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Fulltext Global, regional, and national levels and causes of maternal mortality during 1990-2013: a systematic analysis for the Global Burden of Disease Study 2013

Kassebaum NJ, Bertozzi-Villa A, Coggeshall MS, Shackelford KA, Steiner C, Heuton KR, et al.

Lancet, 2014 Sep 13;384(9947):980-1004.
PMID: 24797575 DOI: 10.1016/S0140-6736(14)60696-6

BACKGROUND: The fifth Millennium Development Goal (MDG 5) established the goal of a 75% reduction in the maternal mortality ratio (MMR; number of maternal deaths per 100,000 livebirths) between 1990 and 2015. We aimed to measure levels and track trends in maternal mortality, the key causes contributing to maternal death, and timing of maternal death with respect to delivery.
METHODS: We used robust statistical methods including the Cause of Death Ensemble model (CODEm) to analyse a database of data for 7065 site-years and estimate the number of maternal deaths from all causes in 188 countries between 1990 and 2013. We estimated the number of pregnancy-related deaths caused by HIV on the basis of a systematic review of the relative risk of dying during pregnancy for HIV-positive women compared with HIV-negative women. We also estimated the fraction of these deaths aggravated by pregnancy on the basis of a systematic review. To estimate the numbers of maternal deaths due to nine different causes, we identified 61 sources from a systematic review and 943 site-years of vital registration data. We also did a systematic review of reports about the timing of maternal death, identifying 142 sources to use in our analysis. We developed estimates for each country for 1990-2013 using Bayesian meta-regression. We estimated 95% uncertainty intervals (UIs) for all values.
FINDINGS: 292,982 (95% UI 261,017-327,792) maternal deaths occurred in 2013, compared with 376,034 (343,483-407,574) in 1990. The global annual rate of change in the MMR was -0·3% (-1·1 to 0·6) from 1990 to 2003, and -2·7% (-3·9 to -1·5) from 2003 to 2013, with evidence of continued acceleration. MMRs reduced consistently in south, east, and southeast Asia between 1990 and 2013, but maternal deaths increased in much of sub-Saharan Africa during the 1990s. 2070 (1290-2866) maternal deaths were related to HIV in 2013, 0·4% (0·2-0·6) of the global total. MMR was highest in the oldest age groups in both 1990 and 2013. In 2013, most deaths occurred intrapartum or postpartum. Causes varied by region and between 1990 and 2013. We recorded substantial variation in the MMR by country in 2013, from 956·8 (685·1-1262·8) in South Sudan to 2·4 (1·6-3·6) in Iceland.
INTERPRETATION: Global rates of change suggest that only 16 countries will achieve the MDG 5 target by 2015. Accelerated reductions since the Millennium Declaration in 2000 coincide with increased development assistance for maternal, newborn, and child health. Setting of targets and associated interventions for after 2015 will need careful consideration of regions that are making slow progress, such as west and central Africa.
FUNDING: Bill & Melinda Gates Foundation.

Matched MeSH terms: Models, Statistical
Fulltext Intermittent Fasting and Obesity-Related Health Outcomes: An Umbrella Review of Meta-analyses of Randomized Clinical Trials

Patikorn C, Roubal K, Veettil SK, Chandran V, Pham T, Lee YY, et al.

JAMA Netw Open, 2021 12 01;4(12):e2139558.
PMID: 34919135 DOI: 10.1001/jamanetworkopen.2021.39558

Importance: Several meta-analyses of randomized clinical trials (RCTs) have demonstrated the many health benefits of intermittent fasting (IF). However, there has been little synthesis of the strength and quality of this evidence in aggregate to date.
Objective: To grade the evidence from published meta-analyses of RCTs that assessed the associations of IF (zero-calorie alternate-day fasting, modified alternate-day fasting, the 5:2 diet, and time-restricted eating) with obesity-related health outcomes.
Evidence Review: PubMed, Embase, and Cochrane database of systematic reviews were searched from database inception to January 12, 2021. Data analysis was conducted from April 2021 through July 2021. Meta-analyses of RCTs investigating effects of IF in adults were included. The effect sizes of IF were recalculated using a random-effects model. We assessed the quality of evidence per association by applying the GRADE criteria (Grading of Recommendations, Assessment, Development, and Evaluations) as high, moderate, low, and very low.
Findings: A total of 11 meta-analyses comprising 130 RCTs (median [IQR] sample size, 38 [24-69] participants; median [IQR] follow-up period, 3 [2-5] months) were included describing 104 unique associations of different types of IF with obesity-related health outcomes (median [IQR] studies per association, 4 [3-5]). There were 28 statistically significant associations (27%) that demonstrated the beneficial outcomes for body mass index, body weight, fat mass, low-density lipoprotein cholesterol, total cholesterol, triglycerides, fasting plasma glucose, fasting insulin, homeostatic model assessment of insulin resistance, and blood pressure. IF was found to be associated with reduced fat-free mass. One significant association (1%) supported by high-quality evidence was modified alternate-day fasting for 1 to 2 months, which was associated with moderate reduction in body mass index in healthy adults and adults with overweight, obesity, or nonalcoholic fatty liver disease compared with regular diet. Six associations (6%) were supported by moderate quality evidence. The remaining associations found to be significant were supported by very low (75 associations [72%]) to low (22 associations [21%]) quality evidence.
Conclusions and Relevance: In this umbrella review, we found beneficial associations of IF with anthropometric and cardiometabolic outcomes supported by moderate to high quality of evidence, which supports the role of IF, especially modified alternate-day fasting, as a weight loss approach for adults with overweight or obesity. More clinical trials with long-term follow-up are needed to investigate the effects of IF on clinical outcomes such as cardiovascular events and mortality.

Matched MeSH terms: Models, Statistical
Smoothing a discrete hazard function for the number of patients colonized with Methicillin-resistant Staphylococcus Aureus in an intensive care unit

Ismail NA, Pettitt AN

Stat Med, 2004 Apr 30;23(8):1247-58.
PMID: 15083481

A new method for estimating the time to colonization of Methicillin-resistant Staphylococcus Aureus (MRSA) patients is developed in this paper. The time to colonization of MRSA is modelled using a Bayesian smoothing approach for the hazard function. There are two prior models discussed in this paper: the first difference prior and the second difference prior. The second difference prior model gives smoother estimates of the hazard functions and, when applied to data from an intensive care unit (ICU), clearly shows increasing hazard up to day 13, then a decreasing hazard. The results clearly demonstrate that the hazard is not constant and provide a useful quantification of the effect of length of stay on the risk of MRSA colonization which provides useful insight.

Matched MeSH terms: Models, Statistical
The identification of high potential archers based on fitness and motor ability variables: A Support Vector Machine approach

Taha Z, Musa RM, P P Abdul Majeed A, Alim MM, Abdullah MR

Hum Mov Sci, 2018 Feb;57:184-193.
PMID: 29248809 DOI: 10.1016/j.humov.2017.12.008

Support Vector Machine (SVM) has been shown to be an effective learning algorithm for classification and prediction. However, the application of SVM for prediction and classification in specific sport has rarely been used to quantify/discriminate low and high-performance athletes. The present study classified and predicted high and low-potential archers from a set of fitness and motor ability variables trained on different SVMs kernel algorithms. 50 youth archers with the mean age and standard deviation of 17.0 ± 0.6 years drawn from various archery programmes completed a six arrows shooting score test. Standard fitness and ability measurements namely hand grip, vertical jump, standing broad jump, static balance, upper muscle strength and the core muscle strength were also recorded. Hierarchical agglomerative cluster analysis (HACA) was used to cluster the archers based on the performance variables tested. SVM models with linear, quadratic, cubic, fine RBF, medium RBF, as well as the coarse RBF kernel functions, were trained based on the measured performance variables. The HACA clustered the archers into high-potential archers (HPA) and low-potential archers (LPA), respectively. The linear, quadratic, cubic, as well as the medium RBF kernel functions models, demonstrated reasonably excellent classification accuracy of 97.5% and 2.5% error rate for the prediction of the HPA and the LPA. The findings of this investigation can be valuable to coaches and sports managers to recognise high potential athletes from a combination of the selected few measured fitness and motor ability performance variables examined which would consequently save cost, time and effort during talent identification programme.

Matched MeSH terms: Models, Statistical
Thresholds for decision-making: informing the cost-effectiveness and affordability of rotavirus vaccines in Malaysia

Loganathan T, Ng CW, Lee WS, Hutubessy RCW, Verguet S, Jit M

Health Policy Plan, 2018 Mar 01;33(2):204-214.
PMID: 29228339 DOI: 10.1093/heapol/czx166

Cost-effectiveness thresholds (CETs) based on the Commission on Macroeconomics and Health (CMH) are extensively used in low- and middle-income countries (LMICs) lacking locally defined CETs. These thresholds were originally intended for global and regional prioritization, and do not reflect local context or affordability at the national level, so their value for informing resource allocation decisions has been questioned. Using these thresholds, rotavirus vaccines are widely regarded as cost-effective interventions in LMICs. However, high vaccine prices remain a barrier towards vaccine introduction. This study aims to evaluate the cost-effectiveness, affordability and threshold price of universal rotavirus vaccination at various CETs in Malaysia. Cost-effectiveness of Rotarix and RotaTeq were evaluated using a multi-cohort model. Pan American Health Organization Revolving Fund's vaccine prices were used as tender price, while the recommended retail price for Malaysia was used as market price. We estimate threshold prices defined as prices at which vaccination becomes cost-effective, at various CETs reflecting economic theories of human capital, societal willingness-to-pay and marginal productivity. A budget impact analysis compared programmatic costs with the healthcare budget. At tender prices, both vaccines were cost-saving. At market prices, cost-effectiveness differed with thresholds used. At market price, using 'CMH thresholds', Rotarix programmes were cost-effective and RotaTeq were not cost-effective from the healthcare provider's perspective, while both vaccines were cost-effective from the societal perspective. Using other CETs, both vaccines were not cost-effective at market price, from the healthcare provider's and societal perspectives. At tender and cost-effective prices, rotavirus vaccination cost ∼1 and 3% of the public health budget, respectively. Using locally defined thresholds, rotavirus vaccination is cost-effective at vaccine prices in line with international tenders, but not at market prices. Thresholds representing marginal productivity are likely to be lower than those reflecting human capital and individual preference measures, and may be useful in determining affordable vaccine prices.

Matched MeSH terms: Models, Statistical
Cost-effectiveness of warfarin medication therapy adherence clinic versus usual medical clinic at Kuala Lumpur Hospital

Thanimalai S, Shafie AA, Ahmad Hassali MA, Sinnadurai J

Value Health Reg Issues, 2018 May;15:34-41.
PMID: 29474176 DOI: 10.1016/j.vhri.2017.05.006

BACKGROUND: Systematic anticoagulation management clinic is recommended to manage patients on chronic warfarin therapy. In Malaysia, the service was introduced as warfarin medication therapy adherence clinic (WMTAC), which is managed by pharmacists with a physician advisory.
OBJECTIVES: To assess the cost-effectiveness of WMTAC in comparison with usual medical clinic (UMC), which is managed by medical officers in Kuala Lumpur Hospital, a tertiary referral hospital in Malaysia.
METHODS: Data from a 6-month retrospective cohort study comparing the two clinics and the mean percentages of time in the therapeutic range for the patients were used to estimate the cost-effectiveness. The mean clinic costs were estimated using the time-motion study. A Markov model with a 6-monthly cycle was used to simulate lifetime cost-effectiveness from the perspective of the health care service provider. The base-case analysis assumed a cohort of patients with atrial fibrillation, 57 years of age with comorbid illnesses. The transition probabilities of these clinic outcomes were obtained from a literature search. Future costs and effectiveness were discounted by 3% to convert to present values. All costs were in Malaysian ringgit standardized for the year 2007.
RESULTS: The mean 6-month treatment cost was lower for the WMTAC, which was significantly lower (P < 0.001). The UMC was found to be dominated by the WMTAC for both intermediate and lifetime analyses. The sensitivity analysis showed that clinic consultation costs had a major impact on the cost-effectiveness analysis.
CONCLUSIONS: WMTAC is a more cost-effective option than UMC in Kuala Lumpur Hospital.
Study site: Medical clinic, Hospital Kuala Lumpur, Malaysia

Matched MeSH terms: Models, Statistical
Fulltext Performance of the CKD-EPI creatinine-cystatin C glomerular filtration rate estimation equations in a multiethnic Asian population

Teo BW, Koh YY, Toh QC, Li J, Sinha AK, Shuter B, et al.

Singapore Med J, 2014 Dec;55(12):656-9.
PMID: 25630321

INTRODUCTION: Clinical practice guidelines recommend using creatinine-based equations to estimate glomerular filtration rates (GFRs). While these equations were formulated for Caucasian-American populations and have adjustment coefficients for African-American populations, they are not validated for other ethnicities. The Chronic Kidney Disease-Epidemiology Collaborative Group (CKD-EPI) recently developed a new equation that uses both creatinine and cystatin C. We aimed to assess the accuracy of this equation in estimating the GFRs of participants (healthy and with chronic kidney disease [CKD]) from a multiethnic Asian population.

METHODS: Serum samples from the Asian Kidney Disease Study and the Singapore Kidney Function Study were used. GFR was measured using plasma clearance of 99mTc-DTPA. GFR was estimated using the CKD-EPI equations. The performance of GFR estimation equations were examined using median and interquartile range values, and the percentage difference from the measured GFR.

RESULTS: The study comprised 335 participants (69.3% with CKD; 38.5% Chinese, 29.6% Malays, 23.6% Indians, 8.3% others), with a mean age of 53.5 ± 15.1 years. Mean standardised serum creatinine was 127 ± 86 μmol/L, while mean standardised serum cystatin C and mean measured GFR were 1.43 ± 0.74 mg/L and 67 ± 33 mL/min/1.73 m2, respectively. The creatinine-cystatin C CKD-EPI equation performed the best, with an estimated GFR of 67 ± 35 mL/min/1.73 m2.

CONCLUSION: The new creatinine-cystatin C equation estimated GFR with little bias, and had increased precision and accuracy in our multiethnic Asian population. This two-biomarker equation may increase the accuracy of population studies on CKD, without the need to consider ethnicity.

Matched MeSH terms: Models, Statistical
Fulltext A spatio-temporal agent-based approach for modeling the spread of zoonotic cutaneous leishmaniasis in northeast Iran

Tabasi M, Alesheikh AA, Sofizadeh A, Saeidian B, Pradhan B, AlAmri A

Parasit Vectors, 2020 Nov 11;13(1):572.
PMID: 33176858 DOI: 10.1186/s13071-020-04447-x

BACKGROUND: Zoonotic cutaneous leishmaniasis (ZCL) is a neglected tropical disease worldwide, especially the Middle East. Although previous works attempt to model the ZCL spread using various environmental factors, the interactions between vectors (Phlebotomus papatasi), reservoir hosts, humans, and the environment can affect its spread. Considering all of these aspects is not a trivial task.
METHODS: An agent-based model (ABM) is a relatively new approach that provides a framework for analyzing the heterogeneity of the interactions, along with biological and environmental factors in such complex systems. The objective of this research is to design and develop an ABM that uses Geospatial Information System (GIS) capabilities, biological behaviors of vectors and reservoir hosts, and an improved Susceptible-Exposed-Infected-Recovered (SEIR) epidemic model to explore the spread of ZCL. Various scenarios were implemented to analyze the future ZCL spreads in different parts of Maraveh Tappeh County, in the northeast region of Golestan Province in northeastern Iran, with alternative socio-ecological conditions.
RESULTS: The results confirmed that the spread of the disease arises principally in the desert, low altitude areas, and riverside population centers. The outcomes also showed that the restricting movement of humans reduces the severity of the transmission. Moreover, the spread of ZCL has a particular temporal pattern, since the most prevalent cases occurred in the fall. The evaluation test also showed the similarity between the results and the reported spatiotemporal trends.
CONCLUSIONS: This study demonstrates the capability and efficiency of ABM to model and predict the spread of ZCL. The results of the presented approach can be considered as a guide for public health management and controlling the vector population .

Matched MeSH terms: Models, Statistical
Prediction of breast cancer risk based on common genetic variants in women of East Asian ancestry

Wen W, Shu XO, Guo X, Cai Q, Long J, Bolla MK, et al.

Breast Cancer Res, 2016 12 08;18(1):124.
PMID: 27931260

BACKGROUND: Approximately 100 common breast cancer susceptibility alleles have been identified in genome-wide association studies (GWAS). The utility of these variants in breast cancer risk prediction models has not been evaluated adequately in women of Asian ancestry.
METHODS: We evaluated 88 breast cancer risk variants that were identified previously by GWAS in 11,760 cases and 11,612 controls of Asian ancestry. SNPs confirmed to be associated with breast cancer risk in Asian women were used to construct a polygenic risk score (PRS). The relative and absolute risks of breast cancer by the PRS percentiles were estimated based on the PRS distribution, and were used to stratify women into different levels of breast cancer risk.
RESULTS: We confirmed significant associations with breast cancer risk for SNPs in 44 of the 78 previously reported loci at P

Matched MeSH terms: Models, Statistical
Fulltext Population Pharmacokinetics of Doripenem in Critically Ill Patients with Sepsis in a Malaysian Intensive Care Unit

Abdul-Aziz MH, Abd Rahman AN, Mat-Nor MB, Sulaiman H, Wallis SC, Lipman J, et al.

Antimicrob Agents Chemother, 2016 01;60(1):206-14.
PMID: 26482304 DOI: 10.1128/AAC.01543-15

Doripenem has been recently introduced in Malaysia and is used for severe infections in the intensive care unit. However, limited data currently exist to guide optimal dosing in this scenario. We aimed to describe the population pharmacokinetics of doripenem in Malaysian critically ill patients with sepsis and use Monte Carlo dosing simulations to develop clinically relevant dosing guidelines for these patients. In this pharmacokinetic study, 12 critically ill adult patients with sepsis receiving 500 mg of doripenem every 8 h as a 1-hour infusion were enrolled. Serial blood samples were collected on 2 different days, and population pharmacokinetic analysis was performed using a nonlinear mixed-effects modeling approach. A two-compartment linear model with between-subject and between-occasion variability on clearance was adequate in describing the data. The typical volume of distribution and clearance of doripenem in this cohort were 0.47 liters/kg and 0.14 liters/kg/h, respectively. Doripenem clearance was significantly influenced by patients' creatinine clearance (CL(CR)), such that a 30-ml/min increase in the estimated CL(CR) would increase doripenem CL by 52%. Monte Carlo dosing simulations suggested that, for pathogens with a MIC of 8 mg/liter, a dose of 1,000 mg every 8 h as a 4-h infusion is optimal for patients with a CL(CR) of 30 to 100 ml/min, while a dose of 2,000 mg every 8 h as a 4-h infusion is best for patients manifesting a CL(CR) of >100 ml/min. Findings from this study suggest that, for doripenem usage in Malaysian critically ill patients, an alternative dosing approach may be meritorious, particularly when multidrug resistance pathogens are involved.

Matched MeSH terms: Models, Statistical*
Environment and air pollution: health services bequeath to grotesque menace

Qureshi MI, Rasli AM, Awan U, Ma J, Ali G, Faridullah, et al.

Environ Sci Pollut Res Int, 2015 Mar;22(5):3467-76.
PMID: 25242593 DOI: 10.1007/s11356-014-3584-2

The objective of the study is to establish the link between air pollution, fossil fuel energy consumption, industrialization, alternative and nuclear energy, combustible renewable and wastes, urbanization, and resulting impact on health services in Malaysia. The study employed two-stage least square regression technique on the time series data from 1975 to 2012 to possibly minimize the problem of endogeniety in the health services model. The results in general show that air pollution and environmental indicators act as a strong contributor to influence Malaysian health services. Urbanization and nuclear energy consumption both significantly increases the life expectancy in Malaysia, while fertility rate decreases along with the increasing urbanization in a country. Fossil fuel energy consumption and industrialization both have an indirect relationship with the infant mortality rate, whereas, carbon dioxide emissions have a direct relationship with the sanitation facility in a country. The results conclude that balancing the air pollution, environment, and health services needs strong policy vistas on the end of the government officials.

Matched MeSH terms: Models, Statistical*
Computerized segmentation and measurement of chronic wound images

Ahmad Fauzi MF, Khansa I, Catignani K, Gordillo G, Sen CK, Gurcan MN

Comput Biol Med, 2015 May;60:74-85.
PMID: 25756704 DOI: 10.1016/j.compbiomed.2015.02.015

An estimated 6.5 million patients in the United States are affected by chronic wounds, with more than US$25 billion and countless hours spent annually for all aspects of chronic wound care. There is a need for an intelligent software tool to analyze wound images, characterize wound tissue composition, measure wound size, and monitor changes in wound in between visits. Performed manually, this process is very time-consuming and subject to intra- and inter-reader variability. In this work, our objective is to develop methods to segment, measure and characterize clinically presented chronic wounds from photographic images. The first step of our method is to generate a Red-Yellow-Black-White (RYKW) probability map, which then guides the segmentation process using either optimal thresholding or region growing. The red, yellow and black probability maps are designed to handle the granulation, slough and eschar tissues, respectively; while the white probability map is to detect the white label card for measurement calibration purposes. The innovative aspects of this work include defining a four-dimensional probability map specific to wound characteristics, a computationally efficient method to segment wound images utilizing the probability map, and auto-calibration of wound measurements using the content of the image. These methods were applied to 80 wound images, captured in a clinical setting at the Ohio State University Comprehensive Wound Center, with the ground truth independently generated by the consensus of at least two clinicians. While the mean inter-reader agreement between the readers varied between 67.4% and 84.3%, the computer achieved an average accuracy of 75.1%.

Matched MeSH terms: Models, Statistical
Fulltext Magnetic resonance image tissue classification using an automatic method

Yazdani S, Yusof R, Riazi A, Karimian A

Diagn Pathol, 2014;9:207.
PMID: 25540017 DOI: 10.1186/s13000-014-0207-7

Brain segmentation in magnetic resonance images (MRI) is an important stage in clinical studies for different issues such as diagnosis, analysis, 3-D visualizations for treatment and surgical planning. MR Image segmentation remains a challenging problem in spite of different existing artifacts such as noise, bias field, partial volume effects and complexity of the images. Some of the automatic brain segmentation techniques are complex and some of them are not sufficiently accurate for certain applications. The goal of this paper is proposing an algorithm that is more accurate and less complex).

Matched MeSH terms: Models, Statistical
Fingerprint verification prediction model in hand dermatitis

Lee CK, Chang CC, Johor A, Othman P, Baba R

Int J Dermatol, 2015 Jul;54(7):765-70.
PMID: 25427962 DOI: 10.1111/ijd.12451

Hand dermatitis associated fingerprint changes is a significant problem and affects fingerprint verification processes. This study was done to develop a clinically useful prediction model for fingerprint verification in patients with hand dermatitis.

Matched MeSH terms: Models, Statistical
Periodontal treatment needs and workforce requirements: comparisons between the normative and sociodental approaches using different skill mix models

Ab-Murat N, Sheiham A, Tsakos G, Watt R

Community Dent Oral Epidemiol, 2015 Apr;43(2):106-15.
PMID: 25178437 DOI: 10.1111/cdoe.12125

Assessment of dental treatment needs has predominantly been based on the normative approach, despite its numerous limitations. The sociodental approach is a more rational method of needs assessment as it incorporates broader concepts of health and needs and behavioural propensity. This study compares estimates of periodontal dental treatment needs and workforce requirements for different skill mixes using normative and sociodental approaches among a sample of adults in Malaysia.

Matched MeSH terms: Models, Statistical
Automated diagnosis of Age-related Macular Degeneration using greyscale features from digital fundus images

Mookiah MR, Acharya UR, Koh JE, Chandran V, Chua CK, Tan JH, et al.

Comput Biol Med, 2014 Oct;53:55-64.
PMID: 25127409 DOI: 10.1016/j.compbiomed.2014.07.015

Age-related Macular Degeneration (AMD) is one of the major causes of vision loss and blindness in ageing population. Currently, there is no cure for AMD, however early detection and subsequent treatment may prevent the severe vision loss or slow the progression of the disease. AMD can be classified into two types: dry and wet AMDs. The people with macular degeneration are mostly affected by dry AMD. Early symptoms of AMD are formation of drusen and yellow pigmentation. These lesions are identified by manual inspection of fundus images by the ophthalmologists. It is a time consuming, tiresome process, and hence an automated diagnosis of AMD screening tool can aid clinicians in their diagnosis significantly. This study proposes an automated dry AMD detection system using various entropies (Shannon, Kapur, Renyi and Yager), Higher Order Spectra (HOS) bispectra features, Fractional Dimension (FD), and Gabor wavelet features extracted from greyscale fundus images. The features are ranked using t-test, Kullback-Lieber Divergence (KLD), Chernoff Bound and Bhattacharyya Distance (CBBD), Receiver Operating Characteristics (ROC) curve-based and Wilcoxon ranking methods in order to select optimum features and classified into normal and AMD classes using Naive Bayes (NB), k-Nearest Neighbour (k-NN), Probabilistic Neural Network (PNN), Decision Tree (DT) and Support Vector Machine (SVM) classifiers. The performance of the proposed system is evaluated using private (Kasturba Medical Hospital, Manipal, India), Automated Retinal Image Analysis (ARIA) and STructured Analysis of the Retina (STARE) datasets. The proposed system yielded the highest average classification accuracies of 90.19%, 95.07% and 95% with 42, 54 and 38 optimal ranked features using SVM classifier for private, ARIA and STARE datasets respectively. This automated AMD detection system can be used for mass fundus image screening and aid clinicians by making better use of their expertise on selected images that require further examination.

Matched MeSH terms: Models, Statistical
Mapping and modelling the geographical distribution of soil-transmitted helminthiases in Peninsular Malaysia: implications for control approaches

Ngui R, Shafie A, Chua KH, Mistam MS, Al-Mekhlafi HM, Sulaiman WW, et al.

Geospat Health, 2014 May;8(2):365-76.
PMID: 24893014

Soil-transmitted helminth (STH) infections in Malaysia are still highly prevalent, especially in rural and remote communities. Complete estimations of the total disease burden in the country has not been performed, since available data are not easily accessible in the public domain. The current study utilised geographical information system (GIS) to collate and map the distribution of STH infections from available empirical survey data in Peninsular Malaysia, highlighting areas where information is lacking. The assembled database, comprising surveys conducted between 1970 and 2012 in 99 different locations, represents one of the most comprehensive compilations of STH infections in the country. It was found that the geographical distribution of STH varies considerably with no clear pattern across the surveyed locations. Our attempt to generate predictive risk maps of STH infections on the basis of ecological limits such as climate and other environmental factors shows that the prevalence of Ascaris lumbricoides is low along the western coast and the southern part of the country, whilst the prevalence is high in the central plains and in the North. In the present study, we demonstrate that GIS can play an important role in providing data for the implementation of sustainable and effective STH control programmes to policy-makers and authorities in charge.

Matched MeSH terms: Models, Statistical
Fulltext Optimization of milk-based medium for efficient cultivation of Bifidobacterium pseudocatenulatum G4 using face-centered central composite-response surface methodology

Abdul Khalil K, Mustafa S, Mohammad R, Bin Ariff A, Shaari Y, Abdul Manap Y, et al.

Biomed Res Int, 2014;2014:787989.
PMID: 24527457 DOI: 10.1155/2014/787989

This study was undertaken to optimize skim milk and yeast extract concentration as a cultivation medium for optimal Bifidobacteria pseudocatenulatum G4 (G4) biomass and β -galactosidase production as well as lactose and free amino nitrogen (FAN) balance after cultivation period. Optimization process in this study involved four steps: screening for significant factors using 2(3) full factorial design, steepest ascent, optimization using FCCD-RSM, and verification. From screening steps, skim milk and yeast extract showed significant influence on the biomass production and, based on the steepest ascent step, middle points of skim milk (6% wt/vol) and yeast extract (1.89% wt/vol) were obtained. A polynomial regression model in FCCD-RSM revealed that both factors were found significant and the strongest influence was given by skim milk concentration. Optimum concentrations of skim milk and yeast extract for maximum biomass G4 and β -galactosidase production meanwhile low in lactose and FAN balance after cultivation period were 5.89% (wt/vol) and 2.31% (wt/vol), respectively. The validation experiments showed that the predicted and experimental values are not significantly different, indicating that the FCCD-RSM model developed is sufficient to describe the cultivation process of G4 using skim-milk-based medium with the addition of yeast extract.

Matched MeSH terms: Models, Statistical
Fulltext Individual skills based volunteerism and life satisfaction among healthcare volunteers in Malaysia: role of employer encouragement, self-esteem and job performance, a cross-sectional study

Veerasamy C, Sambasivan M, Kumar N

PLoS One, 2013;8(10):e77698.
PMID: 24194894 DOI: 10.1371/journal.pone.0077698

The purpose of this paper is to analyze two important outcomes of individual skills-based volunteerism (ISB-V) among healthcare volunteers in Malaysia. The outcomes are: job performance and life satisfaction. This study has empirically tested the impact of individual dimensions of ISB-V along with their inter-relationships in explaining the life satisfaction and job performance. Besides, the effects of employer encouragement to the volunteers, demographic characteristics of volunteers, and self-esteem of volunteers on job performance and life satisfaction have been studied. The data were collected through a questionnaire distributed to 1000 volunteers of St. John Ambulance in Malaysia. Three hundred and sixty six volunteers responded by giving their feedback. The model was tested using Structural Equation Modeling (SEM). The main results of this study are: (1) Volunteer duration and nature of contact affects life satisfaction, (2) volunteer frequency has impact on volunteer duration, (3) self-esteem of volunteers has significant relationships with volunteer frequency, job performance and life satisfaction, (4) job performance of volunteers affect their life satisfaction and (5) current employment level has significant relationships with duration of volunteering, self esteem, employer encouragement and job performance of volunteers. The model in this study has been able to explain 39% of the variance in life satisfaction and 45% of the variance in job performance. The current study adds significantly to the body of knowledge on healthcare volunteerism.

Matched MeSH terms: Models, Statistical
Exploring the effects of roadway characteristics on the frequency and severity of head-on crashes: case studies from Malaysian federal roads

Hosseinpour M, Yahaya AS, Sadullah AF

Accid Anal Prev, 2014 Jan;62:209-22.
PMID: 24172088 DOI: 10.1016/j.aap.2013.10.001

Head-on crashes are among the most severe collision types and of great concern to road safety authorities. Therefore, it justifies more efforts to reduce both the frequency and severity of this collision type. To this end, it is necessary to first identify factors associating with the crash occurrence. This can be done by developing crash prediction models that relate crash outcomes to a set of contributing factors. This study intends to identify the factors affecting both the frequency and severity of head-on crashes that occurred on 448 segments of five federal roads in Malaysia. Data on road characteristics and crash history were collected on the study segments during a 4-year period between 2007 and 2010. The frequency of head-on crashes were fitted by developing and comparing seven count-data models including Poisson, standard negative binomial (NB), random-effect negative binomial, hurdle Poisson, hurdle negative binomial, zero-inflated Poisson, and zero-inflated negative binomial models. To model crash severity, a random-effect generalized ordered probit model (REGOPM) was used given a head-on crash had occurred. With respect to the crash frequency, the random-effect negative binomial (RENB) model was found to outperform the other models according to goodness of fit measures. Based on the results of the model, the variables horizontal curvature, terrain type, heavy-vehicle traffic, and access points were found to be positively related to the frequency of head-on crashes, while posted speed limit and shoulder width decreased the crash frequency. With regard to the crash severity, the results of REGOPM showed that horizontal curvature, paved shoulder width, terrain type, and side friction were associated with more severe crashes, whereas land use, access points, and presence of median reduced the probability of severe crashes. Based on the results of this study, some potential countermeasures were proposed to minimize the risk of head-on crashes.

Matched MeSH terms: Models, Statistical

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