Displaying publications 1 - 20 of 29 in total

Abstract:
Sort:
  1. Fulltext Cardiovascular Disease and Use of Renin-Angiotensin System Inhibitors in COVID-19
    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: Pneumonia, Viral/diagnosis
  2. Fulltext Aerosol-generating procedures in thoracic surgery in the COVID-19 era in Malaysia
    Sathiamurthy N, Balasubbiah N, Dharmaraj B
    Asian Cardiovasc Thorac Ann, 2020 Oct;28(8):495-499.
    PMID: 32787442 DOI: 10.1177/0218492320950898
    BACKGROUND: The Covid-19 pandemic has caused changes in the surgical treatment of non-Covid patients, especially in thoracic surgery because most procedures are aerosol generating. Hospital Kuala Lumpur, where thoracic procedures are performed, was badly affected. We describe our experience in performing aerosol generating procedures safely in thoracic surgery during the Covid-19 era.

    METHODS: Medical records of patients who underwent thoracic surgery from March 18, 2020 to May 17, 2020 were reviewed retrospectively. All patients undergoing thoracic surgery were tested for Covid-19 using the reverse transcriptase polymerase chain reaction method. Patients with malignancy were observed for 10 to 14 days in the ward after testing negative. The healthcare workers donned personal protective equipment for all the cases, and the number of healthcare workers in the operating room was limited to the minimum required.

    RESULTS: A total of 44 procedures were performed in 26 thoracic surgeries. All of these procedures were classified as aerosol generating, and the mean duration of the surgery was 130 ± 43 minutes. None of the healthcare workers involved in the surgery were exposed or infected by Covid-19.

    CONCLUSION: Covid-19 will be a threat for a long time and thoracic surgeons must continue to provide their services, despite having to deal with aerosol generating procedures, in the new normal. Covid-19 testing of all surgical candidates, using the reverse transcriptase polymerase chain reaction, donning full personal protective equipment for healthcare workers, and carefully planned procedures are among the measures suggested to prevent unnecessary Covid-19 exposure in thoracic surgery.

    Matched MeSH terms: Pneumonia, Viral/diagnosis
  3. Fulltext Restructuring burns management during the COVID-19 pandemic: A Malaysian experience
    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: Pneumonia, Viral/diagnosis
  4. Fulltext An Overview of Deep Learning Techniques on Chest X-Ray and CT Scan Identification of COVID-19
    Serena Low WC, Chuah JH, Tee CATH, Anis S, Shoaib MA, Faisal A, et al.
    Comput Math Methods Med, 2021;2021:5528144.
    PMID: 34194535 DOI: 10.1155/2021/5528144
    Pneumonia is an infamous life-threatening lung bacterial or viral infection. The latest viral infection endangering the lives of many people worldwide is the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which causes COVID-19. This paper is aimed at detecting and differentiating viral pneumonia and COVID-19 disease using digital X-ray images. The current practices include tedious conventional processes that solely rely on the radiologist or medical consultant's technical expertise that are limited, time-consuming, inefficient, and outdated. The implementation is easily prone to human errors of being misdiagnosed. The development of deep learning and technology improvement allows medical scientists and researchers to venture into various neural networks and algorithms to develop applications, tools, and instruments that can further support medical radiologists. This paper presents an overview of deep learning techniques made in the chest radiography on COVID-19 and pneumonia cases.
    Matched MeSH terms: Pneumonia, Viral/diagnosis
  5. Fulltext Application of deep learning technique to manage COVID-19 in routine clinical practice using CT images: Results of 10 convolutional neural networks
    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: Pneumonia, Viral/diagnosis*
  6. Fulltext Passengers' destinations from China: low risk of Novel Coronavirus (2019-nCoV) transmission into Africa and South America
    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: Pneumonia, Viral/diagnosis
  7. Pharmacotherapeutic considerations for the management of cardiovascular diseases among hospitalized COVID-19 patients
    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: Pneumonia, Viral/diagnosis
  8. Fulltext Management of the dead during COVID-19 outbreak in Malaysia
    Khoo LS, Hasmi AH, Ibrahim MA, Mahmood MS
    Forensic Sci Med Pathol, 2020 09;16(3):463-470.
    PMID: 32519316 DOI: 10.1007/s12024-020-00269-6
    The emergence of a novel human coronavirus, SARS-CoV-2, causing severe respiratory tract infections in humans, is affecting all countries of the world and has become a global health concern. Since the virus was first identified in December 2019, the number of deaths have been propagating exponentially, causing countries across the world, including Malaysia, to increase emergency measures to combat the virus. Due to the fact that the COVID-19 pandemic does not discriminate its victims, it is of paramount importance to construct a plan for management of the dead for all suspected or confirmed COVID-19 cases, including the unidentified deceased, as an essential portion of the humanitarian forensic action approach. This document provides an overview on ways to maximize the local collective capacity from various government agencies to manage the dead based on the prevailing regulations and legislation in the country, in preparation for possible large scale deaths from this pandemic. The National Institute of Forensic Medicine Malaysia has improvised procedures and guidelines for management of the dead within the existing regulations in order to achieve a balance between medicolegal requirements and the safety of personnel managing the bodies of the deceased with suspected or confirmed COVID-19 infection; at the site of death, during transport, during postmortem procedures, storage and preparation before and during burial or cremation as well as environmental cleaning and disinfection, involving various agencies in the country. A form of temporary controlled burial is as an option to allow the reinvestigation of a decedent to help formally identify victims of the pandemic such as undocumented migrants or refugees who were previously not identified. Due to the different legal requirements and mortality rates between countries, there is no one-size-fits-all approach to the management of the dead. Whenever possible, every opportunity and assistance must be given to families to mourn their loved ones, even in times of crisis or an outbreak, in order to sustain an appropriate level of dignity and respect.
    Matched MeSH terms: Pneumonia, Viral/diagnosis
  9. Fulltext Vesicular drug delivery systems as theranostics in COVID-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: Pneumonia, Viral/diagnosis*
  10. Fulltext A woman with fever and cough: coronavirus disease 2019
    Lu YQ
    Intern Emerg Med, 2020 Nov;15(8):1553-1554.
    PMID: 32232784 DOI: 10.1007/s11739-020-02321-3
    Matched MeSH terms: Pneumonia, Viral/diagnosis*
  11. Fulltext Perception of Health Conditions and Test Availability as Predictors of Adults' Mental Health during the COVID-19 Pandemic: A Survey Study of Adults in Malaysia
    Dai H, Zhang SX, Looi KH, Su R, Li J
    Int J Environ Res Public Health, 2020 07 30;17(15).
    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: Pneumonia, Viral/diagnosis*
  12. Fulltext A RT-PCR assay for the detection of coronaviruses from four genera
    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: Pneumonia, Viral/diagnosis*
  13. Fulltext Forecasting daily confirmed COVID-19 cases in Malaysia using ARIMA models
    Singh S, Murali Sundram B, Rajendran K, Boon Law K, Aris T, Ibrahim H, et al.
    J Infect Dev Ctries, 2020 09 30;14(9):971-976.
    PMID: 33031083 DOI: 10.3855/jidc.13116
    INTRODUCTION: The novel coronavirus infection has become a global threat affecting almost every country in the world. As a result, it has become important to understand the disease trends in order to mitigate its effects. The aim of this study is firstly to develop a prediction model for daily confirmed COVID-19 cases based on several covariates, and secondly, to select the best prediction model based on a subset of these covariates.

    METHODOLOGY: This study was conducted using daily confirmed cases of COVID-19 collected from the official Ministry of Health, Malaysia (MOH) and John Hopkins University websites. An Autoregressive Integrated Moving Average (ARIMA) model was fitted to the training data of observed cases from 22 January to 31 March 2020, and subsequently validated using data on cases from 1 April to 17 April 2020. The ARIMA model satisfactorily forecasted the daily confirmed COVID-19 cases from 18 April 2020 to 1 May 2020 (the testing phase).

    RESULTS: The ARIMA (0,1,0) model produced the best fit to the observed data with a Mean Absolute Percentage Error (MAPE) value of 16.01 and a Bayes Information Criteria (BIC) value of 4.170. The forecasted values showed a downward trend of COVID-19 cases until 1 May 2020. Observed cases during the forecast period were accurately predicted and were placed within the prediction intervals generated by the fitted model.

    CONCLUSIONS: This study finds that ARIMA models with optimally selected covariates are useful tools for monitoring and predicting trends of COVID-19 cases in Malaysia.

    Matched MeSH terms: Pneumonia, Viral/diagnosis
  14. Fulltext Role of biological Data Mining and Machine Learning Techniques in Detecting and Diagnosing the Novel Coronavirus (COVID-19): A Systematic Review
    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: Pneumonia, Viral/diagnosis*
  15. Fulltext Call to Action: SARS-CoV-2 and CerebrovAscular DisordErs (CASCADE)
    Abootalebi S, Aertker BM, Andalibi MS, Asdaghi N, Aykac O, Azarpazhooh MR, et al.
    J Stroke Cerebrovasc Dis, 2020 Sep;29(9):104938.
    PMID: 32807412 DOI: 10.1016/j.jstrokecerebrovasdis.2020.104938
    BACKGROUND AND PURPOSE: The novel severe acute respiratory syndrome coronavirus 2 (SARS-Cov-2), now named coronavirus disease 2019 (COVID-19), may change the risk of stroke through an enhanced systemic inflammatory response, hypercoagulable state, and endothelial damage in the cerebrovascular system. Moreover, due to the current pandemic, some countries have prioritized health resources towards COVID-19 management, making it more challenging to appropriately care for other potentially disabling and fatal diseases such as stroke. The aim of this study is to identify and describe changes in stroke epidemiological trends before, during, and after the COVID-19 pandemic.

    METHODS: This is an international, multicenter, hospital-based study on stroke incidence and outcomes during the COVID-19 pandemic. We will describe patterns in stroke management, stroke hospitalization rate, and stroke severity, subtype (ischemic/hemorrhagic), and outcomes (including in-hospital mortality) in 2020 during COVID-19 pandemic, comparing them with the corresponding data from 2018 and 2019, and subsequently 2021. We will also use an interrupted time series (ITS) analysis to assess the change in stroke hospitalization rates before, during, and after COVID-19, in each participating center.

    CONCLUSION: The proposed study will potentially enable us to better understand the changes in stroke care protocols, differential hospitalization rate, and severity of stroke, as it pertains to the COVID-19 pandemic. Ultimately, this will help guide clinical-based policies surrounding COVID-19 and other similar global pandemics to ensure that management of cerebrovascular comorbidity is appropriately prioritized during the global crisis. It will also guide public health guidelines for at-risk populations to reduce risks of complications from such comorbidities.

    Matched MeSH terms: Pneumonia, Viral/diagnosis
  16. Fulltext Early experience with universal preoperative and pre-procedural screening for COVID-19 in low-risk pediatric surgical patients requiring general anesthesia
    Sii CKS, Lee JA, Nah SA
    Pediatr Surg Int, 2020 Dec;36(12):1407-1411.
    PMID: 33068142 DOI: 10.1007/s00383-020-04760-7
    PURPOSE: The COVID-19 pandemic has placed extraordinary demands on healthcare services worldwide. Some have reported increased viral transmission to healthcare workers during aerosol-generating procedures such as intubation. We report our experience with universal preoperative and preprocedural screening for COVID-19 in children requiring general anaesthesia with low risk of having the infection.

    METHODS: This was a data review involving children aged 

    Matched MeSH terms: Pneumonia, Viral/diagnosis*
  17. Fulltext A novel strategy for community screening of SARS-CoV-2 (COVID-19): Sample pooling method
    Lim KL, Johari NA, Wong ST, Khaw LT, Tan BK, Chan KK, et al.
    PLoS One, 2020;15(8):e0238417.
    PMID: 32857823 DOI: 10.1371/journal.pone.0238417
    The rapid global spread of the coronavirus disease (COVID-19) has inflicted significant health and socioeconomic burden on affected countries. As positive cases continued to rise in Malaysia, public health laboratories experienced an overwhelming demand for COVID-19 screening. The confirmation of positive cases of COVID-19 has solely been based on the detection of the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) using real-time reverse transcription polymerase chain reaction (qRT-PCR). In efforts to increase the cost-effectiveness and efficiency of COVID-19 screening, we evaluated the feasibility of pooling clinical Nasopharyngeal/Oropharyngeal (NP/OP) swab specimens during nucleic acid extraction without a reduction in sensitivity of qRT-PCR. Pools of 10 specimens were extracted and subsequently tested by qRT-PCR according to the WHO-Charité protocol. We demonstrated that the sample pooling method showed no loss of sensitivity. The effectiveness of the pooled testing strategy was evaluated on both retrospective and prospective samples, and the results showed a similar detection sensitivity compared to testing individual sample alone. This study demonstrates the feasibility of using a pooled testing strategy to increase testing capacity and conserve resources, especially when there is a high demand for disease testing.
    Matched MeSH terms: Pneumonia, Viral/diagnosis*
  18. Fulltext Diagnostic techniques for COVID-19 and new developments
    Sheikhzadeh E, Eissa S, Ismail A, Zourob M
    Talanta, 2020 Dec 01;220:121392.
    PMID: 32928412 DOI: 10.1016/j.talanta.2020.121392
    COVID-19 pandemic is a serious global health issue today due to the rapid human to human transmission of SARS-CoV-2, a new type of coronavirus that causes fatal pneumonia. SARS -CoV-2 has a faster rate of transmission than other coronaviruses such as SARS and MERS and until now there are no approved specific drugs or vaccines for treatment. Thus, early diagnosis is crucial to prevent the extensive spread of the disease. The reverse transcription-polymerase chain reaction (RT-PCR) is the most routinely used method until now to detect SARS-CoV-2 infections. However, several other faster and accurate assays are being developed for the diagnosis of COVID-19 aiming to control the spread of infection through the identification of patients and immediate isolation. In this review, we will discuss the various detection methods of the SARS-CoV-2 virus including the recent developments in immunological assays, amplification techniques as well as biosensors.
    Matched MeSH terms: Pneumonia, Viral/diagnosis*
  19. Fulltext All together to Fight COVID-19
    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: Pneumonia, Viral/diagnosis
  20. Risk factors for Nipah virus infection among abattoir workers in Singapore
    Chew MH, Arguin PM, Shay DK, Goh KT, Rollin PE, Shieh WJ, et al.
    J Infect Dis, 2000 May;181(5):1760-3.
    PMID: 10823780
    During 10-19 March 1999, 11 workers in 1 of 2 Singaporean abattoirs developed Nipah-virus associated encephalitis or pneumonia, resulting in 1 fatality. A case-control study was conducted to determine occupational risk factors for infection. Case patients were abattoir A workers who had anti-Nipah IgM antibodies; control subjects were randomly selected abattoir A workers who tested negative for anti-Nipah IgM. All 13 case patients versus 26 (63%) of 41 control subjects reported contact with live pigs (P=.01). Swine importation from Malaysian states concurrently experiencing a Nipah virus outbreak was banned on 3 March 1999; on 19 March 1999, importation of Malaysian pigs was banned, and abattoirs were closed. No unusual illnesses among pigs processed during February-March were reported. Contact with live pigs appeared to be the most important risk factor for human Nipah virus infection. Direct contact with live, potentially infected pigs should be minimized to prevent transmission of this potentially fatal zoonosis to humans.
    Matched MeSH terms: Pneumonia, Viral/diagnosis
Related Terms
Filters
Contact Us

Please provide feedback to Administrator (afdal@afpm.org.my)

External Links