ArticleBMC urology2023
Risk factors and predictive model for acute kidney Injury Transition to acute kidney disease in patients following partial nephrectomy.
Article in BMC urology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed.
- Predicting hemorrhagic complications in robotic-assisted partial nephrectomy for renal tumors: simplifying risk assessment with tumor diameter and depth.Journal of robotic surgery · 2025Article
- The burden of acute kidney disease: an epidemiological review and importance of follow-up care.Clinical kidney journal · 2025Review
- Comparing Perioperative Complications of Off-Clamp versus On-Clamp Partial Nephrectomy for Renal Cancer Using a Novel Energy Balancing Weights Method.Life (Basel, Switzerland) · 2024Article
- Machine learning-based risk prediction of acute kidney disease and hospital mortality in older patients.Frontiers in medicine · 2024Article
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4 authors.
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Abstract
purposeAcute kidney disease (AKD) is believed to be involved in the transition from acute kidney injury (AKI) to chronic kidney disease in general populations, but little is understood about this possibility among kidney surgical populations. This study aimed to elucidate the incidence of AKD after partial nephrectomy and risk factors that promote the AKI to AKD transition.
methodsFrom January 2010 to January 2020, this study retrospectively collected a dataset of consecutive patients with renal masses undergoing partial nephrectomy in 4 urological centers. Cox proportional regression analyses were adopted to identify risk factors that promoted the AKI to AKD transition. To avoid overfitting, the results were then verified by logistic least absolute shrinkage and selection operator (LASSO) regression. A nomogram was then constructed and validated for AKI to AKD transition prediction.
resultsAKI and AKD occurred in 228 (21.4%) and 42 (3.9%) patients among a total of 1062 patients, respectively. In patients with AKI, multivariable Cox regression analysis and LASSO regression identified that age (HR 1.078, 1.029-1.112, p < 0.001), baseline eGFR (HR 1.015, 1.001-1.030, p < 0.001), RENAL score (HR1.612, 1.067-2.437, p = 0.023), ischemia time > 30 min (HR 7.284, 2.210-23.999, p = 0.001), and intraoperative blood loss > 300ml (HR 8.641, 2.751-27.171, p < 0.001) were risk factors for AKD transition. These five risk factors were then integrated into a nomogram. The nomogram showed excellent discrimination, calibration, and clinical net benefit ability.
conclusionAround 3.9% patients following partial nephrectomy would transit from AKI to AKD. Intraoperative blood loss and ischemia time need to be diminished to avoid on-going functional decline. Our nomogram can accurately predict the transition from AKI to AKD.
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