Prediction of mortality in patients with community-acquired pneumonia (CAP) can be assessed using clinical severity scores on admission to hospital. The clinical benefit of such tools is untested in Asian countries. The aim of this study was to determine the early adverse prognostic factors in patients hospitalized with CAP in Malaysia and to assess the usefulness of the British Thoracic Society (BTS) severity criteria.
Comment on: Norsaʼadah B, Rusli BN, Imran AK, Naing L, Winn T. Risk factors of breast cancer in women in Kelantan, Malaysia. Singapore Med J 2005;
46:698-705
We describe a semi-automated technique for the quantitative assessment of breast density from digitized mammograms in comparison with patterns suggested by Tabar. It was developed using the MATLAB-based graphical user interface applications. It is based on an interactive thresholding method, after a short automated method that shows the fibroglandular tissue area, breast area and breast density each time new thresholds are placed on the image. The breast density is taken as a percentage of the fibroglandular tissue to the breast tissue areas. It was tested in four different ways, namely by examining: (i) correlation of the quantitative assessment results with subjective classification, (ii) classification performance using the quantitative assessment technique, (iii) interobserver agreement and (iv) intraobserver agreement. The results of the quantitative assessment correlated well (r2 = 0.92) with the subjective Tabar patterns classified by the radiologist (correctly classified 83% of digitized mammograms). The average kappa coefficient for the agreement between the readers was 0.63. This indicated moderate agreement between the three observers in classifying breast density using the quantitative assessment technique. The kappa coefficient of 0.75 for intraobserver agreement reflected good agreement between two sets of readings. The technique may be useful as a supplement to the radiologist's assessment in classifying mammograms into Tabar's pattern associated with breast cancer risk.
Concentrations of 20 trace elements were determined in muscle and liver of 34 species of marine fish collected from coastal areas of Cambodia, Indonesia, Malaysia and Thailand. Large regional difference was observed in the levels of trace elements in liver of one fish family (Carangidae): the highest mean concentration was observed in fish from the Malaysian coastal waters for V, Cr, Zn, Pb and Bi and those from the Java Sea side of Indonesia for Sn and Hg. To assess the health risk to the Southeast Asian populations from consumption of fish, intake rates of trace elements were estimated. Some marine fish showed Hg levels higher than the guideline values by U.S. Environmental Protection Agency and Joint FAO/WHO Expert Committee on Food Additives (JECFA). This suggests that consumption of these fish may be hazardous to the people.
In this paper, we concisely reviewed the contamination of persistent organic pollutants (POPs) such as polychlorinated dibenzo-p-dioxins (PCDDs), dibenzofurans (PCDFs), biphenyls (PCBs), dichlorodiphenyltrichloroethane and its metabolites (DDTs), hexachlorocyclohexane isomers (HCHs), chlordane compounds (CHLs), hexachlorobenzene (HCB) in human breast milk collected from Asian countries such as Japan, China, Philippines, Vietnam, Cambodia, India, Malaysia, and Indonesia during 1999-2003. Dioxins, PCBs, CHLs in Japanese, and DDTs in Vietnamese, Chinese, Cambodian, Malaysian, and HCHs in Chinese, Indian, and HCB in Chinese breast milk were predominant. In India, levels of dioxins and related compounds (DRCs) in the mothers living around the open dumping site were notably higher than those from the reference site and other Asian developing countries, indicating that significant pollution sources of DRCs are present in the dumping site of India and the residents there have been exposed to relatively higher levels of these contaminants possibly via bovine milk.
The phytotoxic risk of ambient air pollution to local vegetation was assessed in Selangor State, Malaysia. The AOT40 value was calculated by means of the continuously monitored daily maximum concentration and the local diurnal pattern of O3. Together with minor risks associated with the levels of NO2 and SO2, the study found that the monthly AOT40 values in these peri-urban sites were consistently over 1.0 ppm.h, which is well in exceedance of the given European critical level. Linking the O3 level to actual agricultural crop production in Selangor State also indicated that the extent of yield losses could have ranged from 1.6 to 5.0% (by weight) in 2000. Despite a number of uncertainties, the study showed a simple but useful methodological framework for phytotoxic risk assessment with a limited data set, which could contribute to appropriate policy discussion and countermeasures in countries under similar conditions.
The association between fetal sex and outcome of pregnancy and labor has been well documented in western populations. However, no studies in Malaysia or other developing countries have examined the effect of fetal sex on such outcomes.The main objective of this study was to determine the influence of fetal sex on the outcome of labor at term in a cohort of Malaysian nulliparae.A retrospective observational study was designed using data from 4644 Malaysian nulliparae who gave birth consecutively to singleton male babies at Hospital Sultanah Aminah, Johor Bahru, after normal full-term pregnancies.The results of this study indicate that mothers giving birth to male infants have a greater risk of requiring cesarean delivery because male babies are heavier and have statistically significantly greater head circumference (P < .001). These findings concur with those obtained in western populations and suggest that the differences in outcome observed are biological, not dictated by race, ethnicity, or environmental conditions. Such information could help in the antenatal assessment of Malaysian patients and stimulate more comprehensive studies of the mechanisms involved in this sex-based difference in outcomes. Reasons for such differences are proposed.
This study presents a new approach to determine the significant prognosis factors in dengue patients utilizing the self-organizing map (SOM). SOM was used to visualize and determine the significant factors that can differentiate between the dengue patients and the healthy subjects. Bioimpedance analysis (BIA) parameters and symptoms/signs obtained from the 210 dengue patients during their hospitalization were used in this study. Database comprised of 329 sample (210 dengue patients and 119 healthy subjects) were used in the study. Accordingly, two maps were constructed. A total of 35 predictors (17 BIA parameters, 18 symptoms/signs) were investigated on the day of defervescence of fever. The first map was constructed based on BIA parameters while the second map utilized the symptoms and signs. The visualized results indicated that, the significant BIA prognosis factors for differentiating the dengue patients from the healthy subjects are reactance, intracellular water, ratio of the extracellular water and intracellular water, and ratio of the extracellular mass and body cell mass.
Cardiovascular Disease (CVD) is the leading cause of death in both developed and developing countries. While it is relatively easy to identify those who are obviously at high risk and those at the lowest risk for CVD, it is often the large group of individuals with what appears to be modestly abnormal risk factors who contributes most to the burden of CVD. This is where estimation of CVD risk is necessary. Many tools for risk assessment have been devised. All these risk scores have their own inherent advantages and disadvantages. Furthermore, they may also not be directly applicable to a local population. Ideally, each country should have its own risk score that takes into account other factors as well. In the interim, it is worthwhile to be familiar with one of these scores, select one that is most appropriate for your patient and discuss treatment options based on the estimated risk.
Improved methods are required to identify patients with asymptomatic carotid stenosis at high risk for stroke. The Asymptomatic Carotid Emboli Study recently showed embolic signals (ES) detected by transcranial Doppler on 2 recordings that lasted 1-hour independently predict 2-year stroke risk. ES detection is time-consuming, and whether similar predictive information could be obtained from simpler recording protocols is unknown.
With the increasing prevalence of childhood obesity, the metabolic syndrome has been studied among children in many countries but not in Malaysia. Hence, this study aimed to compare metabolic risk factors between overweight/obese and normal weight children and to determine the influence of gender and ethnicity on the metabolic syndrome among school children aged 9-12 years in Kuala Lumpur and its metropolitan suburbs.
Malaria remains a major health problem in Sudan. With a population exceeding 39 million, there are around 7.5 million cases and 35,000 deaths every year. The predicted distribution of malaria derived from climate factors such as maximum and minimum temperatures, rainfall and relative humidity was compared with the actual number of malaria cases in Sudan for the period 2004 to 2010. The predictive calculations were done by fuzzy logic suitability (FLS) applied to the numerical distribution of malaria transmission based on the life cycle characteristics of the Anopheles mosquito accounting for the impact of climate factors on malaria transmission. This information is visualized as a series of maps (presented in video format) using a geographical information systems (GIS) approach. The climate factors were found to be suitable for malaria transmission in the period of May to October, whereas the actual case rates of malaria were high from June to November indicating a positive correlation. While comparisons between the prediction model for June and the case rate model for July did not show a high degree of association (18%), the results later in the year were better, reaching the highest level (55%) for October prediction and November case rate.
Dengue fever is a recurring public health problem afflicting thousands of Malaysians annually. In this paper, the risk map for dengue fever in the peninsular Malaysian states of Selangor and Kuala Lumpur was modelled based on co-kriging and geographical information systems. Using population density and rainfall as the model's only input factors, the area with the highest risk for dengue infection was given as Gombak and Petaling, two districts located on opposite sides of Kuala Lumpur city that was also included in the risk assessment. Comparison of the modelled risk map with the dengue case dataset of 2010, obtained from the Ministry of Health of Malaysia, confirmed that the highest number of cases had been found in an area centred on Kuala Lumpur as predicted our risk profiling.
Risk stratification in ST-elevation myocardial infarction (STEMI) is important, such that the most resource intensive strategy is used to achieve the greatest clinical benefit. This is essential in developing countries with wide variation in health care facilities, scarce resources and increasing burden of cardiovascular diseases. This study sought to validate the Thrombolysis In Myocardial Infarction (TIMI) risk score for STEMI in a multi-ethnic developing country.
This review aimed to explore the extent of the use of diabetes risk assessment tools and to determine influential variables associated with the implementation of these tools. CINAHL, Google Scholar, ISI Citation Indexes, PubMed, and Scopus were searched from inception to January 2013. Studies that reported the use of diabetes risk assessment tools to identify individuals at risk of diabetes were included. Of the 1719 articles identified, 24 were included. Follow-up of high risk individuals for diagnosis of diabetes was conducted in 5 studies. Barriers to the uptake of diabetes risk assessment tools by healthcare practitioners included (1) attitudes toward the tools; (2) impracticality of using the tools and (3) lack of reimbursement and regulatory support. Individuals were reluctant to undertake self-assessment of diabetes risk due to (1) lack of perceived severity of type 2 diabetes; (2) impracticality of the tools; and (3) concerns related to finding out the results. The current use of non-invasive diabetes risk assessment scores as screening tools appears to be limited. Practical follow up systems as well as strategies to address other barriers to the implementation of diabetes risk assessment tools are essential and need to be developed.
17α-ethynylestradiol (EE2) is a synthetic hormone, which is a derivative of the natural hormone, estradiol (E2). EE2 is an orally bio-active estrogen, and is one of the most commonly used medications for humans as well as livestock and aquaculture activity. EE2 has become a widespread problem in the environment due to its high resistance to the process of degradation and its tendency to (i) absorb organic matter, (ii) accumulate in sediment and (iii) concentrate in biota. Numerous studies have reported the ability of EE2 to alter sex determination, delay sexual maturity, and decrease the secondary sexual characteristics of exposed organisms even at a low concentration (ng/L) by mimicking its natural analogue, 17β-estradiol (E2). Thus, the aim of this review is to provide an overview of the science regarding EE2, the concentration levels in the environment (water, sediment and biota) and summarize the effects of this compound on exposed biota at various concentrations, stage life, sex, and species. The challenges in respect of EE2 include the extension of the limited database on the EE2 pollution profile in the environment, its fate and transport mechanism, as well as the exposure level of EE2 for better prediction and definition revision of EE2 toxicity end points, notably for the purpose of environmental risk assessment.
The aim of this study was to develop a risk-based decision-making framework for the selection of sediment dredging option. Descriptions using case studies of the newly integrated, holistic and staged framework were followed. The first stage utilized the historical dredging monitoring data and the contamination level in media data into Ecological Risk Assessment phases, which have been altered for benefits in cost, time and simplicity. How Multi-Criteria Decision Analysis (MCDA) can be used to analyze and prioritize dredging areas based on environmental, socio-economic and managerial criteria was described for the next stage. The results from MCDA will be integrated into Ecological Risk Assessment to characterize the degree of contamination in the prioritized areas. The last stage was later described using these findings and analyzed using MCDA, in order to identify the best sediment dredging option, accounting for the economic, environmental and technical aspects of dredging, which is beneficial for dredging and sediment management industries.
Fall is a common and a major cause of injuries. It is important to find elderlies who are prone to falls. The majority of serious falls occur during walking among the older adults. Analyzing the spatio-temporal parameters of walking is an easy way of assessment in the clinical setting, but is it capable of distinguishing a faller from a non-faller elderly? Through a systematic review of the literature, the objective of this systematic review was to identify and summarize the differences in the spatio-temporal parameters of walking in elderly fallers and non-fallers and to find out if these parameters are capable of distinguishing a faller from a non-faller. All original research articles which compared any special or temporal walking parameters in faller and non-faller elderlies were systematically searched within the Scopus and Embase databases. Effect size analysis was also done to standardize findings and compare the gait parameters of fallers and non-fallers across the selected studies. The electronic search led to 5381 articles. After title and abstract screening 30 articles were chosen; further assessment of the full texts led to 17 eligible articles for inclusion in the review. It seems that temporal measurements are more sensitive to the detection of risk of fall in elderly people. The results of the 17 selected studies showed that fallers have a tendency toward a slower walking speed and cadence, longer stride time, and double support duration. Also, fallers showed shorter stride and step length, wider step width and more variability in spatio-temporal parameters of gait. According to the effect size analysis, step length, gait speed, stride length and stance time variability were respectively more capable of differentiating faller from non-faller elderlies. However, because of the difference of methodology and number of studies which investigated each parameter, these results are prone to imprecision. Spatio-temporal analysis of level walking is not sufficient and cannot act as a reliable predictor of falls in elderly individuals.
The purpose of this study was to develop a risk prediction score for distinguishing benign ovarian mass from malignant tumors using CA-125, human epididymis protein 4 (HE4), ultrasound findings, and menopausal status. The risk prediction score was compared to the risk of malignancy index and risk of ovarian malignancy algorithm (ROMA).
Genetic risk prediction has several potential applications in medical research and clinical practice and could be used, for example, to stratify a heterogeneous population of patients by their predicted genetic risk. However, for polygenic traits, such as psychiatric disorders, the accuracy of risk prediction is low. Here we use a multivariate linear mixed model and apply multi-trait genomic best linear unbiased prediction for genetic risk prediction. This method exploits correlations between disorders and simultaneously evaluates individual risk for each disorder. We show that the multivariate approach significantly increases the prediction accuracy for schizophrenia, bipolar disorder, and major depressive disorder in the discovery as well as in independent validation datasets. By grouping SNPs based on genome annotation and fitting multiple random effects, we show that the prediction accuracy could be further improved. The gain in prediction accuracy of the multivariate approach is equivalent to an increase in sample size of 34% for schizophrenia, 68% for bipolar disorder, and 76% for major depressive disorders using single trait models. Because our approach can be readily applied to any number of GWAS datasets of correlated traits, it is a flexible and powerful tool to maximize prediction accuracy. With current sample size, risk predictors are not useful in a clinical setting but already are a valuable research tool, for example in experimental designs comparing cases with high and low polygenic risk.