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  1. Jovanović V, Rudnev M, Abdelrahman M, Abdul Kadir NB, Adebayo DF, Akaliyski P, et al.
    Psychol Assess, 2024 Jan;36(1):14-29.
    PMID: 38010780 DOI: 10.1037/pas0001270
    Coronavirus Anxiety Scale (CAS) is a widely used measure that captures somatic symptoms of coronavirus-related anxiety. In a large-scale collaboration spanning 60 countries (Ntotal = 21,513), we examined the CAS's measurement invariance and assessed the convergent validity of CAS scores in relation to the fear of COVID-19 (FCV-19S) and the satisfaction with life (SWLS-3) scales. We utilized both conventional exact invariance tests and alignment procedures, with results revealing that the single-factor model fit the data well in almost all countries. Partial scalar invariance was supported in a subset of 56 countries. To ensure the robustness of results, given the unbalanced samples, we employed resampling techniques both with and without replacement and found the results were more stable in larger samples. The alignment procedure demonstrated a high degree of measurement invariance with 9% of the parameters exhibiting noninvariance. We also conducted simulations of alignment using the parameters estimated in the current model. Findings demonstrated reliability of the means but indicated challenges in estimating the latent variances. Strong positive correlations between CAS and FCV-19S estimated with all three different approaches were found in most countries. Correlations of CAS and SWLS-3 were weak and negative but significantly differed from zero in several countries. Overall, the study provided support for the measurement invariance of the CAS and offered evidence of its convergent validity while also highlighting issues with variance estimation. (PsycInfo Database Record (c) 2024 APA, all rights reserved).
    Matched MeSH terms: Humans
  2. Vasuthevan K, Vaithilingam S, Ng JWJ
    PLoS One, 2024;19(1):e0295746.
    PMID: 38166113 DOI: 10.1371/journal.pone.0295746
    The COVID-19 pandemic has revolutionized the teaching pedagogy in higher education as universities are forecasted to increase investments in learning technology infrastructure to transition away from traditional teaching methods. Therefore, it is crucial to investigate whether academics intend to continually integrate learning technologies as part of a permanent pedagogical change beyond the COVID-19 pandemic. Drawing upon the Unified Theory of Acceptance and Use of Technology (UTAUT), and Expectation Confirmation Model (ECM), this study examines the salient determinants influencing the continuance intention of academics to use learning technologies in their teaching pedagogy during and after COVID-19. Primary data collected from a private university was analyzed using the partial least squares structural equation modelling technique (PLS-SEM). The findings revealed two sequential mediating relationships which serve as the mechanism linking the relationship between facilitating conditions and their continuance intention to use learning technologies during and beyond the COVID-19 pandemic.
    Matched MeSH terms: Humans
  3. Shuhardi SA, Mohamed Said MS, Kew TY, Ramli R
    Am J Case Rep, 2023 Dec 29;24:e942163.
    PMID: 38155491 DOI: 10.12659/AJCR.942163
    BACKGROUND Systemic lupus erythematosus (SLE) is an autoimmune disease with diverse manifestations. The involvement of the musculoskeletal system is very common, and infection is one of the manifestations, which can involve any part of the body. We report a case of a middle-aged woman with recurrent episodes of infection of her left temple. CASE REPORT A 51-year old woman was referred to our clinic following failures to eradicate infection on her left temple for 9 months. Examination revealed facial asymmetry, with diffuse non-tender swelling involving her left temple area, which extended to her cheek. Computed tomography and magnetic resonance imaging (MRI) showed a periosteal reaction of the zygomatic bone. Left temporalis muscle thickening and residual osteomyelitis of the zygomatic bone were also shown by MRI. In view of the unresolved infection with incision and drainage and antibiotics, further blood investigations led to the discovery of SLE. The antinuclear antibody and anti-double-stranded DNA were positive. In addition, low nephelometry markers, C3 (26.7 mg/dL) and C4 (8.24 mg/dL), were observed. This patient was treated with 200 mg of oral hydrochloroquine once daily and 5 mg of oral prednisolone once daily. After 6 months of treatment, the infection subsided, and the structures involved showed remarkable healing. The patient is still taking the same dose and frequency of both drugs at the present time. CONCLUSIONS Temporalis pyomyositis and osteomyelitis of the zygomatic bone could be manifestation of SLE disease; however, the involvement of infection cannot be ruled out.
    Matched MeSH terms: Humans
  4. Saniasiaya J, Kulasegarah J
    BMJ Case Rep, 2023 Dec 28;16(12).
    PMID: 38154869 DOI: 10.1136/bcr-2023-258290
    Audiovestibular symptoms following COVID-19 have been long acknowledged, especially in adults. However, acute labyrinthitis presenting as an early manifestation of COVID-19 has not been reported in children. We report COVID-19-induced acute labyrinthitis in a teenager. We report on a boy in his early adolescence with a sudden onset of spinning sensation, imbalance and unilateral hearing loss with a positive SARS-CoV-2 test. Vestibular investigations point towards right labyrinthine hypofunction, and an audiometry test revealed right-sided severe hearing loss. Symptoms improved gradually with steroids and vestibular rehabilitation therapy. However, the long-term repercussions of post-COVID-19 acute labyrinthitis are unknown and must be followed up closely. To our knowledge, this is the first reported case of acute labyrinthitis secondary to COVID-19 in paediatrics. Additionally, we conducted a literature search to elucidate the outcome of COVID-19-induced acute vestibular syndrome in children.
    Matched MeSH terms: Humans
  5. Hwong WY, Ng SW, Tong SF, Ab Rahman N, Law WC, Wong SK, et al.
    BMC Health Serv Res, 2024 Jan 05;24(1):34.
    PMID: 38183003 DOI: 10.1186/s12913-023-10397-8
    BACKGROUND: Translation into clinical practice for use of intravenous thrombolysis (IVT) for the management of ischemic stroke remains a challenge especially across low- and middle-income countries, with regional inconsistencies in its rate. This study aimed at identifying factors that influenced the provision of IVT and the variation in its rates in Malaysia.

    METHODS: A multiple case study underpinning the Tailored Implementation for Chronic Diseases framework was carried out in three public hospitals with differing rates of IVT using a multiple method design. Twenty-five in-depth interviews and 12 focus groups discussions were conducted among 89 healthcare providers, along with a survey on hospital resources and a medical records review to identify reasons for not receiving IVT. Qualitative data were analysed using reflective thematic method, before triangulated with quantitative findings.

    RESULTS: Of five factors identified, three factors that distinctively influenced the variation of IVT across the hospitals were: 1) leadership through quality stroke champions, 2) team cohesiveness which entailed team dynamics and its degree of alignment and, 3) facilitative work process which included workflow simplification and familiarity with IVT. Two other factors that were consistently identified as barriers in these hospitals included patient factors which largely encompassed delayed presentation, and resource constraints. About 50.0 - 67.6% of ischemic stroke patients missed the opportunity to receive IVT due to delayed presentation.

    CONCLUSIONS: In addition to the global effort to explore sustainable measures to improve patients' emergency response for stroke, attempts to improve the provision of IVT for stroke care should also consider the inclusion of interventions targeting on health systems perspectives such as promoting quality leadership, team cohesiveness and workflow optimisation.

    Matched MeSH terms: Humans
  6. Franklin F, Rajamanikam A, Phang WK, Raju CS, Gill JS, Francis B, et al.
    Sci Rep, 2024 Jan 03;14(1):385.
    PMID: 38172146 DOI: 10.1038/s41598-023-50299-7
    The aetiology of schizophrenia is multifactorial, and the identification of its risk factors are scarce and highly variable. A cross-sectional study was conducted to investigate the risk factors associated with schizophrenia among Malaysian sub-population. A total of 120 individuals diagnosed with schizophrenia (SZ) and 180 non-schizophrenic (NS) individuals participated in a questionnaire-based survey. Data of complete questionnaire responses obtained from 91 SZ and 120 NS participants were used in statistical analyses. Stool samples were obtained from the participants and screened for gut parasites and fungi using conventional polymerase chain reaction (PCR). The median age were 46 years (interquartile range (IQR) 37 to 60 years) and 35 years (IQR 24 to 47.75 years) for SZ and NS respectively. Multivariable binary logistic regression showed that the factors associated with increased risk of SZ were age, sex, unemployment, presence of other chronic ailment, smoking, and high dairy consumption per week. These factors, except sex, were positively associated with the severity of SZ. Breastfed at infancy as well as vitamin and supplement consumption showed a protective effect against SZ. After data clean-up, fungal or parasitic infections were found in 98% (39/42). of SZ participants and 6.1% (3/49) of NS participants. Our findings identified non-modifiable risk factors (age and sex) and modifiable lifestyle-related risk factors (unemployment, presence of other chronic ailment, smoking, and high dairy consumption per week) associated with SZ and implicate the need for medical attention in preventing fungal and parasitic infections in SZ.
    Matched MeSH terms: Humans
  7. Hussein AM, Sharifai AG, Alia OM, Abualigah L, Almotairi KH, Abujayyab SKM, et al.
    Sci Rep, 2024 Jan 04;14(1):534.
    PMID: 38177156 DOI: 10.1038/s41598-023-47038-3
    The most widely used method for detecting Coronavirus Disease 2019 (COVID-19) is real-time polymerase chain reaction. However, this method has several drawbacks, including high cost, lengthy turnaround time for results, and the potential for false-negative results due to limited sensitivity. To address these issues, additional technologies such as computed tomography (CT) or X-rays have been employed for diagnosing the disease. Chest X-rays are more commonly used than CT scans due to the widespread availability of X-ray machines, lower ionizing radiation, and lower cost of equipment. COVID-19 presents certain radiological biomarkers that can be observed through chest X-rays, making it necessary for radiologists to manually search for these biomarkers. However, this process is time-consuming and prone to errors. Therefore, there is a critical need to develop an automated system for evaluating chest X-rays. Deep learning techniques can be employed to expedite this process. In this study, a deep learning-based method called Custom Convolutional Neural Network (Custom-CNN) is proposed for identifying COVID-19 infection in chest X-rays. The Custom-CNN model consists of eight weighted layers and utilizes strategies like dropout and batch normalization to enhance performance and reduce overfitting. The proposed approach achieved a classification accuracy of 98.19% and aims to accurately classify COVID-19, normal, and pneumonia samples.
    Matched MeSH terms: Humans
  8. Mukherjee D, Bhavnani S, Lockwood Estrin G, Rao V, Dasgupta J, Irfan H, et al.
    Autism, 2024 Jan;28(1):6-31.
    PMID: 36336996 DOI: 10.1177/13623613221133176
    The challenge of finding autistic children, and finding them early enough to make a difference for them and their families, becomes all the greater in parts of the world where human and material resources are in short supply. Poverty of resources delays interventions, translating into a poverty of outcomes. Digital tools carry potential to lessen this delay because they can be administered by non-specialists in children's homes, schools or other everyday environments, they can measure a wide range of autistic behaviours objectively and they can automate analysis without requiring an expert in computers or statistics. This literature review aimed to identify and describe digital tools for screening children who may be at risk for autism. These tools are predominantly at the 'proof-of-concept' stage. Both portable (laptops, mobile phones, smart toys) and fixed (desktop computers, virtual-reality platforms) technologies are used to present computerised games, or to record children's behaviours or speech. Computerised analysis of children's interactions with these technologies differentiates children with and without autism, with promising results. Tasks assessing social responses and hand and body movements are the most reliable in distinguishing autistic from typically developing children. Such digital tools hold immense potential for early identification of autism spectrum disorder risk at a large scale. Next steps should be to further validate these tools and to evaluate their applicability in a variety of settings. Crucially, stakeholders from underserved communities globally must be involved in this research, lest it fail to capture the issues that these stakeholders are facing.
    Matched MeSH terms: Humans
  9. Chee ZJ, Scheeren AM, De Vries M
    Autism, 2024 Jan;28(1):32-42.
    PMID: 36632803 DOI: 10.1177/13623613221147395
    The AQ-28 is a questionnaire measuring autistic traits, that is, traits that are related to Autism Spectrum Conditions, but its reliability in other cultures has not been thoroughly evaluated. We, therefore, tested whether the properties of the AQ-28 are comparable between two countries with different cultures, Malaysia and the Netherlands. A total of 437 Malaysian and 818 Dutch participants completed the AQ-28 online. We measured whether the AQ-28 measures autistic traits similarly in Malaysia and the Netherlands. The AQ-28 measures autistic traits similarly, and the reliability was acceptable and good in the general population of Malaysia and the Netherlands, respectively. However, Malaysians scored higher than Dutch participants. Moreover, 11 AQ-28 items showed cultural bias, indicating that these items are answered/interpreted differently in Malaysia and the Netherlands. Cross-cultural differences in interpreting, reporting, and/or expressing autistic traits highlighted in this study could potentially explain why some items are culturally biased and why Malaysians score higher on these items. The findings of this work imply that cutoff scores derived from one culture should not be generalised to another culture. Moreover, the findings are informative for future development of culturally neutral or appropriate screening and diagnostic tools for autism.
    Matched MeSH terms: Humans
  10. Ahmed H, Nisar QA, Khan W, Patwary AK, Zaman S
    Environ Sci Pollut Res Int, 2023 Nov;30(54):115882-115895.
    PMID: 37897574 DOI: 10.1007/s11356-023-30644-z
    The purpose of this study is to investigate the impact of a set of green human resource management (HRM) practices on sustainable performance in Pakistani higher education institutions (HEIs), while also taking into account the mediating influence of environmental consciousness and green intellectual capital. Furthermore, the study aims to assess the association between environmental consciousness and green intellectual capital, along with the sustainable outcome. The study data was collected from 250 HR managers and executive officers who were responsible for implementing green HRM practices and sustainable performance in the education sector of Pakistan. Smart PLS-4 software was used to perform the statistical analysis of the data. According to the results of this study, green HRM practices play a substantial role in enhancing sustainable performance. The study also identified a link between green HRM practices and sustainable performance via environmental awareness and green intellectual capital. The research contributes to the theoretical paradigm's social cognitive theory by offering information on green HRM practice bundles and sustainable performance. The research also demonstrates that green intellectual capital and environmental consciousness operate as a bridge between green HRM practices and long-term sustainable performance. The study's findings have real-world applications for education, policymakers, and human resource managers at the highest levels. In order to achieve sustainable performance, the study emphasizes the significance of developing green intellectual capital and implementing green HRM practices.
    Matched MeSH terms: Humans
  11. Selvan S, Thangaraj SJJ, Samson Isaac J, Benil T, Muthulakshmi K, Almoallim HS, et al.
    Biomed Res Int, 2022;2022:2003184.
    PMID: 35958813 DOI: 10.1155/2022/2003184
    Prenatal heart disease, generally known as cardiac problems (CHDs), is a group of ailments that damage the heartbeat and has recently now become top deaths worldwide. It connects a plethora of cardiovascular diseases risks to the urgent in need of accurate, trustworthy, and effective approaches for early recognition. Data preprocessing is a common method for evaluating big quantities of information in the medical business. To help clinicians forecast heart problems, investigators utilize a range of data mining algorithms to examine enormous volumes of intricate medical information. The system is predicated on classification models such as NB, KNN, DT, and RF algorithms, so it includes a variety of cardiac disease-related variables. It takes do with an entire dataset from the medical research database of patients with heart disease. The set has 300 instances and 75 attributes. Considering their relevance in establishing the usefulness of alternate approaches, only 15 of the 75 criteria are examined. The purpose of this research is to predict whether or not a person will develop cardiovascular disease. According to the statistics, naïve Bayes classifier has the highest overall accuracy.
    Matched MeSH terms: Humans
  12. Ali QM, Nisar QA, Abidin RZU, Qammar R, Abbass K
    Environ Sci Pollut Res Int, 2023 Dec;30(60):124474-124487.
    PMID: 35349063 DOI: 10.1007/s11356-022-19888-3
    The research aims to examine the role of green human resource management (GHRM) in the university's environmental performance. Furthermore, this research also focuses on the mediating effect of green commitment and pro-environmental behavior. It also aims to check how green self-efficacy moderates the relationship between green commitment and pro-environmental behavior. The paper opted for a quantitative design using the convenience sampling technique/approach by collecting the data through a structured questionnaire on 208 academic staff currently employed in the university. The data were collected from August until December 2021 on two campuses (Gujranwala, Jhelum) of the University of Punjab in Pakistan. The current study results give empirical insights that show how green human resource management practices lead to environmental performance at a greater level in a university setting. Study results proposed that change in behavior of employees through human resource management practices can ultimately affect the organization's environmental performance. Further results also demonstrate that green self-efficacy moderates the relationship between green commitment and pro-environmental behavior. This study highlights the role of the university staff's level of commitment and self-efficacy, which are beneficial for enhancing the university's environmental performance. The originality of this study fills the gap in how green commitment mediates the relationship of green human resource management and environmental performance further; it fulfills the gap of green self-efficacy that moderates the relationship of pro-environmental behavior and green commitment. The study sheds light on green human resource management practices in the higher education sector. It emphasizes the vital role of academic staff's environmentally conscious behavior in enhancing a university's environmental performance. The further study highlighted the increasing concept of green human resource management as a set of building the ability, enhancing motivation, and providing opportunities to influence workers' pro-environmental behaviors. The conclusion of the current research was capable of validating the positive concerns of green GHRM, behaviors, and commitments for environmental performance.
    Matched MeSH terms: Humans
  13. Al-Worafi YM, Goh KW, Hermansyah A, Tan CS, Ming LC
    JMIR Med Educ, 2024 Jan 12;10:e47339.
    PMID: 38214967 DOI: 10.2196/47339
    BACKGROUND: Artificial Intelligence (AI) plays an important role in many fields, including medical education, practice, and research. Many medical educators started using ChatGPT at the end of 2022 for many purposes.

    OBJECTIVE: The aim of this study was to explore the potential uses, benefits, and risks of using ChatGPT in education modules on integrated pharmacotherapy of infectious disease.

    METHODS: A content analysis was conducted to investigate the applications of ChatGPT in education modules on integrated pharmacotherapy of infectious disease. Questions pertaining to curriculum development, syllabus design, lecture note preparation, and examination construction were posed during data collection. Three experienced professors rated the appropriateness and precision of the answers provided by ChatGPT. The consensus rating was considered. The professors also discussed the prospective applications, benefits, and risks of ChatGPT in this educational setting.

    RESULTS: ChatGPT demonstrated the ability to contribute to various aspects of curriculum design, with ratings ranging from 50% to 92% for appropriateness and accuracy. However, there were limitations and risks associated with its use, including incomplete syllabi, the absence of essential learning objectives, and the inability to design valid questionnaires and qualitative studies. It was suggested that educators use ChatGPT as a resource rather than relying primarily on its output. There are recommendations for effectively incorporating ChatGPT into the curriculum of the education modules on integrated pharmacotherapy of infectious disease.

    CONCLUSIONS: Medical and health sciences educators can use ChatGPT as a guide in many aspects related to the development of the curriculum of the education modules on integrated pharmacotherapy of infectious disease, syllabus design, lecture notes preparation, and examination preparation with caution.

    Matched MeSH terms: Humans
  14. Ng JSC, Chervier C, Carmenta R, Samdin Z, Azhar B, Karsenty A
    Environ Manage, 2024 Jan;73(1):259-273.
    PMID: 37667018 DOI: 10.1007/s00267-023-01876-z
    The jurisdictional approach concept emerged in response to the widespread failure of sectoral forest conservation projects. Despite its increasing popularity, understanding jurisdictional approach outcomes is challenging, given that many remain in either the formation or implementation stage. Furthermore, diverse stakeholders hold different perspectives on what exactly a jurisdictional approach is intended to pursue. These different perspectives are important to unravel, as having a shared understanding of the outcomes is important to build the critical support needed for it. This study aims to add to the limited evidence with a case study in Sabah, Malaysia, which is committed to addressing a leading deforestation driver (palm oil) through sustainability certification in a jurisdiction. We used Q-methodology to explore stakeholder perceptions, revealing three distinct perspectives regarding what outcomes jurisdictional approaches should pursue. We asked about outcomes achievable within ten years (2022-2032) and considering real-world constraints. We found different perspectives regarding economic, environmental, governance, and smallholders' welfare outcomes. However, we found consensus among stakeholders about some outcomes: (i) that achieving zero-deforestation is untenable, (ii) that issuing compensation or incentives to private land owners to not convert forests into plantations is unrealistic, (iii) that the human well-being of plantation workers could improve through better welfare, and (iv) the free, prior and informed consent given by local communities being required legally. The findings offer insights into key stakeholders' perceptions of the deliverables of jurisdictional approaches and the difficulty of achieving its objectives under real-world constraints.
    Matched MeSH terms: Humans
  15. Yolanda R, Lheknim V, B A R A, Price WW, Hendrickx ME
    Zootaxa, 2023 Aug 16;5330(3):413-429.
    PMID: 38221129 DOI: 10.11646/zootaxa.5330.3.5
    The zoogeographic distribution of lophogastrid species (Crustacea: Peracarida: Lophogastrida) occurring in the Indonesian waters is presented. For each species, data on general distribution, bathymetric ranges, habitat and localities reported on published data are provided. A total of 20 lophogastrid species belonging to three families and seven genera occur in Indonesian waters (about 38% of all known lophogastrids species worldwide), a number greater than other areas of Southeast Asia. Also, based on current information, the number of species or species richness is greater than other regions, such as Madagascar, North Pacific off Japan, Mediterranean, Canary Island, northern mid-Atlantic ridge, Iberian Peninsula, Mexico, and Angola Basin (SE Atlantic). Most of the Indonesian species are distributed worldwide, but one species, Lophogaster inermis appears to be endemic to Indonesia. Previous listings of Paralophogaster intermedius occurring in Southeast Asian waters is not verified in any collections, and has therefore been removed from our updated list.
    Matched MeSH terms: Humans
  16. Krishnan R, Shamsher S, Adzura S
    Med J Malaysia, 2023 Nov;78(6):849-851.
    PMID: 38031231
    We describe a potential cause of eye injury, its concerns and ways to prevent it. The first author underwent a left cataract operation and was prescribed eye drops postoperatively. While applying one of the eye drops, he felt an object hitting the lower eyelid. A serrated plastic piece had fallen off the bottle. Had it fallen on the operated site, it might have caused serious untoward complications. Nurses, carers and patients need to be educated to remove the serrated piece from the bottle before applying eye drops. Manufacturers of eye drops should design safer bottles without such serrated pieces to prevent such eye injuries.
    Matched MeSH terms: Humans
  17. Gangurde R, Jagota V, Khan MS, Sakthi VS, Boppana UM, Osei B, et al.
    Biomed Res Int, 2023;2023:6970256.
    PMID: 36760472 DOI: 10.1155/2023/6970256
    The application of computational approaches in medical science for diagnosis is made possible by the development in technical advancements connected to computer and biological sciences. The current cancer diagnosis system is becoming outmoded due to the new and rapid growth in cancer cases, and new, effective, and efficient methodologies are now required. Accurate cancer-type prediction is essential for cancer diagnosis and treatment. Understanding, diagnosing, and identifying the various types of cancer can be greatly aided by knowledge of the cancer genes. The Convolution Neural Network (CNN) and neural pattern recognition (NPR) approaches are used in this study paper to detect and predict the type of cancer. Different Convolution Neural Networks (CNNs) have been proposed by various researchers up to this point. Each model concentrated on a certain set of parameters to simulate the expression of genes. We have developed a novel CNN-NPR architecture that predicts cancer type while accounting for the tissue of origin using high-dimensional gene expression inputs. The 5000-person sample of the 1-D CNN integrated with NPR is trained and tested on the gene profile, mapping with various cancer kinds. The proposed model's accuracy of 94% suggests that the suggested combination may be useful for long-term cancer diagnosis and detection. Fewer parameters are required for the suggested model to be efficiently trained before prediction.
    Matched MeSH terms: Humans
  18. Nor Hashimah AMN, Lim AL, Mohd Zain M, Gun SC, Mohd Isa L, Chong HC, et al.
    Med J Malaysia, 2023 Dec;78(7):870-875.
    PMID: 38159920
    INTRODUCTION: The aim of this study was to analyse the clinical characteristics of patients with rheumatoid arthritis receiving biologics therapy and investigate the association between types of biologics and tuberculosis (TB) infections in 13 tertiary hospitals in Malaysia.

    MATERIALS AND METHODS: This was a retrospective study that included all RA patients receiving biologics therapy in 13 tertiary hospitals in Malaysia from January 2008 to December 2018.

    RESULTS: We had 735 RA patients who received biologics therapy. Twenty-one of the 735 patients were diagnosed with TB infection after treatment with biologics. The calculated prevalence of TB infection in RA patients treated with biologics was 2.9% (29 per 1000 patients). Four groups of biologics were used in our patient cohort: monoclonal TNF inhibitors, etanercept, tocilizumab, and rituximab, with monoclonal TNF inhibitors being the most commonly used biologic. The median duration of biologics therapy before the diagnosis of TB was 8 months. 75% of patients had at least one co-morbidity and all patients had at least one ongoing cDMARD therapy at the time of TB diagnosis. More than half of the patients were on steroid therapy with an average prednisolone dose of 5 mg daily.

    CONCLUSION: Although the study population and data were limited, this study illustrates the spectrum of TB infections in RA patients receiving biologics and potential risk factors associated with biologics therapy in Malaysia.

    Matched MeSH terms: Humans
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