Symptoms associated with adverse dengue fever prognoses at the time of reporting in the 2015 dengue outbreak in Taiwan

Risks of anxiety disorders, depressive disorders, and sleep disorders in patients with dengue fever: A nationwide, population-based cohort study

BACKGROUND

Dengue virus (DENV) infection, a common mosquito-borne disease, has been linked to several mental disorders like depression and anxiety. However, the temporal risk of these disorders after DENV infection is not well studied.

METHODS

This population-based cohort study encompassed 45,334 recently lab-confirmed dengue patients in Taiwan spanning 2002 to 2015, matched at a 1:5 ratio with non-dengue individuals based on age, gender, and residence (n = 226,670). Employing subdistribution hazard regression analysis, we assessed the immediate (<3 months), intermediate (3-12 months), and prolonged (>12 months) risks of anxiety disorders, depressive disorders, and sleep disorders post DENV infection. Corrections for multiple comparisons were carried out using the Benjamini-Hochberg procedure.

RESULTS

A significant increase in depressive disorder risk across all timeframes post-infection was observed (<3 months [aSHR 1.90, 95% CI 1.20-2.99], 3-12 months [aSHR 1.68, 95% CI 1.32-2.14], and >12 months [aSHR 1.14, 95% CI 1.03-1.25]). Sleep disorder risk was higher only during 3-12 months (aSHR 1.55, 95% CI 1.18-2.04). No elevated anxiety disorder risk was found. Subgroup analysis of hospitalized dengue patients showed increased risk of anxiety disorders within 3 months (aSHR 2.14, 95% CI 1.19-3.85) and persistent risk of depressive disorders across all periods. Hospitalized dengue patients also had elevated sleep disorder risk within the first year.

CONCLUSION

Dengue patients exhibited significantly elevated risks of depressive disorders in both the short and long term. However, dengue's impact on sleep disorders and anxiety seems to be short-lived. Further research is essential to elucidate the underlying mechanisms.

Risk factors associated with dengue complications and death: A cohort study in Peru

BACKGROUND

Dengue has emerged as an unprecedented epidemic in Peru, and it is anticipated that this issue will escalate further owing to climate change. This study aimed to determine the risk factors associated with death from dengue in patients treated at Hospital II in Pucallpa, Peru.

METHODOLOGY

This retrospective cohort study collected information from the medical records of patients with a diagnosis of dengue treated at Hospital II Pucallpa-Peru between January 2019 and March 2023. The primary outcome was death, and the secondary outcome was death, development of severe dengue, or Intensive Care Unit (ICU) admission. Cox regression models were used to determine risk factors.

FINDINGS

The clinical records of 152 patients were evaluated, with a median age of 27.5 years (interquartile range, 11-45). Among all patients, 29 (19.1%) developed severe dengue, 31 (20.4%) were admitted to the ICU, and 13 (8.6%) died during follow-up. In the survival analysis, bilirubin >1.2 mg/dL was associated with a higher risk of death aHR: 11.38 (95% CI: 1.2 106.8). Additionally, factors associated with poor prognosis included having 1 to 3 comorbidities aRR: 1.92 (1.2 to 3.2), AST ≥251 U/L aRR: 6.79 (2.2 to 21.4), history of previous dengue aRR: 1.84 (1.0 to 3.3), and fibrinogen ≥400 mg/dL aRR: 2.23 (1.2 to 4.1).

SIGNIFICANCE

Elevated bilirubin was associated with death from dengue, whereas an increase in comorbidities and a history of previous dengue were related to a poor prognosis of the disease. Early identification of severe dengue would be more feasible with improved access to laboratory testing, particularly in tropical areas with a high dengue incidence.

Improving dengue fever predictions in Taiwan based on feature selection and random forests

BACKGROUND

Dengue fever is a well-studied vector-borne disease in tropical and subtropical areas of the world. Several methods for predicting the occurrence of dengue fever in Taiwan have been proposed. However, to the best of our knowledge, no study has investigated the relationship between air quality indices (AQIs) and dengue fever in Taiwan.

RESULTS

This study aimed to develop a dengue fever prediction model in which meteorological factors, a vector index, and AQIs were incorporated into different machine learning algorithms. A total of 805 meteorological records from 2013 to 2015 were collected from government open-source data after preprocessing. In addition to well-known dengue-related factors, we investigated the effects of novel variables, including particulate matter with an aerodynamic diameter < 10 µm (PM10), PM2.5, and an ultraviolet index, for predicting dengue fever occurrence. The collected dataset was randomly divided into an 80% training set and a 20% test set. The experimental results showed that the random forests achieved an area under the receiver operating characteristic curve of 0.9547 for the test set, which was the best compared with the other machine learning algorithms. In addition, the temperature was the most important factor in our variable importance analysis, and it showed a positive effect on dengue fever at < 30 °C but had less of an effect at > 30 °C. The AQIs were not as important as temperature, but one was selected in the process of filtering the variables and showed a certain influence on the final results.

CONCLUSIONS

Our study is the first to demonstrate that AQI negatively affects dengue fever occurrence in Taiwan. The proposed prediction model can be used as an early warning system for public health to prevent dengue fever outbreaks.

Re-examination of the risk of dementia after dengue virus infection: A population-based cohort study

Dengue infection can affect the central nervous system and cause various neurological complications. Previous studies also suggest dengue was associated with a significantly increased long-term risk of dementia. A population-based cohort study was conducted using national health databases in Taiwan and included 37,928 laboratory-confirmed dengue patients aged ≥ 45 years between 2002 and 2015, along with 151,712 matched nondengue individuals. Subdistribution hazard regression models showed a slightly increased risk of Alzheimer's disease, and unspecified dementia, non-vascular dementia, and overall dementia in dengue patients than the nondengue group, adjusted for age, sex, area of residence, urbanization level, income, comorbidities, and all-cause clinical visits within one year before the index date. After considering multiple comparisons using Bonferroni correction, only overall dementia and non-vascular dementia remained statistically significant (adjusted SHR 1.13, 95% CI 1.05-1.21, p = 0.0009; E-value 1.51, 95% CI 1.28-NA). Sensitivity analyses in which dementia cases occurring in the first three or five years after the index dates were excluded revealed no association between dengue and dementia. In conclusion, this study found dengue patients had a slightly increased risk of non-vascular dementia and total dementia than those without dengue. However, the small corresponding E-values and sensitivity analyses suggest the association between dengue and dementia may not be causal.

Reinvestigation of the risk of stroke after dengue virus infection: A population-based cohort study

BACKGROUND

Dengue virus (DENV) infection is the most prevalent mosquito-borne viral disease. Stroke is a severe manifestation of dengue. However, few large-scale studies have investigated post-dengue risk of stroke.

METHODS

This population-based cohort study included 57,934 newly diagnosed, laboratory-confirmed dengue patients in Taiwan from 2002 to 2015; patients were matched to nondengue individuals by age, sex, and area of residence at a ratio of 1:4 (n = 231,736). We used subdistribution hazard regression to evaluate short-term (≤ 30 days), medium-term (31-365 days), and long-term (1-3 years) risk of stroke after DENV infection. The robustness of the results to unmeasured confounding was assessed with E-values.

RESULTS

DENV infection was associated with a significantly increased risk of overall stroke (aSHR 4.51; 95% CI: 3.23-6.32; P < 0.0001; E-value = 8.49), hemorrhagic stroke (aSHR 4.13; 95% CI: 2.20-7.76; P < 0.0001; E-value =7.73), and ischemic stroke (aSHR 3.80; 95% CI: 2.37-6.11; P < 0.0001; E-value = 7.06) within 30 days. Stratified analysis by age showed that the aSHRs for overall stroke, hemorrhagic stroke, and ischemic stroke were larger among dengue patients aged ≥ 65 during the first 30 days. The 30-day risks of overall stroke, hemorrhagic stroke, and ischemic stroke among elderly dengue patients were 6.71, 1.29, and 3.49 per 1000, respectively. No increased risk was observed after 30 days.

CONCLUSION

DENV infection was associated with a significant short-term increased risk of stroke. Clinical practitioners should remain alert to patients with stroke-associated symptoms during epidemic seasons, especially elderly patients.

Development and Utility of Practical Indicators of Critical Outcomes in Dengue Patients Presenting to Hospital: A Retrospective Cross-Sectional Study

Global travel and climate change have drastically increased the number of countries with endemic or epidemic dengue. The largest dengue outbreak in Taiwan, with 43,419 cases and 228 deaths, occurred in 2015. Practical and cost-effective tools for early prediction of clinical outcomes in dengue patients, especially the elderly, are limited. This study identified the clinical profile and prognostic indicators of critical outcomes in dengue patients on the basis of clinical parameters and comorbidities. A retrospective cross-sectional study was conducted in a tertiary hospital from 1 July 2015 to 30 November 2015. Patients diagnosed with dengue were enrolled, and the initial clinical presentations, diagnostic laboratory data, details of the underlying comorbidities, and initial management recommendations based on 2009 World Health Organization (WHO) guidelines were used to evaluate prognostic indicators of critical outcomes in dengue patients. Dengue patients from another regional hospital were used to evaluate accuracy. A group B (4 points) classification, temperature < 38.5 °C (1 point), lower diastolic blood pressure (1 point), prolonged activated partial thromboplastin time (aPTT) (2 points), and elevated liver enzymes (1 point) were included in the scoring system. The area under the receiver operating characteristic curve of the clinical model was 0.933 (95% confidence interval [CI]: 0.905–0.960). The tool had good predictive value and clinical applicability for identifying patients with critical outcomes.

Re-examination of the risk of autoimmune diseases after dengue virus infection: A population-based cohort study

Previous studies suggested that dengue was associated with an increased risk of several autoimmune diseases. However, this association still needs to be explored due to the limitations of these studies. A population-based cohort study was conducted using national health databases in Taiwan and included 63,814 newly diagnosed, laboratory-confirmed dengue patients between 2002 and 2015 and 1:4 controls (n = 255,256) matched by age, sex, area of residence and symptom onset time. Multivariate Cox proportional hazard regression models were used to investigate the risk of autoimmune diseases after dengue infection. Dengue patients had a slightly higher risk of overall autoimmune diseases than non-dengue controls (aHR 1.16; P = 0.0002). Stratified analyses by specific autoimmune diseases showed that only autoimmune encephalomyelitis remained statistically significant after Bonferroni correction for multiple testing (aHR 2.72; P < 0.0001). Sixteen (0.025%) dengue patients and no (0%) controls developed autoimmune encephalomyelitis in the first month of follow-up (HR >9999, P < 0.0001), but the risk between groups was not significantly different thereafter. Contrary to previous studies, our findings showed that dengue was associated with an increased short-term risk of a rare complication, autoimmune encephalomyelitis, but not associated with other autoimmune diseases.

Risk and predictive factors for severe dengue infection: A systematic review and meta-analysis

Background

Dengue is a major public health issue worldwide and severe dengue (SD) is life threatening. It is critical to triage patients with dengue infection in the early stage. However, there is limited knowledge on early indicators of SD. The objective of this study is to identify risk factors for the prognosis of SD and try to find out some potential predictive factors for SD from dengue fever (DF) in the early of infection.

Methods

The PubMed, Cochrane Library and Web of Science databases were searched for relevant studies from June 1999 to December 2020. The pooled odds ratio (OR) or standardized mean difference (SMD) with 95% confidence intervals (CI) of identified factors was calculated using a fixed or random effect model in the meta-analysis. Tests for heterogeneity, publication bias, subgroup analyses, meta-regression, and a sensitivity analysis were further performed.

Findings

A total of 6,848 candidate articles were retrieved, 87 studies with 35,184 DF and 8,173 SD cases met the eligibility criteria. A total of 64 factors were identified, including population and virus characteristics, clinical symptoms and signs, laboratory biomarkers, cytokines, and chemokines; of these factors, 34 were found to be significantly different between DF and SD, while the other 30 factors were not significantly different between the two groups after pooling the data from the relevant studies. Additionally, 9 factors were positive associated with SD within 7 days after illness when the timing subgroup analysis were performed.

Conclusions

Practical factors and biomarkers for the identification of SD were established, which will be helpful for a prompt diagnosis and early effective treatment for those at greatest risk. These outcomes also enhance our knowledge of the clinical manifestations and pathogenesis of SD.

Rapidly Containing the First Indigenous Outbreak of Chikungunya in Taiwan-Lessons Learned

The first indigenous outbreak of chikungunya in Taiwan occurred in New Taipei City, northern Taiwan, from August to October 2019. This study identified important containment strategies for controlling the outbreak. The outbreak investigation and ovitrap data were collected from the Department of Health, New Taipei City Government. A geographic information system (GIS) was applied for spatial analysis, and descriptive statistics were used to compute the demographic features and medical visits of confirmed cases. There were 19 residents infected during the outbreak. The source of this outbreak was a mountain trail with abundant Aedes albopictus. The atypical symptoms and lack of a rapid test led to multiple clinical visits by the patients (mean: 2.79; standard deviation: 1.65). The clinical symptoms of chikungunya are very similar to those of dengue fever. We noted that only eight patients were polymerase chain reaction (PCR)-positive in their first blood collection, and an average of 3.13 days between illness onset and PCR-positive results. The improved laboratory panel test, targeted and rapid insecticide spraying at the households and their communities, strict closure of the mountain trail, and ovitrap surveillance for evaluating intervention were important approaches to rapidly contain the outbreak.

Cytokine Signature of Dengue Patients at Different Severity of the Disease

Clinical presentations of dengue fever (DF) are diverse and non-specific, causing unpredictable progression and outcomes. Its progression and severity have been associated with cytokine levels alteration. In this study, dengue patients were classified into groups following the 2009 WHO dengue classification scheme to investigate the cytokine signature at different severity of the disease: dengue without warning sign symptoms (A); dengue with warning signs (B); severe dengue (C); other fever (OF) and healthy (Healthy). We analyzed 23 different cytokines simultaneously, namely IL-1b, IL-2, IL-4, IL-6, IL-8, IL-10, IL-12p70, IL-17A, IL-33, CD14, CD54, CD62E, CD62L, CD62p, CD106, CD121b, CD154, CD178, GM-CSF, IFN-g, MIF, ST2 and TNF from patients admitted to National Cheng Kung University Hospital during the 2015 Taiwan dengue outbreak. Cytokines TNF, CD54, CD62E, CD62L, CD62P, GM-CSF, IL-1b, IL-2, IL-6, IL-8, IL-10, IL-12p70, IL-17A, INF-g and MIF were elevated while CD106, CD154, IL-4 and L-33 were decreased when compared to the control. IL-10 demonstrated to be a potential diagnostic marker for DF (H and A group; AUC = 0.944, H and OF group; AUC = 0.969). CD121b demonstrated to be predictive of the SD (A and B group; AUC = 0.744, B and C group; AUC = 0.775). Our results demonstrate the cytokine profile changes during the progression of dengue and highlight possible biomarkers for optimizing effective intervention strategies.

Comparing machine learning with case-control models to identify confirmed dengue cases

In recent decades, the global incidence of dengue has increased. Affected countries have responded with more effective surveillance strategies to detect outbreaks early, monitor the trends, and implement prevention and control measures. We have applied newly developed machine learning approaches to identify laboratory-confirmed dengue cases from 4,894 emergency department patients with dengue-like illness (DLI) who received laboratory tests. Among them, 60.11% (2942 cases) were confirmed to have dengue. Using just four input variables [age, body temperature, white blood cells counts (WBCs) and platelets], not only the state-of-the-art deep neural network (DNN) prediction models but also the conventional decision tree (DT) and logistic regression (LR) models delivered performances with receiver operating characteristic (ROC) curves areas under curves (AUCs) of the ranging from 83.75% to 85.87% [for DT, DNN and LR: 84.60% ± 0.03%, 85.87% ± 0.54%, 83.75% ± 0.17%, respectively]. Subgroup analyses found all the models were very sensitive particularly in the pre-epidemic period. Pre-peak sensitivities (<35 weeks) were 92.6%, 92.9%, and 93.1% in DT, DNN, and LR respectively. Adjusted odds ratios examined with LR for low WBCs [≤ 3.2 (x103/μL)], fever (≥38°C), low platelet counts [< 100 (x103/μL)], and elderly (≥ 65 years) were 5.17 [95% confidence interval (CI): 3.96-6.76], 3.17 [95%CI: 2.74-3.66], 3.10 [95%CI: 2.44-3.94], and 1.77 [95%CI: 1.50-2.10], respectively. Our prediction models can readily be used in resource-poor countries where viral/serologic tests are inconvenient and can also be applied for real-time syndromic surveillance to monitor trends of dengue cases and even be integrated with mosquito/environment surveillance for early warning and immediate prevention/control measures. In other words, a local community hospital/clinic with an instrument of complete blood counts (including platelets) can provide a sentinel screening during outbreaks. In conclusion, the machine learning approach can facilitate medical and public health efforts to minimize the health threat of dengue epidemics. However, laboratory confirmation remains the primary goal of surveillance and outbreak investigation.

Dengue and Zika virus infections are enhanced by live attenuated dengue vaccine but not by recombinant DSV4 vaccine candidate in mouse models

Background

A tetravalent live attenuated dengue vaccine, Dengvaxia, sensitised naïve recipients to severe dengue illness upon a subsequent natural dengue infection and is suspected to be due to antibody-dependent enhancement (ADE). ADE has also been implicated in the severe neurological outcomes of Zika virus (ZIKV) infection. It has become evident that cross-reactive antibodies targeting the viral pre-membrane protein and fusion-loop epitope are ADE-competent. A pre-clinical tetravalent dengue sub-unit vaccine candidate, DSV4, eliminates these ADE-competent epitopes.

Methods

We compared protective efficacy and ADE-competence of murine polyclonal antibodies induced by DSV4, Dengvaxia and an ‘in house’ tetravalent mixture of all four laboratory DENV strains, TV DENV, using established mouse models.

Findings

DSV4-induced antibodies, known to be predominantly type-specific, provided significant protection against lethal DENV challenge, but did not promote ADE of either DENV or ZIKV infection in vivo. Antibodies elicited by Dengvaxia and TV DENV, which are predominantly cross-reactive, not only failed to offer protection against lethal DENV challenge, but also promoted ADE of both DENV and ZIKV infection in vivo.

Interpretation

Protective efficacy against DENV infection may be linked to the induction of neutralising antibodies which are type-specific rather than cross-reactive. Whole virus-based dengue vaccines may be associated with ADE risk, despite their potent virus-neutralising capacity. Vaccines designed to eliminate ADE-competent epitopes may help eliminate/minimise ADE risk.

Funding

This study was supported partly by ICGEB, India, the National Biopharma Mission, DBT, Government of India, Sun Pharmaceutical Industries Limited, India, and NIAID, NIH, USA.

The spectrum of disease severity, the burden of hospitalizations and associated risk factors in confirmed dengue among persons of all ages: findings from a population based longitudinal study from Barbados

Background: Dengue can be severe and potentially fatal in a small proportion. Risk factors for severe dengue have been highlighted but long term population based study is lacking. We assesses the severity and hospitalization in dengue.Methods: This is a longitudinal population based prospective study of all persons with confirmed dengue in Barbados during the years 2006 through 2015. Most recent WHO criteria were used for classifying dengue severity. Disease severity and hospitalization need were two main outcomes.Results: There were 2939 ambulatory and 1234 hospitalized cases. Compared to those in the age group 16-60 years, the risk of hospitalization was higher among persons over 61 years (RR = 1.8) and those under 16 years (RR = 1.7). Overall, 190 (4.4%), 771 (17.8%) and 3202 (73.7%) were classified as severe and dengue with and without warning signs respectively. The risk of severe dengue was higher in the over 60 years age group compared to the 16-60 years (RR = 1.97). Primary infection was at a lower risk of severe dengue compared to secondary infection (RR = 0.46).Conclusions: Less than 5% of dengue presents with severe disease, the risk being highest among the elderly and those with previous dengue.

Validation of the easyscreen flavivirus dengue alphavirus detection kit based on 3base amplification technology and its application to the 2016/17 Vanuatu dengue outbreak

BACKGROUND

The family flaviviridae and alphaviridae contain a diverse group of pathogens that cause significant morbidity and mortality worldwide. Diagnosis of the virus responsible for disease is essential to ensure patients receive appropriate clinical management. Very few real-time RT-PCR based assays are able to detect the presence of all members of these families using a single primer and probe set. We have developed a novel chemistry, 3base, which simplifies the viral nucleic acids allowing the design of RT-PCR assays capable of pan-family identification.

METHODOLOGY/PRINCIPAL FINDING

Synthetic constructs, viral nucleic acids, intact viral particles and characterised reference materials were used to determine the specificity and sensitivity of the assays. Synthetic constructs demonstrated the sensitivities of the pan-flavivirus detection component were in the range of 13 copies per PCR. The pan-alphavirus assay had a sensitivity range of 10-25 copies per reaction depending on the viral strain. Lower limit of detection studies using whole virus particles demonstrated that sensitivity for assays was in the range of 1-2 copies per reaction. No cross reactivity was observed with a number of commonly encountered viral strains. Proficiency panels showed 100% concordance with the expected results and the assays performed as well as, if not better than, other assays used in laboratories worldwide. After initial assay validation the pan-viral assays were then tested during the 2016-2017 Vanuatu dengue-2 outbreak. Positive results were detected in 116 positives from a total of 187 suspected dengue samples.

CONCLUSIONS/SIGNIFICANCE

The pan-viral screening assays described here utilise a novel 3base technology and are shown to provide a sensitive and specific method to screen and thereafter speciate flavi- and/or alpha- viruses in clinical samples. The assays performed well in an outbreak situation and can be used to detect positive clinical samples containing any flavivirus or alphavirus in approximately 3 hours 30 minutes.

Dynamic changes of soluble ST2 levels predicted fatality and were involved in coagulopathy in dengue fever in the elderly

Background

Severe dengue virus (DENV) infection involves plasma leakage and vascular collapse, and leads to significant morbidity and death. Serum soluble ST2 (sST2 [interleukin (IL)-1 receptor like-1 protein: IL-1-RL-1]) levels are high in pediatric cases of DENV infection, and the disease progresses. However, the correlation between serum sST2 levels and the outcomes of DENV infection in the elderly (≥65 years) is unclear. We thus explored the mechanisms of serial sST2 level changes involved in the coagulopathy and bloodstream infections of elderly patients in Taiwan’s 2015 DENV outbreak.

Methods

This retrospective study was done in a tertiary medical center in southern Taiwan during the outbreak. All DENV-infected patients who, between July 1, 2015, and December 31, 2015, provided a written informed consent for at least two blood sample analyses were enrolled and reviewed. The serum levels of sST2 were quantified. ΔsST2 is defined as the “changes of sST2 levels in serially paired samples”. Receiver operating characteristic (ROC) curve and area under the ROC curve (AUC) analyses were used to evaluate the prognostic ability of ΔsST2.

Results

Forty-three patients with DENV infection were enrolled. Mean patient age was 75.0 ± 12.2 years and the case fatality rate was 44.2% (19/43). Significantly more non-survivors than survivors had increased ST2 level (78.9% vs. 12.5%, p < 0.001). The AUC value for serum ΔsST2 level was 0.857 for predicting DENV fatality. Moreover, patients given frozen fresh plasma (FFP) transfusions were significantly (p = 0.025) more likely to have higher serum ST2 level changes than were those who had not. DENV-infected patients with early bloodstream infections (BSIs) seemed to have higher ST2 levels than those who did not have BSIs.

Conclusions

Serum ST2 levels increased in the elderly (≥ 65 years of age) with DENV infection. The changes in serum sST2 levels might be a critical indicator of DENV infection severity for the elderly; sST2 is an important modulator of coagulopathy in severe DENV infections.

Dengue virus (DENV) infection is a mosquito-borne disease that annually affects at least 50 million people worldwide. The cytokine response during DENV infection is mercurial and abstruse. IL-1 receptor-like-1 (IL-1R-L-1 [aka ST2]) protein is associated with the severity of DENV infection, and elevated cytokine levels are important early predictors of dengue hemorrhagic fever and dengue shock syndrome. ST2, a member of the interleukin-1-receptor/toll-like receptor (TLR) superfamily, is an important biomarker of severe forms of pediatric DENV infection. We first confirmed a similar trend in the elderly cohort. Serial changes of soluble ST2 (sST2) levels were a more reliable predictor for dengue fatality than a single measurement was. Patients given fresh frozen plasma (FFP) transfusions had significantly higher serum ST2 levels than those who had not been given FFP transfusions. SerumsST2 might be necessary for modulating coagulopathy in severe DENV infections. The exact molecular mechanism and the optimal timing for sST2 testing need further investigation.

Trajectories of hepatic and coagulation dysfunctions related to a rapidly fatal outcome among hospitalized patients with dengue fever in Tainan, 2015

Background

Hepatic dysfunction and coagulopathy are common in acute dengue illness. We analyzed the trajectories of the above parameters in the survivors and fatal patients in the outbreak in Tainan, 2015.

Methods

A retrospective study was conducted using data from a tertiary hospital between January and December 2015. Multilevel modeling (MLM) was used to identify the changes in aminotransferase (AST), alanine aminotransferase (ALT), activated partial thromboplastin time (aPTT), and platelet counts from Day 0 to Day 7 of the onset of dengue infection. The machine-learning algorithm was used by purity measure assumption to calculate the accuracy of serum transaminases and coagulation variables to discriminate between the fatal and survival groups.

Results

There were 4,069 dengue patients, of which 0.9% died in one week after illness onset (i.e., early mortality). Case fatality rate was the highest for those aged ≥70 years. Both AST and ALT values of the fatal group were significantly higher than those of the survivor group from Day 3 (AST median, 624 U/L vs. 60 U/L, p < 0.001; ALT median, 116 U/L vs. 29 U/L, p = 0.01) of illness onset and peaked on Day 6 (AST median, 9805 U/L vs. 90 U/L, p < 0.001; ALT median, 1504 U/L vs. 49 U/L, p < 0.001). AST ≥ 203 U/L, ALT ≥ 55 U/L, AST²/ALT criteria ≥337.35, or AST/platelet count ratio index (APRI) ≥ 19.18 on Day 3 of dengue infection had a high true positive rate, 90%, 78%, 100%, or 100%, respectively, of early mortality. The platelet counts of the fatal group declined significantly than those of the survivor group since Day 3 of illness onset (median, 19 x10³/μl vs. 91 x10³/μl, p < 0.01), and aPTT values of the fatal group significantly prolonged longer since Day 5 (median, 68.7 seconds vs. 40.1 seconds, p < 0.001).

Conclusions

AST, ALT, and platelet counts should be monitored closely from Day 0 to Day 3 of dengue infection, and aPTT be followed up on Day 5 of infection to identify the individuals at risk for early mortality.

Dengue fever (DF) is currently one of the most severe public health problems. Clinical presentations of dengue are diverse and non-specific, often with unpredictable clinical progression and outcome. Hepatic dysfunction and abnormal coagulation factors are common in acute dengue illness, reflected by abnormal alanine aminotransferase (AST), aspartate aminotransferase (ALT), activated partial thromboplastin time (aPTT), and platelet counts. However, there is no information available about the monitoring frequency required, which could help identify those dengue patients who are likely to die, especially during epidemic outbreaks with limited healthcare resources. We examined all the laboratory-confirmed dengue patients who admitted to the major tertiary hospital in Tainan during the 2015 dengue outbreak, and the different trajectories of hepatic function and coagulation factors between survivors and rapidly fatal dengue patients were analyzed. Although there were no differences in AST, ALT, aPTT, and platelet counts between the survivor and fatal groups on the day DF symptoms first appeared, the differences increased from the early stages of infection and became more prominent during the early stages of the illness. The necessity of monitoring the AST, ALT, aPTT, and platelet count frequently during the febrile phase is emphasized by this study.

Seroepidemiology of dengue virus infection among adults during the ending phase of a severe dengue epidemic in southern Taiwan, 2015

BACKGROUND

A severe dengue epidemic occurred in 2015 which resulted in over 22,000 laboratory-confirmed cases. A cross-sectional seroprevalence study was conducted during the ending phase of this epidemic to evaluate the true incidence of dengue virus (DENV) infection and the level of herd immunity.

METHODS

Adult residents in three administrative districts with high dengue incidence were recruited; workers in two districts with intermediate dengue incidence were also recruited for comparison. DENV-specific IgM and IgG were tested using commercial enzyme-linked immunosorbent assays. DENV RNA was detected using commercial quantitative real-time reverse transcriptase polymerase chain reaction assay. Univariate and multivariate logistic regressions were performed to identify risk factors for recent and past DENV infection.

RESULTS

The overall seroprevalence of anti-DENV IgM and IgG in 1391 participants was 6.8 and 17.4%, respectively. The risk of recent DENV infection increased with age, with the elderly having the highest risk of infection. Living in areas with high incidence of reported dengue cases and having family members being diagnosed with dengue in 2015 were also independent risk factors for recent DENV infection. One sample was found to have asymptomatic viremia with viral load as high as 10⁵ PFU/ml.

CONCLUSIONS

Comparing the seroprevalence of anti-DENV IgM with the incidence of reported dengue cases in 2015, we estimated that 1 out of 3.7 dengue infections were reported to the surveillance system; widespread use of rapid diagnostic tests might contribute to this high reporting rate. The results also indicate that the overall herd immunity remains low and the current approved Dengvaxia® is not quite suitable for vaccination in Taiwan.

Clinical Profile and Outcome of Dengue Fever in Multidisciplinary Intensive Care Unit of a Tertiary Level Hospital in India

Background

India is one of the seven identified countries in South-East Asia region regularly reporting dengue fever (DF)/dengue hemorrhagic fever (DHF) outbreaks. Even though the dengue prodrome and evolution of illness are most often similar in many patients, progress and outcome may differ significantly depending on the severity of illness as well as treatment instituted. We studied the clinical manifestations, outcome and factors predicting mortality of serology confirmed dengue fever cases admitted in Multidisciplinary Intensive Care Unit (MICU) of a high acuity healthcare facility in India.

Methodology

All patients with serology proven dengue fever admitted to MICU between 1st July 2015 and1st December 2015 were included in the study. Clinical presentation, laboratory findings, severity of illness scores and outcome were recorded.

Results

Majority of the patients (58.4%) belonged to 21–40 year age group. Hepatic (96.8%) followed by hematological (79.2%) involvement were the most common findings. CNS involvement observed among 27%. Survival to hospital discharge was 78.9%. Respiratory and gastrointestinal system involvement was associated with increased mortality. Acute respiratory distress syndrome (ARDS), acute kidney injury (AKI) and shock were the clinical syndromes associated with mortality. Serum lactate, aspartate transaminase (AST) and alanine transaminase (ALT) were significantly elevated among non survivors. Significant difference in sequential organ failure assessment (SOFA) and acute physiology and chronic health evaluation (APACHE) scores was also observed among survivors and non survivors.

Conclusion

Organ system involvement and higher disease severity scores are strong predictors of mortality. High index of suspicion for atypical manifestations of dengue is warranted.

How to cite this article

Padyana M, Karanth S, Vaidya S, Gopaldas JA. Clinical Profile and Outcome of Dengue Fever in Multidisciplinary Intensive Care Unit of a Tertiary Level Hospital in India. Indian J Crit Care Med 2019;23(6):270–273.

Prognostic Factors in Adult Patients with Dengue: Developing Risk Scoring Models and Emphasizing Factors Associated with Death ≤7 Days after Illness Onset and ≤3 Days after Presentation

Dengue is a mosquito-borne viral disease that is a threat to global health. However, information relating to mortality ≤7 days after dengue onset and ≤3 days after presentation is limited. We retrospectively analyzed 1086 adults with dengue during a 12-year period. Three scoring models were established: model-1 (death ≤3 days after presentation), model-2 (death ≤7 days after illness onset), and model-3 (overall fatality). In total, 39 patients with fatal dengue were identified, of which 17 and 14 patients died ≤7 days after illness onset and ≤3 days after presentation, respectively. In model-1 (range: 0‒4 points), gastrointestinal bleeding ≤72 h after presentation, thrombocytopenia (<50 × 10⁸ cells/L) at presentation, and acute kidney injury after hospitalization, using a cutoff level of 2 points, exhibited good discrimination (area under the receiver curve (AUC): 0.975) between survivors and non-survivors. In model-2, the significant predictors were gastrointestinal bleeding ≤72 h after presentation, and hemoconcentration and leukocytosis after hospitalization. Model-2 (range: 0⁻4 points) showed an AUC of 0.974, with a cutoff value of 2 points. The independent factors in model-2 were the predictors of overall mortality (model-3), which include thrombocytopenia (<50 × 10⁸ cells/L) at presentation. Using a cutoff value of 2 points, model-3 (range: 0⁻7 points) revealed an excellent discrimination between survivors and non-survivors (AUC: 0.963).

Spatial Clustering of Dengue Fever Incidence and Its Association with Surrounding Greenness

With more than 58,000 cases reported by the country's Centers for Disease Control, the dengue outbreaks from 2014 to 2015 seriously impacted the southern part of Taiwan. This study aims to assess the spatial autocorrelation of the dengue fever (DF) outbreak in southern Taiwan in 2014 and 2015, and to further understand the effects of green space (such as forests, farms, grass, and parks) allocation on DF. In this study, two different greenness indexes were used. The first green metric, the normalized difference vegetation index (NDVI), was provided by the long-term NASA MODIS satellite NDVI database, which quantifies and represents the overall vegetation greenness. The latest 2013 land use survey GIS database completed by the National Land Surveying and Mapping Center was obtained to access another green metric, green land use in Taiwan. We first used Spearman's rho to find out the relationship between DF and green space, and then three spatial autocorrelation methods, including Global Moran's I, high/low clustering, and Hot Spot were employed to assess the spatial autocorrelation of DF outbreak. In considering the impact of social and environmental factors in DF, we used generalized linear mixed models (GLMM) to further clarify the relationship between different types of green land use and dengue cases. Results of spatial autocorrelation analysis showed a high aggregation of dengue epidemic in southern Taiwan, and the metropolitan areas were the main hotspots. Results of correlation analysis and GLMM showed a positive correlation between parks and dengue fever, and the other five green space metrics and land types revealed a negative association with DF. Our findings may be an important asset for improving surveillance and control interventions for dengue.