METHODS: We performed a systematic search of relevant studies on Ovid (MEDLINE), EMBASE, the Cochrane Library, Web of Science, Scopus and grey literature databases. At least two authors independently conducted the literature search, selecting eligible studies, and extracting data. Meta-analysis using random-effects model was conducted to compute the pooled odds ratio with 95% confidence intervals (CI).
FINDINGS: We obtained a total of 13,333 articles from the searches. For the final analysis, we included a total of fifteen studies among pediatric patients. Three cohort studies, two case-control studies, and one cross-sectional study found an association between obesity and dengue severity. In contrast, six cohort studies and three case-control studies found no significant relationship between obesity and dengue severity. Our meta-analysis revealed that there was 38 percent higher odds (Odds Ratio = 1.38; 95% CI:1.10, 1.73) of developing severe dengue infection among obese children compared to non-obese children. We found no heterogeneity found between studies. The differences in obesity classification, study quality, and study design do not modify the association between obesity and dengue severity.
CONCLUSION: This review found that obesity is a risk factor for dengue severity among children. The result highlights and improves our understanding that obesity might influence the severity of dengue infection.
METHOD: This is a retrospective cohort study of confirmed severe dengue patients that were admitted in 2014 to Hospital Kuala Lumpur. Data on baseline characteristics, clinical parameters, and laboratory findings at diagnosis of severe dengue were collected. The outcome of interest is death among patients diagnosed with severe dengue.
RESULTS: There were 199 patients with severe dengue included in the study. Multivariate analysis found lethargy, OR 3.84 (95% CI 1.23-12.03); bleeding, OR 8.88 (95% CI 2.91-27.15); pulse rate, OR 1.04 (95% CI 1.01-1.07); serum bicarbonate, OR 0.79 (95% CI 0.70-0.89) and serum lactate OR 1.27 (95% CI 1.09-1.47), to be statistically significant predictors of death. The regression equation to our model with the highest AUROC, 83.5 (95% CI 72.4-94.6), is: Log odds of death amongst severe dengue cases = - 1.021 - 0.220(Serum bicarbonate) + 0.001(ALT) + 0.067(Age) - 0.190(Gender).
CONCLUSION: This study showed that a large proportion of severe dengue occurred early, whilst patients were still febrile. The best prediction model to predict death at recognition of severe dengue is a model that incorporates serum bicarbonate and ALT levels.
METHODS: This was a retrospective cohort study of confirmed dengue patients who were warded in Kuala Lumpur Hospital between December 2014 and January 2015. CK, AST, ALT, hematocrit, platelet count, WBC and serum albumin were taken upon ward admission and repeated at timed intervals. Composite indices based on admission AST and ALT were analyzed. Correlation coefficients and coefficients of determination were computed.
RESULTS: Among the 365 cases reviewed, twenty-two (6%) patients had severe dengue. AST and ALT were found to be good at identification of severe dengue. The AST2/ALT composite index was the most accurate (AUC 0.83; 95% CI 0.73 - 0.93). Optimal cutoff was 402 with a sensitivity of 59.1% (95% CI: 36.4 - 79.3%) and specificity of 92.4% (95% CI: 89.1 - 95.0%). Modified cutoff of 653 had a sensitivity of 40.9% (95% CI: 20.7 - 63.7%) and specificity of 97.4% (95% CI: 95.1 - 98.8%). Our analyses also suggested that several underlying biological processes represented by biomarkers tested were unrelated despite occurring in the same disease entity. Also, markers of plasma leakage were discordant and AST was likely hepatic in origin.
CONCLUSIONS: The composite index AST2/ALT may be used as a marker for identification of severe dengue based on admission AST and ALT, with two choices of cutoff values, 402 and 653. AST is most likely of liver origin and CK does not provide additional value.
METHODS: In-depth individual interviews with thematic saturation were conducted between May and July 2018. The data was analyzed using thematic analysis.
RESULTS: Based on expert opinion, diagnosis of severe dengue is challenging as it depends on astute clinical interpretation of non-dengue-specific clinical and laboratory findings. A specific test that detects impending manifestation of severe dengue could 1) overcome failure in identifying severe disease for referral or admission, 2) facilitate timely and appropriate management of plasma leakage and bleeding, 3) overcome the lack of clinical expertise and laboratory diagnosis in rural health settings. The most important feature of any diagnostics for severe dengue is the point-of-care (POC) format where it can be performed at or near the bedside.
CONCLUSION: The development of diagnostics to detect impending severe dengue is warranted to reduce the morbidity and mortality rates of dengue infection and it should be prioritized.