Background The ability to predict the progression to severe dengue is crucial in managing patients with dengue fever. Severe dengue is defined by one or more of the following signs: severe plasma leakage, severe bleeding, or severe organ involvement as it can be a life-threatening condition if left untreated.
 Objective To identify clinical manifestations and laboratory parameters associated with dengue hemorrhagic fever disease progression in children by systematic review and meta-analysis.
 Methods We searched six medical databases for studies published from Jan 1, 2000, to Dec 31, 2020. The meta-analysis used random-effects or fixed-effects models to estimate pooled effect sizes. We assessed heterogeneity using Cochrane Q and I2 statistics, publication bias by Egger’s test and LFK index (Doi plot), and categorized subgroup analysis by country. This study was registered with PROSPERO, CRD42021224439.
 Results We included 49 papers in the systematic review, and we encased the final selected 39 papers comprising 23 potential predictors in the meta-analyses. The other 10 papers were not included because the raw data could not be calculated for the effect measure in the meta-analysis. Among 23 factors studied, seven clinical manifestations demonstrated association with disease progression in children, including neurological signs, gastrointestinal bleeding, clinical fluid accumulation, hepatomegaly, vomiting, abdominal pain, and petechiae. Six laboratory parameters were associated during the early days of illness, including elevated hematocrit, aspartate aminotransferase [AST], and alanine aminotransferase [ALT], low platelet count, low albumin levels, and elevated activated partial thromboplastin time. Dengue virus serotype 2 (DENV-2) and secondary infections were also associated with severe disease progression.
 Conclusion This review supports the use of the warning signs described in the 2009 WHO guidelines. In addition, monitoring serum albumin, AST/ALT levels, identifying infecting dengue serotypes, and immunological status can improve the prediction of further risk of disease progression.
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