Development of a Prognostic Prediction Model to Determine Severe Dengue in Children

Advances in the Epidemiology, Pathogenesis, Diagnostic Methods, and Vaccine Development of Dengue Fever: A Comprehensive Review

Dengue fever (DF) is a common mosquito-borne viral infection caused by any of the four dengue virus (DENV) serotypes. In recent years, the global incidence of DF has risen rapidly, which has widely threatened the health of millions of people in the United States, Southeast Asia, and the Western Pacific. The challenges for the prevention and control of DENV infection have become increasingly severe. Over the years, advances in the area of DF research have been continuously updating. In this review, we provide an updated and more in-depth overview of dengue epidemiology and pathogenesis, along with recent progress in diagnostic approaches (including methods to address cross-reactivity with other flaviviruses) and an expanded discussion of current dengue vaccine development, such as CYD-TDV (Dengvaxia), TV003/TV005, and the new TAK-003. This comprehensive perspective aims to offer references for the prevention, clinical diagnosis, and control of the disease.

Role of interleukin-10 and interferon-β as predictive factors of severity in a paediatric population with dengue

The febrile illness caused by dengue is a global public health problem whose incidence is increasing. This infection can range from mild fever to severe illness with plasma leakage and shock; therefore, biomarkers of severity are urgently needed to elucidate the pathological mechanism of the disease. To explore the levels of interleukin (IL)-10 and interferon (IFN)-β in children with dengue to identify these proteins as biomarkers of severity. This study compared the serum levels of IL-10 and IFN-β in 208 Colombian paediatric patients with different degrees of severity of dengue virus infection. A total of three study groups (dengue without warning signs, dengue with warning signs, and severe dengue) were designated according to the World Health Organization classification system. Serotype type 2 was the most prevalent type, and the most frequently reported symptom was vomiting, followed by abdominal pain. Platelet values, aspartate transaminase and alanine transaminase levels and clotting times were the most altered laboratory parameters among the study groups and were more pathological in patients with severe dengue. In addition, IL-10 levels were significantly higher in those with severe dengue than in those with milder forms of infection (P < .05), and IFN-β levels were much lower in the group of patients with severe dengue than in the group with dengue without warning signs (P < .05). These results demonstrate differences in immune responses to dengue infections and suggest several molecular targets for the future development of biomarkers that can serve as diagnostic and prognostic tools for the severity of dengue disease.

Development of a Scoring Model to Predict Severe Dengue in Children at Admission to Emergency Care: An Observational Study

OBJECTIVE

Dengue has emerged as the most widely spread mosquito-borne disease, hyperendemic in India. Although severe dengue occurs only in a small proportion of cases, delays in the recognition and management can result in significant morbidity and mortality. Risk stratification of children in the emergency care and identifying those at risk for worsening during hospital stay facilitates optimum utilization of health care resources. The objective of our study was to develop and validate a scoring model to predict the development of severe dengue in hospitalized children by identifying risk factors present in them at the time of admission to the emergency department.

METHODS

A retrospective study of consecutive children aged 1 month to 18 years admitted with serologically confirmed dengue from January 2019 through December 2021 was conducted. Analysis of clinical and laboratory parameters of children resulted in the development of a comprehensive predictive scoring model. This model was internally validated prospectively on 107 children presenting with nonsevere dengue to emergency care.

RESULTS

A total of 743 children with confirmed dengue were studied out of which 216 (29.1%) had severe dengue. Presence of third spacing (odds ratio [OR] 3.74, 95% confidence interval [CI] 1.088-7.42, P < 0.001), tender hepatomegaly (OR 1.62, 95% CI 1.04-2.52, P < 0.032), respiratory distress (OR 3.50, 95% CI 1.89-6.51, P < 0.001), and moderate (OR 3.51, 95% CI 1.82-6.74, P < 0.001) to severe (OR 4.76, 95% CI 2.59-8.76, P < 0.001) elevation of aspartate aminotransferase were independent risk factors found to be associated with development of severe dengue. A score ≥7 had a specificity of 87%, negative predictive value of 86%, and overall diagnostic accuracy of 78.5% for predicting severe dengue.

CONCLUSIONS

The dengue severity scoring model was found to have reasonable diagnostic accuracy in predicting severe disease prior to hospitalization. However, more studies are required to validate the score in different emergency care settings with varied pediatric populations.

Severe COVID-19 multisystem inflammatory syndrome versus severe dengue in children from Indonesia: a cross-sectional study

INTRODUCTION

Severe multisystem inflammatory syndrome in children (MIS-C) and severe dengue are challenging to identify during the COVID-19 pandemic in dengue-endemic areas. Fever, multiorgan involvement, and shock characterize both severe MIS-C and severe dengue. Distinguishing between the two diseases is beneficial in initiating proper management.

METHODS

Medical records of children < 18 years old who were hospitalized at Hasan Sadikin General Hospital's PICU between December 2020 and July 2022 with severe MIS-C or severe dengue were recorded. Differences were assessed using comparative and descriptive analyses.

RESULTS

Seventeen severe dengue patients and 4 severe MIS-C were included. The average age of severe MIS-C was 11.5 years (SD ± 2.9, 95% CI), and that of severe dengue patients was 6.2 years (SD ± 4.4, 95% CI) (p value = 0.034, 95%). Fever and abdominal pain were the most common symptoms in both groups (p = 0.471, 95% CI). Rash (p = 0.049) and nonpurulent conjunctivitis (p = 0.035) were two symptoms with significant differences. The highest platelet count (p-value = 0.006, 95% CI), AST (p-value = 0.026, 95% CI), and D-dimer level (p-value = 0.025, 95% CI) were significantly different between the two cohorts. Cardiac abnormalities were found in all (100%) severe MIS-C patients, but only one (5.9%) in severe dengue patients.

CONCLUSION

Age, rash, nonpurulent conjunctivitis, platelet count, AST and D-dimer level may distinguish severe MIS-C from severe dengue fever.

A cross-sectional study to assess the epidemiological situation and associated risk factors of dengue fever; knowledge, attitudes, and practices about dengue prevention in Khyber Pakhtunkhwa Province, Pakistan

Background

Dengue fever has been responsible for around 12 countrywide large outbreaks in Pakistan, resulting in 286,262 morbidities and 1,108 deaths. Khyber Pakhtunkhwa (KP) is the most recently impacted province. This study aimed to investigate the molecular, epidemiological, and potential elements that contribute to increasing dengue transmission patterns, and knowledge, attitude, and practice (KAP) toward dengue in KP province.

Method

This cross-sectional community-based study was conducted (June-December, 2021) in two phases. Phase I involved the epidemiological (n = 5,242) and molecular analysis of DENV in 500 randomly collected blood samples of the 2021 dengue outbreak in KP. Phase II focused on assessing dengue-KAP levels in healthy communities (n = 14,745, aged >18 years), adopting a cross-sectional clustered multistage sampling in eight districts (dengue-hotspot vs. non-hotspot) of KP. Chi-square tests and logistic regression analysis were applied.

Results

Peshawar district had the highest dengue cases (60.0%) associated with the predominant co-circulation of DENV-2 (45.8%) and DENV-3 (50.4%) serotypes. A rise in cases was reported in October (41.8%) followed by September (27.9%) and August (14.4%; p < 0.001). Males (63.7%, p < 0.001) and individuals aged 16–30 years (37.0%, p < 0.001) were highly affected. General workers (18.0%), families with a monthly income of 10,000–20,000 Pak rupees (50.5%), unmarried (71.0%), uneducated (31%), families with higher human density (>10 individuals per household), and those (29.0%) who faced power outages for more than 7/24 h were the most affected. Moreover, co-morbidities like renal failure and bronchial asthma were associated with disease severity. A community survey on KAP revealed that an average of 74, 60, and 43% of the participants demonstrated good knowledge, attitudes, and dengue preventive practices, respectively.

Conclusion

Multiple poor socioeconomic elements are influencing dengue fever transmission in the province. Higher KAP levels may explain the low frequency of dengue in non-hotspot districts. Our study emphasizes the need for effective and long-term public health education, strengthened vector surveillance, and expanded laboratory capacity for better diagnosis and management of dengue cases to better predict the burden and seasonality of disease in the country.

Outcomes among children and adults at risk of severe dengue in Sri Lanka: Opportunity for outpatient case management in countries with high disease burden

Background

Healthcare systems in dengue-endemic countries are often overburdened due to the high number of patients hospitalized according to dengue management guidelines. We systematically evaluated clinical outcomes in a large cohort of patients hospitalized with acute dengue to support triaging of patients to ambulatory versus inpatient management in the future.

Methods/Principal findings

From June 2017- December 2018, we conducted surveillance among children and adults with fever within the prior 7 days who were hospitalized at the largest tertiary-care (1,800 bed) hospital in the Southern Province, Sri Lanka. Patients who developed platelet count ≤100,000/μL (threshold for hospital admission in Sri Lanka) and who met at least two clinical criteria consistent with dengue were eligible for enrollment. We confirmed acute dengue by testing sera collected at enrollment for dengue NS1 antigen or IgM antibodies. We defined primary outcomes as per the 1997 and 2009 World Health Organization (WHO) classification criteria: dengue hemorrhagic fever (DHF; WHO 1997), dengue shock syndrome (DSS; WHO 1997), and severe dengue (WHO 2009). Overall, 1064 patients were confirmed as having acute dengue: 318 (17.4%) by NS1 rapid antigen testing and 746 (40.7%) by IgM antibody testing. Of these 1064 patients, 994 (93.4%) were adults ≥18 years and 704 (66.2%) were male. The majority (56, 80%) of children and more than half of adults (544, 54.7%) developed DHF during hospitalization, while 6 (8.6%) children and 22 (2.2%) adults developed DSS. Overall, 10 (14.3%) children and 113 (11.4%) adults developed severe dengue. A total of 2 (0.2%) patients died during hospitalization.

Conclusions

One-half of patients hospitalized with acute dengue progressed to develop DHF and a very small number developed DSS or severe dengue. Developing an algorithm for triaging patients to ambulatory versus inpatient management should be the future goal to optimize utilization of healthcare resources in dengue-endemic countries.

In countries where dengue is prevalent, hospitals are often overwhelmed due to the high numbers of patient admissions during dengue epidemics. We studied 1064 children and adults hospitalized with acute dengue in Sri Lanka to determine the prevalence of severe disease outcomes to support the development of a system which can limit hospitalizations in the future. We found that only half of patients developed severe disease outcomes during hospitalization and only a small minority of patients developed life-threatening disease. For dengue-prevalent countries, developing systems to identify patients with acute dengue who can be managed without hospital admission should be a priority.

Clinical predictors of severe dengue: a systematic review and meta-analysis

Background

Severe dengue is a life-threatening complication; rapid identification of these cases, followed by adequate management is crucial to improve the clinical prognosis. Therefore, this study aimed to identify risk factors and predictors of severe dengue.

Methods

A literature search for studies reporting risk factors of severe dengue among individuals with dengue virus infection was conducted in PubMed, Scopus and Web of Science database from inception to December 31, 2020. Pooled odds ratios (ORs) for patients’ demographic characteristics, co-morbidities, and warning signs were estimated using an inverse variance heterogeneity model.

Results

We included 143 articles in the meta-analysis from a total of 13 090 articles retrieved from the literature search. The risk factors of severe dengue were: being a child [OR = 1.96; 95% confidence interval (CI): 1.22–3.13], secondary infection (OR = 3.23; 95% CI: 2.28–4.57), and patients with pre-existing diabetes (OR = 2.88; 95% CI: 1.72–4.81) and renal disease (OR = 4.54; 95% CI: 1.55–13.31). Warning signs strongly associated with severe disease were increased haematocrit with a concurrent decrease in platelet count (OR = 5.13; 95% CI: 1.61–16.34), abdominal pain (OR = 2.00; 95% CI: 1.49–2.68), lethargy (OR = 2.73; 95% CI: 1.05–7.10), vomiting (OR = 1.80; 95% CI: 1.43–2.26), hepatomegaly (OR = 5.92; 95% CI: 3.29–10.66), ascites (OR = 6.30; 95% CI: 3.75–10.60), pleural effusion (OR = 5.72; 95% CI: 3.24–10.10) and melena (OR = 4.05; 95% CI: 1.64–10.00).

Conclusions

Our meta-analysis identified children, secondary infection, diabetes and renal disease(s) as important predictors of severe dengue. Our finding also supports the predictive ability of the WHO warning signs to identify severe dengue. These findings are useful for clinicians to identify severe dengue for management and timely interventions.

Supplementary Information

The online version contains supplementary material available at 10.1186/s40249-021-00908-2.

Risk predictors of progression to severe disease during the febrile phase of dengue: a systematic review and meta-analysis

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 without; crude OR 4·38 [2·58-7·43]), hypertension (240 [35·0%] of 685 vs 763 [20·6%] of 3695; 2·19 [1·36-3·53]), renal disease (44 [45·8%] of 96 vs 271 [16·0%] of 1690; 4·67 [2·21-9·88]), and cardiovascular disease (nine [23·1%] of 39 vs 155 [8·6%] of 1793; 2·79 [1·04-7·50]). Clinical features during the febrile phase associated with progression to severe disease were vomiting (329 [13·5%] of 2432 with vs 258 [6·8%] of 3797 without; 2·25 [1·87-2·71]), abdominal pain and tenderness (321 [17·7%] of 1814 vs 435 [8·1%] of 5357; 1·92 [1·35-2·74]), spontaneous or mucosal bleeding (147 [17·9%] of 822 vs 676 [10·8%] of 6235; 1·57 [1·13-2·19]), and the presence of clinical fluid accumulation (40 [42·1%] of 95 vs 212 [14·9%] of 1425; 4·61 [2·29-9·26]). During the first 4 days of illness, platelet count was lower (standardised mean difference -0·34 [95% CI -0·54 to -0·15]), serum albumin was lower (-0·5 [-0·86 to -0·15]), and aminotransferase concentrations were higher (aspartate aminotransferase [AST] 1·06 [0·54 to 1·57] and alanine aminotransferase [ALT] 0·73 [0·36 to 1·09]) among individuals who progressed to severe disease. Dengue virus serotype 2 was associated with severe disease in children. Secondary infections (vs primary infections) were also associated with severe disease (1682 [11·8%] of 14 252 with vs 507 [5·2%] of 9660 without; OR 2·26 [95% CI 1·65-3·09]). Although the included studies had a moderate to high risk of bias in terms of study confounding, the risk of bias was low to moderate in other domains. Heterogeneity of the pooled results varied from low to high on different factors.

INTERPRETATION

This analysis supports monitoring of the warning signs described in the 2009 WHO guidelines on dengue. In addition, testing for infecting serotype and monitoring platelet count and serum albumin, AST, and ALT concentrations during the febrile phase of illness could improve the early prediction of severe dengue.

FUNDING

Wellcome Trust, National Institute for Health Research, Collaborative Project to Increase Production of Rural Doctors, and Royal Thai Government.

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.

Risk Factors and Predictors of Severe Dengue in Saudi Population in Jeddah, Western Saudi Arabia: A Retrospective Study

This study was performed to determine the risk factors and predictors of severe dengue fever (SDF) in Saudi population in Jeddah, Western Saudi Arabia. This 7-year retrospective study included children and adults with confirmed dengue from 2010 to 2016. Demographic, clinical, laboratory, serological, and virologic data were collected. Comparative analyses were performed between pediatric and adult SDF cases defined according to the WHO 2009 dengue classification. During the study period, dengue was confirmed in 17,646 cases with predominant infection of adults (6.5 times that of children) and males (3.8 times that of females). May and June were associated with 43.9% of total dengue cases. All 56 pediatric and 187 adult SDF cases were hospitalized. At least one warning sign of severe illness was present in 92.2% of total SDF cases. Mortality rates were 8.9% and 10.7% of pediatric and adult SDF cases, respectively. Multiple logistic regression detected that the most significant risk factors and predictors of SDF in adults versus children were significantly more secondary dengue infection (adjusted odds ratio [AOR]: 2.20, 95% CI: 1.09-4.44, P = 0.02), significantly less clinical fluid accumulation (AOR: 0.17, 95% CI: 0.07-0.44, P < 0.001) and significantly less neutropenia (AOR: 0.41, 95% CI: 0.17-0.97, P = 0.04). This was the first large multicenter study evaluating SDF in Saudi population and considering the WHO 2009 dengue classification, which showed predominant infection of adults and males with dengue, few SDF cases with low mortality and highlighted predictors of SDF in adults versus children. Consideration of warning signs for severe dengue may result in hospital admission, prompting closer monitoring, timely and proper interventions and reduced mortality in SDF cases.

Severe Dengue Prognosis Using Human Genome Data and Machine Learning

Dengue has become one of the most important worldwide arthropod-borne diseases. Dengue phenotypes are based on laboratorial and clinical exams, which are known to be inaccurate.

OBJECTIVE

We present a machine learning approach for the prediction of dengue fever severity based solely on human genome data.

METHODS

One hundred and two Brazilian dengue patients and controls were genotyped for 322 innate immunity single nucleotide polymorphisms (SNPs). Our model uses a support vector machine algorithm to find the optimal loci classification subset and then an artificial neural network (ANN) is used to classify patients into dengue fever or severe dengue.

RESULTS

The ANN trained on 13 key immune SNPs selected under dominant or recessive models produced median values of accuracy greater than 86%, and sensitivity and specificity over 98% and 51%, respectively.

CONCLUSION

The proposed classification method, using only genome markers, can be used to identify individuals at high risk for developing the severe dengue phenotype even in uninfected conditions.

SIGNIFICANCE

Our results suggest that the genetic context is a key element in phenotype definition in dengue. The methodology proposed here is extendable to other Mendelian based and genetically influenced diseases.