A Prognostic Model for Development of Profound Shock among Children Presenting with Dengue Shock Syndrome

Pediatric Profound Dengue Shock Syndrome and Use of Point-of-Care Ultrasound During Mechanical Ventilation to Guide Treatment: Single-Center Retrospective Study, 2013-2021

OBJECTIVES

Profound dengue shock syndrome (DSS) complicated by severe respiratory failure necessitating mechanical ventilation (MV) accounts for high case fatality rates among PICU-admitted patients. A major challenge to management is the assessment of intravascular volume, which can be hampered by severe plasma leakage and the use of MV.

DESIGN

Retrospective cohort, from 2013 to 2021.

PATIENTS

Sixty-seven children with profound DSS supported by MV, some of whom underwent bedside point-of-care ultrasound (POCUS) for assessment and monitoring of hemodynamics and fluid administration.

SETTING

PICU of the tertiary Children's Hospital No. 2 in Vietnam.

INTERVENTIONS

None.

MEASUREMENTS AND MAIN RESULTS

We analyzed data clinical and laboratory data during PICU stay. In particular, during use of MV (i.e., at times 0-, 6-, and 24-hr after commencement) and fluid resuscitation. The primary study outcome was 28-day in-hospital mortality, and the secondary outcomes were associations with changes in hemodynamics, blood lactate, and vasoactive-inotrope score (VIS). Patients had a median age of 7 years (interquartile range, 4-9). Use of POCUS during fluid management (39/67), as opposed to not using (28/67), was associated with lower mortality (6/39 [15%] vs. 18/28 [64%]; difference 49 % [95% CI, 28-70%], p < 0.001). Use of POCUS was associated with lower odds of death (adjusted odds ratio 0.17 [95% CI, 0.04-0.76], p = 0.02). The utilization of POCUS, versus not, was associated with greater use of resuscitation fluid, and reductions in VIS and pediatric logistic organ dysfunction (PELOD-2) score at 24 hours after MV and PICU discharge.

CONCLUSIONS

In our experience of pediatric patients with profound DSS and undergoing MV (2013-2021), POCUS use was associated with lower odds of death, a higher volume of resuscitation fluid, and improvements in the blood lactate levels, VIS, and PELOD-2 score.

Dengue models based on machine learning techniques: A systematic literature review

BACKGROUND

Dengue modeling is a research topic that has increased in recent years. Early prediction and decision-making are key factors to control dengue. This Systematic Literature Review (SLR) analyzes three modeling approaches of dengue: diagnostic, epidemic, intervention. These approaches require models of prediction, prescription and optimization. This SLR establishes the state-of-the-art in dengue modeling, using machine learning, in the last years.

METHODS

Several databases were selected to search the articles. The selection was made based on Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) methodology. Sixty-four articles were obtained and analyzed to describe their strengths and limitations. Finally, challenges and opportunities for research on machine-learning for dengue modeling were identified.

RESULTS

Logistic regression was the most used modeling approach for the diagnosis of dengue (59.1%). The analysis of the epidemic approach showed that linear regression (17.4%) is the most used technique within the spatial analysis. Finally, the most used intervention modeling is General Linear Model with 70%.

CONCLUSIONS

We conclude that cause-effect models may improve diagnosis and understanding of dengue. Models that manage uncertainty can also be helpful, because of low data-quality in healthcare. Finally, decentralization of data, using federated learning, may decrease computational costs and allow model building without compromising data security.

Early Predictors of Mortality in Children with Severe Dengue Fever: A Prospective Study

OBJECTIVE

The aim of the study was to identify early predictors of mortality in children with severe dengue fever admitted to pediatric intensive care unit (PICU).

MATERIALS AND METHODS

All consecutive children with laboratory-confirmed severe dengue fever were enrolled in this prospective observational study. Besides demographic data, disease severity and organ dysfunction scores, laboratory investigations and interventions are done in PICU were recorded and analyzed.

RESULTS

During the study period of 42 months, 172 patients with dengue fever were admitted to PICU. A total of 78 (45.3%) patients with severe dengue fever were included and analyzed. There were 20 (25.6%) deaths. There were significant differences in disease severity and organ dysfunction scores, transaminases, blood lactate level and serum creatinine between survivors and nonsurvivors. A significantly higher number of nonsurvivors required interventions in first 24 hours of admission. Platelet counts (P value 0.22) and hematocrit (P value 0.47) were not statistically different in 2 groups. There was a significantly high vasopressor-inotrope score (VIS) (<0.001) and positive fluid balance >10% (0.002) in nonsurvivors. Multivariate stepwise logistic regression analysis identified serum glutamic pyruvic transaminases (≥ 284 IU/L; odds ratio [OR] 1.002, 95% confidence interval [CI]: 1.001-1.003), blood lactate level (≥2.73 mmol/L; OR 2.08, 95% CI: 1.354-3.202), Pediatric Risk of Mortality score at 12 hours (≥14.5; OR 1.35, 95% CI: 1.077-1.693), VIS (≥22.5, OR 1.129, 95% CI: 1.059-1.204) and positive fluid balance >10% (OR 22.937, 95% CI: 2.393-219.84) at 24 hours of admission as independent predictors of mortality.

CONCLUSION

Disease severity, hyperlactatemia at admission, need for multiple vasoactive drugs and positive fluid balance are predictors of mortality in severe dengue infection in children admitted to PICU.

Diagnostic accuracy and predictive value in differentiating the severity of dengue infection

OBJECTIVE

To review the diagnostic test accuracy and predictive value of statistical models in differentiating the severity of dengue infection.

METHODS

Electronic searches were conducted in the Cochrane Database of Systematic Reviews, Cochrane Central Register of Controlled Trials, MEDLINE (complete), PubMed and Scopus. Eligible studies to be included in this review were cohort studies with participants confirmed by laboratory test for dengue infection and comparison among the different severity of dengue infection by using statistical models. The methodological quality of the paper was assessed by independent reviewers using QUADAS-2.

RESULTS

Twenty-six studies published from 1994 to 2017 were included. Most diagnostic models produced an accuracy of 75% to 80% except one with 86%. Two models predicting severe dengue according to the WHO 2009 classification have 86% accuracy. Both of these logistic regression models were applied during the first three days of illness, and their sensitivity and specificity were 91-100% and 79.3-86%, respectively. Another model which evaluated the 30-day mortality of dengue infection had an accuracy of 98.5%.

CONCLUSION

Although there are several potential predictive or diagnostic models for dengue infection, their limitations could affect their validity. It is recommended that these models be revalidated in other clinical settings and their methods be improved and standardised in future.

Cardio-haemodynamic assessment and venous lactate in severe dengue: Relationship with recurrent shock and respiratory distress

Background

Dengue can cause plasma leakage that may lead to dengue shock syndrome (DSS). In approximately 30% of DSS cases, recurrent episodes of shock occur. These patients have a higher risk of fluid overload, respiratory distress and poor outcomes. We investigated the association of echocardiographically-derived cardiac function and intravascular volume parameters plus lactate levels, with the outcomes of recurrent shock and respiratory distress in severe dengue.

Methods/Principle findings

We performed a prospective observational study in Paediatric and adult ICU, at the Hospital for Tropical Diseases (HTD), Ho Chi Minh City, Vietnam. Patients with dengue were enrolled within 12 hours of admission to paediatric or adult ICU. A haemodynamic assessment and portable echocardiograms were carried out daily for 5 days from enrolment and all interventions recorded.

102 patients were enrolled; 22 patients did not develop DSS, 48 had a single episode of shock and 32 had recurrent shock. Patients with recurrent shock had a higher enrolment pulse than those with 1 episode or no shock (median: 114 vs. 100 vs. 100 b/min, P = 0.002), significantly lower Stroke Volume Index (SVI), (median: 21.6 vs. 22.8 vs. 26.8mls/m², P<0.001) and higher lactate levels (4.2 vs. 2.9 vs. 2.2 mmol/l, P = 0.001). Higher SVI and worse left ventricular function (higher Left Myocardial Performance Index) on study days 3–5 was associated with the secondary endpoint of respiratory distress. There was an association between the total IV fluid administered during the ICU admission and respiratory distress (OR: 1.03, 95% CI 1.01–1.06, P = 0.001). Admission lactate levels predicted patients who subsequently developed recurrent shock (P = 0.004), and correlated positively with the total IV fluid volume received (rho: 0.323, P = 0.001) and also with admission ALT (rho: 0.764, P<0.001) and AST (rho: 0.773, P<0.001).

Conclusions/Significance

Echo-derived intravascular volume assessment and venous lactate levels can help identify dengue patients at high risk of recurrent shock and respiratory distress in ICU. These findings may serve to, not only assist in the management of DSS patients, but also these haemodynamic endpoints could be used in future dengue fluid intervention trials.

Dengue is a viral illness that can lead to severe and potentially fatal complications. The most common complication is fluid leakage from blood vessels, which can cause low blood pressure or dengue shock syndrome (DSS). The majority of patients recover with simple intravenous fluid replacement, however in approximately 30% of DSS cases, recurrent episodes of shock occur, and these patients have a higher risk of fluid overload, respiratory distress and death. We investigated whether using portable echocardiograms (Echo) in the intensive care unit (ICU) to assess cardiac function and intravascular volume parameters as well as blood lactate levels, can help identify these patients. We found patients who developed recurrent shock had higher heart rates and lower Stroke Volume Index (SVI), and higher lactate levels at enrolment than those with 1 episode or no shock. Higher SVI and worse cardiac function after 3 days in ICU was associated with respiratory distress. Admission lactate levels predicted patients who subsequently developed recurrent shock and correlated positively with the total IV fluid volume received. These results demonstrate that Echo-derived intravascular volume assessment and venous lactate levels can help identify dengue patients at high risk of poor outcomes in the ICU, and could assist in the management of severe dengue.

The value of daily platelet counts for predicting dengue shock syndrome: Results from a prospective observational study of 2301 Vietnamese children with dengue

BACKGROUND

Dengue is the most important mosquito-borne viral infection to affect humans. Although it usually manifests as a self-limited febrile illness, complications may occur as the fever subsides. A systemic vascular leak syndrome that sometimes progresses to life-threatening hypovolaemic shock is the most serious complication seen in children, typically accompanied by haemoconcentration and thrombocytopenia. Robust evidence on risk factors, especially features present early in the illness course, for progression to dengue shock syndrome (DSS) is lacking. Moreover, the potential value of incorporating serial haematocrit and platelet measurements in prediction models has never been assessed.

METHODOLOGY/PRINCIPAL FINDINGS

We analyzed data from a prospective observational study of Vietnamese children aged 5-15 years admitted with clinically suspected dengue to the Hospital for Tropical Diseases in Ho Chi Minh City between 2001 and 2009. The analysis population comprised all children with laboratory-confirmed dengue enrolled between days 1-4 of illness. Logistic regression was the main statistical model for all univariate and multivariable analyses. The prognostic value of daily haematocrit levels and platelet counts were assessed using graphs and separate regression models fitted on each day of illness. Among the 2301 children included in the analysis, 143 (6%) progressed to DSS. Significant baseline risk factors for DSS included a history of vomiting, higher temperature, a palpable liver, and a lower platelet count. Prediction models that included serial daily platelet counts demonstrated better ability to discriminate patients who developed DSS from others, than models based on enrolment information only. However inclusion of daily haematocrit values did not improve prediction of DSS.

CONCLUSIONS/SIGNIFICANCE

Daily monitoring of platelet counts is important to help identify patients at high risk of DSS. Development of dynamic prediction models that incorporate signs, symptoms, and daily laboratory measurements, could improve DSS prediction and thereby reduce the burden on health services in endemic areas.

[Clinical profile of dengue and predictive severity variables among children at a secondary care hospital of Chilpancingo, Guerrero, Mexico: case series]

BACKGROUND

Dengue continues to increase globally. Currently, the highest incidence of first infection occurs in paediatric population, where severe dengue fever is potentially lethal. This study characterizes the clinical profile of paediatric patients with dengue fever in the South of Mexico.

METHODS

We undertook a series case study of 133 paediatric inpatients who presented clinical diagnosis of non-severe dengue and severe dengue fever. We described univariate analysis as means or percentages, using 0.05 as significance level. We estimated the prediction of severe dengue considering clinical signs and symptoms only using GLMM (Generalised Linear Mixed Models).

RESULTS

58% (77/133) patients had severe dengue. There were significant differences among the dengue groups, in the following signs and symptoms: Fever, abdominal pain, epistaxis and platelet count. Children older than four years old had a higher proportion of severe dengue (p<0.05). GLMM identified a group of four clinical signs and symptoms (fever ≥39°C, myalgia, arthralgia and abdominal pain) as predictors of severe dengue.

CONCLUSIONS

The results of this exploratory study suggest changes in the frequency of clinical signs and symptoms among paediatric inpatients. Paediatric patients with a presumptive diagnosis of dengue, showing fever of ≥39° C, myalgia, arthralgia and abdominal pain should be considered as potential cases of severe dengue.

Development of a Simple Clinical Risk Score for Early Prediction of Severe Dengue in Adult Patients

We aimed to develop and validate a risk score to aid in the early identification of laboratory-confirmed dengue patients at high risk of severe dengue (SD) (i.e. severe plasma leakage with shock or respiratory distress, or severe bleeding or organ impairment). We retrospectively analyzed data of 1184 non-SD patients at hospital presentation and 69 SD patients before SD onset. We fit a logistic regression model using 85% of the population and converted the model coefficients to a numeric risk score. Subsequently, we validated the score using the remaining 15% of patients. Using the derivation cohort, two scoring algorithms for predicting SD were developed: models 1 (dengue illness ≤4 days) and 2 (dengue illness >4 days). In model 1, we identified four variables: age ≥65 years, minor gastrointestinal bleeding, leukocytosis, and platelet count ≥100×10⁹ cells/L. Model 1 (ranging from −2 to +6 points) showed good discrimination between SD and non-SD, with an area under the receiver operating characteristic curve (AUC) of 0.848 (95% confidence interval [CI], 0.771–0.924). The optimal cutoff value for model 1 was 1 point, with a sensitivity and specificity for predicting SD of 70.3% and 90.6%, respectively. In model 2 (ranging from 0 to +3 points), significant predictors were age ≥65 years and leukocytosis. Model 2 showed an AUC of 0.859 (95% CI, 0.756–0.963), with an optimal cutoff value of 1 point (sensitivity, 80.3%; specificity, 85.8%). The median interval from hospital presentation to SD was 1 day. This finding underscores the importance of close monitoring, timely resuscitation of shock including intravenous fluid adjustment and early correction of dengue-related complications to prevent the progressive dengue severity. In the validation data, AUCs of 0.904 (95% CI, 0.825–0.983) and 0.917 (95% CI, 0.833–1.0) in models 1 and 2, respectively, were achieved. The observed SD rates (in both cohorts) were <3% for patients with a score <1 point, but >50% for those with a score of ≥2 points, irrespective of the day of illness onset, suggesting that our simple risk score can be easily implemented in resource-limited countries for early prediction of dengue patients at risk of SD provided that they have rapid dengue confirmed tests. For patients with other acute febrile illnesses or bacterial infections usually have SD risk score of >1. Thus, these scoring algorithms cannot totally replace good clinical judgement of the physician, and most importantly, early differentiating dengue from other febrile illnesses is critical for appropriate monitoring and management.

Metabolomics-Based Discovery of Small Molecule Biomarkers in Serum Associated with Dengue Virus Infections and Disease Outcomes

BACKGROUND

Epidemic dengue fever (DF) and dengue hemorrhagic fever/dengue shock syndrome (DHF/DSS) are overwhelming public health capacity for diagnosis and clinical care of dengue patients throughout the tropical and subtropical world. The ability to predict severe dengue disease outcomes (DHF/DSS) using acute phase clinical specimens would be of enormous value to physicians and health care workers for appropriate triaging of patients for clinical management. Advances in the field of metabolomics and analytic software provide new opportunities to identify host small molecule biomarkers (SMBs) in acute phase clinical specimens that differentiate dengue disease outcomes.

METHODOLOGY/PRINCIPAL FINDINGS

Exploratory metabolomic studies were conducted to characterize the serum metabolome of patients who experienced different dengue disease outcomes. Serum samples from dengue patients from Nicaragua and Mexico were retrospectively obtained, and hydrophilic interaction liquid chromatography (HILIC)-mass spectrometry (MS) identified small molecule metabolites that were associated with and statistically differentiated DHF/DSS, DF, and non-dengue (ND) diagnosis groups. In the Nicaraguan samples, 191 metabolites differentiated DF from ND outcomes and 83 differentiated DHF/DSS and DF outcomes. In the Mexican samples, 306 metabolites differentiated DF from ND and 37 differentiated DHF/DSS and DF outcomes. The structural identities of 13 metabolites were confirmed using tandem mass spectrometry (MS/MS). Metabolomic analysis of serum samples from patients diagnosed as DF who progressed to DHF/DSS identified 65 metabolites that predicted dengue disease outcomes. Differential perturbation of the serum metabolome was demonstrated following infection with different DENV serotypes and following primary and secondary DENV infections.

CONCLUSIONS/SIGNIFICANCE

These results provide proof-of-concept that a metabolomics approach can be used to identify metabolites or SMBs in serum specimens that are associated with distinct DENV infections and disease outcomes. The differentiating metabolites also provide insights into metabolic pathways and pathogenic and immunologic mechanisms associated with dengue disease severity.

Recent advances in dengue pathogenesis and clinical management

This review describes and commentates on recent advances in the understanding of dengue pathogenesis and immunity, plus clinical research on vaccines and therapeutics. We expand specifically on the role of the dermis in dengue virus infection, the contribution of cellular and humoral immune responses to pathogenesis and immunity, NS1 and mechanisms of virus immune evasion. Additionally we review a series of therapeutic intervention trials for dengue, as well as recent clinical research aimed at improving clinical diagnosis, risk prediction and disease classification.