137 subjects aged between 9 and 93 years were recruited for this study, 54 experienced clinical symptoms were considered positive tests, while the remaining 83 tested negative. Optimal results were obtained by combining the KNN imputation technique and three tilting features with SVM with 90.5% accuracy, 87.0% sensitivity, 92.7% specificity, 88.6% precision, 87.8% F1 score, and 95.4% ROC (receiver operating characteristics) AUC (area under curve).
CONCLUSIONS: The proposed algorithm effectively classifies VVS patients with over 90% accuracy. However, the study was confined to a small sample size. More clinical datasets are required to ensure that our approach is generalizable.
METHODOLOGY: Data for the study, consisting of 2553 older adults aged 60 years and older, were drawn from a nationwide household survey entitled "Determinants of Wellness among Older Malaysians: A Health Promotion Perspective" conducted in 2010.
RESULTS: Current smokers had lower rates of cognitive impairment compared to never smokers (17.4% vs 25.9%), while cognitive function in former or ex-smokers was almost similar to that of the never smokers. Findings from multiple logistic regression analysis showed that current smokers were 37% less likely to be cognitively impaired, compared to the never smokers (odds ratio [OR] = .63; 95% confidence interval [CI]: .46-.86) while controlling for potential confounders. No difference in cognitive function was observed between former smokers and never smokers (OR = .94; 95% CI: .71-1.25).
CONCLUSION: Although the findings indicated a negative association between cigarette smoking and cognitive impairment, we are unable to conclude whether this relationship is causal or affected by other unmeasured confounding factors, especially survival bias.