ArticleKidney international reports2017
Improving the Prediction of Cardiac Surgery-Associated Acute Kidney Injury.
Article in Kidney international reports, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers, 1 of them a synthesis that pooled it.
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Who cites it
10 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Machine learning in predicting cardiac surgery-associated acute kidney injury: A systemic review and meta-analysis.Frontiers in cardiovascular medicine · 2022Pooled it
- Thrombelastometry guided blood-component therapy after cardiac surgery: a randomized study.BMC anesthesiology · 2019Trial
- Establishment and validation of a prediction model for acute kidney injury in moderate severe and severe acute pancreatitis patients.European journal of medical research · 2025Article
- Predicting pre- and post-operative acute kidney injury in elderly patients with coronary artery disease.Heliyon · 2024Article
- Prospective evaluation of novel biomarkers of acute kidney injury in dogs following cardiac surgery under cardiopulmonary bypass.Journal of veterinary emergency and critical care (San Antonio, Tex. : 2001) · 2022Article
- Associated factors and short-term mortality of early versus late acute kidney injury following on-pump cardiac surgery.Interactive cardiovascular and thoracic surgery · 2022Article
- IGFBP7 as a preoperative predictor of congestive acute kidney injury after cardiac surgery.Open heart · 2022Article
- Risk Factors for Acute Kidney Injury Following Cardiac Surgery and Performance of Leicester Score in a Spanish Cohort.Journal of clinical medicine · 2022Article
- Machine learning for the prediction of acute kidney injury in patients after cardiac surgery.Frontiers in surgery · 2022Article
- Kidney Injury Molecule 1 (KIM-1) as an Early Predictor for Acute Kidney Injury in Post-Cardiopulmonary Bypass (CPB) in Open Heart Surgery Patients.International journal of nephrology · 2019Article
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Authors and funding
9 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
introductionAcute kidney injury (AKI) is a potentially fatal complication of cardiac surgery. The inability to predict cardiac surgery-associated AKI is a major barrier to prevention and early treatment. Current clinical risk models for the prediction of cardiac surgery-associated AKI are insufficient, particularly in patients with preexisting kidney dysfunction.
methodsTo identify intraoperative variables that might improve the performance of a validated clinical risk score (Cleveland Clinic Score, CCS) for the prediction of cardiac surgery-associated AKI, we conducted a prospective cohort study in 289 consecutive elective cardiac surgery patients at a tertiary care center. We compared the area under the receiver operator characteristic curve (AUC) of a base model including only the CCS with models containing additional selected intraoperative variables including mean arterial pressure, hematocrit, duration of procedure, blood transfusions, and fluid balance. AKI was defined by the Kidney Disease Improving Global Outcomes 2012 criteria.
resultsThe CCS alone gave an AUC of 0.72 (95% confidence interval, 0.62-0.82) for postoperative AKI. Nadir intraoperative hematocrit was the only variable that improved AUC for postoperative AKI when added to the CCS (AUC = 0.78; 95% confidence interval, 0.70-0.87; DISCUSSION: Nadir intraoperative hematocrit is useful in improving discrimination of clinical risk scores for AKI, and may provide a target for intervention.
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