Displaying publications 21 - 40 of 313 in total

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  1. Khoh WH, Pang YH, Yap HY
    F1000Res, 2022;11:283.
    PMID: 37600220 DOI: 10.12688/f1000research.74134.2
    Background: With the advances in current technology, hand gesture recognition has gained considerable attention. It has been extended to recognize more distinctive movements, such as a signature, in human-computer interaction (HCI) which enables the computer to identify a person in a non-contact acquisition environment. This application is known as in-air hand gesture signature recognition. To our knowledge, there are no publicly accessible databases and no detailed descriptions of the acquisitional protocol in this domain. Methods: This paper aims to demonstrate the procedure for collecting the in-air hand gesture signature's database. This database is disseminated as a reference database in the relevant field for evaluation purposes. The database is constructed from the signatures of 100 volunteer participants, who contributed their signatures in two different sessions. Each session provided 10 genuine samples enrolled using a Microsoft Kinect sensor camera to generate a genuine dataset. In addition, a forgery dataset was also collected by imitating the genuine samples. For evaluation, each sample was preprocessed with hand localization and predictive hand segmentation algorithms to extract the hand region. Then, several vector-based features were extracted. Results: In this work, classification performance analysis and system robustness analysis were carried out. In the classification analysis, a multiclass Support Vector Machine (SVM) was employed to classify the samples and 97.43% accuracy was achieved; while the system robustness analysis demonstrated low error rates of 2.41% and 5.07% in random forgery and skilled forgery attacks, respectively. Conclusions: These findings indicate that hand gesture signature is not only feasible for human classification, but its properties are also robust against forgery attacks.
    Matched MeSH terms: Databases, Factual
  2. Daud A, Nawi AM, Aizuddin AN, Yahya MF
    Glob Heart, 2023;18(1):46.
    PMID: 37649652 DOI: 10.5334/gh.1255
    BACKGROUND: Bystander cardiopulmonary resuscitation (CPR) and using an automated external defibrillator (AED) can improve out-of-hospital cardiac arrest survival. However, bystander CPR and AED rates remained consistently low. The goal of this systematic review was to assess factors influencing community willingness to perform CPR and use an AED for out-of-hospital cardiac arrest survival (OHCA) victims, as well as its barriers.

    METHODS: The review processes (PROSPERO: CRD42021257851) were conducted following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) review protocol; formulation of review questions; systematic search strategy based on identification, screening, and eligibility using established databases including Scopus, Web of Science, and Medline Complete via EBSCOhost; quality appraisal; and data extraction and analysis. There is identification of full-text journal articles that were published between 2016 and 2021 and written in English.

    RESULTS: Of the final 13 articles, there are six identified factors associated with willingness to perform CPR and use an AED, including socio-demographics, training, attitudes, perceived norms, self-efficacy, and legal obligation. Younger age, men, higher level of education, employed, married, having trained in CPR and AED in the previous 5 years, having received CPR education on four or more occasions, having a positive attitude and perception toward CPR and AED, having confidence to perform CPR and to apply an AED, and legal liability protection under emergency medical service law were reasons why one would be more likely to indicate a willingness to perform CPR and use an AED. The most reported barriers were fear of litigation and injuring a victim.

    CONCLUSIONS: There is a need to empower all the contributing factors and reduce the barrier by emphasizing the importance of CPR and AEDs. The role played by all stakeholders should be strengthened to ensure the success of intervention programs, and indirectly, that can reduce morbidity and mortality among the community from OHCA.

    Matched MeSH terms: Databases, Factual
  3. Saraswathy J, Hariharan M, Nadarajaw T, Khairunizam W, Yaacob S
    Australas Phys Eng Sci Med, 2014 Jun;37(2):439-56.
    PMID: 24691930 DOI: 10.1007/s13246-014-0264-y
    Wavelet theory is emerging as one of the prevalent tool in signal and image processing applications. However, the most suitable mother wavelet for these applications is still a relative question mark amongst researchers. Selection of best mother wavelet through parameterization leads to better findings for the analysis in comparison to random selection. The objective of this article is to compare the performance of the existing members of mother wavelets and to select the most suitable mother wavelet for accurate infant cry classification. Optimal wavelet is found using three different criteria namely the degree of similarity of mother wavelets, regularity of mother wavelets and accuracy of correct recognition during classification processes. Recorded normal and pathological infant cry signals are decomposed into five levels using wavelet packet transform. Energy and entropy features are extracted at different sub bands of cry signals and their effectiveness are tested with four supervised neural network architectures. Findings of this study expound that, the Finite impulse response based approximation of Meyer is the best wavelet candidate for accurate infant cry classification analysis.
    Matched MeSH terms: Databases, Factual
  4. Hariharan M, Sindhu R, Yaacob S
    Comput Methods Programs Biomed, 2012 Nov;108(2):559-69.
    PMID: 21824676 DOI: 10.1016/j.cmpb.2011.07.010
    Crying is the most noticeable behavior of infancy. Infant cry signals can be used to identify physical or psychological status of an infant. Recently, acoustic analysis of infant cry signal has shown promising results and it has been proven to be an excellent tool to investigate the pathological status of an infant. This paper proposes short-time Fourier transform (STFT) based time-frequency analysis of infant cry signals. Few statistical features are derived from the time-frequency plot of infant cry signals and used as features to quantify infant cry signals. General Regression Neural Network (GRNN) is employed as a classifier for discriminating infant cry signals. Two classes of infant cry signals are considered such as normal cry signals and pathological cry signals from deaf infants. To prove the reliability of the proposed features, two neural network models such as Multilayer Perceptron (MLP) and Time-Delay Neural Network (TDNN) trained by scaled conjugate gradient algorithm are also used as classifiers. The experimental results show that the GRNN classifier gives very promising classification accuracy compared to MLP and TDNN and the proposed method can effectively classify normal and pathological infant cries.
    Matched MeSH terms: Databases, Factual
  5. Tseng ML, Chang CH, Lin CR, Wu KJ, Chen Q, Xia L, et al.
    Environ Sci Pollut Res Int, 2020 Sep;27(27):33543-33567.
    PMID: 32572746 DOI: 10.1007/s11356-020-09284-0
    This study conducts a comprehensive literature review of articles on the triple bottom line (TBL) published from January 1997 to September 2018 to provide significant insights and support to guide further discussion. There were three booms in TBL publications, occurring in 2003, 2011, and 2015, and many articles attempt to address the issue of sustainability by employing the TBL. This literature analysis includes 720, 132, and 58 articles from the Web of Science (WOS), Inspec, and Scopus databases, respectively, and reveals the gaps in existing research. To discover the barriers and points of overlap, these articles are categorized into six aspects of the TBL: economic, environmental, social, operations, technology, and engineering. Examining the top 3 journals in terms of published articles on each aspect reveals the research trends and gaps. The findings provide solid evidence confirming the argument that the TBL as currently defined is insufficient to cover the entire concept of sustainability. The social and engineering aspects still require more discussion to support the linkage of the TBL and to reinforce its theoretical basis. Additionally, to discover the gaps in the data sources, theories applied, methods adopted, and types of contributions, this article summarizes 82 highly cited articles covering each aspect. This article offers theoretical insights by identifying the top contributing countries, institutions, authors, keyword networks, and authorship networks to encourage scholars to push the current discussion further forward, and it provides practical insights to bridge the gap between theory and practice for enhancing the efficiency and effectiveness of improvements.
    Matched MeSH terms: Databases, Factual
  6. Kanapathipillai R, McManus H, Kamarulzaman A, Lim PL, Templeton DJ, Law M, et al.
    PLoS One, 2014;9(2):e86122.
    PMID: 24516527 DOI: 10.1371/journal.pone.0086122
    INTRODUCTION: Magnitude and frequency of HIV viral load blips in resource-limited settings, has not previously been assessed. This study was undertaken in a cohort from a high income country (Australia) known as AHOD (Australian HIV Observational Database) and another cohort from a mixture of Asian countries of varying national income per capita, TAHOD (TREAT Asia HIV Observational Database).

    METHODS: Blips were defined as detectable VL (≥ 50 copies/mL) preceded and followed by undetectable VL (<50 copies/mL). Virological failure (VF) was defined as two consecutive VL ≥50 copies/ml. Cox proportional hazard models of time to first VF after entry, were developed.

    RESULTS: 5040 patients (AHOD n = 2597 and TAHOD n = 2521) were included; 910 (18%) of patients experienced blips. 744 (21%) and 166 (11%) of high- and middle/low-income participants, respectively, experienced blips ever. 711 (14%) experienced blips prior to virological failure. 559 (16%) and 152 (10%) of high- and middle/low-income participants, respectively, experienced blips prior to virological failure. VL testing occurred at a median frequency of 175 and 91 days in middle/low- and high-income sites, respectively. Longer time to VF occurred in middle/low income sites, compared with high-income sites (adjusted hazards ratio (AHR) 0.41; p<0.001), adjusted for year of first cART, Hepatitis C co-infection, cART regimen, and prior blips. Prior blips were not a significant predictor of VF in univariate analysis (AHR 0.97, p = 0.82). Differing magnitudes of blips were not significant in univariate analyses as predictors of virological failure (p = 0.360 for blip 50-≤1000, p = 0.309 for blip 50-≤400 and p = 0.300 for blip 50-≤200). 209 of 866 (24%) patients were switched to an alternate regimen in the setting of a blip.

    CONCLUSION: Despite a lower proportion of blips occurring in low/middle-income settings, no significant difference was found between settings. Nonetheless, a substantial number of participants were switched to alternative regimens in the setting of blips.

    Matched MeSH terms: Databases, Factual
  7. Jiamsakul A, Polizzotto M, Wen-Wei Ku S, Tanuma J, Hui E, Chaiwarith R, et al.
    J Acquir Immune Defic Syndr, 2019 03 01;80(3):301-307.
    PMID: 30531303 DOI: 10.1097/QAI.0000000000001918
    BACKGROUND: Hematological malignancies have continued to be highly prevalent among people living with HIV (PLHIV). This study assessed the occurrence of, risk factors for, and outcomes of hematological and nonhematological malignancies in PLHIV in Asia.

    METHODS: Incidence of malignancy after cohort enrollment was evaluated. Factors associated with development of hematological and nonhematological malignancy were analyzed using competing risk regression and survival time using Kaplan-Meier.

    RESULTS: Of 7455 patients, 107 patients (1%) developed a malignancy: 34 (0.5%) hematological [0.08 per 100 person-years (/100PY)] and 73 (1%) nonhematological (0.17/100PY). Of the hematological malignancies, non-Hodgkin lymphoma was predominant (n = 26, 76%): immunoblastic (n = 6, 18%), Burkitt (n = 5, 15%), diffuse large B-cell (n = 5, 15%), and unspecified (n = 10, 30%). Others include central nervous system lymphoma (n = 7, 21%) and myelodysplastic syndrome (n = 1, 3%). Nonhematological malignancies were mostly Kaposi sarcoma (n = 12, 16%) and cervical cancer (n = 10, 14%). Risk factors for hematological malignancy included age >50 vs. ≤30 years [subhazard ratio (SHR) = 6.48, 95% confidence interval (CI): 1.79 to 23.43] and being from a high-income vs. a lower-middle-income country (SHR = 3.97, 95% CI: 1.45 to 10.84). Risk was reduced with CD4 351-500 cells/µL (SHR = 0.20, 95% CI: 0.05 to 0.74) and CD4 >500 cells/µL (SHR = 0.14, 95% CI: 0.04 to 0.78), compared to CD4 ≤200 cells/µL. Similar risk factors were seen for nonhematological malignancy, with prior AIDS diagnosis showing a weak association. Patients diagnosed with a hematological malignancy had shorter survival time compared to patients diagnosed with a nonhematological malignancy.

    CONCLUSIONS: Nonhematological malignancies were common but non-Hodgkin lymphoma was more predominant in our cohort. PLHIV from high-income countries were more likely to be diagnosed, indicating a potential underdiagnosis of cancer in low-income settings.

    Matched MeSH terms: Databases, Factual
  8. Azadnia AH, Taheri S, Ghadimi P, Saman MZ, Wong KY
    ScientificWorldJournal, 2013;2013:246578.
    PMID: 23864823 DOI: 10.1155/2013/246578
    One of the cost-intensive issues in managing warehouses is the order picking problem which deals with the retrieval of items from their storage locations in order to meet customer requests. Many solution approaches have been proposed in order to minimize traveling distance in the process of order picking. However, in practice, customer orders have to be completed by certain due dates in order to avoid tardiness which is neglected in most of the related scientific papers. Consequently, we proposed a novel solution approach in order to minimize tardiness which consists of four phases. First of all, weighted association rule mining has been used to calculate associations between orders with respect to their due date. Next, a batching model based on binary integer programming has been formulated to maximize the associations between orders within each batch. Subsequently, the order picking phase will come up which used a Genetic Algorithm integrated with the Traveling Salesman Problem in order to identify the most suitable travel path. Finally, the Genetic Algorithm has been applied for sequencing the constructed batches in order to minimize tardiness. Illustrative examples and comparisons are presented to demonstrate the proficiency and solution quality of the proposed approach.
    Matched MeSH terms: Databases, Factual*
  9. Arif SM, Holliday JD, Willett P
    J Chem Inf Model, 2010 Aug 23;50(8):1340-9.
    PMID: 20672867 DOI: 10.1021/ci1001235
    This paper discusses the weighting of two-dimensional fingerprints for similarity-based virtual screening, specifically the use of weights that assign greatest importance to the substructural fragments that occur least frequently in the database that is being screened. Virtual screening experiments using the MDL Drug Data Report and World of Molecular Bioactivity databases show that the use of such inverse frequency weighting schemes can result, in some circumstances, in marked increases in screening effectiveness when compared with the use of conventional, unweighted fingerprints. Analysis of the characteristics of the various schemes demonstrates that such weights are best used to weight the fingerprint of the reference structure in a similarity search, with the database structures' fingerprints unweighted. However, the increases in performance resulting from such weights are only observed with structurally homogeneous sets of active molecules; when the actives are diverse, the best results are obtained using conventional, unweighted fingerprints for both the reference structure and the database structures.
    Matched MeSH terms: Databases, Factual
  10. Bauer M, Glenn T, Alda M, Andreassen OA, Angelopoulos E, Ardau R, et al.
    Eur. Psychiatry, 2015 Jan;30(1):99-105.
    PMID: 25498240 DOI: 10.1016/j.eurpsy.2014.10.005
    PURPOSE: Two common approaches to identify subgroups of patients with bipolar disorder are clustering methodology (mixture analysis) based on the age of onset, and a birth cohort analysis. This study investigates if a birth cohort effect will influence the results of clustering on the age of onset, using a large, international database.

    METHODS: The database includes 4037 patients with a diagnosis of bipolar I disorder, previously collected at 36 collection sites in 23 countries. Generalized estimating equations (GEE) were used to adjust the data for country median age, and in some models, birth cohort. Model-based clustering (mixture analysis) was then performed on the age of onset data using the residuals. Clinical variables in subgroups were compared.

    RESULTS: There was a strong birth cohort effect. Without adjusting for the birth cohort, three subgroups were found by clustering. After adjusting for the birth cohort or when considering only those born after 1959, two subgroups were found. With results of either two or three subgroups, the youngest subgroup was more likely to have a family history of mood disorders and a first episode with depressed polarity. However, without adjusting for birth cohort (three subgroups), family history and polarity of the first episode could not be distinguished between the middle and oldest subgroups.

    CONCLUSION: These results using international data confirm prior findings using single country data, that there are subgroups of bipolar I disorder based on the age of onset, and that there is a birth cohort effect. Including the birth cohort adjustment altered the number and characteristics of subgroups detected when clustering by age of onset. Further investigation is needed to determine if combining both approaches will identify subgroups that are more useful for research.

    Matched MeSH terms: Databases, Factual
  11. Bauer M, Glenn T, Alda M, Andreassen OA, Angelopoulos E, Ardau R, et al.
    J Psychiatr Res, 2015 May;64:1-8.
    PMID: 25862378 DOI: 10.1016/j.jpsychires.2015.03.013
    Environmental conditions early in life may imprint the circadian system and influence response to environmental signals later in life. We previously determined that a large springtime increase in solar insolation at the onset location was associated with a younger age of onset of bipolar disorder, especially with a family history of mood disorders. This study investigated whether the hours of daylight at the birth location affected this association.
    Matched MeSH terms: Databases, Factual/statistics & numerical data
  12. Alofe O, Kisanga E, Inayat-Hussain SH, Fukumura M, Garcia-Milian R, Perera L, et al.
    Environ Int, 2019 10;131:104969.
    PMID: 31310931 DOI: 10.1016/j.envint.2019.104969
    Environmental and occupational exposure to industrial chemicals has been linked to toxic and carcinogenic effects in animal models and human studies. However, current toxicology testing does not thoroughly explore the endocrine disrupting effects of industrial chemicals, which may have low dose effects not predicted when determining the limit of toxicity. The objective of this study was to evaluate the endocrine disrupting potential of a broad range of chemicals used in the petrochemical sector. Therefore, 139 chemicals were classified for reproductive toxicity based on the United Nations Globally Harmonized System for hazard classification. These chemicals were evaluated in PubMed for reported endocrine disrupting activity, and their endocrine disrupting potential was estimated by identifying chemicals with active nuclear receptor endpoints publicly available databases. Evaluation of ToxCast data suggested that these chemicals preferentially alter the activity of the estrogen receptor (ER). Four chemicals were prioritized for in vitro testing using the ER-positive, immortalized human uterine Ishikawa cell line and a range of concentrations below the reported limit of toxicity in humans. We found that 2,6-di-tert-butyl-p-cresol (BHT) and diethanolamine (DEA) repressed the basal expression of estrogen-responsive genes PGR, NPPC, and GREB1 in Ishikawa cells, while tetrachloroethylene (PCE) and 2,2'-methyliminodiethanol (MDEA) induced the expression of these genes. Furthermore, low-dose combinations of PCE and MDEA produced additive effects. All four chemicals interfered with estradiol-mediated induction of PGR, NPPC, and GREB1. Molecular docking demonstrated that these chemicals could bind to the ligand binding site of ERα, suggesting the potential for direct stimulatory or inhibitory effects. We found that these chemicals altered rates of proliferation and regulated the expression of cell proliferation associated genes. These findings demonstrate previously unappreciated endocrine disrupting effects and underscore the importance of testing the endocrine disrupting potential of chemicals in the future to better understand their potential to impact public health.
    Matched MeSH terms: Databases, Factual*
  13. Chai HY, Swee TT, Seng GH, Wee LK
    Biomed Eng Online, 2013;12:27.
    PMID: 23565999 DOI: 10.1186/1475-925X-12-27
    The high variations of background luminance, low contrast and excessively enhanced contrast of hand bone radiograph often impede the bone age assessment rating system in evaluating the degree of epiphyseal plates and ossification centers development. The Global Histogram equalization (GHE) has been the most frequently adopted image contrast enhancement technique but the performance is not satisfying. A brightness and detail preserving histogram equalization method with good contrast enhancement effect has been a goal of much recent research in histogram equalization. Nevertheless, producing a well-balanced histogram equalized radiograph in terms of its brightness preservation, detail preservation and contrast enhancement is deemed to be a daunting task.
    Matched MeSH terms: Databases, Factual
  14. Thai YC, Sim D, McCaffrey TA, Ramadas A, Malini H, Watterson JL
    PLoS One, 2023;18(2):e0282118.
    PMID: 36854022 DOI: 10.1371/journal.pone.0282118
    INTRODUCTION: Digital technology-based interventions have gained popularity over the last two decades, due to the ease with which they are scalable and low in implementation cost. Multicomponent health promotion programmes, with significant digital components, are increasingly being deployed in the workplace to assess and promote employees' health behaviours and reduce risk of chronic diseases. However, little is known about workplace digital health interventions in low- and middle- income countries (LMICs).

    METHODS: Various combinations of keywords related to "digital health", "intervention", "workplace" and "developing country" were applied in Ovid MEDLINE, EMBASE, CINAHL Plus, PsycINFO, Scopus and Cochrane Library for peer-reviewed articles in English language. Manual searches were performed to supplement the database search. The screening process was conducted in two phases and a narrative synthesis to summarise the data. The review protocol was written prior to undertaking the review (OSF Registry:10.17605/OSF.IO/QPR9J).

    RESULTS: The search strategy identified 10,298 publications, of which 24 were included. Included studies employed the following study designs: randomized-controlled trials (RCTs) (n = 12), quasi-experimental (n = 4), pilot studies (n = 4), pre-post studies (n = 2) and cohort studies (n = 2). Most of the studies reported positive feedback of the use of digital wellness interventions in workplace settings.

    CONCLUSIONS: This review is the first to map and describe the impact of digital wellness interventions in the workplace in LMICs. Only a small number of studies met the inclusion criteria. Modest evidence was found that digital workplace wellness interventions were feasible, cost-effective, and acceptable. However, long-term, and consistent effects were not found, and further studies are needed to provide more evidence. This scoping review identified multiple digital health interventions in LMIC workplace settings and highlighted a few important research gaps.

    Matched MeSH terms: Databases, Factual
  15. Tian X, Tian Z, Khatib SFA, Wang Y
    PLoS One, 2024;19(4):e0300195.
    PMID: 38625972 DOI: 10.1371/journal.pone.0300195
    Internet finance has permeated into myriad households, bringing about lifestyle convenience alongside potential risks. Presently, internet finance enterprises are progressively adopting machine learning and other artificial intelligence methods for risk alertness. What is the current status of the application of various machine learning models and algorithms across different institutions? Is there an optimal machine learning algorithm suited for the majority of internet finance platforms and application scenarios? Scholars have embarked on a series of studies addressing these questions; however, the focus predominantly lies in comparing different algorithms within specific platforms and contexts, lacking a comprehensive discourse and summary on the utilization of machine learning in this domain. Thus, based on the data from Web of Science and Scopus databases, this paper conducts a systematic literature review on all aspects of machine learning in internet finance risk in recent years, based on publications trends, geographical distribution, literature focus, machine learning models and algorithms, and evaluations. The research reveals that machine learning, as a nascent technology, whether through basic algorithms or intricate algorithmic combinations, has made significant strides compared to traditional credit scoring methods in predicting accuracy, time efficiency, and robustness in internet finance risk management. Nonetheless, there exist noticeable disparities among different algorithms, and factors such as model structure, sample data, and parameter settings also influence prediction accuracy, although generally, updated algorithms tend to achieve higher accuracy. Consequently, there is no one-size-fits-all approach applicable to all platforms; each platform should enhance its machine learning models and algorithms based on its unique characteristics, data, and the development of AI technology, starting from key evaluation indicators to mitigate internet finance risks.
    Matched MeSH terms: Databases, Factual
  16. Wang X, Teh SH, Wang XH
    Ital J Pediatr, 2024 Jan 18;50(1):9.
    PMID: 38238820 DOI: 10.1186/s13052-024-01577-1
    BACKGROUND: Cerebral palsy (CP) is characterized by abnormal pronunciation, posture, and movement. Spastic CP accounts for more than 70% of all CP. To date, there has been no bibliometric analysis to summarize study on spastic CP. Here, we aim to conduct a bibliometric analysis of spastic CP to summarize this field's knowledge structure, research hotspots, and frontiers.

    METHOD: Publications about spastic CP were searched utilizing the Web of Science Core Collection (WoSCC) database from 1 January 2000 to 30 November 2022, the WoSCC literature analysis wire, VOSviewer 1.6.18, CiteSpace 6.1.R4 and Online analysis platform for bibliometrics were used to conduct the analysis.

    RESULTS: A total of 3988 publications, consisting of 3699 articles and 289 reviews, were included in our study. The United States emerged as the most productive country, while Kathleen Univ Leuven was the most productive institution. The leading author was Desloovere K. A total of 238 journals contributed to this field, with Developmental medicine and child neurology being the leading journal. Important keywords and keyword clusters included Spastic cerebral palsy, Reliability, and Gross motor function. Keywords identified through burst detection indicated that hotspots in this field were management, randomized controlled trials, and definition.

    CONCLUSION: Based on the analysis of bibliometric on spastic CP over the past 20 years, the trends and the knowledge graph of the countries, institutions, authors, references, and the keywords have been identified, providing accurate and expedited insights into critical information and potentially new directions in the study of spastic CP.

    Matched MeSH terms: Databases, Factual
  17. 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
  18. Lee CY, Liu KT, Lu HT, Mohd Ali R, Fong AYY, Wan Ahmad WA
    PLoS One, 2021;16(2):e0246474.
    PMID: 33556136 DOI: 10.1371/journal.pone.0246474
    BACKGROUND: Sex and gender differences in acute coronary syndrome (ACS) have been well studied in the western population. However, limited studies have examined the trends of these differences in a multi-ethnic Asian population.

    OBJECTIVES: To study the trends in sex and gender differences in ACS using the Malaysian NCVD-ACS Registry.

    METHODS: Data from 24 hospitals involving 35,232 ACS patients (79.44% men and 20.56% women) from 1st. Jan 2012 to 31st. Dec 2016 were analysed. Data were collected on demographic characteristics, coronary risk factors, anthropometrics, treatments and outcomes. Analyses were done for ACS as a whole and separately for ST-segment elevation myocardial infarction (STEMI), Non-STEMI and unstable angina. These were then compared to published data from March 2006 to February 2010 which included 13,591 ACS patients (75.8% men and 24.2% women).

    RESULTS: Women were older and more likely to have diabetes mellitus, hypertension, dyslipidemia, previous heart failure and renal failure than men. Women remained less likely to receive aspirin, beta-blocker, angiotensin-converting enzyme inhibitor (ACE-I) and statin. Women were less likely to undergo angiography and percutaneous coronary intervention (PCI) despite an overall increase. In the STEMI cohort, despite a marked increase in presentation with Killip class IV, women were less likely to received primary PCI or fibrinolysis and had longer median door-to-needle and door-to-balloon time compared to men, although these had improved. Women had higher unadjusted in-hospital, 30-Day and 1-year mortality rates compared to men for the STEMI and NSTEMI cohorts. After multivariate adjustments, 1-year mortality remained significantly higher for women with STEMI (adjusted OR: 1.31 (1.09-1.57), p<0.003) but were no longer significant for NSTEMI cohort.

    CONCLUSION: Women continued to have longer system delays, receive less aggressive pharmacotherapies and invasive treatments with poorer outcome. There is an urgent need for increased effort from all stakeholders if we are to narrow this gap.

    Matched MeSH terms: Databases, Factual
  19. Ferrario A, Stephens P, Guan X, Ross-Degnan D, Wagner A
    Bull World Health Organ, 2020 Jul 01;98(7):467-474.
    PMID: 32742032 DOI: 10.2471/BLT.19.243998
    OBJECTIVE: To assess sales of anti-cancer medicines in the 2017 World Health Organization's WHO Model list of essential medicines in China, Indonesia, Kazakhstan, Malaysia, Philippines and Thailand from 2007 (2008 for Kazakhstan and Malaysia) to 2017.

    METHODS: We extracted sales volume data for 39 anti-cancer medicines from the IQVIA database. We divided the total quantity sold by the reference defined daily dose to estimate the total number of defined daily doses sold, per country per year, for three types of anti-cancer therapies (traditional chemotherapy, targeted therapy and endocrine therapy). We adjusted these data by the number of new cancer cases in each country for each year.

    FINDINGS: We observed an increase in sales across all types of anti-cancer therapies in all countries. The largest number of defined daily doses of traditional chemotherapy per new cancer case was sold in Thailand; however, the largest relative increase per new cancer case occurred in Indonesia (9.48-fold). The largest absolute and relative increases in sales of defined daily doses of targeted therapies per new cancer case occurred in Kazakhstan. Malaysia sold the largest number of adjusted defined daily doses of endocrine therapies in 2017, while China and Indonesia more than doubled their adjusted sales volumes between 2007 and 2017.

    CONCLUSION: The use of sales data can fill an important knowledge gap in the use of anti-cancer medicines, particularly during periods of insurance coverage expansion. Combined with other data, sales volume data can help to monitor efforts to improve equitable access to essential medicines.

    Matched MeSH terms: Databases, Factual
  20. Maresova P, Krejcar O, Maskuriy R, Bakar NAA, Selamat A, Truhlarova Z, et al.
    BMC Geriatr, 2023 Jul 21;23(1):447.
    PMID: 37474928 DOI: 10.1186/s12877-023-04106-7
    BACKGROUND: Attention is focused on the health and physical fitness of older adults due to their increasing age. Maintaining physical abilities, including safe walking and movement, significantly contributes to the perception of health in old age. One of the early signs of declining fitness in older adults is limited mobility. Approximately one third of 70-year-olds and most 80-year-olds report restrictions on mobility in their apartments and immediate surroundings. Restriction or loss of mobility is a complex multifactorial process, which makes older adults prone to falls, injuries, and hospitalizations and worsens their quality of life while increasing overall mortality.

    OBJECTIVE: The objective of the study is to identify the factors that have had a significant impact on mobility in recent years and currently, and to identify gaps in our understanding of these factors. The study aims to highlight areas where further research is needed and where new and effective solutions are required.

    METHODS: The PRISMA methodology was used to conduct a scoping review in the Scopus and Web of Science databases. Papers published from 2007 to 2021 were searched in November 2021. Of these, 52 papers were selected from the initial 788 outputs for the final analysis.

    RESULTS: The final selected papers were analyzed, and the key determinants were found to be environmental, physical, cognitive, and psychosocial, which confirms the findings of previous studies. One new determinant is technological. New and effective solutions lie in understanding the interactions between different determinants of mobility, addressing environmental factors, and exploring opportunities in the context of emerging technologies, such as the integration of smart home technologies, design of accessible and age-friendly public spaces, development of policies and regulations, and exploration of innovative financing models to support the integration of assistive technologies into the lives of seniors.

    CONCLUSION: For an effective and comprehensive solution to support senior mobility, the determinants cannot be solved separately. Physical, cognitive, psychosocial, and technological determinants can often be perceived as the cause/motivation for mobility. Further research on these determinants can help to arrive at solutions for environmental determinants, which, in turn, will help improve mobility. Future studies should investigate financial aspects, especially since many technological solutions are expensive and not commonly available, which limits their use.

    Matched MeSH terms: Databases, Factual
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