Publications
78 results found
Rosenberger KD, Phung Khanh L, Tobian F, et al., 2023, Early diagnostic indicators of dengue versus other febrile illnesses in Asia and Latin America (IDAMS study): a multicentre, prospective, observational study., Lancet Glob Health, Vol: 11, Pages: e361-e372
BACKGROUND: Improvements in the early diagnosis of dengue are urgently needed, especially in resource-limited settings where the distinction between dengue and other febrile illnesses is crucial for patient management. METHODS: In this prospective, observational study (IDAMS), we included patients aged 5 years and older with undifferentiated fever at presentation from 26 outpatient facilities in eight countries (Bangladesh, Brazil, Cambodia, El Salvador, Indonesia, Malaysia, Venezuela, and Viet Nam). We used multivariable logistic regression to investigate the association between clinical symptoms and laboratory tests with dengue versus other febrile illnesses between day 2 and day 5 after onset of fever (ie, illness days). We built a set of candidate regression models including clinical and laboratory variables to reflect the need of a comprehensive versus parsimonious approach. We assessed performance of these models via standard measures of diagnostic values. FINDINGS: Between Oct 18, 2011, and Aug 4, 2016, we recruited 7428 patients, of whom 2694 (36%) were diagnosed with laboratory-confirmed dengue and 2495 (34%) with (non-dengue) other febrile illnesses and met inclusion criteria, and were included in the analysis. 2703 (52%) of 5189 included patients were younger than 15 years, 2486 (48%) were aged 15 years or older, 2179 (42%) were female and 3010 (58%) were male. Platelet count, white blood cell count, and the change in these variables from the previous day of illness had a strong association with dengue. Cough and rhinitis had strong associations with other febrile illnesses, whereas bleeding, anorexia, and skin flush were generally associated with dengue. Model performance increased between day 2 and 5 of illness. The comprehensive model (18 clinical and laboratory predictors) had sensitivities of 0·80 to 0·87 and specificities of 0·80 to 0·91, whereas the parsimonious model (eight clinical and laboratory predictors) had sensit
Hernandez Perez B, Stiff O, Ming D, et al., 2023, Learning meaningful latent space representations for patient risk stratification: model development and validation for dengue and other acute febrile illness, Frontiers in Digital Health, Vol: 5, Pages: 1-16, ISSN: 2673-253X
Background: Increased data availability has prompted the creation of clinical decision support systems. These systems utilise clinical information to enhance health care provision, both to predict the likelihood of specific clinical outcomes or evaluate the risk of further complications. However, their adoption remains low due to concerns regarding the quality of recommendations, and a lack of clarity on how results are best obtained and presented.Methods: We used autoencoders capable of reducing the dimensionality of complex datasets in order to produce a 2D representation denoted as latent space to support understanding of complex clinical data. In this output, meaningful representations of individual patient profiles are spatially mapped in an unsupervised manner according to their input clinical parameters. This technique was then applied to a large real-world clinical dataset of over 12,000 patients with an illness compatible with dengue infection in Ho Chi Minh City, Vietnam between 1999 and 2021. Dengue is a systemic viral disease which exerts significant health and economic burden worldwide, and up to 5% of hospitalised patients develop life-threatening complications.Results: The latent space produced by the selected autoencoder aligns with established clinical characteristics exhibited by patients with dengue infection, as well as features of disease progression. Similar clinical phenotypes are represented close to each other in the latent space and clustered according to outcomes broadly described by the World Health Organisation dengue guidelines. Balancing distance metrics and density metrics produced results covering most of the latent space, and improved visualisation whilst preserving utility, with similar patients grouped closer together. In this case, this balance is achieved by using the sigmoid activation function and one hidden layer with three neurons, in addition to the latent dimension layer, which produces the output (Pearson, 0.840; Spearman
Ming D, Nguyen QH, An LP, et al., 2023, Mapping patient pathways and understanding clinical decision-making in dengue management to inform the development of digital health tools, BMC Medical Informatics and Decision Making, Vol: 23, Pages: 1-9, ISSN: 1472-6947
BackgroundDengue is a common viral illness and severe disease results in life-threatening complications. Healthcare services in low- and middle-income countries treat the majority of dengue cases worldwide. However, the clinical decision-making processes which result in effective treatment are poorly characterised within this setting. In order to improve clinical care through interventions relating to digital clinical decision-support systems (CDSS), we set out to establish a framework for clinical decision-making in dengue management to inform implementation.MethodsWe utilised process mapping and task analysis methods to characterise existing dengue management at the Hospital for Tropical Diseases, Ho Chi Minh City, Vietnam. This is a tertiary referral hospital which manages approximately 30,000 patients with dengue each year, accepting referrals from Ho Chi Minh city and the surrounding catchment area. Initial findings were expanded through semi-structured interviews with clinicians in order to understand clinical reasoning and cognitive factors in detail. A grounded theory was used for coding and emergent themes were developed through iterative discussions with clinician-researchers.ResultsKey clinical decision-making points were identified: (i) at the initial patient evaluation for dengue diagnosis to decide on hospital admission and the provision of fluid/blood product therapy, (ii) in those patients who develop severe disease or other complications, (iii) at the point of recurrent shock in balancing the need for fluid therapy with complications of volume overload. From interviews the following themes were identified: prioritising clinical diagnosis and evaluation over existing diagnostics, the role of dengue guidelines published by the Ministry of Health, the impact of seasonality and caseload on decision-making strategies, and the potential role of digital decision-support and disease scoring tools.ConclusionsThe study highlights the contemporary priorities i
Thi Hue Kien D, Edenborough K, Da Silva Goncalves D, et al., 2023, Genome evolution of dengue virus serotype 1 under selection by Wolbachia pipientis in Aedes aegypti mosquitoes, Virus Evolution, Vol: 9
The introgression of antiviral strains of Wolbachia into Aedes aegypti mosquito populations is a public health intervention for the control of dengue. Plausibly, dengue virus (DENV) could evolve to bypass the antiviral effects of Wolbachia and undermine this approach. Here, we established a serial-passage system to investigate the evolution of DENV in Ae. aegypti mosquitoes infected with the wMel strain of Wolbachia. Using this system, we report on virus genetic outcomes after twenty passages of serotype 1 of DENV (DENV-1). An amino acid substitution, E203K, in the DENV-1 envelope protein was more frequently detected in the consensus sequence of virus populations passaged in wMel-infected Ae. aegypti than wild-type counterparts. Positive selection at residue 203 was reproducible; it occurred in passaged virus populations from independent DENV-1-infected patients and also in a second, independent experimental system. In wild-type mosquitoes and human cells, the 203K variant was rapidly replaced by the progenitor sequence. These findings provide proof of concept that wMel-associated selection of virus populations can occur in experimental conditions. Field-based studies are needed to explore whether wMel imparts selective pressure on DENV evolution in locations where wMel is established.
Vuong NL, Cheung KW, Periaswamy B, et al., 2022, Hyperinflammatory Syndrome, Natural Killer Cell Function, and Genetic Polymorphisms in the Pathogenesis of Severe Dengue., J Infect Dis, Vol: 226, Pages: 1338-1347
BACKGROUND: Severe dengue, characterized by shock and organ dysfunction, is driven by an excessive host immune response. We investigated the role of hyperinflammation in dengue pathogenesis. METHODS: Patients recruited into an observational study were divided into 3 plasma leak severity grades. Hyperinflammatory biomarkers were measured at 4 time points. Frequencies, activation, and cytotoxic potential of natural killer (NK) cells were analyzed by flow cytometry. RNA was extracted from sorted CD56+ NK cells and libraries were prepared using SMART-Seq and sequenced using HiSeq3000 (Illumina). RESULTS: Sixty-nine patients were included (grade 0, 42 patients; grade 1, 19 patients; grade 2, 8 patients). Patients with grade 2 leakage had higher biomarkers than grade 0, including higher peak ferritin levels (83.3% vs 45.2%) and H-scores (median, 148.5 vs 105.5). NK cells from grade 2 patients exhibited decreased expression of perforin and granzyme B and activation markers. RNA sequencing revealed 3 single-nucleotide polymorphisms in NK cell functional genes associated with more severe leakage-NK cell lectin-like receptor K1 gene (KLRK1) and perforin 1 (PRF1). CONCLUSIONS: Features of hyperinflammation are associated with dengue severity, including higher biomarkers, impaired NK cell function, and polymorphisms in NK cell cytolytic function genes (KLRK1 and PRF1). Trials of immunomodulatory therapy in these patients is now warranted.
McBride A, Nguyen LV, Nguyen VH, et al., 2022, A modified Sequential Organ Failure Assessment score for dengue: development, evaluation and proposal for use in clinical trials, BMC INFECTIOUS DISEASES, Vol: 22
Choisy M, McBride A, Chambers M, et al., 2022, Climate change and health in Southeast Asia – defining research priorities and the role of the Wellcome Trust Africa Asia Programmes, Wellcome Open Research, Vol: 6, Pages: 278-278
<ns4:p>This article summarises a recent virtual meeting organised by the Oxford University Clinical Research Unit in Vietnam on the topic of climate change and health, bringing local partners, faculty and external collaborators together from across the Wellcome and Oxford networks. Attendees included invited local and global climate scientists, clinicians, modelers, epidemiologists and community engagement practitioners, with a view to setting priorities, identifying synergies and fostering collaborations to help define the regional climate and health research agenda. In this summary paper, we outline the major themes and topics that were identified and what will be needed to take forward this research for the next decade. We aim to take a broad, collaborative approach to including climate science in our current portfolio where it touches on infectious diseases now, and more broadly in our future research directions. We will focus on strengthening our research portfolio on climate-sensitive diseases, and supplement this with high quality data obtained from internal studies and external collaborations, obtained by multiple methods, ranging from traditional epidemiology to innovative technology and artificial intelligence and community-led research. Through timely agenda setting and involvement of local stakeholders, we aim to help support and shape research into global heating and health in the region.</ns4:p>
Trieu HT, Khanh LP, Ming DKY, et al., 2022, The compensatory reserve index predicts recurrent shock in patients with severe dengue, BMC Medicine, Vol: 20, ISSN: 1741-7015
BACKGROUND: Dengue shock syndrome (DSS) is one of the major clinical phenotypes of severe dengue. It is defined by significant plasma leak, leading to intravascular volume depletion and eventually cardiovascular collapse. The compensatory reserve Index (CRI) is a new physiological parameter, derived from feature analysis of the pulse arterial waveform that tracks real-time changes in central volume. We investigated the utility of CRI to predict recurrent shock in severe dengue patients admitted to the ICU. METHODS: We performed a prospective observational study in the pediatric and adult intensive care units at the Hospital for Tropical Diseases, Ho Chi Minh City, Vietnam. Patients were monitored with hourly clinical parameters and vital signs, in addition to continuous recording of the arterial waveform using pulse oximetry. The waveform data was wirelessly transmitted to a laptop where it was synchronized with the patient's clinical data. RESULTS: One hundred three patients with suspected severe dengue were recruited to this study. Sixty-three patients had the minimum required dataset for analysis. Median age was 11 years (IQR 8-14 years). CRI had a negative correlation with heart rate and moderate negative association with blood pressure. CRI was found to predict recurrent shock within 12 h of being measured (OR 2.24, 95% CI 1.54-3.26), P < 0.001). The median duration from CRI measurement to the first recurrent shock was 5.4 h (IQR 2.9-6.8). A CRI cutoff of 0.4 provided the best combination of sensitivity and specificity for predicting recurrent shock (0.66 [95% CI 0.47-0.85] and 0.86 [95% CI 0.80-0.92] respectively). CONCLUSION: CRI is a useful non-invasive method for monitoring intravascular volume status in patients with severe dengue.
Ming DK, Tuan NM, Hernandez B, et al., 2022, The diagnosis of dengue in patients presenting with acute febrile illness using supervised machine learning and impact of seasonality, Frontiers in Digital Health, Vol: 4, ISSN: 2673-253X
Background: Symptomatic dengue infection can result in a life-threatening shock syndrome and timely diagnosis is essential. Point-of-care tests for non-structural protein 1 and IgM are used widely but performance can be limited. We developed a supervised machine learning model to predict whether patients with acute febrile illnesses had a diagnosis of dengue or other febrile illnesses (OFI). The impact of seasonality on model performance over time was examined.Methods: We analysed data from a prospective observational clinical study in Vietnam. Enrolled patients presented with an acute febrile illness of <72 h duration. A gradient boosting model (XGBoost) was used to predict final diagnosis using age, sex, haematocrit, platelet, white cell, and lymphocyte count collected on enrolment. Data was randomly split 80/20% into a training and hold-out set, respectively, with the latter not used in model development. Cross-validation and hold out set testing was used, with performance over time evaluated through a rolling window approach.Results: We included 8,100 patients recruited between 16th October 2010 and 10th December 2014. In total 2,240 (27.7%) patients were diagnosed with dengue infection. The optimised model from training data had an overall median area under the receiver operator curve (AUROC) of 0.86 (interquartile range 0.84–0.86), specificity of 0.92, sensitivity of 0.56, positive predictive value of 0.73, negative predictive value (NPV) of 0.84, and Brier score of 0.13 in predicting the final diagnosis, with similar performances in hold-out set testing (AUROC of 0.86). Model performances varied significantly over time as a function of seasonality and other factors. Incorporation of a dynamic threshold which continuously learns from recent cases resulted in a more consistent performance throughout the year (NPV >90%).Conclusion: Supervised machine learning models are able to discriminate between dengue and OFI diagnoses in patients presenting with
Chanh HQ, Trieu HT, Vuong HNT, et al., 2022, Novel Clinical Monitoring Approaches for Reemergence of Diphtheria Myocarditis, Vietnam., Emerg Infect Dis, Vol: 28, Pages: 282-290
Diphtheria is a life-threatening, vaccine-preventable disease caused by toxigenic Corynebacterium bacterial species that continues to cause substantial disease and death worldwide, particularly in vulnerable populations. Further outbreaks of vaccine-preventable diseases are forecast because of health service disruptions caused by the coronavirus disease pandemic. Diphtheria causes a spectrum of clinical disease, ranging from cutaneous forms to severe respiratory infections with systemic complications, including cardiac and neurologic. In this synopsis, we describe a case of oropharyngeal diphtheria in a 7-year-old boy in Vietnam who experienced severe myocarditis complications. We also review the cardiac complications of diphtheria and discuss how noninvasive bedside imaging technologies to monitor myocardial function and hemodynamic parameters can help improve the management of this neglected infectious disease.
Ming DK, Hernandez B, Sangkaew S, et al., 2022, Applied machine learning for the risk-stratification and clinical decision support of hospitalised patients with dengue in Vietnam, PLOS Digital Health, Vol: 1, Pages: e0000005-e0000005
BackgroundIdentifying patients at risk of dengue shock syndrome (DSS) is vital for effective healthcare delivery. This can be challenging in endemic settings because of high caseloads and limited resources. Machine learning models trained using clinical data could support decision-making in this context.MethodsWe developed supervised machine learning prediction models using pooled data from adult and paediatric patients hospitalised with dengue. Individuals from 5 prospective clinical studies in Ho Chi Minh City, Vietnam conducted between 12th April 2001 and 30th January 2018 were included. The outcome was onset of dengue shock syndrome during hospitalisation. Data underwent random stratified splitting at 80:20 ratio with the former used only for model development. Ten-fold cross-validation was used for hyperparameter optimisation and confidence intervals derived from percentile bootstrapping. Optimised models were evaluated against the hold-out set.FindingsThe final dataset included 4,131 patients (477 adults and 3,654 children). DSS was experienced by 222 (5.4%) of individuals. Predictors were age, sex, weight, day of illness at hospitalisation, indices of haematocrit and platelets over first 48 hours of admission and before the onset of DSS. An artificial neural network model (ANN) model had best performance with an area under receiver operator curve (AUROC) of 0.83 (95% confidence interval [CI], 0.76–0.85) in predicting DSS. When evaluated against the independent hold-out set this calibrated model exhibited an AUROC of 0.82, specificity of 0.84, sensitivity of 0.66, positive predictive value of 0.18 and negative predictive value of 0.98.InterpretationThe study demonstrates additional insights can be obtained from basic healthcare data, when applied through a machine learning framework. The high negative predictive value could support interventions such as early discharge or ambulatory patient management in this population. Work is underway to incorporate t
Kerdegari H, Phung NTH, McBride A, et al., 2021, B-Line Detection and Localization in Lung Ultrasound Videos Using Spatiotemporal Attention, APPLIED SCIENCES-BASEL, Vol: 11
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- Citations: 1
Sangkaew S, Ming D, Boonyasiri A, et al., 2021, Transaminases and serum albumin as early predictors of severe dengue reply, Lancet Infectious Diseases, Vol: 21, Pages: 1489-1490, ISSN: 1473-3099
Choisy M, McBride A, Chambers M, et al., 2021, Climate change and health in Southeast Asia – defining research priorities and the role of the Wellcome Trust Africa Asia Programmes, Wellcome Open Research, Vol: 6, Pages: 278-278
<ns4:p>This article summarises a recent virtual meeting organised by the Oxford University Clinical Research Unit in Vietnam on the topic of climate change and health, bringing local partners, faculty and external collaborators together from across the Wellcome and Oxford networks. Attendees included invited local and global climate scientists, clinicians, modelers, epidemiologists and community engagement practitioners, with a view to setting priorities, identifying synergies and fostering collaborations to help define the regional climate and health research agenda. In this summary paper, we outline the major themes and topics that were identified and what will be needed to take forward this research for the next decade. We aim to take a broad, collaborative approach to including climate science in our current portfolio where it touches on infectious diseases now, and more broadly in our future research directions. We will focus on strengthening our research portfolio on climate-sensitive diseases, and supplement this with high quality data obtained from internal studies and external collaborations, obtained by multiple methods, ranging from traditional epidemiology to innovative technology and artificial intelligence and community-led research. Through timely agenda setting and involvement of local stakeholders, we aim to help support and shape research into global heating and health in the region.</ns4:p>
Pley C, Evans M, Lowe R, et al., 2021, Digital and technological innovation in vector-borne disease surveillance to predict, detect, and control climate-driven outbreaks, LANCET PLANETARY HEALTH, Vol: 5, Pages: E739-E745
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- Citations: 5
Kartsonaki C, 2021, Characteristics and outcomes of an international cohort of 400,000 hospitalised patients with Covid-19
<jats:title>Abstract</jats:title><jats:sec><jats:title>Background</jats:title><jats:p>Policymakers need robust data to respond to the COVID-19 pandemic. We describe demographic features, treatments and clinical outcomes in the International Severe Acute Respiratory and emerging Infection Consortium (ISARIC) COVID-19 cohort, the world’s largest international, standardised cohort of hospitalised patients.</jats:p></jats:sec><jats:sec><jats:title>Methods</jats:title><jats:p>The dataset analysed includes COVID-19 patients hospitalised between January 2020 and May 2021. We investigated how symptoms on admission, comorbidities, risk factors, and treatments varied by age, sex, and other characteristics. We used Cox proportional hazards models to investigate associations between demographics, symptoms, comorbidities, and other factors with risk of death, admission to intensive care unit (ICU), and invasive mechanical ventilation (IMV).</jats:p></jats:sec><jats:sec><jats:title>Findings</jats:title><jats:p>439,922 patients with laboratory-confirmed (91.7%) or clinically-diagnosed (8.3%) SARS-CoV-2 infection from 49 countries were enrolled. Age (adjusted hazard ratio [HR] per 10 years 1.49 [95% CI 1.49-1.50]) and male sex (1.26 [1.24-1.28]) were associated with a higher risk of death. Rates of admission to ICU and use of IMV increased with age up to age 60, then dropped. Symptoms, comorbidities, and treatments varied by age and had varied associations with clinical outcomes. Tuberculosis was associated with an 86% higher risk of death, and HIV with an 87% higher risk of death. Case fatality ratio varied by country partly due to differences in the clinical characteristics of recruited patients.</jats:p></jats:sec><jats:sec><jats:title>Interpretation</jats:title><jats:p>The size of our international database and the standardized da
Sangkaew S, Ming D, Boonyasiri A, et al., 2021, Risk predictors of progression to severe disease during the febrile phase of dengue: a systematic review and meta-analysis, Lancet Infectious Diseases, Vol: 21, Pages: 1014-1026, ISSN: 1473-3099
BACKGROUND: The ability to accurately predict early progression of dengue to severe disease is crucial for patient triage and clinical management. Previous systematic reviews and meta-analyses have found significant heterogeneity in predictors of severe disease due to large variation in these factors during the time course of the illness. We aimed to identify factors associated with progression to severe dengue disease that are detectable specifically in the febrile phase. METHODS: We did a systematic review and meta-analysis to identify predictors identifiable during the febrile phase associated with progression to severe disease defined according to WHO criteria. Eight medical databases were searched for studies published from Jan 1, 1997, to Jan 31, 2020. Original clinical studies in English assessing the association of factors detected during the febrile phase with progression to severe dengue were selected and assessed by three reviewers, with discrepancies resolved by consensus. Meta-analyses were done using random-effects models to estimate pooled effect sizes. Only predictors reported in at least four studies were included in the meta-analyses. Heterogeneity was assessed using the Cochrane Q and I2 statistics, and publication bias was assessed by Egger's test. We did subgroup analyses of studies with children and adults. The study is registered with PROSPERO, CRD42018093363. FINDINGS: Of 6643 studies identified, 150 articles were included in the systematic review, and 122 articles comprising 25 potential predictors were included in the meta-analyses. Female patients had a higher risk of severe dengue than male patients in the main analysis (2674 [16·2%] of 16 481 vs 3052 [10·5%] of 29 142; odds ratio [OR] 1·13 [95% CI 1·01-1·26) but not in the subgroup analysis of studies with children. Pre-existing comorbidities associated with severe disease were diabetes (135 [31·3%] of 431 with vs 868 [16·0%] of 5421 witho
McBride A, Mehta P, Rivino L, et al., 2021, Targeting hyperinflammation in infection: can we harness the COVID-19 therapeutics momentum to end the dengue drugs drought? Comment, LANCET MICROBE, Vol: 2, Pages: E277-E278
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ISARIC Clinical Characterisation Group, 2021, COVID-19 symptoms at hospital admission vary with age and sex: results from the ISARIC prospective multinational observational study, Infection: journal of infectious disease, Vol: 49, Pages: 899-905, ISSN: 0300-8126
BACKGROUND: The ISARIC prospective multinational observational study is the largest cohort of hospitalized patients with COVID-19. We present relationships of age, sex, and nationality to presenting symptoms. METHODS: International, prospective observational study of 60 109 hospitalized symptomatic patients with laboratory-confirmed COVID-19 recruited from 43 countries between 30 January and 3 August 2020. Logistic regression was performed to evaluate relationships of age and sex to published COVID-19 case definitions and the most commonly reported symptoms. RESULTS: 'Typical' symptoms of fever (69%), cough (68%) and shortness of breath (66%) were the most commonly reported. 92% of patients experienced at least one of these. Prevalence of typical symptoms was greatest in 30- to 60-year-olds (respectively 80, 79, 69%; at least one 95%). They were reported less frequently in children (≤ 18 years: 69, 48, 23; 85%), older adults (≥ 70 years: 61, 62, 65; 90%), and women (66, 66, 64; 90%; vs. men 71, 70, 67; 93%, each P < 0.001). The most common atypical presentations under 60 years of age were nausea and vomiting and abdominal pain, and over 60 years was confusion. Regression models showed significant differences in symptoms with sex, age and country. INTERPRETATION: This international collaboration has allowed us to report reliable symptom data from the largest cohort of patients admitted to hospital with COVID-19. Adults over 60 and children admitted to hospital with COVID-19 are less likely to present with typical symptoms. Nausea and vomiting are common atypical presentations under 30 years. Confusion is a frequent atypical presentation of COVID-19 in adults over 60 years. Women are less likely to experience typical symptoms than men.
Nguyen LV, Phung KL, Ming DKY, et al., 2021, Combination of inflammatory and vascular markers in the febrile phase of dengue is associated with more severe outcomes, eLife, Vol: 10, ISSN: 2050-084X
Background:Early identification of severe dengue patients is important regarding patient management and resource allocation. We investigated the association of 10 biomarkers (VCAM-1, SDC-1, Ang-2, IL-8, IP-10, IL-1RA, sCD163, sTREM-1, ferritin, CRP) with the development of severe/moderate dengue (S/MD).Methods:We performed a nested case-control study from a multi-country study. A total of 281 S/MD and 556 uncomplicated dengue cases were included.Results:On days 1–3 from symptom onset, higher levels of any biomarker increased the risk of developing S/MD. When assessing together, SDC-1 and IL-1RA were stable, while IP-10 changed the association from positive to negative; others showed weaker associations. The best combinations associated with S/MD comprised IL-1RA, Ang-2, IL-8, ferritin, IP-10, and SDC-1 for children, and SDC-1, IL-8, ferritin, sTREM-1, IL-1RA, IP-10, and sCD163 for adults.Conclusions:Our findings assist the development of biomarker panels for clinical use and could improve triage and risk prediction in dengue patients.Funding:This study was supported by the EU's Seventh Framework Programme (FP7-281803 IDAMS), the WHO, and the Bill and Melinda Gates Foundation.
Nguyen LV, Nguyen THQ, Nguyen THT, et al., 2021, Higher Plasma Viremia in the Febrile Phase Is Associated With Adverse Dengue Outcomes Irrespective of Infecting Serotype or Host Immune Status: An Analysis of 5642 Vietnamese Cases, CLINICAL INFECTIOUS DISEASES, Vol: 72, Pages: E1074-E1083, ISSN: 1058-4838
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Li Bassi G, Suen JY, Dalton HJ, et al., 2021, An appraisal of respiratory system compliance in mechanically ventilated covid-19 patients, CRITICAL CARE, Vol: 25, ISSN: 1364-8535
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- Citations: 7
Pham QT, Rabaa MA, Duong HL, et al., 2021, The First 100 Days of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) Control in Vietnam, CLINICAL INFECTIOUS DISEASES, Vol: 72, Pages: E334-E342, ISSN: 1058-4838
Haymet AB, Bartnikowski N, Wood ES, et al., 2021, Studying the Endothelial Glycocalyx in vitro: What Is Missing?, FRONTIERS IN CARDIOVASCULAR MEDICINE, Vol: 8, ISSN: 2297-055X
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Vuong NL, Lam PK, Ming DKY, et al., 2021, Combination of inflammatory and vascular markers in the febrile phase of dengue is associated with more severe outcomes
<jats:title>Abstract</jats:title><jats:sec><jats:title>Background</jats:title><jats:p>Early identification of severe dengue patients is important regarding patient management and resource allocation. We investigated the association of ten biomarkers (VCAM-1, SDC-1, Ang-2, IL-8, IP-10, IL-1RA, sCD163, sTREM-1, ferritin, CRP) with the development of severe/moderate dengue (S/MD).</jats:p></jats:sec><jats:sec><jats:title>Methods</jats:title><jats:p>We performed a nested case-control study from a multi-country study. A total of 281 S/MD and 556 uncomplicated dengue cases were included.</jats:p></jats:sec><jats:sec><jats:title>Results</jats:title><jats:p>On days 1-3 from symptom onset, higher levels of any biomarker increased the risk of developing S/MD. When assessing together, SDC-1 and IL-1RA were stable, while IP-10 changed the association from positive to negative; others showed weaker associations. The best combinations associated with S/MD comprised IL-1RA, Ang-2, IL-8, ferritin, IP-10, and SDC-1 for children, and SDC-1, IL-8, ferritin, sTREM-1, IL-1RA, IP-10, and sCD163 for adults.</jats:p></jats:sec><jats:sec><jats:title>Conclusions</jats:title><jats:p>Our findings assist the development of biomarker panels for clinical use and could improve triage and risk prediction in dengue patients.</jats:p></jats:sec><jats:sec><jats:title>Summary of the main point</jats:title><jats:p>Higher levels of any of VCAM-1, SDC-1, Ang-2, IL-8, IP-10, IL-1RA, sCD163, sTREM-1, ferritin, and CRP on illness days 1-3 increased the risk of developing severe/moderate dengue. The relationships differed between children and adults and some changed when assessed together.</jats:p></jats:sec>
Nguyen VVC, Ho BH, Greeff H, et al., 2021, Wearable remote monitoring for patients with COVID-19 in low-resource settings: case study, BMJ INNOVATIONS, Vol: 7, ISSN: 2055-8074
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- Citations: 2
Choisy M, McBride A, Chambers M, et al., 2021, Climate change and health in Southeast Asia - defining research priorities and the role of the Wellcome Trust Africa Asia Programmes., Wellcome Open Res, Vol: 6, ISSN: 2398-502X
This article summarises a recent virtual meeting organised by the Oxford University Clinical Research Unit in Vietnam on the topic of climate change and health, bringing local partners, faculty and external collaborators together from across the Wellcome and Oxford networks. Attendees included invited local and global climate scientists, clinicians, modelers, epidemiologists and community engagement practitioners, with a view to setting priorities, identifying synergies and fostering collaborations to help define the regional climate and health research agenda. In this summary paper, we outline the major themes and topics that were identified and what will be needed to take forward this research for the next decade. We aim to take a broad, collaborative approach to including climate science in our current portfolio where it touches on infectious diseases now, and more broadly in our future research directions. We will focus on strengthening our research portfolio on climate-sensitive diseases, and supplement this with high quality data obtained from internal studies and external collaborations, obtained by multiple methods, ranging from traditional epidemiology to innovative technology and artificial intelligence and community-led research. Through timely agenda setting and involvement of local stakeholders, we aim to help support and shape research into global heating and health in the region.
McBride A, Chanh HQ, Fraser JF, et al., 2020, Microvascular dysfunction in septic and dengue shock: Pathophysiology and implications for clinical management., Glob Cardiol Sci Pract, Vol: 2020, ISSN: 2305-7823
The microcirculation comprising of arterioles, capillaries and post-capillary venules is the terminal vascular network of the systemic circulation. Microvascular homeostasis, comprising of a balance between vasoconstriction, vasodilation and endothelial permeability in healthy states, regulates tissue perfusion. In severe infections, systemic inflammation occurs irrespective of the infecting microorganism(s), resulting in microcirculatory dysregulation and dysfunction, which impairs tissue perfusion and often precedes end-organ failure. The common hallmarks of microvascular dysfunction in both septic shock and dengue shock, are endothelial cell activation, glycocalyx degradation and plasma leak through a disrupted endothelial barrier. Microvascular tone is also impaired by a reduced bioavailability of nitric oxide. In vitro and in vivo studies have however demonstrated that the nature and extent of microvascular dysfunction as well as responses to volume expansion resuscitation differ in these two clinical syndromes. This review compares and contrasts the pathophysiology of microcirculatory dysfunction in septic versus dengue shock and the attendant effects of fluid administration during resuscitation.
Nguyen VVC, Vo TL, Nguyen TD, et al., 2020, The Natural History and Transmission Potential of Asymptomatic Severe Acute Respiratory Syndrome Coronavirus 2 Infection, CLINICAL INFECTIOUS DISEASES, Vol: 71, Pages: 2679-2687, ISSN: 1058-4838
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Zellweger RM, Yacoub S, Chan YFZ, et al., 2020, Disentangling etiologies of CNS infections in Singapore using multiple correspondence analysis and random forest, SCIENTIFIC REPORTS, Vol: 10, ISSN: 2045-2322
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