Displaying publications 1 - 20 of 31 in total

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  1. Sharif S, Arshad SS, Hair-Bejo M, Omar AR, Zeenathul NA, Hafidz MA
    J Feline Med Surg, 2009 Dec;11(12):1031-4.
    PMID: 19818660 DOI: 10.1016/j.jfms.2009.08.005
    The prevalence of feline coronavirus (FCoV) was studied in two catteries in Malaysia. Rectal swabs or faecal samples were collected from a total of 44 clinically healthy Persian purebred and mix-breed cats. RNA extracted from the faecal material was subjected to a reverse transcription-polymerase chain reaction (RT-PCR) using primers flanking for a conserved region of the virus genome. The overall prevalence of FCoV infection was 84% and the infection rate was higher in Persian purebred cats (96%) than mix-breed cats (70%). There was no significant association between the age or gender of tested cats and shedding the virus. This study is the first PCR-based survey for FCoV in Malaysia and showed the ubiquitous presence of FCoV in Malaysian cat colonies.
    Matched MeSH terms: Coronavirus Infections/diagnosis
  2. Premila Devi J, Noraini W, Norhayati R, Chee Kheong C, Badrul AS, Zainah S, et al.
    Euro Surveill, 2014 May 08;19(18).
    PMID: 24832116
    On 14 April 2014, the first laboratory-confirmed case of Middle East respiratory syndrome coronavirus (MERS-CoV) infection was reported in Malaysia in a man in his mid-fifties, who developed pneumonia with respiratory distress, after returning from a pilgrimage to Saudi Arabia. The case succumbed to his illness three days after admission at a local hospital. The follow-up of 199 close contacts identified through contact tracing and vigilant surveillance did not result in detecting any other confirmed cases of MERS-CoV infection.
    Matched MeSH terms: Coronavirus Infections/diagnosis*
  3. Al-Khannaq MN, Ng KT, Oong XY, Pang YK, Takebe Y, Chook JB, et al.
    Virol J, 2016 Feb 25;13:33.
    PMID: 26916286 DOI: 10.1186/s12985-016-0488-4
    BACKGROUND: Despite the worldwide circulation of human coronavirus OC43 (HCoV-OC43) and HKU1 (HCoV-HKU1), data on their molecular epidemiology and evolutionary dynamics in the tropical Southeast Asia region is lacking.
    METHODS: The study aimed to investigate the genetic diversity, temporal distribution, population history and clinical symptoms of betacoronavirus infections in Kuala Lumpur, Malaysia between 2012 and 2013. A total of 2,060 adults presented with acute respiratory symptoms were screened for the presence of betacoronaviruses using multiplex PCR. The spike glycoprotein, nucleocapsid and 1a genes were sequenced for phylogenetic reconstruction and Bayesian coalescent inference.
    RESULTS: A total of 48/2060 (2.4 %) specimens were tested positive for HCoV-OC43 (1.3 %) and HCoV-HKU1 (1.1 %). Both HCoV-OC43 and HCoV-HKU1 were co-circulating throughout the year, with the lowest detection rates reported in the October-January period. Phylogenetic analysis of the spike gene showed that the majority of HCoV-OC43 isolates were grouped into two previously undefined genotypes, provisionally assigned as novel lineage 1 and novel lineage 2. Sign of natural recombination was observed in these potentially novel lineages. Location mapping showed that the novel lineage 1 is currently circulating in Malaysia, Thailand, Japan and China, while novel lineage 2 can be found in Malaysia and China. Molecular dating showed the origin of HCoV-OC43 around late 1950s, before it diverged into genotypes A (1960s), B (1990s), and other genotypes (2000s). Phylogenetic analysis revealed that 27.3 % of the HCoV-HKU1 strains belong to genotype A while 72.7 % belongs to genotype B. The tree root of HCoV-HKU1 was similar to that of HCoV-OC43, with the tMRCA of genotypes A and B estimated around the 1990s and 2000s, respectively. Correlation of HCoV-OC43 and HCoV-HKU1 with the severity of respiratory symptoms was not observed.
    CONCLUSIONS: The present study reported the molecular complexity and evolutionary dynamics of human betacoronaviruses among adults with acute respiratory symptoms in a tropical country. Two novel HCoV-OC43 genetic lineages were identified, warranting further investigation on their genotypic and phenotypic characteristics.
    Study site: Primary Care Clinic, University Malaya Medical Centre (UMMC), Kuala Lumpur, Malaysia
    Matched MeSH terms: Coronavirus Infections/diagnosis
  4. Haider N, Yavlinsky A, Simons D, Osman AY, Ntoumi F, Zumla A, et al.
    Epidemiol Infect, 2020 02 26;148:e41.
    PMID: 32100667 DOI: 10.1017/S0950268820000424
    Novel Coronavirus (2019-nCoV [SARS-COV-2]) was detected in humans during the last week of December 2019 at Wuhan city in China, and caused 24 554 cases in 27 countries and territories as of 5 February 2020. The objective of this study was to estimate the risk of transmission of 2019-nCoV through human passenger air flight from four major cities of China (Wuhan, Beijing, Shanghai and Guangzhou) to the passengers' destination countries. We extracted the weekly simulated passengers' end destination data for the period of 1-31 January 2020 from FLIRT, an online air travel dataset that uses information from 800 airlines to show the direct flight and passengers' end destination. We estimated a risk index of 2019-nCoV transmission based on the number of travellers to destination countries, weighted by the number of confirmed cases of the departed city reported by the World Health Organization (WHO). We ranked each country based on the risk index in four quantiles (4th quantile being the highest risk and 1st quantile being the lowest risk). During the period, 388 287 passengers were destined for 1297 airports in 168 countries or territories across the world. The risk index of 2019-nCoV among the countries had a very high correlation with the WHO-reported confirmed cases (0.97). According to our risk score classification, of the countries that reported at least one Coronavirus-infected pneumonia (COVID-19) case as of 5 February 2020, 24 countries were in the 4th quantile of the risk index, two in the 3rd quantile, one in the 2nd quantile and none in the 1st quantile. Outside China, countries with a higher risk of 2019-nCoV transmission are Thailand, Cambodia, Malaysia, Canada and the USA, all of which reported at least one case. In pan-Europe, UK, France, Russia, Germany and Italy; in North America, USA and Canada; in Oceania, Australia had high risk, all of them reported at least one case. In Africa and South America, the risk of transmission is very low with Ethiopia, South Africa, Egypt, Mauritius and Brazil showing a similar risk of transmission compared to the risk of any of the countries where at least one case is detected. The risk of transmission on 31 January 2020 was very high in neighbouring Asian countries, followed by Europe (UK, France, Russia and Germany), Oceania (Australia) and North America (USA and Canada). Increased public health response including early case recognition, isolation of identified case, contract tracing and targeted airport screening, public awareness and vigilance of health workers will help mitigate the force of further spread to naïve countries.
    Matched MeSH terms: Coronavirus Infections/diagnosis
  5. Mawaddah A, Gendeh HS, Lum SG, Marina MB
    Malays J Pathol, 2020 Apr;42(1):23-35.
    PMID: 32342928
    INTRODUCTION: To review the present literature on upper respiratory tract sampling in COVID-19 and provide recommendations to improve healthcare practices and directions in future studies.

    METHODS: Twelve relevant manuscripts were sourced from a total of 7288 search results obtained using PubMed, Medline and Google Scholar. The search keywords used were COVID-19, nasopharyngeal, oropharyngeal, swabs, SARS and CoV2. Original manuscripts were obtained and analysed by all authors. The review included manuscripts which have not undergone rigorous peer-review process in view of the magnitude of the topic discussed.

    RESULTS: The viral load of SARS-CoV-2 RNA in the upper respiratory tract was significantly higher during the first week and peaked at 4-6 days after onset of symptoms, during which it can be potentially sampled. Nasopharyngeal swab has demonstrated higher viral load than oropharyngeal swab, where the difference in paired samples is best seen at 0-9 days after the onset of illness. Sensitivity of nasopharyngeal swab was higher than oropharyngeal swabs in COVID-19 patients. Patient self-collected throat washing has been shown to contain higher viral load than nasopharyngeal or oropharyngeal swab, with significantly higher sensitivity when compared with paired nasopharyngeal swab.

    RECOMMENDATIONS: Routine nasopharyngeal swab of suspected COVID-19 infection should take anatomy of the nasal cavity into consideration to increase patient comfort and diagnostic yield. Routine oropharyngeal swab should be replaced by throat washing which has demonstrated better diagnostic accuracy, and it is safe towards others.

    Matched MeSH terms: Coronavirus Infections/diagnosis*
  6. Zainol Rashid Z, Othman SN, Abdul Samat MN, Ali UK, Wong KK
    Malays J Pathol, 2020 Apr;42(1):13-21.
    PMID: 32342927
    INTRODUCTION: The World Health Organization (WHO) declared COVID-19 outbreak as a world pandemic on 12th March 2020. Diagnosis of suspected cases is confirmed by nucleic acid assays with real-time PCR, using respiratory samples. Serology tests are comparatively easier to perform, but their utility may be limited by the performance and the fact that antibodies appear later during the disease course. We aimed to describe the performance data on serological assays for COVID-19.

    MATERIALS AND METHODS: A review of multiple reports and kit inserts on the diagnostic performance of rapid tests from various manufacturers that are commercially available were performed. Only preliminary data are available currently.

    RESULTS: From a total of nine rapid detection test (RDT) kits, three kits offer total antibody detection, while six kits offer combination SARS-CoV-2 IgM and IgG detection in two separate test lines. All kits are based on colloidal gold-labeled immunochromatography principle and one-step method with results obtained within 15 minutes, using whole blood, serum or plasma samples. The sensitivity for both IgM and IgG tests ranges between 72.7% and 100%, while specificity ranges between 98.7% to 100%. Two immunochromatography using nasopharyngeal or throat swab for detection of COVID-19 specific antigen are also reviewed.

    CONCLUSIONS: There is much to determine regarding the value of serological testing in COVID-19 diagnosis and monitoring. More comprehensive evaluations of their performance are rapidly underway. The use of serology methods requires appropriate interpretations of the results and understanding the strengths and limitations of such tests.

    Matched MeSH terms: Coronavirus Infections/diagnosis*
  7. Tan GC, Cheong SK
    Malays J Pathol, 2020 Apr;42(1):1.
    PMID: 32342925
    No abstract available.
    Matched MeSH terms: Coronavirus Infections/diagnosis*
  8. Albahri AS, Hamid RA, Alwan JK, Al-Qays ZT, Zaidan AA, Zaidan BB, et al.
    J Med Syst, 2020 May 25;44(7):122.
    PMID: 32451808 DOI: 10.1007/s10916-020-01582-x
    Coronaviruses (CoVs) are a large family of viruses that are common in many animal species, including camels, cattle, cats and bats. Animal CoVs, such as Middle East respiratory syndrome-CoV, severe acute respiratory syndrome (SARS)-CoV, and the new virus named SARS-CoV-2, rarely infect and spread among humans. On January 30, 2020, the International Health Regulations Emergency Committee of the World Health Organisation declared the outbreak of the resulting disease from this new CoV called 'COVID-19', as a 'public health emergency of international concern'. This global pandemic has affected almost the whole planet and caused the death of more than 315,131 patients as of the date of this article. In this context, publishers, journals and researchers are urged to research different domains and stop the spread of this deadly virus. The increasing interest in developing artificial intelligence (AI) applications has addressed several medical problems. However, such applications remain insufficient given the high potential threat posed by this virus to global public health. This systematic review addresses automated AI applications based on data mining and machine learning (ML) algorithms for detecting and diagnosing COVID-19. We aimed to obtain an overview of this critical virus, address the limitations of utilising data mining and ML algorithms, and provide the health sector with the benefits of this technique. We used five databases, namely, IEEE Xplore, Web of Science, PubMed, ScienceDirect and Scopus and performed three sequences of search queries between 2010 and 2020. Accurate exclusion criteria and selection strategy were applied to screen the obtained 1305 articles. Only eight articles were fully evaluated and included in this review, and this number only emphasised the insufficiency of research in this important area. After analysing all included studies, the results were distributed following the year of publication and the commonly used data mining and ML algorithms. The results found in all papers were discussed to find the gaps in all reviewed papers. Characteristics, such as motivations, challenges, limitations, recommendations, case studies, and features and classes used, were analysed in detail. This study reviewed the state-of-the-art techniques for CoV prediction algorithms based on data mining and ML assessment. The reliability and acceptability of extracted information and datasets from implemented technologies in the literature were considered. Findings showed that researchers must proceed with insights they gain, focus on identifying solutions for CoV problems, and introduce new improvements. The growing emphasis on data mining and ML techniques in medical fields can provide the right environment for change and improvement.
    Matched MeSH terms: Coronavirus Infections/diagnosis*
  9. Winkler AS, Knauss S, Schmutzhard E, Leonardi M, Padovani A, Abd-Allah F, et al.
    Lancet Neurol, 2020 06;19(6):482-484.
    PMID: 32470416 DOI: 10.1016/S1474-4422(20)30150-2
    Matched MeSH terms: Coronavirus Infections/diagnosis*
  10. Momtazmanesh S, Ochs HD, Uddin LQ, Perc M, Routes JM, Vieira DN, et al.
    Am J Trop Med Hyg, 2020 06;102(6):1181-1183.
    PMID: 32323644 DOI: 10.4269/ajtmh.20-0281
    Novel coronavirus disease (COVID-19), named a pandemic by the WHO, is the current global health crisis. National and international collaboration are indispensable for combating COVID-19 and other similar potential outbreaks. International efforts to tackle this complex problem have led to remarkable scientific advances. Yet, as a global society, we can and must take additional measures to fight this pandemic. Undoubtedly, our approach toward COVID-19 was not perfect, and testing has not been deployed fast enough to arrest the epidemic early on. It is critical that we revise our approaches to be more prepared for pandemics as a united body by promoting global cooperation and commitment.
    Matched MeSH terms: Coronavirus Infections/diagnosis
  11. Kow CS, Zaidi STR, Hasan SS
    Am J Cardiovasc Drugs, 2020 Jun;20(3):217-221.
    PMID: 32281055 DOI: 10.1007/s40256-020-00406-0
    There is ongoing debate on the safety of renin-angiotensin system (RAS) inhibitors in COVID-19. Recently published studies highlight a potential relationship between cardiovascular disease (CVD) and COVID-19. This article aims to summarize the evidence on the use of RAS inhibitors in CVD patients with COVID-19, focusing on safety issues of the RAS inhibitors and their relationship with COVID-19.
    Matched MeSH terms: Coronavirus Infections/diagnosis
  12. Ardakani AA, Kanafi AR, Acharya UR, Khadem N, Mohammadi A
    Comput Biol Med, 2020 06;121:103795.
    PMID: 32568676 DOI: 10.1016/j.compbiomed.2020.103795
    Fast diagnostic methods can control and prevent the spread of pandemic diseases like coronavirus disease 2019 (COVID-19) and assist physicians to better manage patients in high workload conditions. Although a laboratory test is the current routine diagnostic tool, it is time-consuming, imposing a high cost and requiring a well-equipped laboratory for analysis. Computed tomography (CT) has thus far become a fast method to diagnose patients with COVID-19. However, the performance of radiologists in diagnosis of COVID-19 was moderate. Accordingly, additional investigations are needed to improve the performance in diagnosing COVID-19. In this study is suggested a rapid and valid method for COVID-19 diagnosis using an artificial intelligence technique based. 1020 CT slices from 108 patients with laboratory proven COVID-19 (the COVID-19 group) and 86 patients with other atypical and viral pneumonia diseases (the non-COVID-19 group) were included. Ten well-known convolutional neural networks were used to distinguish infection of COVID-19 from non-COVID-19 groups: AlexNet, VGG-16, VGG-19, SqueezeNet, GoogleNet, MobileNet-V2, ResNet-18, ResNet-50, ResNet-101, and Xception. Among all networks, the best performance was achieved by ResNet-101 and Xception. ResNet-101 could distinguish COVID-19 from non-COVID-19 cases with an AUC of 0.994 (sensitivity, 100%; specificity, 99.02%; accuracy, 99.51%). Xception achieved an AUC of 0.994 (sensitivity, 98.04%; specificity, 100%; accuracy, 99.02%). However, the performance of the radiologist was moderate with an AUC of 0.873 (sensitivity, 89.21%; specificity, 83.33%; accuracy, 86.27%). ResNet-101 can be considered as a high sensitivity model to characterize and diagnose COVID-19 infections, and can be used as an adjuvant tool in radiology departments.
    Matched MeSH terms: Coronavirus Infections/diagnosis*
  13. Xiu L, Binder RA, Alarja NA, Kochek K, Coleman KK, Than ST, et al.
    J Clin Virol, 2020 07;128:104391.
    PMID: 32403008 DOI: 10.1016/j.jcv.2020.104391
    BACKGROUND: During the past two decades, three novel coronaviruses (CoVs) have emerged to cause international human epidemics with severe morbidity. CoVs have also emerged to cause severe epidemics in animals. A better understanding of the natural hosts and genetic diversity of CoVs are needed to help mitigate these threats.

    OBJECTIVE: To design and evaluate a molecular diagnostic tool for detection and identification of all currently recognized and potentially future emergent CoVs from the Orthocoronavirinae subfamily.

    STUDY DESIGN AND RESULTS: We designed a semi-nested, reverse transcription RT-PCR assay based upon 38 published genome sequences of human and animal CoVs. We evaluated this assay with 14 human and animal CoVs and 11 other non-CoV respiratory viruses. Through sequencing the assay's target amplicon, the assay correctly identified each of the CoVs; no cross-reactivity with 11 common respiratory viruses was observed. The limits of detection ranged from 4 to 4 × 102 copies/reaction, depending on the CoV species tested. To assess the assay's clinical performance, we tested a large panel of previously studied specimens: 192 human respiratory specimens from pneumonia patients, 5 clinical specimens from COVID-19 patients, 81 poultry oral secretion specimens, 109 pig slurry specimens, and 31 aerosol samples from a live bird market. The amplicons of all RT-PCR-positive samples were confirmed by Sanger sequencing. Our assay performed well with all tested specimens across all sample types.

    CONCLUSIONS: This assay can be used for detection and identification of all previously recognized CoVs, including SARS-CoV-2, and potentially any emergent CoVs in the Orthocoronavirinae subfamily.

    Matched MeSH terms: Coronavirus Infections/diagnosis*
  14. Gómez Román R, Wang LF, Lee B, Halpin K, de Wit E, Broder CC, et al.
    mSphere, 2020 07 08;5(4).
    PMID: 32641430 DOI: 10.1128/mSphere.00602-20
    Nipah disease is listed as one of the WHO priority diseases that pose the greatest public health risk due to their epidemic potential. More than 200 experts from around the world convened in Singapore last year to mark the 20th anniversary of the first Nipah virus outbreaks in Malaysia and Singapore. Most of these experts are now involved in responding to the coronavirus disease 2019 (COVID-19) pandemic. Here, members of the Organizing Committee of the 2019 Nipah Virus International Conference review highlights from the Nipah@20 Conference and reflect on key lessons learned from Nipah that could be applied to the understanding of the COVID-19 pandemic and to preparedness against future emerging infectious diseases (EIDs) of pandemic potential.
    Matched MeSH terms: Coronavirus Infections/diagnosis
  15. Dai H, Zhang SX, Looi KH, Su R, Li J
    PMID: 32751459 DOI: 10.3390/ijerph17155498
    Research identifying adults' mental health during the coronavirus disease 2019 (COVID-19) pandemic relies solely on demographic predictors without examining adults' health condition as a potential predictor. This study aims to examine individuals' perception of health conditions and test availability as potential predictors of mental health-insomnia, anxiety, depression, and distress-during the COVID-19 pandemic. An online survey of 669 adults in Malaysia was conducted during 2-8 May 2020, six weeks after the Movement Control Order (MCO) was issued. We found adults' perception of health conditions had curvilinear relationships (horizontally reversed J-shaped) with insomnia, anxiety, depression, and distress. Perceived test availability for COVID-19 also had curvilinear relationships (horizontally reversed J-shaped) with anxiety and depression. Younger adults reported worse mental health, but people from various religions and ethnic groups did not differ significantly in reported mental health. The results indicated that adults with worse health conditions had more mental health problems, and the worse degree deepened for unhealthy people. Perceived test availability negatively predicted anxiety and depression, especially for adults perceiving COVID-19 test unavailability. The significant predictions of perceived health condition and perceived COVID-19 test availability suggest a new direction for the literature to identify the psychiatric risk factors directly from health-related variables during a pandemic.
    Matched MeSH terms: Coronavirus Infections/diagnosis*
  16. Sam IC, Chong J, Kamarudin R, Jafar FL, Lee LM, Bador MK, et al.
    Trans R Soc Trop Med Hyg, 2020 08 01;114(8):553-555.
    PMID: 32497211 DOI: 10.1093/trstmh/traa037
    Matched MeSH terms: Coronavirus Infections/diagnosis*
  17. Ilenghoven D, Hisham A, Ibrahim S, Mohd Yussof SJ
    Burns, 2020 08;46(5):1236-1239.
    PMID: 32471558 DOI: 10.1016/j.burns.2020.05.008
    Matched MeSH terms: Coronavirus Infections/diagnosis
  18. Kow CS, Thiruchelvam K, Hasan SS
    Expert Rev Cardiovasc Ther, 2020 Aug;18(8):475-485.
    PMID: 32700573 DOI: 10.1080/14779072.2020.1797492
    INTRODUCTION: Cardiovascular diseases (CVDs) are among the most frequently identified comorbidities in hospitalized patients with COVID-19. Patients with CV comorbidities are typically prescribed with long-term medications. We reviewed the management of co-medications prescribed for CVDs among hospitalized COVID-19 patients.

    AREAS COVERED: There is no specific contraindication or caution related to COVID-19 on the use of antihypertensives unless patients develop severe hypotension from septic shock where all antihypertensives should be discontinued or severe hyperkalemia in which continuation of renin-angiotensin system inhibitors is not desired. The continuation of antiplatelet or statin is not desired when severe thrombocytopenia or severe transminitis develop, respectively. Patients with atrial fibrillation receiving oral anticoagulants, particularly those who are critically ill, should be considered for substitution to parenteral anticoagulants.

    EXPERT OPINION: An individualized approach to medication management among hospitalized COVID-19 patients with concurrent CVDs would seem prudent with attention paid to changes in clinical conditions and medications intended for COVID-19. The decision to modify prescribed long-term CV medications should be entailed by close follow-up to check if a revision on the decision is needed, with resumption of any long-term CV medication before discharge if it is discontinued during hospitalization for COVID-19, to ensure continuity of care.

    Matched MeSH terms: Coronavirus Infections/diagnosis
  19. Satija S, Mehta M, Sharma M, Prasher P, Gupta G, Chellappan DK, et al.
    Future Med Chem, 2020 09;12(18):1607-1609.
    PMID: 32589055 DOI: 10.4155/fmc-2020-0149
    Matched MeSH terms: Coronavirus Infections/diagnosis*
  20. Iqhbal KM, Ahmad NH
    Med J Malaysia, 2020 09;75(5):585-586.
    PMID: 32918431
    No abstract provided.
    Matched MeSH terms: Coronavirus Infections/diagnosis
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