Abstract
BACKGROUND: Dengue infection poses a significant global health challenge, particularly in tropical and subtropical regions. Among its severe complications, Acute kidney injury (AKI) stands out due to its association with increased morbidity, mortality, and healthcare burdens. This Meta-analysis aim to identify and evaluate the predictors of AKI among dengue patients, facilitating early detection and management strategies to mitigate AKI's impact. METHODS: We searched PubMed, EMBASE, and Web of Science databases, covering literature up to February 2024. We included human observational studies reporting on AKI predictors in confirmed dengue cases. Nested-Knowledge software was used for screening and data extraction. The Newcastle-Ottawa Scale was used for quality assessment. R software (V 4.3) was utilized to compute pooled odds ratios (ORs) and 95% confidence intervals (CIs) for each predictor. RESULTS: Our search yielded nine studies involving diverse geographic locations and patient demographics. A total of 9,198 patients were included in the studies, with 542 diagnosed with AKI. in which key predictors of AKI identified include severe forms of dengue (OR: 2.22, 95% CI: 1.02-3.42), male gender (OR: 3.13, 95% CI: 1.82-4.44), comorbidities such as diabetes mellitus (OR: 3.298, 95% CI: 0.274-6.322), and chronic kidney disease (OR: 2.2, 95% CI: 0.42-11.24), as well as co-infections and clinical manifestations like rhabdomyolysis and major bleeding. CONCLUSION: Our study identifies several predictors of AKI in dengue patients. These findings indicate the importance of early identification and intervention for high-risk individuals. Future research should focus on standardizing AKI diagnostic criteria within the dengue context and exploring the mechanisms underlying these associations to improve patient care and outcomes.