Displaying publications 1 - 20 of 29 in total

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  1. 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: Pneumonia, Viral/diagnosis
  2. 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: Pneumonia, Viral/diagnosis*
  3. Iqhbal KM, Ahmad NH
    Med J Malaysia, 2020 09;75(5):585-586.
    PMID: 32918431
    No abstract provided.
    Matched MeSH terms: Pneumonia, Viral/diagnosis
  4. Ng BH, Andrea YLB, Nuratiqah NA, Faisal AH, Soo CI, Najma K, et al.
    Med J Malaysia, 2020 09;75(5):582-584.
    PMID: 32918430
    The world feels strange as we face what is for most of us our first ever pandemic. The number of newly diagnosed cases rises daily in many parts of the world, and we are faced with the reality that there are still many things to learn about this new disease. We share here our experience of treating our first 199 COVID-19 patients in the Hospital Canselor Tuanku Muhriz, Pusat Perubatan Universiti Kebangsaan Malaysia (PPUKM).
    Matched MeSH terms: Pneumonia, Viral/diagnosis*
  5. Soh TV, Dzawani M, Noorlina N, Nik F, Norazmi A
    Med J Malaysia, 2020 09;75(5):479-484.
    PMID: 32918413
    BACKGROUND: The COVID-19 is a disease caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). This study aims to describe the clinical characteristics of COVID-19 patients admitted to Hospital Tengku Ampuan Afzan (HTAA), Pahang, Malaysia and to identify the clinical and laboratory markers for severe disease, complications and virologic clearance according to clinical staging.

    METHODS: This was a single-centre, retrospective, descriptive study. All COVID-19 patients admitted to HTAA from March 9 to April 15, 2020, were included in the study. Patients were categorised according to clinical staging. Data obtained from the medical report includes baseline characteristics of patients, comorbidities, presenting symptoms, laboratory findings, treatments, complications, and outcomes.

    RESULTS: Of the total of 247 patients hospitalised, the majority consisted at clinical-stage 1 (43%) and stage 2 (39%) disease. Older patients, diabetes mellitus, hypertension, cardiovascular diseases, and chronic kidney disease were found more common among patients with severe disease. Fever was uncommon and the majority had normal haemoglobin levels, white cell counts, and platelet counts. C-reactive protein (CRP) was found statistically significant to predict pneumonia or hypoxia at a cut-off value of 14mg/L (sensitivity 73.8%, specificity 91.3%) and 50mg/L (sensitivity 100%, specificity 96.4%) respectively. Pneumonia was mostly diagnosed radiologically using chest radiography, especially among clinical stage 3. Acute kidney injury (AKI) was a significant complication, with 31% of clinical stage 3 and above developed AKI and 44% of them requiring haemodialysis. Median virologic clearance time was 15 days from onset of illness, and asymptomatic patients had longer clearance time.

    CONCLUSION: COVID-19 presented with a wide spectrum of clinical patterns. CRP was a valuable predictor of severe disease. In this study risk and severity of acute kidney injury were found to be higher. A longer duration of virologic clearance was observed among the asymptomatic patients.
    Matched MeSH terms: Pneumonia, Viral/diagnosis*
  6. 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: Pneumonia, Viral/diagnosis*
  7. 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: Pneumonia, Viral/diagnosis*
  8. Tan GC, Cheong SK
    Malays J Pathol, 2020 Apr;42(1):1.
    PMID: 32342925
    No abstract available.
    Matched MeSH terms: Pneumonia, Viral/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: Pneumonia, Viral/diagnosis*
  10. 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
  11. 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
  12. 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*
  13. 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*
  14. 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*
  15. 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. 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*
  17. 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
  18. 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*
  19. 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: Pneumonia, Viral/diagnosis*
  20. 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*
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