Wasp venom-induced acute kidney injury: current progress and prospects

Previous studies have highlighted the significant role of complement activation in kidney injuries induced by rhabdomyolysis, intravascular hemolysis, sepsis, and ischemia-reperfusion. Nevertheless, the specific role and mechanism of complement activation in acute kidney injury (AKI) caused by wasp venom remain unclear. The aim of this study was to elucidate the specific complement pathway activated and investigate complement activation in AKI induced by wasp venom. In this study, a complement-depleted mouse model was used to investigate the role of complement in wasp venom-induced AKI. Mice were randomly categorized into control, cobra venom factor (CVF), AKI, and CVF + AKI groups. Compared to the AKI group, the CVF + AKI group showed improved pathological changes in kidneys and reduced blood urea nitrogen (BUN) levels. The expression levels of renal complement 3 (C3), complement 5 (C5), complement 1q (C1q), factor B (FB), mannose-binding lectin (MBL), and C5b-9 in AKI group were upregulated compared with the control group. Conversely, the renal tissue expression levels of C3, C5, C1q, FB, MBL, and C5b-9 were decreased in the CVF + AKI group compared to those in the AKI group. Complement activation occurs through all three pathways in AKI induced by wasp venom. Furthermore, complement depletion by CVF attenuates wasp venom-induced nephrotoxicity, suggesting that complement activation plays a primary role in the pathogenesis of wasp venom-induced AKI.

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Machine-Learning Based Prediction Model for Acute Kidney Injury Induced by Multiple Wasp Stings: Incorporating Four Admission Clinical Indices

Wu,

Zhang,

Zhang

et al. 2024

Preprint

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Acute kidney injury (AKI) following multiple wasp stings is a severe complication with potentially poor outcomes. Despite extensive research on AKI's risk factors, predictive models for wasp sting-related AKI are limited. This study aims to develop and validate a machine learning-based clinical prediction model for AKI in individuals with wasp stings. We retrospectively analyzed clinical data from 214 patients with wasp sting injuries. Among these patients, 34.6% (74/214) developed AKI. Using least absolute shrinkage and selection operator (LASSO) regression and multivariate logistic regression analysis, the number of stings, presence of gross hematuria, systemic inflammatory response index (SIRI), and platelet count were identified as prognostic factors. A nomogram was constructed and evaluated for its predictive accuracy, showing an area under the curve (AUC) of 0.757 (95% CI 0.711 to 0.804) and a concordance index (C-index) of 0.75. The model's performance was assessed through internal validation, leave-one-out cross-validation, net reclassification improvement (NRI), integrated discrimination improvement (IDI), and decision curve analysis (DCA). Validation confirmed the model's reliability and superior discrimination ability over existing models, as demonstrated by NRI, IDI, and DCA. This nomogram accurately predicts the risk of AKI in wasp sting patients, facilitating early identification and management of those at risk.

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Wasp venom-induced acute kidney injury: current progress and prospects

Cited by 4 publications

References 90 publications

A rare concurrence of acute tubular necrosis and chronic glomerular sclerosis in a patient with wasp stings

A rare concurrence of acute tubular necrosis and chronic glomerular sclerosis in a patient with wasp stings

Complement activation in wasp venom-induced acute kidney injury

Machine-Learning Based Prediction Model for Acute Kidney Injury Induced by Multiple Wasp Stings: Incorporating Four Admission Clinical Indices

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