An Evidence-Based Algorithm for Early Prognosis of Severe Dengue in the Outpatient Setting

Development of a novel lectin-based gold nanoparticle point-of-care immunoassay for rapid diagnosis of patients with severe Dengue infection

Rapid diagnosis of patients with severe Dengue infection can be useful for the efficient clinical management of cases caused by the Dengue virus. Lateral Flow Immunoassay (LFIA) have been broadly used for rapid Dengue diagnosis, because of their quick readouts with the human eye, simplicity of use, and affordability. Despite the availability of several commercial Dengue point-of-care assays, none has shown to be successful in discriminating between severe and nonsevere forms of Dengue infection. In the current study, for the first time, a novel lectin-based point-of-care assay for the early detection of patients with severe Dengue infection with gold-adorned sheets as detection labels is being reported. In this assay, Dengue severity was diagnosed by detecting the glycosylation profile of vitronectin, a known Dengue severity marker. Two lectins were employed namely DSA (Datura stramonium) and MAA (Maackia amurensis) that can recognize specific glycans like galactose Gal-(1-4) GlcNAc and sialic acid in an (α2-3) linkage, which displayed high sensitivity and high specificity, i.e. 90% and 85% for DSA and 90.91% and 95% for MAA. The new assay has a detection limit of 5 µg µl-1 and enables the quick (30 min) and sensitive detection of severe Dengue cases. The reported point-of-care immunoassay exhibits considerable promise for early identification of patients with Dengue severity.

Routine blood parameters of dengue infected children and adults. A meta-analysis

The World Health Organization (WHO) has revised dengue case classification in 2009 to better reflect the severity of the disease. However, there was no comprehensive meta-analysis of pooled routine blood parameters according to the age or the categories of the 2009 WHO classification. This study aimed to meta-analyze the routine blood parameters of dengue infected children and adults. Electronic search was performed with eligible articles included for review. Meta-analysis was conducted for six blood parameters stratified into children, adults and all ages, which were further grouped into the three 2009 WHO case classifications (dengue without warning signs, DwoWS; dengue with warning signs, DwWS; severe dengue, SD), non-severe dengue (non-SD) and 'All' cases. A total of 55 articles were included in the meta-analysis. Fifteen studies were conducted in the children's age category, 31 studies in the adult category and nine studies in all ages. The four selected pooled blood parameters for children were white blood cell (WBC) (×103/L) with 5.11 (SD), 5.64 (DwWS), 5.52 (DwoWS) and 4.68 (Non-SD) hematocrit (HCT) (%) with 36.78 (SD), 40.70 (DwWS), 35.00 (DwoWS) and 29.78 (Non-SD) platelet (PLT) (×103/µL) with 78.66 (SD), 108.01 (DwWS), 153.47 (DwoWS) and 108.29 (non-SD); and aspartate aminotransferase (AST) (/µL) with 248.88 (SD), 170.83 (DwWS), 83.24 (DwoWS) and 102.99 (non-SD). For adult, WBC were 4.96 (SD), 6.44 (DwWS), 7.74 (DwoWS) and 3.61 (non-SD); HCT were 39.50 (SD), 39.00 (DwWS), 37.45 (DwoWS) and 41.68 (non-SD); PLT were 49.62 (SD), 96.60 (DwWS), 114.37 (DwoWS) and 71.13 (non-SD); and AST were 399.50 (SD), 141.01 (DwWS), 96.19 (DwoWS) and 118.13 (non-SD). These blood parameters could not differentiate between each dengue severity according to the WHO 2009 classification, SD, DwoWS, DwWS and non-SD, because the timing of blood drawing was not known and there was an overlapping confidence interval among the clinical classification. Hence, these pooled blood parameter values could not be used to guide clinicians in management and did not correlate with severity as in previous scientific literatures and guidelines.

Improving dengue diagnosis and case confirmation in children by combining rapid diagnostic tests, clinical, and laboratory variables

Background

Dengue is the most widely distributed arboviral disease in tropical and subtropical countries. Most suspected cases are diagnosed according to the clinical criteria, and early diagnosis is difficult. Moreover, in underdeveloped countries, several factors continue to challenge the diagnosis and surveillance of dengue cases. This study aimed to design a diagnostic algorithm using rapid diagnostic tests (RDTs), ELISA tests, and clinical and hematological variables to confirm dengue cases in febrile patients in Colombia.

Methods

Altogether, 505 samples were collected. Serum samples were evaluated by RDTs (IgM and IgG antibodies and NS1 antigen), capture IgM and IgG ELISAs, and endpoint hemi-nested RT-PCR assay (qualitative). We statistically analyzed the performance of individual tests to determine the most useful ones to confirm dengue cases accurately.

Results

Individual results for IgM, IgG, and NS1 RDTs yielded lower sensitivity and specificity values than the reference standard. High sensitivity and specificity were obtained after combining IgM and NS1 ELISA results (96.3% and 96.4%) and NS1 RDT plus IgM ELISA results (90.3% and 96.2%), respectively. Adjusted odds ratios (aORs) were calculated for clinical variables and laboratory tests to differentiate dengue from other febrile illnesses (OFI). This approach showed that myalgia, abdominal tenderness, and platelet count were identified with higher sensitivity to confirm dengue cases. IgM RDT and NS1 RDT differentiated dengue cases from OFI. A positive IgM RDT or a positive NS1 RDT combined with specific signs or symptoms confirmed 81.6% of dengue cases. A combination of clinical findings and a positive NS1 RDT or positive ELISA IgM confirmed 90.6% of the cases.

Conclusion

Our findings showed that clinical diagnoses in pediatric population alone cannot confirm true dengue cases and needs to be complemented by laboratory diagnostic tests. We also demonstrate the usefulness of combining clinical criteria with RDTs, suggesting that their implementation with the IgM ELISA test improves dengue case confirmation.

Prognostic Indicators for the Early Prediction of Severe Dengue Infection: A Retrospective Study in a University Hospital in Thailand

This study aimed to develop simple diagnostic guidelines which would be useful for the early detection of severe dengue infections. Retrospective data of patients with dengue infection were reviewed. Patients with diagnosed dengue infection were categorized in line with the International Statistical Classification of Diseases (ICD-10): A90, dengue fever; A91, dengue hemorrhagic fever; and A910, dengue hemorrhagic fever with shock. A total of 302 dengue-infected patients were enrolled, of which 136 (45%) were male and 166 (55%) were female. Multivariate analysis was conducted to determine independent diagnostic predictors of severe dengue infection and to convert simple diagnostic guidelines into a scoring system for disease severity. Coefficients for significant predictors of disease severity generated by ordinal multivariable logistic regression analysis were transformed into item scores. The derived total scores ranged from 0 to 38.6. The cut-off score for predicting dengue severity was higher than 14, with an area under the receiver operating curve (AUROC) of 0.902. The predicted positive value (PPV) was 68.7% and the negative predictive value (NPV) was 94.1%. Our study demonstrates that several diagnostic parameters can be effectively combined into a simple score sheet with predictive value for the severity evaluation of dengue infection.

The Diagnosis of Dengue in Patients Presenting With Acute Febrile Illness Using Supervised Machine Learning and Impact of Seasonality

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 an early undifferentiated febrile illness. These models could be of clinical utility in supporting healthcare decision-making and provide passive surveillance across dengue endemic regions. Effects of seasonality and changing disease prevalence must however be taken into account-this is of significant importance given unpredictable effects of human-induced climate change and the impact on health.

Prognostic indicators associated with progresses of severe dengue

Background

Dengue usually progress abnormally, especially in the critical phase. The main causes of death were shock, severe bleeding and organ failure. The aim of our study was to evaluate prognostic indicators of severe dengue according to the phases of the disease progression.

Methods

A cross-sectional study was conducted from July to December 2017 at the National Hospital for Tropical Diseases and the Hospital for Tropical Diseases of Ho Chi Minh City. 326 patients, aged 6 years and over, including 99/326 patients with severe dengue and 227/326 patients with non-severe dengue, hospitalized in the first 3 days of illness, confirmed Dengue virus by the RT-PCR assay have been registered for the study. Clinical manifestations were monitored daily. The hematocrit, white blood cells, platelet, serum albumin, ALT, AST, bilirubin, prothrombin time (PT%, PTs), fibrinogen, aPTT, INR and creatinine were evaluated at two times: febrile phase and critical phase.

Results

Independent factors associated with severe dengue were identified on multivariate logistic regression models. During the first 3 days of the disease, the prognostic indicators were platelet count ≤ 100 G/L (OR = 2.2; 95%CI: 1.2–3.9), or serum albumin < 35 g/L (OR = 3.3; 95%CI: 1.8–6.1). From day 4–6, the indicator were AST > 400 U/L (OR = 3.0; 95%CI: 1.1–7.9), ALT > 400 U/L (OR = 6.6; 95%CI: 1.7–24.6), albumin < 35 g/L (OR = 3.0; 95%CI: 1.5–5.9), and bilirubin total >17 μmol/L (OR = 4.6; 95%CI: 2.0–10.4).

Conclusion

To predict the risk of patients with severe dengue, prognostic laboratory indicators should be indicated consistent with the progression of the disease. During the first 3 days of illness, prognostic indicators should be platelet count, or serum albumin. From the 4th - 6th day of illness, prognostic indicators should be AST, ALT, albumin, or bilirubin total.

Predictive markers for the early prognosis of dengue severity: A systematic review and meta-analysis

BACKGROUND

Predictive markers represent a solution for the proactive management of severe dengue. Despite the low mortality rate resulting from severe cases, dengue requires constant examination and round-the-clock nursing care due to the unpredictable progression of complications, posing a burden on clinical triage and material resources. Accordingly, identifying markers that allow for predicting disease prognosis from the initial diagnosis is needed. Given the improved pathogenesis understanding, myriad candidates have been proposed to be associated with severe dengue progression. Thus, we aim to review the relationship between the available biomarkers and severe dengue.

METHODOLOGY

We performed a systematic review and meta-analysis to compare the differences in host data collected within 72 hours of fever onset amongst the different disease severity levels. We searched nine bibliographic databases without restrictive criteria of language and publication date. We assessed risk of bias and graded robustness of evidence using NHLBI quality assessments and GRADE, respectively. This study protocol is registered in PROSPERO (CRD42018104495).

PRINCIPAL FINDINGS

Of 4000 records found, 40 studies for qualitative synthesis, 19 for meta-analysis. We identified 108 host and viral markers collected within 72 hours of fever onset from 6160 laboratory-confirmed dengue cases, including hematopoietic parameters, biochemical substances, clinical symptoms, immune mediators, viral particles, and host genes. Overall, inconsistent case classifications explained substantial heterogeneity, and meta-analyses lacked statistical power. Still, moderate-certainty evidence indicated significantly lower platelet counts (SMD -0.65, 95% CI -0.97 to -0.32) and higher AST levels (SMD 0.87, 95% CI 0.36 to 1.38) in severe cases when compared to non-severe dengue during this time window.

CONCLUSION

The findings suggest that alterations of platelet count and AST level-in the first 72 hours of fever onset-are independent markers predicting the development of severe dengue.

Clinical signs and symptoms associated with WHO severe dengue classification: a systematic review and meta-analysis

The World Health Organization (WHO) introduced the new dengue classification in 2009. We aimed to assess the association of clinical signs and symptoms with WHO severe dengue classification in clinical practice. A systematic literature search was performed using the databases of PubMed, Embase, and Scopus between 2009 and 2018 according to PRISMA guideline. Meta-analysis was performed with the RevMan software. A random or fixed-effect model was applied to pool odds ratios and 95% confidence intervals of important signs and symptoms across studies. Thirty nine articles from 1790 records were included in this review. In our meta-analysis, signs and symptoms associated with higher risk of severe dengue were comorbidity, vomiting, persistent vomiting, abdominal pain or tenderness, pleural effusion, ascites, epistaxis, gum bleeding, GI bleeding, skin bleeding, lethargy or restlessness, hepatomegaly (>2 cm), increased HCT with decreased platelets, shock, dyspnea, impaired consciousness, thrombocytopenia, elevated AST and ALT, gall bladder wall thickening and secondary infection. This review shows new factors comorbidity, epistaxis, GI and skin bleeding, dyspnea, gall bladder wall thickening and secondary infection may be useful to refine the 2009 classification to triage severe dengue patients.

Development of a bedside score to predict dengue severity

Background

In 2017, New Caledonia experienced an outbreak of severe dengue causing high hospital burden (4379 cases, 416 hospital admissions, 15 deaths). We decided to build a local operational model predictive of dengue severity, which was needed to ease the healthcare circuit.

Methods

We retrospectively analyzed clinical and biological parameters associated with severe dengue in the cohort of patients hospitalized at the Territorial Hospital between January and July 2017 with confirmed dengue, in order to elaborate a comprehensive patient’s score. Patients were compared in univariate and multivariate analyses. Predictive models for severity were built using a descending step-wise method.

Results

Out of 383 included patients, 130 (34%) developed severe dengue and 13 (3.4%) died. Major risk factors identified in univariate analysis were: age, comorbidities, presence of at least one alert sign, platelets count < 30 × 10⁹/L, prothrombin time < 60%, AST and/or ALT > 10 N, and previous dengue infection. Severity was not influenced by the infecting dengue serotype nor by previous Zika infection.

Two models to predict dengue severity were built according to sex. Best models for females and males had respectively a median Area Under the Curve = 0.80 and 0.88, a sensitivity = 84.5 and 84.5%, a specificity = 78.6 and 95.5%, a positive predictive value = 63.3 and 92.9%, a negative predictive value = 92.8 and 91.3%. Models were secondarily validated on 130 patients hospitalized for dengue in 2018.

Conclusion

We built robust and efficient models to calculate a bedside score able to predict dengue severity in our setting. We propose the spreadsheet for dengue severity score calculations to health practitioners facing dengue outbreaks of enhanced severity in order to improve patients’ medical management and hospitalization flow.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12879-021-06146-z.

Electrolyte Imbalance at Admission Does Not Predict the Length of Stay or Mortality in Dengue-Infected Patients

Background

A pattern of both clinical and biochemical abnormalities is associated with dengue virus infection (DVI). Among the various DVI-related biochemical defects, electrolyte imbalance is one that can alter the morbidity and mortality among patients. However, there is a dearth of evidence to assess the relationship between electrolyte imbalance and the length of stay or mortality in dengue-infected patients in Pakistan. In the current study, we aimed to investigate the association between electrolyte imbalance at the time of admission and the length of stay and mortality among dengue-infected patients.

Methods

We conducted a retrospective study at a large tertiary care hospital from November 2018 to November 2019. All patients with known chronic diseases and coinfections or those who were taking diuretics therapies or angiotensin-converting enzyme inhibitors were excluded. Our main exposure of interest was electrolytes imbalance and the outcome measure was the length of stay and mortality.

Results

A total of 1,008 dengue patients were enrolled with a mean length of stay of 2.56 days. Around 29.3% had hyponatremia and 23.2% had hypokalemia at the time of admission, and 21.9% of patients had a stay beyond three days. In multivariable analysis, hyponatremia [adjusted odds ratios (aOR) = 1.29; 95% confidence interval (CI): 0.59-2.84] and hypokalemia (aOR = 2.36; 95% CI: 0.91-6.10) were not found to be associated with the length of stay. However, patients with high troponin levels at admission had a prolonged stay beyond three days (aOR = 5.74; 95% CI: 2.34-14.11). There was a statistically significant association of creatinine levels (aOR = 14.74; 95% CI: 4.19-15.85) and diabetes mellitus (DM) (aOR = 4.36; 95% CI: 1.21-15.74) with mortality after controlling for potential confounders.

Conclusion

Electrolyte imbalance at admission is not a predictor of length of stay or fatalities in the hospital among patients with DVI. However, troponin levels at admission can increase hospitalization days whereas DM and renal injury have been found to worsen mortality rates.

Implementation of a Multiplex rRT-PCR for Zika, Chikungunya, and Dengue Viruses: Improving Arboviral Detection in an Endemic Region

Arboviral diagnosis has been complicated throughout the tropical and subtropical Americas by the recent co-circulation of Zika virus (ZIKV), chikungunya virus (CHIKV), and dengue virus (DENV). The aim of this study was to implement a multiplex real-time RT-PCR (rRT-PCR) for ZIKV, CHIKV, and DENV in Paraguay to test patients who were clinically suspected of having dengue. We tested 110 sera from patients who presented to the Hospital de Clínicas in 2016 and had testing for DENV nonstructural protein 1 (NS1; 40 positive and 70 negative). Using a composite reference standard, we confirmed 51 dengue cases (46.4%): 38/40 NS1 positive and 13/70 NS1 negative. Chikungunya virus and ZIKV were detected in one sample each, both were DENV NS1 negative. The NS1 test demonstrated good agreement with rRT-PCR for DENV. However, multiplex rRT-PCR identified a subset of dengue cases and additional arboviral infections that would not be detected if NS1 assays are relied upon for diagnosis.

Antibody-Dependent Enhancement of Severe Disease Is Mediated by Serum Viral Load in Pediatric Dengue Virus Infections

BACKGROUND

Low preexisting anti-dengue virus (DENV) antibody levels are associated with elevated disease severity. While antibody-dependent enhancement of dengue is thought to be driven by viral load, this has not been conclusively shown. We evaluated the association between preinfection anti-DENV antibody titers, viral load, and disease severity among 133 dengue cases in a Nicaraguan pediatric cohort study.

METHODS

Viral load was quantified in acute-phase serum by real-time reverse transcription polymerase chain reaction and analyzed in relation to preinfection antibody titer (measured by inhibition enzyme-linked immunosorbent assay) and dengue severity, categorized using 3 definitions.

RESULTS

Higher viral load was significantly associated with dengue severity; for each increase of 1.0 log10 copies/mL, the odds of severe dengue increased approximately 50%, regardless of severity definition. Viral load at presentation and the odds of severe disease were highest among patients with low to intermediate preinfection antibody titers and lowest among those with the highest antibody titers. We showed the effect of preinfection antibody titer on disease severity was mediated by viral load for each of 3 dengue severity outcomes.

CONCLUSIONS

This study demonstrates the association between preinfection anti-DENV antibody titer, serum viral load, and disease severity, and provides evidence for the mechanism of antibody-dependent enhancement in dengue cases.

Plasma cell-free DNA: a potential biomarker for early prediction of severe dengue

Background

Considerable progress has been made in dengue management, however the lack of appropriate predictors of severity has led to huge number of unwanted admissions mostly decided on the grounds of warning signs. Apoptosis related mediators, among others, are known to correlate with severe dengue (SD) although no predictive validity is established. The objective of this study was to investigate the association of plasma cell-free DNA (cfDNA) with SD, and evaluate its prognostic value in SD prediction at acute phase.

Methods

This was a hospital-based prospective cohort study conducted in Vietnam. All the recruited patients were required to be admitted to the hospital and were strictly monitored for various laboratory and clinical parameters (including progression to SD) until discharged. Plasma samples collected during acute phase (6–48 h before defervescence) were used to estimate the level of cfDNA.

Results

Of the 61 dengue patients, SD patients (n = 8) developed shock syndrome in 4.8 days (95% CI 3.7–5.4) after the fever onset. Plasma cfDNA levels before the defervescence of SD patients were significantly higher than the non-SD group (p = 0.0493). From the receiver operating characteristic (ROC) curve analysis, a cut-off of > 36.9 ng/mL was able to predict SD with a good sensitivity (87.5%), specificity (54.7%), and area under the curve (AUC) (0.72, 95% CI 0.55–0.88; p = 0.0493).

Conclusions

Taken together, these findings suggest that cfDNA could serve as a potential prognostic biomarker of SD. Studies with cfDNA kinetics and its combination with other biomarkers and clinical parameters would further improve the diagnostic ability for SD.

Electronic supplementary material

The online version of this article (10.1186/s12941-019-0309-x) contains supplementary material, which is available to authorized users.

Burden of dengue among febrile patients at the time of chikungunya introduction in Piedecuesta, Colombia

OBJECTIVE

To estimate the age-specific incidence of symptomatic dengue and chikungunya in Colombia.

METHOD

A passive facility-based fever surveillance study was conducted among individuals with undifferentiated fever. Confirmatory diagnostics included serological and molecular tests in paired samples, and surveillance's underreporting was assessed using capture-recapture methods.

RESULTS

Of 839 febrile participants 686 completed the study. There were 33.2% (295/839) dengue infections (51% primary infections), and 35.9% (191/532) of negative dengue cases there were chikungunya cases. On average, dengue cases were younger (median = 18 years) than chikungunya cases (median = 25 years). Thrombocytopaenia and abdominal pain were the main dengue predictors, while presence of rash was the main predictor for chikungunya diagnosis. Underreporting of dengue was 31%; the estimated expansion factors indicate an underreporting rate of dengue cases of threefold for all cases and of almost sixfold for inpatients.

CONCLUSIONS

These findings highlight the ongoing coexistence of both arboviruses, a distinct clinical profile of each condition in the study area that could be used by clinicians to generate a differential diagnosis, and the presence of underreporting, mostly among hospitalised cases.

Use of structural equation models to predict dengue illness phenotype

Background

Early recognition of dengue, particularly patients at risk for plasma leakage, is important to clinical management. The objective of this study was to build predictive models for dengue, dengue hemorrhagic fever (DHF), and dengue shock syndrome (DSS) using structural equation modelling (SEM), a statistical method that evaluates mechanistic pathways.

Methods/Findings

We performed SEM using data from 257 Thai children enrolled within 72 h of febrile illness onset, 156 with dengue and 101 with non-dengue febrile illnesses. Models for dengue, DHF, and DSS were developed based on data obtained three and one day(s) prior to fever resolution (fever days -3 and -1, respectively). Models were validated using data from 897 subjects who were not used for model development. Predictors for dengue and DSS included age, tourniquet test, aspartate aminotransferase, and white blood cell, % lymphocytes, and platelet counts. Predictors for DHF included age, aspartate aminotransferase, hematocrit, tourniquet test, and white blood cell and platelet counts. The models showed good predictive performances in the validation set, with area under the receiver operating characteristic curves (AUC) at fever day -3 of 0.84, 0.67, and 0.70 for prediction of dengue, DHF, and DSS, respectively. Predictive performance was comparable using data based on the timing relative to enrollment or illness onset, and improved closer to the critical phase (AUC 0.73 to 0.94, 0.61 to 0.93, and 0.70 to 0.96 for dengue, DHF, and DSS, respectively).

Conclusions

Predictive models developed using SEM have potential use in guiding clinical management of suspected dengue prior to the critical phase of illness.

Dengue virus infection is one of the most critical public health issues, particularly in tropical and subtropical regions. This study developed statistical predictive models using the data obtained from 257 Thai children for dengue, dengue hemorrhagic fever, and dengue shock syndrome using structural equation modelling (SEM). We performed SEM based on clinical and laboratory factors on three and one day(s) prior to fever resolution. Our SEM models showed that age, tourniquet test, aspartate aminotransferase, and white blood cell, % lymphocytes, and platelet counts on three days prior to fever resolution were important risk factors for dengue and dengue hemorrhagic fever. Age, aspartate aminotransferase, hematocrit, tourniquet test, and white blood cell and platelet counts were important risk factors for dengue shock syndrome. Our predictive models showed good performances in the validation subjects (n = 897) who were not used for SEM, and thus we concluded that our predictive models can be practically used to guide clinical management of suspected dengue patients. Our study also showed that SEM can be used to predict the developments or severities of other illnesses.

Salivary Detection of Dengue Virus NS1 Protein with a Label-Free Immunosensor for Early Dengue Diagnosis

Dengue virus (DENV) is a highly pathogenic, arthropod-borne virus transmitted between people by Aedes mosquitoes. Despite efforts to prevent global spread, the potential for DENV epidemics is increasing world-wide. Annually, 3.6 billion people are at risk of infection. With no licensed vaccine, early diagnosis of dengue infection is critical for clinical management and patient survival. Detection of DENV non-structural protein 1 (NS1) is a clinically accepted biomarker for the early detection of DENV infection. Unfortunately, virtually all of the laboratory and commercial DENV NS1 diagnostic methods require a blood draw for sample analysis, limiting point-of-care diagnostics and decreases patient willingness. Alternatively, NS1 in human saliva has been identified for the potential early diagnosis of DENV infection. The collection of saliva is simple, non-invasive, painless, and inexpensive, even by minimally trained personnel. In this study, we present a label-free chemiresistive immunosensor for the detection of the DENV NS1 protein utilizing a network of single-walled carbon nanotubes functionalized with anti-dengue NS1 monoclonal antibodies. NS1 was successfully detected in adulterated artificial human saliva over the range of clinically relevant concentrations with high sensitivity and selectivity. It has potential application in clinical diagnosis and the ease of collection allows for self-testing, even within the home.

A Blood RNA Signature Detecting Severe Disease in Young Dengue Patients at Hospital Arrival

Background

Early detection of severe dengue can improve patient care and survival. To date, no reliable single-gene biomarker exists. We hypothesized that robust multigene signatures exist.

Methods

We performed a prospective study on Cambodian dengue patients aged 4 to 22 years. Peripheral blood mononuclear cells (PBMCs) were obtained at hospital admission. We analyzed 42 transcriptomic profiles of patients with secondary dengue infected with dengue serotype 1. Our novel signature discovery approach controls the number of included genes and captures nonlinear relationships between transcript concentrations and severity. We evaluated the signature on secondary cases infected with different serotypes using 2 datasets: 22 PBMC samples from additional patients in our cohort and 32 whole blood samples from an independent cohort.

Results

We identified an 18-gene signature for detecting severe dengue in patients with secondary infection upon hospital admission with a sensitivity of 0.93 (95% confidence interval [CI], .82-.98), specificity of 0.67 (95% CI, .53-.80), and area under the receiver operating characteristic curve (AUC) of 0.86 (95% CI, .75-.97). At validation, the signature had empirical AUCs of 0.85 (95% CI, .69-1.00) and 0.83 (95% CI, .68-.98) for the PBMCs and whole blood datasets, respectively.

Conclusions

The signature could detect severe dengue in secondary-infected patients upon hospital admission. Its genes offer new insights into the pathogenesis of severe dengue.

Clinical and Laboratory Profile of Zika and Dengue Infected Patients: Lessons Learned From the Co-circulation of Dengue, Zika and Chikungunya in Brazil

Background: The current triple epidemic caused by dengue, zika and chikungunya constitutes a serious health problem in Brazil. The aim of this study was to investigate acute samples (up to the 7 days of symptoms) from patients presenting acute fever syndrome suspected as arboviral infection and characterize the clinical and laboratorial profile during the co-circulation of dengue, zika and chikungunya in Campo Grande, Mato Grosso do Sul (MS), midwest region of Brazil. Methods: All suspected cases (n=134) were tested by using serological and molecular diagnostic tests including DENV, ZIKV and CHIKV RT-PCR, Dengue nonstructural protein 1 (NS1) antigen capture ELISA, anti- DENV IgM ELISA and anti-CHIKV IgM ELISA. In addition, clinical, hematological and biochemical parameters of infected patients were analyzed. Results: It was observed that 79.1% of the blood samples were confirmed for ZIKV and/or DENV infection Of those, 38.0% patients were DENV monoinfected, 26.8% were ZIKV monoinfected and 13.4% were DENV/ZIKV co-infected. Seven patients presented Chikungunya IgM antibodies indicating a previous CHIKV infection. Common symptoms included fever, rash, arthralgia, myalgia, prostration, headache and conjunctivitis. Statistical analysis showed that pruritus and edema were associated with ZIKV infection while prostration and vomiting were more associated with dengue. Additionally, total protein and ALT levels were significantly different in DENV patients compared to ZIKV ones. Some DENV infected patients as well as co-infected needed hospitalization and venous hydration. Otherwise, most ZIKV infected patients presented mild clinical course. Among the pregnant women studied (n=11), three were ZIKV monoinfected while four were DENV monoinfected and two were DENV-1/ZIKV coinfected. In general, normal birth outcomes were observed except for the death due to respiratory insufficiency of one baby born to a mother coinfected with DENV-1/ZIKV. Conclusions: Herein, we provide evidence of the co-circulation of DENV, ZIKV and CHIKV infections in the Campo Grande, MS, Brazil, with a high frequency of DENV-1/ZIKV coinfection. Laboratorial diagnosis poses a challenge where those arboviruses are endemic and differential diagnosis proved to imperative for cases characterization. The knowledge about disease severity during arbovirus coinfections is still scarce and there are several issues emphasizing the importance of adequate management of patients at risk areas.

Dengue Antiviral Development: A Continuing Journey

Dengue fever is a leading cause of illness and mortality in the tropics and subtropics. There are no therapeutics currently available and a recently approved vaccine is not very efficacious demanding an urgent need to develop an effective antiviral. The path to successful dengue drug development depends on availability of relevant preclinical testing models and better understanding of dengue pathogenesis. In recent years, efforts to develop dengue therapeutics have focused on both repurposing approved drugs as well as discovery of new chemical entities that act via virus or host targeted mechanisms. Here, we discuss the various innovative approaches, their outcome, and the lessons gleaned from the development efforts.

Dengue Virus Serotypes 1 and 2 Responsible for Major Dengue Outbreaks in Nepal: Clinical, Laboratory, and Epidemiological Features

Dengue virus (DENV) is expanding toward previously nonendemic areas. DENV has recently been introduced in Nepal with limited information. We report the clinical features and serotype distribution of DENV in Nepal during the 2010 outbreaks. A total of 1,215 clinical dengue cases at two major hospitals of central and western Nepal were investigated. Demographic, clinical, and laboratory parameters were recorded. Serum specimens were tested for DENV by IgM/IgG enzyme-linked immunosorbent assays (ELISAs) and reverse transcription polymerase chain reaction (RT-PCR). We confirmed DENV infection in 403 (33%) patients from 12 districts with an estimated case fatality rate of 1.5%. DENV infection was more common in adults (87%) and urban settings (74%). We detected all four serotypes but DENV-1 and -2 were mainly responsible for major outbreaks (92%). Overall, 60% of all DENV infections were secondary and 17% were severe dengue; both being more frequent among the DENV-2 infections. Rash, bleeding, abdominal pain, hepatomegaly, elevated liver enzymes, and thrombocytopenia were significantly more common in severe dengue compared with nonsevere infections. We also confirmed the expansion of dengue to hill urban areas (DENV-1 and -2), including the capital Kathmandu (altitude, 1,300 m) though > 90% cases were from southern plains. Differential clinical and laboratory features probably help in clinical decisions. Multiple serotypes circulation and elevated secondary infections pose potential risk of severe outbreaks and deaths in the future. Therefore, a country with recent dengue introduction, like Nepal, urgently requires a systematic surveillance and appropriate control measures in place to respond to any disastrous outbreaks.

A lethal model of disseminated dengue virus type 1 infection in AG129 mice

The mosquito-borne disease dengue is caused by four serologically and genetically related flaviviruses termed DENV-1 to DENV-4. Dengue is a global public health concern, with both the geographical range and burden of disease increasing rapidly. Clinically, dengue ranges from a relatively mild self-limiting illness to a severe life-threatening and sometimes fatal disease. Infection with one DENV serotype produces life-long homotypic immunity, but incomplete and short-term heterotypic protection. The development of small-animal models that recapitulate the characteristics of the disseminated disease seen clinically has been difficult, slowing the development of vaccines and therapeutics. The AG129 mouse (deficient in interferon alpha/beta and gamma receptor signalling) has proven to be valuable for this purpose, with the development of models of disseminated DENV-2,-3 and -4 disease. Recently, a DENV-1 AG129 model was described, but it requires antibody-dependent enhancement (ADE) to produce lethality. Here we describe a new AG129 model utilizing a non-mouse-adapted DENV-1 strain, West Pacific 74, that does not require ADE to induce lethal disease. Following high-titre intraperitoneal challenge, animals experience a virus infection with dissemination to multiple visceral tissues, including the liver, spleen and intestine. The animals also become thrombocytopenic, but vascular leakage is less prominent than in AG129 models with other DENV serotypes. Taken together, our studies demonstrate that this model is an important addition to dengue research, particularly for understanding the pathological basis of the disease between DENV serotypes and allowing the full spectrum of activity to test comparisons for putative vaccines and antivirals.