Prevalence of acute kidney injury among dengue cases: a systematic review and meta-analysis.
Ganesh BushiMuhammed ShabilBijaya Kumar PadhiMohammed AhmedPratima PandeyPrakasini SatapathySarvesh RustagiKeerti Bhusan PradhanZahraa Haleem Al-QaimRanjit SahPublished in: Transactions of the Royal Society of Tropical Medicine and Hygiene (2023)
Numerous studies have shown a correlation between dengue virus (DENV) infection and kidney disease. However, there is no existing meta-analysis on the prevalence of kidney diseases in the dengue population. A thorough systematic review and meta-analysis were undertaken to determine the prevalence of renal problems in people with DENV infection in order to fill this knowledge gap. A rigorous electronic literature search was carried out up to 25 January 2023 in a number of databases, including ProQuest, EBSCOhost, Scopus, PubMed and Web of Science. The search aimed to find articles that reported on the prevalence of kidney diseases in patients with DENV infection. Using the modified Newcastle-Ottawa Scale, the quality of the included studies was assessed. The meta-analysis included a total of 37 studies with 21 764 participants reporting on the prevalence of acute kidney injury (AKI) in individuals with DENV infection. The pooled prevalence of AKI in dengue patients was found to be 8% (95% confidence interval 6 to 11), with high heterogeneity across studies. The studies included are of moderate quality. The study revealed a high AKI prevalence in dengue patients, underlining the need for regular renal examination to detect AKI early and reduce hospitalization risk. Further research is needed to understand the dengue-kidney relationship and develop effective management strategies.
Keyphrases
- dengue virus
- acute kidney injury
- zika virus
- aedes aegypti
- risk factors
- systematic review
- case control
- end stage renal disease
- cardiac surgery
- chronic kidney disease
- emergency department
- ejection fraction
- mental health
- prognostic factors
- newly diagnosed
- randomized controlled trial
- single cell
- patient reported outcomes
- machine learning
- clinical trial
- meta analyses
- big data
- adverse drug
- study protocol