ArticleCanadian journal of kidney health and disease2015
Validating a scoring tool to predict acute kidney injury (AKI) following cardiac surgery.
Article in Canadian journal of kidney health and disease, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers, 1 of them a synthesis that pooled it.
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Who cites it
13 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Clinical prediction models in cardiac surgery-associated acute kidney injury: a systematic review and meta-analysis.Critical care (London, England) · 2026Pooled it
- Article
- Temporary bilateral clamping of renal arteries induces ischemia-reperfusion: A new pig model of acute kidney injury using total intravenous anesthesia.Physiological reports · 2025Article
- Explainable Preoperative Automated Machine Learning Prediction Model for Cardiac Surgery-Associated Acute Kidney Injury.Journal of clinical medicine · 2022Article
- Predicting Acute Kidney Injury after Cardiac Surgery by Machine Learning Approaches.Journal of clinical medicine · 2020Article
- Temporal Pattern Detection to Predict Adverse Events in Critical Care: Case Study With Acute Kidney Injury.JMIR medical informatics · 2020Article
- Biomarker enhanced risk prediction for development of AKI after cardiac surgery.BMC nephrology · 2018Article
- The National Early Warning Score and its subcomponents recorded within ±24 h of emergency medical admission are poor predictors of hospital-acquired acute kidney injury.Clinical medicine (London, England) · 2018Article
- Predicting AKI in emergency admissions: an external validation study of the acute kidney injury prediction score (APS).BMJ open · 2017Article
- Improving the Prediction of Cardiac Surgery-Associated Acute Kidney Injury.Kidney international reports · 2017Article
- Utilizing electronic health records to predict acute kidney injury risk and outcomes: workgroup statements from the 15(th) ADQI Consensus Conference.Canadian journal of kidney health and disease · 2016Review
- A Predictive Model for Assessing Surgery-Related Acute Kidney Injury Risk in Hypertensive Patients: A Retrospective Cohort Study.PloS one · 2016Article
- Applicability of the Cleveland clinic scoring system for the risk prediction of acute kidney injury after cardiac surgery in a South Asian cohort.Indian heart journalArticle
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4 authors.
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No grant is acknowledged in the PubMed record.
Abstract
backgroundAcute kidney injury (AKI) after cardiac surgery is associated with an increased risk of mortality. Preoperative risk scores can identify patients at risk for AKI and facilitate preventive strategies. Currently, validated risk scores are used to predict AKI requiring dialysis (AKI-D); less is known about whether these tools predict less severe forms of AKI.
objectiveTo evaluate the Cleveland Clinic scoring tool in predicting both AKI-D and less severe stages of AKI in patients after cardiac surgery in a Canadian tertiary care center.
designRetrospective case-control study.
settingRegina Qu'Appelle Health Region (RQHR) from 2007 to 2011. PATIENTS: Patients who underwent cardiac surgery and developed postoperative kidney injury (n = 2316). MEASUREMENTS: Data on risk factors for AKI and outcomes of cardiac surgery were collected from a retrospective chart review.
methodsThe primary outcome was AKI, defined as Stage 1 (increase in serum creatinine 1.5-1.9 X baseline within 5 days), Stage 2 (increase 2.0-2.9 X baseline), or Stage 3 (increase 3.0 X baseline or more OR initiation of dialysis during hospital stay). We assessed the performance of a modified version of the Cleveland Clinic tool using receiver operating curve analyses.
resultsThe incidence of AKI was 6.1% (Stage 1), 2.6% (Stage 2), and 5.8% (Stage 3). The area under the curve (AUC) for the Cleveland score was 0.61 (95% CI: 0.56 to 0.65; p < 0.001) for Stage 1, 0.61 (95% CI: 0.54 to 0.68; p < 0.01) for Stage 2, and 0.78 (95% CI: 0.74 to 0.82; p < 0.001) for Stage 3. Greater level of risk on the Cleveland tool was associated with a higher risk of Stage 3 AKI. LIMITATIONS: Lack of prospective validation.
conclusionsThe modified Cleveland Clinic tool was valid in identifying patients with severe stages of AKI but did not have strong discrimination for early AKI stages.
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