Do We Need to Personalize Renal Function Assessment in the Stratification of Patients Undergoing Cardiac Surgery?
BACKGROUND: Renal dysfunction is an independent predictor of morbidity and mortality in cardiac surgery. For a better assessment of renal function, calculation of creatinine clearance (CC) may be necessary.
OBJECTIVE: To objectively evaluate whether CC is a better risk predictor than serum creatinine (SC) in patients undergoing cardiac surgery.
METHODS: Analysis of 3,285 patients registered in a prospective, consecutive and mandatory manner in the Sao Paulo Registry of Cardiovascular Surgery (REPLICCAR) between November 2013 and January 2015. Values of SC, CC (Cockcroft-Gault) and EuroSCORE II were obtained. Association analysis of SC and CC with morbidity and mortality was performed by calibration and discrimination tests. Independent multivariate models with SC and CC were generated by multiple logistic regression to predict morbidity and mortality following cardiac surgery.
RESULTS: Despite the association between SC and mortality, it did not calibrate properly the risk groups. There was an association between CC and mortality with good calibration of risk groups. In mortality risk prediction, SC was uncalibrated with values > 1.35 mg /dL (p < 0.001). The ROC curve showed that CC is better than SC in predicting both morbidity and mortality risk. In the multivariate model without CC, SC was the only predictor of morbidity, whereas in the model without SC, CC was not only a mortality predictor, but also the only morbidity predictor.
CONCLUSION: Compared with SC, CC is a better parameter of renal function in risk stratification of patients undergoing cardiac surgery.
| Medienart: |
E-Artikel |
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| Erscheinungsjahr: |
2017 |
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| Erschienen: |
2017 |
| Enthalten in: |
Zur Gesamtaufnahme - volume:109 |
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| Enthalten in: |
Arquivos brasileiros de cardiologia - 109(2017), 4 vom: 04. Okt., Seite 290-298 |
| Sprache: |
Portugiesisch |
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| Beteiligte Personen: |
Arthur, Camila P S [VerfasserIn] |
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| Links: |
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| Themen: |
AYI8EX34EU |
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| Anmerkungen: |
Date Completed 24.11.2017 Date Revised 10.12.2019 published: Print-Electronic Citation Status MEDLINE |
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| doi: |
10.5935/abc.20170129 |
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| funding: |
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| Förderinstitution / Projekttitel: |
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| PPN (Katalog-ID): |
NLM275482847 |
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| 500 | |a Date Revised 10.12.2019 | ||
| 500 | |a published: Print-Electronic | ||
| 500 | |a Citation Status MEDLINE | ||
| 520 | |a BACKGROUND: Renal dysfunction is an independent predictor of morbidity and mortality in cardiac surgery. For a better assessment of renal function, calculation of creatinine clearance (CC) may be necessary | ||
| 520 | |a OBJECTIVE: To objectively evaluate whether CC is a better risk predictor than serum creatinine (SC) in patients undergoing cardiac surgery | ||
| 520 | |a METHODS: Analysis of 3,285 patients registered in a prospective, consecutive and mandatory manner in the Sao Paulo Registry of Cardiovascular Surgery (REPLICCAR) between November 2013 and January 2015. Values of SC, CC (Cockcroft-Gault) and EuroSCORE II were obtained. Association analysis of SC and CC with morbidity and mortality was performed by calibration and discrimination tests. Independent multivariate models with SC and CC were generated by multiple logistic regression to predict morbidity and mortality following cardiac surgery | ||
| 520 | |a RESULTS: Despite the association between SC and mortality, it did not calibrate properly the risk groups. There was an association between CC and mortality with good calibration of risk groups. In mortality risk prediction, SC was uncalibrated with values > 1.35 mg /dL (p < 0.001). The ROC curve showed that CC is better than SC in predicting both morbidity and mortality risk. In the multivariate model without CC, SC was the only predictor of morbidity, whereas in the model without SC, CC was not only a mortality predictor, but also the only morbidity predictor | ||
| 520 | |a CONCLUSION: Compared with SC, CC is a better parameter of renal function in risk stratification of patients undergoing cardiac surgery | ||
| 650 | 4 | |a Evaluation Study | |
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| 700 | 1 | |a Osternack, Diogo |e verfasserin |4 aut | |
| 700 | 1 | |a Nakazone, Marcelo Arruda |e verfasserin |4 aut | |
| 700 | 1 | |a Goncharov, Maxim |e verfasserin |4 aut | |
| 700 | 1 | |a Lisboa, Luiz A F |e verfasserin |4 aut | |
| 700 | 1 | |a Dallan, Luís A O |e verfasserin |4 aut | |
| 700 | 1 | |a Pomerantzeff, Pablo M A |e verfasserin |4 aut | |
| 700 | 1 | |a Jatene, Fabio B |e verfasserin |4 aut | |
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