Dengue severity prediction models are usually developed using hospitalized patient data, but triage and hospital admission are mainly evaluated in outpatient settings. This study developed models using clinical and laboratory data from patients in outpatient settings during the febrile phase. Data from two cohort studies in Vietnam and Thailand were used to develop and validate six models: logistic regression with warning signs, Lasso-selected logistic regression, random forest, extreme gradient boosted classification, support vector machine, and artificial neural network. Models predicted dengue shock syndrome (DSS) as the primary endpoint and moderate plasma leakage and/or DSS as the secondary endpoint. We assessed model performance, discrimination, and calibration, using sensitivity, specificity, accuracy, Brier score, AUROC, CITL, calibration slope, calibration plots, and decision curve analysis. The optimal model was the Lasso-selected logistic regression for predicting DSS and the combined endpoint of moderate plasma leakage and/or DSS (Brier score: 0.044 [95% CI 0.043, 0.044] and 0.104 [95% CI 0.104, 0.105]; AUROC: 0.789 [95% CI 0.787, 0.791] and 0.741 [95% CI 0.740, 0.742]). We identified hematocrit, platelet count, lymphocyte count, and aspartate aminotransferase as predictors for DSS, and abdominal pain or tenderness, vomiting, mucosal bleeding, white blood cell count, lymphocyte count, platelet count, aspartate aminotransferase, and serum albumin as predictors for the secondary endpoint. Logistic regression and machine learning models using clinical and laboratory data during the febrile phase can support early prediction of severe disease in outpatient settings. Integrating risk prediction models into a decision support system could improve triage and optimize healthcare and resource allocation in endemic and resource-limited areas.

BACKGROUND:This study aimed to compare the predictive performance of 3 statistical models-logistic regression, classification tree, and structural equation model (SEM)-in predicting severe dengue illness. METHODS:We adopted a modified classification of dengue illness severity based on the World Health Organization's 1997 guideline. We constructed predictive models using demographic factors and laboratory indicators on the day of fever occurrence, with data from 2 hospital cohorts in Thailand (257 Thai children). Different predictive models for each category of severe dengue illness were developed employing logistic regression, classification tree, and SEM. The model's discrimination abilties were analyzed with external validation data sets from 55 and 700 patients not used in model development. RESULTS:From external validation based on predictors on the day of presentation to the hospital, the area under the receiver operating characteristic curve was from 0.65 to 0.84 for the regression models from 0.73 to 0.85 for SEMs. Classification tree models showed good results of sensitivity (0.95 to 0.99) but poor specificity (0.10 to 0.44). CONCLUSIONS:Our study showed that SEM is comparable to logistic regression or classification tree, which was widely used for predicting severe forms of dengue.

Background:Dengue has a wide spectrum of manifestations, from an asymptomatic condition to dengue shock syndrome. Extensive plasma leakage, severe bleeding, or both, could lead to dengue shock syndrome, a common cause of death in dengue-infected patients. Thrombocytopenia is a common laboratory finding in dengue, which correlates with the disease severity and rapidly resolves during the recovery phase. Therefore, refractory thrombocytopenia is rare in patients with dengue. Rhombencephalitis is an inflammatory disease affecting the hindbrain, rarely associated with dengue. We report the second case of dengue-associated rhombencephalitis, wherein the patient developed dengue shock syndrome and severe bleeding associated with refractory thrombocytopenia.Case report:A 47-year-old Thai female with secondary dengue serotype 1 infection developed dengue shock syndrome with rhombencephalitis, manifested as altered sensorium and status epilepticus in the critical phase. Cerebrospinal fluid analysis showed pleocytosis with predominantly mononuclear cells and high protein levels. Magnetic resonance imaging of the brain showed multifocal brain signal abnormalities involving the medulla oblongata, pons, midbrain, bilateral hippocampi, thalami, posterior limb of internal capsules, external capsules, and deep hemispheric white matter. The patient had partial neurological recovery following rhombencephalitis for one month. During the recovery phase, severe bleeding with refractory thrombocytopenia and acute kidney injury were observed. Methylprednisolone with eltrombopag was administered, which resulted in an increased the platelet count, cessation of bleeding and recovery of kidney function within 4 days.Conclusions:Dengue is a potential cause of rhombencephalitis. Dengue-associated rhombencephalitis develops during the critical phase, with only partial neurological recovery. However, severe bleeding and refractory thrombocytopenia were also observed during the recovery phase. Methylprednisolone with a thrombopoietin receptor agonist could be an effective treatment for increasing platelet count and stopping bleeding in dengue.

Dengue is one of the most common mosquito-borne viral diseases affecting both children and adults worldwide, particularly in the countries of Asia and Latin America [1]. An estimated 100–400 million infections occur annually with 50,000 deaths per year [1]. Most symptomatic patients with dengue present with mild non-specifi c symptoms that do not require hospitalization [1-3]. Patients with mild to moderate dengue severity often have clinical manifestations of poor appetite, nausea, vomiting, abdominal pain, and dehydration [2,3]. A number of patients with mild to moderate dengue severity need supportive and symptomatic treatment in the hospital, which mainly comprises intravenous fl uid therapy [1-4]. Severe or complicated cases require hospitalization according to the disease because of plasma leakage [Dengue Hemorrhagic Fever (DHF)/Dengue Shock Syndrome (DSS)] and bleeding [1-4]. Close monitoring and hospitalization are required in patients with dengue who have a risk of death based on characteristics including infancy; elderly age; pregnancy; obesity; and the presence of bleeding, prolonged shock, co-infections, and co-morbidities [2-4]. According to the dengue death review in Thailand, there are pitfalls in dengue case management, which lead to prolonged shock and subsequent multiple organs failure and death. The latest review of 140 of 307 dengue deaths (45.6%) was between 2017 and 2019. The major causes of death were fl uid overload (32%), massive bleeding (30%), prolonged shock (22%) and unusual presentations (16%) (Unpublished data). However, majority of the expired patients had multiple causes of death as described. These causes of death could be explained as follows:

Delayed plasma leakage recognition could lead to improper fluid administration resulting in dengue shock syndrome, subsequently, multi-organ failure, and death. This prospective observational study was conducted in Bangkok, Thailand, between March 2018 and February 2020 to determine predictors of plasma leakage and develop a plasma leakage predictive score among dengue patients aged ≥15 years. Of 667 confirmed dengue patients, 318 (47.7%) developed plasma leakage, and 349 (52.3%) had no plasma leakage. Multivariate analysis showed three independent factors associated with plasma leakage, including body mass index ≥25.0 kg/m2 (odds ratio [OR] = 1.784; 95% confidence interval [CI] = 1.040–3.057; P = 0.035), platelet count <100,000/mm3 on fever days 3 to 4 (OR = 2.151; 95% CI = 1.269–3.647; P = 0.004), and aspartate aminotransferase or alanine aminotransferase ≥100 U/l on fever days 3 to 4 (OR = 2.189; 95% CI = 1.231–3.891; P = 0.008). Because these three parameters had evidence of equality, each independent factor was weighted to give a score of 1 with a total plasma-leak score of 3. Higher scores were associated with increased plasma leakage occurrence, with ORs of 2.017 (95% CI = 1.052–3.869; P = 0.035) for score 1, 6.158 (95% CI = 2.914–13.015; P <0.001) for score 2, and 6.300 (95% CI = 2.419–16.407; P <0.001) for score 3. The area under the receiver operating characteristics curves for predicting plasma leakage was good (0.677 [95% CI = 0.616–0.739]). Patients with a plasma-leak score ≥1 had high sensitivity (88.8%), and those with a plasma-leak score of 3 had high specificity (93.4%) for plasma leakage occurrence. This simple and easily accessible clinical score might help physicians provide early and timely appropriate clinical dengue management in endemic areas.

Without an effective vaccine or specific treatment for dengue, the ability to accurately predict early progression to severe disease relies on patient triage and clinical management. Previous systematic reviews and meta-analyses have found significant heterogeneity in predictors associated with severe disease, due to large variations of these factors during the time-course of the illness. Our study aimed to identify the factors associated with progression to severe dengue disease, which are detectable specifically in the febrile phase. We conducted a systematic review and meta-analysis to identify predictors associated with disease progression identifiable during the febrile phase. Eight medical databases were searched for studies published from January 1997 to February 2018. Relevant studies were selected and assessed by three reviewers with discrepancies resolved by consensus. Meta-analyses were performed using random-effects models to estimate pooled effect sizes. Heterogeneity and publication bias were also assessed. Of 5,293 studies identified, 98 were included in the meta-analyses. The presence of pre-existing comorbidities (diabetes mellitus, hypertension and renal disease) were associated with severe dengue. Vomiting, abdominal pain and tenderness, spontaneous and mucosal bleeding, and clinical fluid accumulation were clinical features associated with progression to severe disease. During the first four days of illness, platelet count, and serum albumin were lower among individuals who progressed to severe disease whilst aminotransferase levels were higher. Dengue virus serotype 2 and secondary infection were also associated with severe disease. This analysis supports the monitoring of the warning signs described in the 2009 WHO guidelines. In addition, testing for infecting serotype and monitoring platelet count, serum albumin, AST and ALT during the febrile phase of illness would improve the early prediction of severe dengue. Funding Statement: The authors state: "There was no funding source for this study." SS acknowledges funding from the Collaborative Project to Increase Production of Rural Doctor and Royal Thai Government Scholarship. ID ackowledges research funding from an Imperial College Junior Research Fellowship, a Wellcome Trust Sir Henry Dale Fellowship, Janssen Pharmaceutica and joint Centre funding from the UK Medical Research Council and Department for International Development. AH is a National Institute for Health Research (NIHR) Senior Investigator. She also acknowledges the support of the NIHR Health Protection Research Unit in Healthcare Associated Infections and Antimicrobial Resistance at Imperial College London in partnership with Public Health England (PHE), in collaboration with The Sanger Institute, the University of Cambridge Veterinary School and Imperial College Health Partners Declaration of Interests: The authors declare no competing interests. Ethics Approval Statement: We followed the protocol described in the Preferred Reporting Items for Systematic Reviews and Meta-analyses for Protocols (PRISMA-P) guidelines and the steps discussed in the guide to systematic review and meta-analysis of prognostic factor studies by Riley et al . Our protocol was registered with PROSPERO (CRD42018093363).

BACKGROUNDMajor histocompatibility complex class I chain-related (MIC) A and B (MICA and MICB) are polymorphic stress molecules recognized by natural killer cells. This study was performed to analyze MIC gene profiles in hospitalized Thai children with acute dengue illness.METHODSMIC allele profiles were determined in a discovery cohort of patients with dengue fever or dengue hemorrhagic fever (DHF) (n = 166) and controls (n = 149). A replication cohort of patients with dengue (n = 222) was used to confirm specific MICB associations with disease.RESULTSMICA*045 and MICB*004 associated with susceptibility to DHF in secondary dengue virus (DENV) infections (odds ratio [OR], 3.22; [95% confidence interval (CI), 1.18-8.84] and 1.99 [1.07-2.13], respectively), and MICB*002 with protection from DHF in secondary DENV infections (OR, 0.41; 95% CI, .21-.68). The protective effect of MICB*002 against secondary DHF was confirmed in the replication cohort (OR, 0.43; 95% CI, .22-.82) and was stronger when MICB*002 is present in individuals also carrying HLA-B*18, B*40, and B*44 alleles which form the B44 supertype of functionally related alleles (0.29, 95% CI, .14-.60).CONCLUSIONSGiven that MICB*002 is a low expresser of soluble proteins, these data indicate that surface expression of MICB*002 with B44 supertype alleles on DENV-infected cells confer a protective advantage in controlling DENV infection using natural killer cells.

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.

BackgroundFollicular helper T cells (TFH) are specialized CD4 T cells required for B-cell help and antibody production.MethodsGiven the postulated role of immune activation in dengue disease, we measured the expansion and activation of TFH in the circulation (peripheral TFH [pTFH]) collected from Thai children with laboratory-confirmed acute dengue virus (DENV) infection.ResultsWe found significant expansion and activation of pTFH subsets during acute infection with the highest frequencies of activated pTFH (PD1hi pTFH and PD1+CD38+ pTFH) detected during the critical phase of illness. Numbers of activated pTFH were higher in patients with secondary compared with primary infections and in patients with more severe disease. We also found a positive correlation between the frequencies of activated pTFH and the frequencies of plasmablasts.ConclusionsTo our knowledge, this is the first ex vivo analysis of pTFH activation during acute DENV infection. Overall, our study supports the model that pTFH contribute to disease evolution during the critical stage of illness.

A fundamental mystery for dengue and other infectious pathogens is how observed patterns of cases relate to actual chains of individual transmission events. These pathways are intimately tied to the mechanisms by which strains interact and compete across spatial scales. Phylogeographic methods have been used to characterize pathogen dispersal at global and regional scales but have yielded few insights into the local spatiotemporal structure of endemic transmission. Using geolocated genotype (800 cases) and serotype (17,291 cases) data, we show that in Bangkok, Thailand, 60% of dengue cases living <200 meters apart come from the same transmission chain, as opposed to 3% of cases separated by 1 to 5 kilometers. At distances <200 meters from a case (encompassing an average of 1300 people in Bangkok), the effective number of chains is 1.7. This number rises by a factor of 7 for each 10-fold increase in the population of the "enclosed" region. This trend is observed regardless of whether population density or area increases, though increases in density over 7000 people per square kilometer do not lead to additional chains. Within Thailand these chains quickly mix, and by the next dengue season viral lineages are no longer highly spatially structured within the country. In contrast, viral flow to neighboring countries is limited. These findings are consistent with local, density-dependent transmission and implicate densely populated communities as key sources of viral diversity, with home location the focal point of transmission. These findings have important implications for targeted vector control and active surveillance.

The global burden of dengue and its geographic distribution have increased over the past several decades. The introduction of dengue in new areas has often been accompanied by high case-fatality rates. Drawing on the experience in managing dengue cases at the Queen Sirikit National Institute of Child Health in Bangkok, Thailand, this article provides the authors' perspectives on key clinical lessons to improve dengue-related outcomes. Parallels between this clinical experience and outcomes reported in randomized controlled trials, results of efforts to disseminate practice recommendations, and suggestions for areas for further research are also discussed.

Long-term observational studies can provide valuable insights into overall dengue epidemiology. Here, we present analysis of dengue cases at a pediatric hospital in Bangkok, Thailand, during a 40-year period from 1973 to 2012. Data were analyzed from 25,715 hospitalized patients with laboratory-confirmed dengue virus (DENV) infection. Several long-term trends in dengue disease were identified including an increase in mean age of hospitalized cases from an average of 7–8 years, an increase after 1990 in the proportion of post-primary cases for DENV-1 and DENV-3, and a decrease in the proportion of dengue hemorrhagic fever and dengue shock syndrome cases in primary and post-primary cases over time. Exploratory mechanistic analysis of these observed trends considered changes in diagnostic methods, demography, force of infection, and Japanese encephalitis vaccination as possible explanations. Thailand is an important setting for studying DENV transmission as it has a "mature" dengue epidemiology with a strong surveillance system in place since the early 1970s. We characterized changes in dengue epidemiology over four decades, and possible impact of demographic and other changes in the human population. These results may inform other countries where similar changes in transmission and population demographics may now or may soon be occurring.

BackgroundHo Chi Minh City and Bangkok are highly dengue endemic. The extent to which disease patterns are attributable to local versus regional dynamics remains unclear. To address this gap we compared key transmission parameters across the locations.Methods and Principal FindingsWe used 2003-2009 age-stratified case data to inform catalytic transmission models. Further, we compared the spatial clustering of serotypes within each city. We found that annual case numbers were highly consistent across the two cities (correlation of 0.77, 95% CI: 0.74-0.79) as was the annual force of infection (correlation of 0.57, 95% CI: 0.46-0.68). Serotypes were less similar with serotype-specific correlations ranging from 0.65 for DENV1 to -0.14 for DENV4. Significant spatial clustering of serotypes was observed in HCMC at distances <500m, similar to previous observations from Bangkok.DiscussionsDengue dynamics are comparable across these two hubs. Low correlation in serotype distribution suggests that similar built environments, vector populations and climate, rather than viral flow drives these observations.

BACKGROUND:Early recognition and treatment of circulatory volume loss is essential in the clinical management of dengue viral infection. We hypothesized that a novel computational algorithm, originally developed for noninvasive monitoring of blood loss in combat casualties, could: (1) indicate the central volume status of children with dengue during the early stages of "shock"; and (2) track fluid resuscitation status.METHODS:Continuous noninvasive photoplethysmographic waveforms were collected over a 5-month period from three children of Thai ethnicity with clinical suspicion of dengue. Waveform data were processed by the algorithm to calculate each child's Compensatory Reserve Index, where 1 represents supine normovolemia and 0 represents the circulatory volume at which hemodynamic decompensation occurs. Values between 1 and 0 indicate the proportion of reserve remaining before hemodynamic decompensation.RESULTS:This case report describes a 7-year-old Thai boy, another 7-year-old Thai boy, and a 9-year-old Thai boy who exhibited signs and symptoms of dengue shock syndrome; all the children had secondary dengue virus infections, documented by serology and reverse transcriptase polymerase chain reaction. The three boys experienced substantial plasma leakage demonstrated by pleural effusion index >25, ascites, and >20 % hemoconcentration. They received fluid administered intravenously; one received a blood transfusion. All three boys showed a significantly low initial Compensatory Reserve Index (≥0.20), indicating a clinical diagnosis of "near shock". Following 5 days with fluid resuscitation treatment, their Compensatory Reserve Index increased towards "normovolemia" (that is, Compensatory Reserve Index >0.75).CONCLUSIONS:The results from these cases demonstrate a new variation in the diagnostic capability to manage patients with dengue shock syndrome. The findings shed new light on a method that can avoid possible adverse effects of shock by noninvasive measurement of a patient's compensatory reserve rather than standard vital signs or invasive diagnostic methods.

BACKGROUND:Human leukocyte antigen (HLA) supertypes are groups of functionally related alleles that present structurally similar antigens to the immune system.OBJECTIVES:To analyze HLA class I supertype associations with clinical outcome in hospitalized Thai children with acute dengue illness.METHODS:Seven hundred sixty-two patients and population-matched controls recruited predominantly in Bangkok were HLA-A and -B typed. HLA supertype frequencies were compared and tested for significant dengue disease associations using logistic regression analyses. Multivariable models were built by conducting forward stepwise selection procedures.RESULTS:In the final logistic regression model, the HLA-B44 supertype was protective against dengue hemorrhagic fever (DHF) in secondary infections (odds ratio [OR] = 0.46, 95% confidence interval [CI], .30-.72), while the HLA-A02 supertype (OR = 1.92, 95% CI, 1.30-2.83) and the HLA-A01/03 supertype (OR = 3.01, 95% CI, 1.01-8.92) were associated with susceptibility to secondary dengue fever. The B07 supertype was associated with susceptibility to secondary DHF in the univariate analysis (OR = 1.60, 95% CI, 1.05-2.46), whereas that was not retained in the final model.CONCLUSIONS:As the HLA-B44 supertype is predicted to target conserved epitopes in dengue, our results suggest that B44 supertype-restricted immune responses to highly conserved regions of the dengue proteome may protect against secondary DHF.

BACKGROUND:Infants born to dengue immune mothers acquire maternal antibodies to dengue. These antibodies, though initially protective, decline during the first year of life to levels thought to be disease enhancing, before reaching undetectable levels. Infants have long been studied to understand the interaction between infection and disease on an individual level. METHODS/FINDINGS:Considering infants (cases <1 year old) as a unique group, we analyzed serotype specific dengue case data from patients admitted to a pediatric hospital in Bangkok, Thailand. We show differences in the propensity of serotypes to cause disease in individuals with dengue antibodies (infants and post-primary cases) and in individuals without dengue antibodies (primary cases). The mean age of infant cases differed among serotypes, consistent with previously observed differential waning of maternal antibody titers by serotype. We show that trends over time in epidemiology of infant cases are consistent with those observed in the whole population, and therefore with trends in the force of infection. CONCLUSIONS/SIGNIFICANCE:Infants with dengue are informative about the interaction between antibody and the dengue serotypes, confirming that in this population DENV-2 and DENV-4 almost exclusively cause disease in the presence of dengue antibody despite infections occurring in others. We also observe differences between the serotypes in the mean age in infant cases, informative about the interaction between waning immunity and disease for the different serotypes in infants. In addition, we show that the mean age of infant cases over time is informative about transmission in the whole population. Therefore, ongoing surveillance for dengue in infants could provide useful insights into dengue epidemiology, particularly after the introduction of a dengue vaccine targeting adults and older children.