ArticleRenal failure2022
A new model to predict acute kidney injury after cardiac surgery in patients with renal insufficiency.
Article in Renal failure, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers, 1 of them a synthesis that pooled it.
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Who cites it
8 citing papers in PubMed, 1 synthesis or guideline pooled it, 11 citations in OpenAlex.
- A systematic review of cardiac surgery clinical prediction models that include intra-operative variables.Perfusion · 2025Pooled it
- Article
- Integration of continuous renal replacement therapy in patients on extracorporeal life support: timing, modality, and future directions.Renal failure · 2025Article
- Development and validation of a prediction model for acute kidney injury following cardiac valve surgery.Frontiers in medicine · 2025Article
- Meaning and Management of Perioperative Oliguria.Anesthesiology · 2024Article
- Diagnosis, pathophysiology and preventive strategies for cardiac surgery-associated acute kidney injury: a narrative review.European journal of medical research · 2023Review
- Acute kidney injury after major orthopedic surgery: A retrospective study of frequency and related risk factors.Acta orthopaedica et traumatologica turcica · 2022Article
- Urinary and serum biomarkers of renal injury in coronary artery bypass grafting: a prospective evaluation with new biomarkers'.Jornal brasileiro de nefrologiaArticle
Corrections and comments
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Authors and funding
4 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectiveTo establish a simple model for predicting postoperative acute kidney injury (AKI) requiring renal replacement therapy (RRT) in patients with renal insufficiency (CKD stages 3-4) who underwent cardiac surgery.
methodsA total of 330 patients were enrolled. Among them, 226 were randomly selected for the development group and the remaining 104 for the validation group. The primary outcome was AKI requiring RRT. A nomogram was constructed based on the multivariate analysis with variables selected by the application of the least absolute shrinkage and selection operator. Meanwhile, the discrimination, calibration, and clinical power of the new model were assessed and compared with those of the Cleveland Clinic score and Simplified Renal Index (SRI) score in the validation group. Results: The rate of RRT in the development group was 10.6% (
conclusionsWe developed and validated a powerful predictive model for predicting severe AKI after cardiac surgery in patients with renal insufficiency, which would be helpful to assess the risk for severe AKI requiring RRT.
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