Displaying publications 181 - 200 of 315 in total

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  1. Samsiah A, Othman N, Jamshed S, Hassali MA, Wan-Mohaina WM
    Eur J Clin Pharmacol, 2016 Dec;72(12):1515-1524.
    PMID: 27637912
    PURPOSE: Reporting and analysing the data on medication errors (MEs) is important and contributes to a better understanding of the error-prone environment. This study aims to examine the characteristics of errors submitted to the National Medication Error Reporting System (MERS) in Malaysia.

    METHODS: A retrospective review of reports received from 1 January 2009 to 31 December 2012 was undertaken. Descriptive statistics method was applied.

    RESULTS: A total of 17,357 MEs reported were reviewed. The majority of errors were from public-funded hospitals. Near misses were classified in 86.3 % of the errors. The majority of errors (98.1 %) had no harmful effects on the patients. Prescribing contributed to more than three-quarters of the overall errors (76.1 %). Pharmacists detected and reported the majority of errors (92.1 %). Cases of erroneous dosage or strength of medicine (30.75 %) were the leading type of error, whilst cardiovascular (25.4 %) was the most common category of drug found.

    CONCLUSIONS: MERS provides rich information on the characteristics of reported MEs. Low contribution to reporting from healthcare facilities other than government hospitals and non-pharmacists requires further investigation. Thus, a feasible approach to promote MERS among healthcare providers in both public and private sectors needs to be formulated and strengthened. Preventive measures to minimise MEs should be directed to improve prescribing competency among the fallible prescribers identified.

    Matched MeSH terms: Databases, Factual
  2. Rehman MZ, Zamli KZ, Almutairi M, Chiroma H, Aamir M, Kader MA, et al.
    PLoS One, 2021;16(12):e0259786.
    PMID: 34855771 DOI: 10.1371/journal.pone.0259786
    Team formation (TF) in social networks exploits graphs (i.e., vertices = experts and edges = skills) to represent a possible collaboration between the experts. These networks lead us towards building cost-effective research teams irrespective of the geolocation of the experts and the size of the dataset. Previously, large datasets were not closely inspected for the large-scale distributions & relationships among the researchers, resulting in the algorithms failing to scale well on the data. Therefore, this paper presents a novel TF algorithm for expert team formation called SSR-TF based on two metrics; communication cost and graph reduction, that will become a basis for future TF's. In SSR-TF, communication cost finds the possibility of collaboration between researchers. The graph reduction scales the large data to only appropriate skills and the experts, resulting in real-time extraction of experts for collaboration. This approach is tested on five organic and benchmark datasets, i.e., UMP, DBLP, ACM, IMDB, and Bibsonomy. The SSR-TF algorithm is able to build cost-effective teams with the most appropriate experts-resulting in the formation of more communicative teams with high expertise levels.
    Matched MeSH terms: Databases, Factual
  3. Karobari MI, Maqbool M, Ahmad P, Abdul MSM, Marya A, Venugopal A, et al.
    Biomed Res Int, 2021;2021:6657167.
    PMID: 34746305 DOI: 10.1155/2021/6657167
    Background: Citation analysis has emerged to play a significant role in recognition of the most useful areas of research. Endodontic microbiology has been a topic of interest for endodontists as well as periodontists and oral surgeons. This bibliometric analysis is aimed at identifying and reporting the characteristics of the top 50 cited articles on endodontic microbiology.

    Methods: The articles were identified through a search on Web of Science (WoS), property of Clarivate Analytics database published on endodontic microbiology. The citation information of the selected articles was recorded. The Journal of Endodontics, International Endodontic Journal, Oral Surgery Oral Medicine Oral Pathology Oral Radiology and Endodontology, Dental Traumatology, and Australian Endodontic Journal were searched in the search title. Descriptive and bivariate analyses were performed using a statistical software package SPSS. Statistical analysis was performed using Shapiro-Wilk, Kruskal-Wallis, Post hoc, Mann-Kendall trend, and Spearman-rank tests.

    Results: The 50 most cited articles were published from 1965 to 2012 with citation count varying from 1065 to 103 times. The total citation counts of articles recorded were 11,525 (WoS), 12,602 (Elseviers' Scopus), and 28,871 (Google Scholar). The most prolific years in terms of publications were 2001, 2002, and 2003, with five publications each, followed by 2005 with four. The year with most citations was 1998, with 1,330 citations, followed by 1965 and 2001, with 1,065 and 1,015 citations, respectively. A total of 136 authors contributed to the top 50 most cited articles with 27 corresponding institutions from 12 different countries. The most common methodological design was in vitro study, followed by clinic-laboratory study, literature review, systematic review and meta-analysis, and animal study.

    Conclusions: The present study provided a detailed list of the top 50 most cited and classic articles on microbiology in endodontics. This will help researchers, students, and clinicians in the field of endodontics as an impressive source of information.

    Matched MeSH terms: Databases, Factual
  4. Faisal A, Ng SC, Goh SL, Lai KW
    Med Biol Eng Comput, 2018 Apr;56(4):657-669.
    PMID: 28849317 DOI: 10.1007/s11517-017-1710-2
    Quantitative thickness computation of knee cartilage in ultrasound images requires segmentation of a monotonous hypoechoic band between the soft tissue-cartilage interface and the cartilage-bone interface. Speckle noise and intensity bias captured in the ultrasound images often complicates the segmentation task. This paper presents knee cartilage segmentation using locally statistical level set method (LSLSM) and thickness computation using normal distance. Comparison on several level set methods in the attempt of segmenting the knee cartilage shows that LSLSM yields a more satisfactory result. When LSLSM was applied to 80 datasets, the qualitative segmentation assessment indicates a substantial agreement with Cohen's κ coefficient of 0.73. The quantitative validation metrics of Dice similarity coefficient and Hausdorff distance have average values of 0.91 ± 0.01 and 6.21 ± 0.59 pixels, respectively. These satisfactory segmentation results are making the true thickness between two interfaces of the cartilage possible to be computed based on the segmented images. The measured cartilage thickness ranged from 1.35 to 2.42 mm with an average value of 1.97 ± 0.11 mm, reflecting the robustness of the segmentation algorithm to various cartilage thickness. These results indicate a potential application of the methods described for assessment of cartilage degeneration where changes in the cartilage thickness can be quantified over time by comparing the true thickness at a certain time interval.
    Matched MeSH terms: Databases, Factual
  5. Feisul IM, Azmi S, Mohd Rizal AM, Zanariah H, Nik Mahir NJ, Fatanah I, et al.
    Med J Malaysia, 2017 10;72(5):271-277.
    PMID: 29197881 MyJurnal
    INTRODUCTION: An economic analysis was performed to estimate the annual cost of diabetes mellitus to Malaysia.

    METHODS: We combined published data and clinical pathways to estimate cost of follow-up and complications, then calculated the overall national cost. Costs consisted of diabetes follow-up and complications costs.

    RESULTS: Patient follow-up was estimated at RM459 per year. Complications cost were RM42,362 per patient per year for nephropathy, RM4,817 for myocardial infarction, RM5,345 for stroke, RM3,880 for heart failure, RM5,519 for foot amputation, RM479 for retinopathy and RM4,812 for cataract extraction.

    CONCLUSION: Overall, we estimated the total cost of diabetes as RM2.04 billion per year for year 2011 (both public and private sector). Of this, RM1.40 billion per year was incurred by the government. Despite some limitations, we believe our study provides insight to the actual cost of diabetes to the country. The high cost to the nation highlights the importance of primary and secondary prevention.
    Matched MeSH terms: Databases, Factual
  6. Liu F, Wang H, Liang SN, Jin Z, Wei S, Li X, et al.
    Comput Biol Med, 2023 May;157:106790.
    PMID: 36958239 DOI: 10.1016/j.compbiomed.2023.106790
    Structural magnetic resonance imaging (sMRI) is a popular technique that is widely applied in Alzheimer's disease (AD) diagnosis. However, only a few structural atrophy areas in sMRI scans are highly associated with AD. The degree of atrophy in patients' brain tissues and the distribution of lesion areas differ among patients. Therefore, a key challenge in sMRI-based AD diagnosis is identifying discriminating atrophy features. Hence, we propose a multiplane and multiscale feature-level fusion attention (MPS-FFA) model. The model has three components, (1) A feature encoder uses a multiscale feature extractor with hybrid attention layers to simultaneously capture and fuse multiple pathological features in the sagittal, coronal, and axial planes. (2) A global attention classifier combines clinical scores and two global attention layers to evaluate the feature impact scores and balance the relative contributions of different feature blocks. (3) A feature similarity discriminator minimizes the feature similarities among heterogeneous labels to enhance the ability of the network to discriminate atrophy features. The MPS-FFA model provides improved interpretability for identifying discriminating features using feature visualization. The experimental results on the baseline sMRI scans from two databases confirm the effectiveness (e.g., accuracy and generalizability) of our method in locating pathological locations. The source code is available at https://github.com/LiuFei-AHU/MPSFFA.
    Matched MeSH terms: Databases, Factual
  7. Basumatary B, Yunus MN, Verma MK
    Res Vet Sci, 2023 May;158:26-33.
    PMID: 36898955 DOI: 10.1016/j.rvsc.2023.02.010
    African swine fever (ASF) is one of the highly contagious diseases of pigs that affect both domestic and wild pigs. The primary purpose of this research was to evaluate the online social attention on the ASF research to inform the research scientists and key stakeholders in the field by reporting the concise information of the most influential articles, social engagement, and impacts of the research. This study employed the altmetrics tool to evaluate the research papers. Bibliographic data of 100 articles were collected from Scopus; altmetric data was collected from the Altmetric.com database and analyzed using SPSS and Tableau. The articles were mainly mentioned on Twitter, followed by News Outlets and significant readers on Mendeley. Pearson correlation coefficients revealed a weak and insignificant correlation between Scopus Citation and Altmetric Attention Score (AAS). Mendeley Readership and Scopus Citation were moderately correlated. However, there was a significant positive correlation between the AAS and Mendeley readership. Using altmetric tools, the paper is the first research to shed light on the characteristics of ASF on social media.
    Matched MeSH terms: Databases, Factual
  8. Wong CK, Ng KS, Choo SQR, Lee CJ, Teo YP, Liew SM, et al.
    J Infect Dev Ctries, 2023 Aug 31;17(8):1138-1145.
    PMID: 37699097 DOI: 10.3855/jidc.16967
    INTRODUCTION: The all-cause mortality for tuberculosis is 1 in every 10 patients in Malaysia. The currently available national surveillance database does not record patients' variables such as socio-economic factors, existing co-morbidities, and risk behavior for investigation. An electronic medical record system can capture this missing information and use it to determine all-cause mortality factors more accurately. Our study aims to determine the factors associated with all-cause mortality in a cohort of tuberculosis patients in a Malaysian tertiary hospital which is equipped with an electronic medical record system.

    METHODOLOGY: Records of patients diagnosed with tuberculosis from 1st January 2018 to 30th September 2019 were retrieved. Sociodemographic and clinical data were extracted. Treatment outcomes and all-cause mortality were recorded at 1 year after diagnosis. Univariate, multivariate, and stepwise regression were used to determine the factors associated with all-cause mortality.

    RESULTS: Four-hundred and seventy-one patients were reviewed. The mean age was 46.6 ± 19.7 years. The all-cause mortality rate at one year of diagnosis was 15.3%. Factors identified were age [aOR 1.026 (95% CI: 1.004-1.049)], chronic kidney disease [aOR 3.269 (1.508-7.088)], HIV positive status [aOR 4.743 (1.505-14.953)], active cancer [aOR 5.758 (1.605-20.652)], liver disease [aOR 6.220 (1.028-37.621)], and moderate to advanced chest X-ray findings [aOR 3.851 (1.033-14.354)].

    CONCLUSIONS: On average, one in seven patients diagnosed with TB died within a year in a Malaysian tertiary hospital. Identification of this vulnerable group using the associated factors found in this study may help to reduce the risk of mortality through early intervention strategies.

    Matched MeSH terms: Databases, Factual
  9. Chong HY, Allotey PA, Chaiyakunapruk N
    BMC Med Genomics, 2018 Oct 26;11(1):94.
    PMID: 30367635 DOI: 10.1186/s12920-018-0420-4
    BACKGROUND: The emergence of personalized medicine (PM) has raised some tensions in healthcare systems. PM is expensive and health budgets are constrained - efficient healthcare delivery is therefore critical. Notwithstanding the cost, many countries have started to adopt this novel technology, including resource-limited Southeast Asia (SEA) countries. This study aimed to describe the status of PM adoption in SEA, highlight the challenges and to propose strategies for future development.

    METHODS: The study included scoping review and key stakeholder interviews in four focus countries - Indonesia, Malaysia, Singapore, and Thailand. The current landscape of PM adoption was evaluated based on an assessment framework of six key themes - healthcare system, governance, access, awareness, implementation, and data. Six PM programs were evaluated for their financing and implementation mechanisms.

    RESULTS: The findings revealed SEA has progressed in adopting PM especially Singapore and Thailand. A regional pharmacogenomics research network has been established. However, PM policies and programs vary significantly. As most PM programs are champion-driven and the available funding is limited, the current PM distribution has the potential to widen existing health disparities. Low PM awareness in the society and the absence of political support with financial investment are fundamental barriers. There is a clear need to broaden opportunities for critical discourse about PM especially for policymakers. Multi-stakeholder, multi-country strategies need to be prioritized in order to leverage resources and expertise.

    CONCLUSIONS: Adopting PM remains in its infancy in SEA. To achieve an effective PM adoption, it is imperative to balance equity issues across diverse populations while improving efficiency in healthcare.

    Matched MeSH terms: Databases, Factual
  10. Yenyuwadee S, Achavanuntakul P, Phisalprapa P, Levin M, Saokaew S, Kanchanasurakit S, et al.
    Acta Derm Venereol, 2024 Jan 08;104:adv18477.
    PMID: 38189223 DOI: 10.2340/actadv.v104.18477
    Utilization of lasers and energy-based devices for surgical scar minimization has been substantially evaluated in placebo-controlled trials. The aim of this study was to compare reported measures of efficacy of lasers and energy-based devices in clinical trials in preventing surgical scar formation in a systematic review and network meta-analyses. Five electronic databases, PubMed, Scopus, Embase, ClinicalTrials.gov, and the Cochrane Library, were searched to retrieve relevant articles. The search was limited to randomized controlled trials that reported on clinical outcomes of surgical scars with treatment initiation no later than 6 months after surgery and a follow-up period of at least 3 months. A total of 18 randomized controlled trials involving 482 participants and 671 postsurgical wounds were included in the network meta-analyses. The results showed that the most efficacious treatments were achieved using low-level laser therapy) (weighted mean difference -3.78; 95% confidence interval (95% CI) -6.32, -1.24) and pulsed dye laser (weighted mean difference -2.46; 95% CI -4.53, -0.38). Nevertheless, low-level laser therapy and pulsed dye laser demonstrated comparable outcomes in surgical scar minimization (weighted mean difference -1.32, 95% CI -3.53, 0.89). The findings of this network meta-analyses suggest that low-level laser therapy and pulsed dye laser are both effective treatments for minimization of scar formation following primary closure of surgical wounds with comparable treatment outcomes.
    Matched MeSH terms: Databases, Factual
  11. Law NLW, Hong LW, Tan SSN, Foo CJ, Lee D, Voon PJ
    BMJ Open, 2024 Feb 10;14(2):e079559.
    PMID: 38341218 DOI: 10.1136/bmjopen-2023-079559
    INTRODUCTION: Multidisciplinary teams (MDTs) are integral to oncology management, involving specialised healthcare professionals who collaborate to develop individualised treatment plans for patients. However, as cancer care grows more complex, MDTs must continually adapt to better address patient needs. This scoping review will explore barriers and challenges MDTs have encountered in the past decade; and propose strategies for optimising their utilisation to overcome these obstacles and improve patient care.

    METHODS AND ANALYSIS: The scoping review will follow Arksey and O'Malley's framework and begin with a literature search using keywords in electronic databases such as PubMed/MEDLINE, Scopus and PsychINFO, covering the period from January 2013 to December 2022 and limited to English language publications. Four independent reviewers will screen titles and abstracts based on predefined inclusion criteria, followed by full-text review of selected titles. Relevant references cited in the publications will also be examined. A Preferred Reporting Items for Systematic reviews and Meta-Analyses flow diagram will be utilised to illustrate the methodology. Data from selected publications will be extracted, analysed, and categorised for further analysis.

    ETHICS AND DISSEMINATION: The results of the scoping review will provide a comprehensive overview of the barriers and challenges encountered by oncology MDTs over the past decade. These findings will contribute to the existing literature and provide insights into areas that require improvement in the functioning of MDTs in oncology management. The results will be disseminated through publication in a scientific journal, which will help to share the findings with the wider healthcare community and facilitate further research and discussion in this field.

    TRIAL REGISTRATION DETAILS: The protocol for this scoping review is registered with Open Science Framework, available at DOI 10.17605/OSF.IO/R3Y8U.

    Matched MeSH terms: Databases, Factual
  12. Slik JW, Arroyo-Rodríguez V, Aiba S, Alvarez-Loayza P, Alves LF, Ashton P, et al.
    Proc Natl Acad Sci U S A, 2015 Jun 16;112(24):7472-7.
    PMID: 26034279 DOI: 10.1073/pnas.1423147112
    The high species richness of tropical forests has long been recognized, yet there remains substantial uncertainty regarding the actual number of tropical tree species. Using a pantropical tree inventory database from closed canopy forests, consisting of 657,630 trees belonging to 11,371 species, we use a fitted value of Fisher's alpha and an approximate pantropical stem total to estimate the minimum number of tropical forest tree species to fall between ∼ 40,000 and ∼ 53,000, i.e., at the high end of previous estimates. Contrary to common assumption, the Indo-Pacific region was found to be as species-rich as the Neotropics, with both regions having a minimum of ∼ 19,000-25,000 tree species. Continental Africa is relatively depauperate with a minimum of ∼ 4,500-6,000 tree species. Very few species are shared among the African, American, and the Indo-Pacific regions. We provide a methodological framework for estimating species richness in trees that may help refine species richness estimates of tree-dependent taxa.
    Matched MeSH terms: Databases, Factual
  13. Rasel MA, Abdul Kareem S, Kwan Z, Yong SS, Obaidellah U
    Comput Biol Med, 2024 Aug;178:108758.
    PMID: 38905895 DOI: 10.1016/j.compbiomed.2024.108758
    Melanoma, one of the deadliest types of skin cancer, accounts for thousands of fatalities globally. The bluish, blue-whitish, or blue-white veil (BWV) is a critical feature for diagnosing melanoma, yet research into detecting BWV in dermatological images is limited. This study utilizes a non-annotated skin lesion dataset, which is converted into an annotated dataset using a proposed imaging algorithm (color threshold techniques) on lesion patches based on color palettes. A Deep Convolutional Neural Network (DCNN) is designed and trained separately on three individual and combined dermoscopic datasets, using custom layers instead of standard activation function layers. The model is developed to categorize skin lesions based on the presence of BWV. The proposed DCNN demonstrates superior performance compared to the conventional BWV detection models across different datasets. The model achieves a testing accuracy of 85.71 % on the augmented PH2 dataset, 95.00 % on the augmented ISIC archive dataset, 95.05 % on the combined augmented (PH2+ISIC archive) dataset, and 90.00 % on the Derm7pt dataset. An explainable artificial intelligence (XAI) algorithm is subsequently applied to interpret the DCNN's decision-making process about the BWV detection. The proposed approach, coupled with XAI, significantly improves the detection of BWV in skin lesions, outperforming existing models and providing a robust tool for early melanoma diagnosis.
    Matched MeSH terms: Databases, Factual
  14. Rasel MA, Kareem SA, Obaidellah U
    Comput Biol Med, 2024 Dec;183:109250.
    PMID: 39395346 DOI: 10.1016/j.compbiomed.2024.109250
    The color of skin lesions is a crucial diagnostic feature for identifying malignant melanoma and other skin diseases. Typical colors associated with melanocytic lesions include tan, brown, black, red, white, and blue-gray. This study introduces a novel feature: the number of colors present in lesions, which can indicate the severity of skin diseases and help distinguish melanomas from benign lesions. We propose a color histogram analysis, a traditional image processing technique, to analyze the pixels of skin lesions from three publicly available datasets: PH2, ISIC2016, and Med-Node, which include dermoscopic and non-dermoscopic images. While the PH2 dataset contains ground truth about skin lesion colors, the ISIC2016 and Med-Node datasets lack such annotations; our algorithm establishes this ground truth using the color histogram analysis based on the PH2 dataset. We then design and train a 19-layer Convolutional Neural Network (CNN) with different skip connections of residual blocks to classify lesions into three categories based on the number of colors present. The DeepDream algorithm is utilized to visualize the learned features of different layers, and multiple configurations of the proposed CNN are tested, achieving the highest weighted F1-score of 75.00 % on the test set. LIME is subsequently applied to identify the most important features influencing the model's decision-making. The findings demonstrate that the number of colors in lesions is a significant feature for describing skin conditions. The proposed CNN, particularly with three skip connections, shows strong potential for clinical application in diagnosing melanoma, supporting its use alongside traditional diagnostic methods.
    Matched MeSH terms: Databases, Factual
  15. Shyam S, Wai TN, Arshad F
    Asia Pac J Clin Nutr, 2012;21(2):201-8.
    PMID: 22507605
    This paper outlines the methodology to add glycaemic index (GI) and glycaemic load (GL) functionality to food DietPLUS, a Microsoft Excel-based Malaysian food composition database and diet intake calculator. Locally determined GI values and published international GI databases were used as the source of GI values. Previously published methodology for GI value assignment was modified to add GI and GL calculators to the database. Two popular local low GI foods were added to the DietPLUS database, bringing up the total number of foods in the database to 838 foods. Overall, in relation to the 539 major carbohydrate foods in the Malaysian Food Composition Database, 243 (45%) food items had local Malaysian values or were directly matched to International GI database and another 180 (33%) of the foods were linked to closely-related foods in the GI databases used. The mean ± SD dietary GI and GL of the dietary intake of 63 women with previous gestational diabetes mellitus, calculated using DietPLUS version3 were, 62 ± 6 and 142 ± 45, respectively. These values were comparable to those reported from other local studies. DietPLUS version3, a simple Microsoft Excel-based programme aids calculation of diet GI and GL for Malaysian diets based on food records.
    Matched MeSH terms: Databases, Factual*
  16. Mohamed IN, Helms PJ, McLay JS
    Basic Clin Pharmacol Toxicol, 2012 Dec;111(6):396-401.
    PMID: 22734606 DOI: 10.1111/j.1742-7843.2012.00917.x
    Drug switching is a common medical practice. It indicates continuation of treatment regardless of the reason why the original therapy was stopped and switched. Therefore, the aims of this study were to develop a novel method for determining drug switching from routinely acquired NHS health data and to explore the aspect of continuation of care for patients. Patients who were first prescribed ramipril, simvastatin and an angiotensin receptor blocker (ARB) between 1 March 2004 and 28 February 2007 and discontinued their medication within 6 months of the index prescription were identified from the PTI database. The identified patients were then categorized into three groups: i) patients who were switched to a different drug for the same medical condition, ii) patients who were being prescribed with other types of antihypertensive/lipid-regulating drug prior to the initiation of study; and iii) patients who were without any continuation of care or therapy. Twenty percent (808), 29%(1429) and 14%(455) of the identified patients discontinued ramipril, simvastatin and ARB, respectively, within 6 months of an index prescription. Among the ramipril discontinuation group, 36.4% of the patients were switched to another antihypertensive, while another 31.6% of them were without continuation of care. In patients discontinuing ARB, 30.6% were switched, while another 30.1% were without continuation of treatment. In patients discontinuing simvastatin, 28.8% were switched to another lipid-regulating medicine, while another 63.1% of them were without continuation of care. The results of this study confirm that primary care prescribing databases can be used to determine drug-switching information and continuation of care/therapy.
    Matched MeSH terms: Databases, Factual*
  17. Ding WY, Lee CK, Choon SE
    Int J Dermatol, 2010 Jul;49(7):834-41.
    PMID: 20618508 DOI: 10.1111/j.1365-4632.2010.04481.x
    BACKGROUND: Adverse drug reactions are most commonly cutaneous in nature. Patterns of cutaneous adverse drug reactions (ADRs) and their causative drugs vary among the different populations previously studied.
    OBJECTIVE: Our aim is to determine the clinical pattern of drug eruptions and the common drugs implicated, particularly in severe cutaneous ADRs in our population.
    MATERIALS AND METHODS: This study was done by analyzing the database established for all adverse cutaneous drug reactions seen from January 2001 until December 2008.
    RESULTS: A total of 281 cutaneous ADRs were seen in 280 patients. The most common reaction pattern was maculopapular eruption (111 cases, 39.5%) followed by Stevens-Johnson Syndrome (SJS: 79 cases, 28.1%), drug reaction with eosinophilia and systemic symptoms (DRESS: 19 cases, 6.8%), toxic epidermal necrolysis (TEN: 16 cases, 5.7 %), urticaria/angioedema (15 cases, 5.3%) and fixed drug eruptions (15 cases, 5.3%). Antibiotics (38.8%) and anticonvulsants (23.8%) accounted for 62.6% of the 281 cutaneous ADRs seen. Allopurinol was implicated in 39 (13.9%), carbamazepine in 29 (10.3%), phenytoin in 27 (9.6%) and cotrimoxazole in 26 (9.3%) cases. Carbamazepine, allopurinol and cotrimoxazole were the three main causative drugs of SJS/TEN accounting for 24.0%, 18.8% and 12.5% respectively of the 96 cases seen whereas DRESS was mainly caused by allopurinol (10 cases, 52.6%) and phenytoin (3 cases, 15.8%).
    DISCUSSION: The reaction patterns and drugs causing cutaneous ADRs in our population are similar to those seen in other countries although we have a much higher proportion of severe cutaneous ADRs probably due to referral bias, different prescribing habit and a higher prevalence of HLA-B*1502 and HLA-B*5801 which are genetic markers for carbamazepine-induced SJS/TEN and allopurinol-induced SJS/TEN/DRESS respectively.
    CONCLUSION: The most common reaction pattern seen in our study population was maculopapular eruptions. Antibiotics, anticonvulsants and NSAIDs were the most frequently implicated drug groups. Carbamazepine and allopurinol were the two main causative drugs of severe ADRs in our population.
    Matched MeSH terms: Databases, Factual/statistics & numerical data
  18. Hayati AN, Kamarul AK
    Med J Malaysia, 2008 Sep;63 Suppl C:50-4.
    PMID: 19227674
    To create a nationwide system to capture data on completed suicide in Malaysia i.e. the morbidity, geographic and temporal trends and the population at high risk of suicide. Data from this registry can later be used to stimulate and facilitate further research on suicide. This paper describes the rationale and processes involved in developing a national suicide registry in 2007. The diagnosis of suicide is based on the ICD-10 codes for fatal intentional self-harm (X60-X84). A case report form with an accompanying instruction manual had been prepared to ensure systematic and uniform data collection. State Forensic Pathologist's offices are responsible for data collection in their respective states, and in turn will submit the data to a central data management unit. Data collection began in July 2007 and currently in data cleaning process. Training for source data producers is ongoing. In 2008, the NSRM plans to involve university hospitals into its network as currently only Ministry of Health hospitals are involved. The NSRM will be launching its online application for case registration this year while an overview of results will be available via its public domain at www.nsrm.gov.my beginning 20 April 2008. To efficiently capture the data on suicide, a concerted effort between various agencies is needed. A lot of conceptual work and data base development remains to be done in order to position preventive efforts on a more solid foundation.
    Matched MeSH terms: Databases, Factual/statistics & numerical data
  19. Saokaew S, Sugimoto T, Kamae I, Pratoomsoot C, Chaiyakunapruk N
    PLoS One, 2015;10(11):e0141993.
    PMID: 26560127 DOI: 10.1371/journal.pone.0141993
    Health technology assessment (HTA) has been continuously used for value-based healthcare decisions over the last decade. Healthcare databases represent an important source of information for HTA, which has seen a surge in use in Western countries. Although HTA agencies have been established in Asia-Pacific region, application and understanding of healthcare databases for HTA is rather limited. Thus, we reviewed existing databases to assess their potential for HTA in Thailand where HTA has been used officially and Japan where HTA is going to be officially introduced.
    Matched MeSH terms: Databases, Factual/statistics & numerical data*
  20. Khoo TB
    J Child Neurol, 2013 Jan;28(1):56-9.
    PMID: 22532543 DOI: 10.1177/0883073812439623
    In its 2010 report, the International League Against Epilepsy Commission on Classification and Terminology had made a number of changes to the organization, terminology, and classification of seizures and epilepsies. This study aims to test the usefulness of this revised classification scheme on children with epilepsies aged between 0 and 18 years old. Of 527 patients, 75.1% only had 1 type of seizure and the commonest was focal seizure (61.9%). A specific electroclinical syndrome diagnosis could be made in 27.5%. Only 2.1% had a distinctive constellation. In this cohort, 46.9% had an underlying structural, metabolic, or genetic etiology. Among the important causes were pre-/perinatal insults, malformation of cortical development, intracranial infections, and neurocutaneous syndromes. However, 23.5% of the patients in our cohort were classified as having "epilepsies of unknown cause." The revised classification scheme is generally useful for pediatric patients. To make it more inclusive and clinically meaningful, some local customizations are required.

    Study site: The pediatric neurology clinic at the Institute of Pediatrics, Kuala
    Lumpur Hospital
    Matched MeSH terms: Databases, Factual/statistics & numerical data
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