Observational studyRenal failure2020
A visual risk assessment tool for acute kidney injury after intracranial aneurysm clipping surgery.
Observational study in Renal failure, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers, 1 of them a synthesis that pooled it.
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Who cites it
9 citing papers in PubMed, 1 synthesis or guideline pooled it, 11 citations in OpenAlex.
- Characterization of Risk Prediction Models for Acute Kidney Injury: A Systematic Review and Meta-analysis.JAMA network open · 2023Pooled it
- Incidence of contrast-associated acute kidney injury differs by procedure type in neuroendovascular surgery.The neuroradiology journal · 2026Article
- A machine learning predictive model for acute kidney injury among aneurysmal subarachnoid hemorrhage patients.BMC medical informatics and decision making · 2025Article
- Development and validation of a nomogram for predicting low Kt/VBMC nephrology · 2025Article
- A low preoperative platelet-to-white blood cell ratio is associated with acute kidney injury following cerebral aneurysm treatment in South Korea.Acute and critical care · 2025Article
- Development and validation of a nomogram for predicting in-hospital death in cirrhotic patients with acute kidney injury.BMC nephrology · 2024Article
- Association between serum calcium level and the risk of acute kidney injury in ICU patients with subarachnoid hemorrhage: a retrospective cohort study.Frontiers in neurology · 2024Article
- Article
- Development and validation of a nomogram for predicting acute kidney injury after orthotopic liver transplantation.Renal failure · 2021Article
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Authors and funding
14 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectiveThe aim of the study was to establish a predictive postoperative nomogram for acute kidney injury (AKI) after intracranial aneurysm clipping surgery, in order to early identify patients with high postoperative AKI risk.
methodsThis is a retrospective study, which included patients who underwent intracranial aneurysm clipping surgery. Multivariate logistic regression was employed to select confound factors that associated with AKI, then incorporated into the nomogram. The predictive accuracy of the model was assessed by concordance index (C-Index).
resultsA total of 365 patients after intracranial aneurysm clipping surgery were enrolled in the study eventually, of which 68 (18.63%) suffered postoperative AKI, and the incidence of stage 1, stage 2 and stage 3 were 92.65% (63/68), 5.88% (4/68), and 1.47% (1/68), respectively. Univariate logistic regression revealed that high density lipoprotein (HDL), prothrombin time (PT), estimated glomerular filtration rate (eGFR), size of aneurysm ≥10 mm, and aneurysm ruptured before surgery were associated with AKI after surgery, while multivariate logistic regression showed same results as the size of aneurysm ≥10 mm and aneurysm ruptured were independent AKI risk factors. In addition, the nomogram demonstrated a good accuracy in estimating intracranial aneurysm clipping associated AKI, as a C-Index and a bootstrap-corrected one of 0.772 and 0.737, respectively. Moreover, calibration plots showed consistency with the actual presence of AKI.
conclusionThe novel nomogram model can serve as a promising predictive tool to improve the identification of AKI among those who underwent intracranial aneurysm clipping surgery.
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