Displaying publications 121 - 140 of 870 in total

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  1. Rabihah Md. Sum
    MyJurnal
    Risk management requires human judgements, from risk identification, assessment to response. Although automated tools are useful in handling large amounts of data and in performing complex calculations rapidly, humans undertake the entire risk management process. They bring to the process their intuitions, insights, previous experiences and skills. Therefore, creating a rich source of information of risks faced by an organisation. Ignoring human factors may impoverish information and limit risk management to only measurable factors. This study contributes to the field of decision-making and risk assessment by investigating and discussing in detail how to quantify subjective judgements using the Analytic Hierarchy Process (AHP). AHP is used to assess risk of an insurance company. It discusses how to do risk assessment by combining both intuition and analytic in the decision-making process. The study defines intuition as knowledge and experience, and analytic as the mathematics or quantitative analysis to derive the result. It demonstrates how Analytic Hierarchy Process (AHP) - a flexible multi-attribute or multi-criteria decision making tool, enables risk managers to use both intuition and analytic to do risk assessment. Risk assessment using AHP produces global priority weights representing the overall risk ranking of an insurance company. The study develops a risk assessment problem and uses AHP to organise and structure risks and sub-risks of the problem. It uses formative evaluation method with open-ended questionnaires to obtain feedbacks from risk managers on AHP. Three employees of a risk management department in a government agency assesses the risks using AHP. AHP strengths are easy to use and understand, improves risk assessment and useful for risk assessment problems that have scarce or no data. AHP limitation are the numbers and repetitiveness of the pairwise comparisons. The participants either ignore some of the pairwise questions or they answer randomly instead of deliberate judgements.
    Matched MeSH terms: Risk Assessment
  2. Yang SR, Yeh YL
    Sains Malaysiana, 2015;44:1677-1683.
    Countering the dangers associated the present extreme climate not only requires continuous improvement of local disaster
    prevention engineering infrastructure but also needs an enhanced understanding of the causes of the disasters. This study
    investigates the geologic hazard risk of 53 slopeland villages in Pingtung county of southern Taiwan. First, remote sensing
    (RS) techniques were utilized to interpret environmental geology and geologic hazard zonation, including dip slope, fault,
    landslide and debris flow. GIS map overlay analysis was used to further identify the extent of the geologic hazard zonation.
    As a final step, field investigation is used to comprehend geologic, topographic conditions and the geologic hazard risk
    specific to each locality. Based on data analysis and field investigation results, this study successfully integrates RS, GIS
    and GPS techniques to construct a geologic hazard risk assessment method of slopeland village. The results of this study
    can be used to promote support for future disaster prevention and disaster mitigation efforts.
    Matched MeSH terms: Risk Assessment
  3. Sarva Mangala Praveena, Caryn Liew Suet Lin
    Sains Malaysiana, 2015;44:91-99.
    Freshwater fish has been studied and reported numerously. However, little attention has been made and limited studies available on local marine fish in Malaysia. Thus, in this study, concentrations of heavy metals (Cd, Cr, Pb and Cu) were studied in four major local marine fish Megalaspis cordyla (hardtail scad), Rastrelliger kanagurta (Indian mackerel), Selaroides leptolepis (yellowstripe scad) and Sardinella fimbriata (fringescale sardinella). The study was also intended to estimate potential health risk assessment from these heavy metals to the consumption of fish and assess maximum allowable fish consumption rate. The range of heavy metal concentrations were 0.053-0.096 mg/kg for Cd, 1.16-2.34 mg/kg for Cr, 8.34-12.44 mg/kg for Pb and 1.40-3.21 mg/kg for Cu in four major self-caught saltwater fish. Heavy metal levels of Cd and Cu in the local marine fish from Port Dickson are below the limit enforced by Food Regulations (1985) while the levels of Cr and Pb have exceeded the limit. Potential health risks associated with Cd, Cr, Cu and Pb were assessed based on target hazard quotients. HQ values calculated for Cd, Cr and Cu were less than 1, thus indicate that no adverse effects while HQ values for Pb exceeded 1 for all the fish species assessed with the exception of Megalaspis spp and Sardinella sppa. Cr was the highest while Pb concentrations were the lowest in all the studied fish samples for maximum allowable fish consumption rate. A long term monitoring program is crucial to be done in coastal areas with high consumption of local marine fish along Port Dickson to obtain real consumption rates and other cofounders factors in local population.
    Matched MeSH terms: Risk Assessment
  4. Pulikkotil SJ, Nath S, Muthukumaraswamy, Dharamarajan L, Jing KT, Vaithilingam RD
    Community Dent Health, 2020 Feb 27;37(1):12-21.
    PMID: 32031339 DOI: 10.1922/CDH_4569Pulikkotil10
    OBJECTIVE: To determine whether alcohol consumption is associated with the risk of periodontitis.

    BASIC RESEARCH DESIGN: Systematic review and meta-analysis of observational studies performed using the Preferred Reporting Items for Systematic Review and Meta-Analyses guidelines.

    METHOD: PubMed and Scopus were searched for eligible articles published in English from inception till November 2018. The quality of studies was assessed by the Newcastle Ottawa Scale. Pooled odds ratios (OR) and 95% confidence intervals (CI) were calculated for the risk of periodontitis associated with highest versus lowest/non-alcohol in a random effects meta-analysis model. Heterogeneity and sensitivity were investigated in meta regression analysis. A funnel plot was used to assess publication bias.

    RESULTS: Twenty-nine observational studies were included. One study with two separate datasets was considered as two separate studies for analysis. Alcohol consumption was significantly associated with the presence of periodontitis (OR = 1.26, 95% CI= 1.11-1.41). Significant heterogeneity (I2=71%) was present in the overall analysis, primarily attributable to sampling cross-sectional studies (I2=76.6%). A funnel plot and Egger tests (p=0.0001) suggested the presence of publication bias.

    CONCLUSION: Alcohol consumption was associated with increased occurrence of periodontitis and should be considered as a parameter in periodontal risk assessment. Publication bias should be explored in future studies.

    Matched MeSH terms: Risk Assessment
  5. Masseran N, Mohd Safari MA
    J Environ Manage, 2020 Jun 15;264:110429.
    PMID: 32217317 DOI: 10.1016/j.jenvman.2020.110429
    Intensity-duration-frequency (IDF) curves can serve as useful tools in risk assessment of extreme environmental events. Thus, this study proposes an IDF approach for evaluating the risk of expected occurrences of extreme air pollution as measured by an air pollution index (API). Hourly data of Klang city in Malaysia from 1997 to 2016 are analyzed. For each year, a block maxima size is determined based on four different monsoon seasons. Generalized extreme value (GEV) distribution is used as a model to represent the probabilistic behavior of maximum intensity of the API, which is derived from each block. Based on the GEV model, the IDF curves are developed to estimate the extreme pollution intensities that correspond to various duration hours and return periods. Considering the IDF curves, we found that for any duration hour, the magnitude of pollution intensity tends to be high in parallel with increasing return periods. In fact, a high-intensity pollution event that poses a high risk of affecting the environment is less frequent than low-intensity pollution. In conclusion, the IDF curves provide a good basis for decision makers to assess the expected risk of extreme pollution events in the future.
    Matched MeSH terms: Risk Assessment
  6. Mohammad Razaul Karim, Sumiani Yusoff, Hashim Abdul Razak, Faisal I. Chowdhury, Hossain Zabed
    Sains Malaysiana, 2018;47:523-530.
    Technical benefit of incorporation of Palm Oil Clinker (POC) in cement-based applications has been proven in recent
    studies. The aim of this work was to assess the heavy metal leaching behavior to ensure environmental safety of using
    POC in cement-based applications. The chemical composition, morphology, total organic carbon (TOC) and mineralogy
    were determined using XRF, FESEM, TOC analyzers and XRD to select appropriate chemical reagents for complete digestion.
    HNO3
    , HF and HClO4
    were used for digestion of POC to measure heavy metal content using ICP-MS. The chemical reagents
    CH3
    COOH, NH2
    OH-HCl, H2
    O2
    +CH3
    COONH4
    and HF+HNO3
    +HCl were used for extraction of acid soluble, reducible,
    oxidizable and residual fractions of heavy metals in POC, respectively. The leaching toxicity of the POC was investigated
    by the USEPA 1311 TCLP method. The result showed the presence of Be, V, Cr, Ni, Cu, Zn, As, Se, Ag, Cd, Ba and Pb with
    levels of 5.13, 11.02, 2.65, 1.93, 45.43, 11.84, 15.07, 0, 0, 81.97 and 1.76 mg/kg, respectively, in POC. The leaching value
    in mg/L of As (4.56), Cu(1.05), Be (0.89), Zn(0.51), Ba(0.26), Ni (0.17), V(0.15), Cr(0.001) and Se (0.001) is found well
    below the standard limit of risk. Risk assessment code (RAC) analysis confirms the safe incorporation of POC in cementbased
    applications.
    Matched MeSH terms: Risk Assessment
  7. Nurulain M, Syed Ismail S, Emilia Z, Vivien H
    Malaysian Journal of Public Health Medicine, 2017;17 Special(1):123-132.
    Agriculture sector accounts significant numbers of injuries and fatalities in the workplace particularly related to pesticide management. Among three main pathways of pesticide exposure, dermal contact is the most common route, which exposure usually occurs during pesticide mixing/loading, application, harvesting and other farming activities. This review aims to present and discuss several vital components of pesticide dermal exposure among agriculture workers, as well as pesticide application in agriculture sector in Malaysia involving different commodity agriculture sub-sectors. Pesticide exposure was discussed from perspective of three pesticide management activities (i.e. preparation, application and cleaning) that contribute to the risk of exposure through three routes (i.e. emission, deposition, transfer). Moreover, this paper also discussed pesticide dermal exposure risk assessment methods which can be defined into exposure assessment and effect assessment. The exposure rate was affected by various factors such as application equipment, application rate and duration, type of pesticide formulation, pesticide management stage, usage of personal protective equipment, training and aptitude of the applicator as well as environmental factors (i.e. temperature, humidity, wind speed and direction). The factors mention earlier have been used to explain the exposure distribution over different parts of the body and support the fact that pesticide type was not a major factor in total exposure.
    Matched MeSH terms: Risk Assessment
  8. Ghani Z, Anuar A, Majid Z, Yoneda M
    Sains Malaysiana, 2017;46:2383-2392.
    This study describes the development of a multimedia environmental fate and transport model of dichlorodiphenyltrichloroethane (DDT) at Sungai Sayong watershed. Based on the latest estimated DDT emission, the DDT concentrations in air, soil, water and sediment as well as the transfer processes were simulated under the equilibrium and steady-state assumption. Model predictions suggested that soil and sediment was the dominant sink of DDT. The results showed that the model predicted was generally good agreement with field data. Compared with degradation reaction, advection outflow was more important processes occurred in the model. Sensitivities of the model estimates to input parameters were tested. The result showed that vapour pressure (Ps) and organic carbon water partition coefficient (KOC) were the most influential parameters for the model output. The model output-concentrations of DDT in multimedia environment is very important as it can be used in future for human exposure and risk assessment of organochlorine pesticides (OCPs) at Sungai Sayong Basin.
    Matched MeSH terms: Risk Assessment
  9. Ahmed MF, Mokhtar MB
    PMID: 32344678 DOI: 10.3390/ijerph17082966
    Although toxic Cd (cadmium) and Cr (chromium) in the aquatic environment are mainly from natural sources, human activities have increased their concentrations. Several studies have reported higher concentrations of Cd and Cr in the aquatic environment of Malaysia; however, the association between metal ingestion via drinking water and human health risk has not been established. This study collected water samples from four stages of the drinking water supply chain at Langat River Basin, Malaysia in 2015 to analyze the samples by inductivity coupled plasma mass spectrometry. Mean concentrations of Cd and Cr and the time-series river data (2004-2014) of these metals were significantly within the safe limit of drinking water quality standard proposed by the Ministry of Health Malaysia and the World Health Organization. Hazard quotient (HQ) and lifetime cancer risk (LCR) values of Cd and Cr in 2015 and 2020 also indicate no significant human health risk of its ingestion via drinking water. Additionally, management of pollution sources in the Langat Basin from 2004 to 2015 decreased Cr concentration in 2020 on the basis of autoregression moving average. Although Cd and Cr concentrations were found to be within the safe limits at Langat Basin, high concentrations of these metals have been found in household tap water, especially due to the contamination in the water distribution pipeline. Therefore, a two-layer water filtration system should be introduced in the basin to achieve the United Nations Sustainable Development Goals (SDGs) 2030 agenda of a better and more sustainable future for all, especially via SDG 6 of supplying safe drinking water at the household level.
    Matched MeSH terms: Risk Assessment
  10. Zhang H, Zhang F, Song J, Tan ML, Kung HT, Johnson VC
    Environ Res, 2021 11;202:111702.
    PMID: 34284019 DOI: 10.1016/j.envres.2021.111702
    This study aims to analyze the pollution characteristics and sources of heavy metal elements for the first time in the Zhundong mining area in Xinjiang using the linear regression model. Additionaly, the health risks with their probability and infleuencing factors on different groups of people's were also evaluated using Monte Carlo (MC) simulation approach. The results shows that 89.28% of Hg was from coal combustion, 40.28% of Pb was from transportation, and 19.54% of As was from atmospheric dust. The main source of Cu and Cr was coal dust, Hg has the greatest impact on potential ecological risks. which accounted for 60.2% and 81.46% of the Cu and Cr content in soil, respectively. The all samples taken from Pb have been Extremely polluted (100%). 93.3% samples taken from As have been Extremely polluted. The overall potential ecological risk was moderate. Adults experienced higher non-carcinogenic risks of heavy metals from their diets than children. Interestingly, body weight was the main factor affecting the adult's health risks. This research provides more comprehensive information for better soil management, soil remediation, and soil pollution control in the Xinjiang mining areas.
    Matched MeSH terms: Risk Assessment
  11. Saleem F, Hassali M, Shafie A, Atif M
    J Young Pharm, 2012 Apr;4(2):101-7.
    PMID: 22754262 DOI: 10.4103/0975-1483.96624
    The study is aimed to explore the perceptions and experiences of hypertensive patients toward medication use and adherence. The study was qualitative in nature conducted at Sandamen Provisional Hospital of Quetta city, Pakistan; a public hospital catering to the health needs of about 40% of the population. A qualitative approach was used to gain an in-depth knowledge of the issues. Sixteen patients were interviewed, and the saturation point was achieved after the 14(th) interview. All interviews were audio-taped, transcribed verbatim, and were then analyzed for thematic contents by the standard content analysis framework. Thematic content analysis yielded five major themes. (1) Perceived benefits and risks of medications, (2) physician's interaction with patients, (3) perception toward traditional remedies, (4) layman concept toward medications, and (5) beliefs toward hypertension and its control. The majority of the patients carried specific unrealistic beliefs regarding the long-term use of medication; yet these beliefs were heavily accepted and practiced by the society. The study indicated a number of key themes that can be used in changing the beliefs and experiences of hypertensive patients. Physician's attitude, patient's past experiences, and knowledge related to hypertension were noted as major contributing factors thus resulting in nonadherence to therapy prescribed.
    Matched MeSH terms: Risk Assessment
  12. Sajid MR, Almehmadi BA, Sami W, Alzahrani MK, Muhammad N, Chesneau C, et al.
    PMID: 34886312 DOI: 10.3390/ijerph182312586
    Criticism of the implementation of existing risk prediction models (RPMs) for cardiovascular diseases (CVDs) in new populations motivates researchers to develop regional models. The predominant usage of laboratory features in these RPMs is also causing reproducibility issues in low-middle-income countries (LMICs). Further, conventional logistic regression analysis (LRA) does not consider non-linear associations and interaction terms in developing these RPMs, which might oversimplify the phenomenon. This study aims to develop alternative machine learning (ML)-based RPMs that may perform better at predicting CVD status using nonlaboratory features in comparison to conventional RPMs. The data was based on a case-control study conducted at the Punjab Institute of Cardiology, Pakistan. Data from 460 subjects, aged between 30 and 76 years, with (1:1) gender-based matching, was collected. We tested various ML models to identify the best model/models considering LRA as a baseline RPM. An artificial neural network and a linear support vector machine outperformed the conventional RPM in the majority of performance matrices. The predictive accuracies of the best performed ML-based RPMs were between 80.86 and 81.09% and were found to be higher than 79.56% for the baseline RPM. The discriminating capabilities of the ML-based RPMs were also comparable to baseline RPMs. Further, ML-based RPMs identified substantially different orders of features as compared to baseline RPM. This study concludes that nonlaboratory feature-based RPMs can be a good choice for early risk assessment of CVDs in LMICs. ML-based RPMs can identify better order of features as compared to the conventional approach, which subsequently provided models with improved prognostic capabilities.
    Matched MeSH terms: Risk Assessment
  13. Ahmad P, Chaudhary FA, Asif JA, AlSagob EI, Alkahtany MF, Almadi KH, et al.
    Work, 2022;71(1):177-186.
    PMID: 34924411 DOI: 10.3233/WOR-205093
    BACKGROUND: When anxiety is persistent among dental students, the consequence could be poor academic performance, ill health, lack of empathy, and exhaustion.

    OBJECTIVE: This study aimed to determine the level of anxiety along with anxiety-provoking factors among clinical dental students.

    METHODS: This study included dental undergraduate and postgraduate clinical students from a public university. A modified version of the self-administered Moss and McManus questionnaire, which consisted of 50 items, was utilized to evaluate the levels of anxiety. The results were analyzed using SPSS® version 24. The significance level was set at p 

    Matched MeSH terms: Risk Assessment
  14. Praveena SM, Omar NA
    Food Chem, 2017 Nov 15;235:203-211.
    PMID: 28554627 DOI: 10.1016/j.foodchem.2017.05.049
    Heavy metal in rice studies has attracted a greater concern worldwide. However, there have been limited studies on marketed rice samples although it represents a vital ingestion portion for a real estimation of human health risk. This study was aimed to determine both total and bioaccessible of trace elements and heavy metals (Cd, Cr, Cu, Co, Al, Zn, As, Pb and Fe) in 22 varieties of cooked rice using an inductively coupled plasma-optical emission spectroscopy. Both total and bioaccessible of trace elements and heavy metals were digested using closed-nitric acid digestion and Rijksinstituut voor Volksgezondheid en Milieu (RIVM) in vitro digestion model, respectively. Human health risks via Health Risk Assessment (HRA) were conducted to understand exposure risks involving adults and children representing Malaysian population. Zinc was the highest while As was the lowest contents for total and in their bioavailable forms. Four clusters were identified: (1) Pb, As, Co, Cd and Cr; (2) Cu and Al; (3) Fe and (4) Zn. For HRA, there was no any risks found from single element exposure. While potential carcinogenic health risks present for both adult and children from single As exposure (Life time Cancer Risk, LCR>1×10(-4)). Total Hazard Quotient values for adult and children were 27.0 and 18.0, respectively while total LCR values for adult and children were 0.0049 and 0.0032, respectively.
    Matched MeSH terms: Risk Assessment
  15. Norlen Mohamed, Lokman Hakim Sulaiman, Thahirahtul Asma Zakaria, Anis Salwa Kamarudin, Daud Abdul Rahim
    Int J Public Health Res, 2016;6(1):685-694.
    MyJurnal
    Introduction During haze, at what level should Air Pollutant Index (API) showed, public
    or private school be closed is not without controversy and is very much
    debated. Therefore, the aim of this paper is to objectively quantify the
    potential inhaled dose of PM10 associated with exposure at school and home
    microenvironments during haze. The result of the health risk assessment will
    be used to propose the API level for closing the school during haze episode.

    Methods A hypothetical haze exposure scenario was created using the breakpoints of
    PM10 concentration for calculation of API and respective inhaled dose during
    haze. To determine the potential inhaled dose, we have considered many
    factors that include time spent for specific physical intensity at school and
    home microenvironments, age-specific and physical intensity-specific
    inhalation rate (m3/min), and the indoor/outdoor ratio of PM10. To calculate
    risk quotient (RQ), the inhaled dose was compared with the health reference
    dose computed based on the concentration of PM10 in the Malaysian
    Ambient Air Quality Standard.

    Results When considering the specific exposure at each microenvironment (school
    and home), the potential inhaled dose of PM10 was substantially lower when
    school is closed for both primary and secondary school. The calculated risk
    quotient (RQ) indicates that primary school children are likely to be affected
    at slightly lower PM10 concentration (equivalent to API of 197) as compared
    to secondary school children. Short duration of high physical activity
    intensity during school breaks has contributed to a large proportion of inhaled
    dose among school children indicating the important to avoid physical
    activities during haze.

    Conclusion Based on the assessment, taking into account the uncertainty of risk
    assessment methodology, we proposed school to be closed when API reach
    190 for both primary and secondary schools. These findings and
    recommendations are only valid for naturally ventilated school and applicable
    in the context of the current API calculation system and the existing
    Recommended Air Quality Guideline values in Malaysia.
    Matched MeSH terms: Risk Assessment
  16. Madadi R, Mohamadi S, Rastegari M, Karbassi A, Rakib MRJ, Khandaker MU, et al.
    Sci Rep, 2022 Nov 17;12(1):19736.
    PMID: 36396803 DOI: 10.1038/s41598-022-21242-z
    Rapid industrialization and urbanization have resulted in environmental pollution and unsustainable development of cities. The concentration of 12 potentially toxic metal(loid)s in windowsill dust samples (n = 50) were investigated from different functional areas of Qom city with the highest level of urbanization in Iran. Spatial analyses (ArcGIS 10.3) and multivariate statistics including Principal Component Analysis and Spearman correlation (using STATISTICA-V.12) were adopted to scrutinize the possible sources of pollution. The windowsill dust was very highly enriched with Sb (50 mg/kg) and Pb (1686 mg/kg). Modified degree of contamination (mCd) and the pollution load indices (PLIzone) indicate that windowsill dust in all functional areas was polluted in the order of industrial > commercial > residential > green space. Arsenic, Cd, Mo, Pb, Sb, Cu, and Zn were sourced from a mixture of traffic and industrial activities, while Mn in the dust mainly stemmed from mining activities. Non-carcinogenic health risk (HI) showed chronic exposure of Pb for children in the industrial zone (HI = 1.73). The estimations suggest the possible carcinogenic risk of As, Pb, and Cr in the dust. The findings of this study reveal poor environmental management of the city. Emergency plans should be developed to minimize the health risks of dust to residents.
    Matched MeSH terms: Risk Assessment
  17. Huynh-Le MP, Karunamuni R, Fan CC, Asona L, Thompson WK, Martinez ME, et al.
    Prostate Cancer Prostatic Dis, 2022 Apr;25(4):755-761.
    PMID: 35152271 DOI: 10.1038/s41391-022-00497-7
    BACKGROUND: Prostate cancer risk stratification using single-nucleotide polymorphisms (SNPs) demonstrates considerable promise in men of European, Asian, and African genetic ancestries, but there is still need for increased accuracy. We evaluated whether including additional SNPs in a prostate cancer polygenic hazard score (PHS) would improve associations with clinically significant prostate cancer in multi-ancestry datasets.

    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.

    Matched MeSH terms: Risk Assessment
  18. Kasim S, Malek S, Song C, Wan Ahmad WA, Fong A, Ibrahim KS, et al.
    PLoS One, 2022;17(12):e0278944.
    PMID: 36508425 DOI: 10.1371/journal.pone.0278944
    BACKGROUND: Conventional risk score for predicting in-hospital mortality following Acute Coronary Syndrome (ACS) is not catered for Asian patients and requires different types of scoring algorithms for STEMI and NSTEMI patients.

    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.

    Matched MeSH terms: Risk Assessment
  19. Widiastuti T, Robani A, Sukmaningrum PS, Mawardi I, Ningsih S, Herianingrum S, et al.
    PLoS One, 2022;17(5):e0269039.
    PMID: 35617300 DOI: 10.1371/journal.pone.0269039
    The utilization of Islamic social finance instruments is far behind what is expected. To realize its full potential, Islamic social finance instruments must be integrated. This study examined solutions and priority strategies for integrating sustainable Islamic social finance that could be implemented in the short and long term using the Benefit, Opportunity, Cost, and Risk (BOCR) framework, which includes six aspects: Governance, sustainable financing, institutional aspect, human resources, regulations, and supporting technology. This qualitative research employed the Analytic Network Process (ANP) method using the benefit, opportunity, cost, and risk analysis. The data were obtained mainly through focus group discussions and in-depth interviews with respondents among academics, practitioners, associations, regulators, and community leaders. The respondents were selected for their expertise and experience in the selected topic. The data were processed using the Microsoft Excel and Super Decision software. There are several findings worth considering from the analysis. First, the highest priority in integrating Islamic social finance aspects are human resources (0.97), regulation (0.86), and technology (0.76). Second, based on the short- and long-term analysis, financial integration through sustainable financing (0.01 and 1.44, respectively) and improving human resource quality through certification and training (0.01 and 1.56, respectively) is a priority solution and strategy to integrate sustainable Islamic social finance. Meanwhile, according to expert judgments, integrating national data (0.24) and optimizing technology use (0.18) are priority solutions and strategies. The findings emphasize the critical role of improving human resource quality to utilize technology, with experts identifying a national data integration as the most critical solution. As a result, relevant stakeholders are concerned about technology management training for Islamic philanthropic managers, with the goal of maximizing the potential of technology's growing role and adoption.
    Matched MeSH terms: Risk Assessment
  20. Mohd Hanafiah Z, Wan Mohtar WHM, Abd Manan TS, Bachi NA, Abu Tahrim N, Abd Hamid HH, et al.
    PeerJ, 2023;11:e14719.
    PMID: 36748091 DOI: 10.7717/peerj.14719
    The environmental fate of non-steroidal anti-inflammatory drugs (NSAIDs) in the urban water cycle is still uncertain and their status is mainly assessed based on specific water components and information on human risk assessments. This study (a) explores the environmental fate of NSAIDs (ibuprofen, IBU; naproxen, NAP; ketoprofen, KET; diazepam, DIA; and diclofenac, DIC) in the urban water cycle, including wastewater, river, and treated water via gas chromatography-mass spectrophotometry (GCMS), (b) assesses the efficiency of reducing the targeted NSAIDs in sewage treatment plant (STP) using analysis of variance (ANOVA), and (c) evaluates the ecological risk assessment of these drugs in the urban water cycle via teratogenic index (TI) and risk quotient (RQ). The primary receptor of contaminants comes from urban areas, as a high concentration of NSAIDs is detected (ranging from 5.87 × 103 to 7.18 × 104 ng/L). The percentage of NSAIDs removal in STP ranged from 25.6% to 92.3%. The NAP and KET were still detected at trace levels in treated water, indicating the persistent presence in the water cycle. The TI values for NAP and DIA (influent and effluent) were more than 1, showing a risk of a teratogenic effect. The IBU, KET, and DIC had values of less than 1, indicating the risk of lethal embryo effects. The NAP and DIA can be classified as Human Pregnancy Category C (2.1 > TI ≥ 0.76). This work proved that these drugs exist in the current urban water cycle, which could induce adverse effects on humans and the environment (RQ in high and low-risk categories). Therefore, they should be minimized, if not eliminated, from the primary sources of the pollutant (i.e., STPs). These pollutants should be considered a priority to be monitored, given focus to, and listed in the guideline due to their persistent presence in the urban water cycle.
    Matched MeSH terms: Risk Assessment
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