Interactive cardiovascular and thoracic surgery · 2016
A clinical score to predict acute kidney injury after cardiac surgery in a Southeast-Asian population.
СтатьяМногоцентровое исследованиеНазвание и аннотация: Перевод в очереди
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Nah Chung Wei, Ti Lian Kah, Liu Weiling, Ng Roderica Rui Ge, Shen Liang, Chew Sophia Tsong Huey
Аннотация
OBJECTIVES: Acute kidney injury (AKI) post-cardiac surgery is associated with significant in-hospital and long-term morbidity. This study aimed to develop a risk score for postoperative AKI in a Southeast-Asian population.
METHODS: A total of 2508 patients underwent cardiac surgery at the two main heart centres in Singapore between July 2008 and November 2011, of which 2385 met the inclusion criteria. The primary outcome was AKI, defined using the Acute Kidney Injury Network (AKIN) criteria. The scoring model was developed on the test cohort of 2385 and validated with another 500 prospectively recruited patients. Logistic regression analysis was used to identify independent predictors of AKI.
RESULTS: The risk factors in this model are age ≥65 years, hypertension, estimate glomerular filtration rate (eGFR) ≤60 ml/min, use of intra-aortic balloon pump and cardiopulmonary bypass (CPB) time ≥120 min, which were similar to previous AKI risk models. Other risk factors in our model include preoperative anaemia, intraoperative red blood cell transfusion and lowest haematocrit during CPB, which have not been described previously. The clinical score ranged from 0 to 14 points with three major risk categories. The AKI frequencies are as follows: 0-4 points (18%), 5-8 points (39%) and 9-14 points (64%). The area under the receiver operating curve (ROC) for the test cohort was 0.70 (95% CI 0.68-0.72), similar to the validation cohort (0.75; 95% CI 0.70-0.80).
CONCLUSIONS: In conclusion, the risk model is valid in predicting AKI post-cardiac surgery and can be used for the early diagnosis and treatment of AKI.
METHODS: A total of 2508 patients underwent cardiac surgery at the two main heart centres in Singapore between July 2008 and November 2011, of which 2385 met the inclusion criteria. The primary outcome was AKI, defined using the Acute Kidney Injury Network (AKIN) criteria. The scoring model was developed on the test cohort of 2385 and validated with another 500 prospectively recruited patients. Logistic regression analysis was used to identify independent predictors of AKI.
RESULTS: The risk factors in this model are age ≥65 years, hypertension, estimate glomerular filtration rate (eGFR) ≤60 ml/min, use of intra-aortic balloon pump and cardiopulmonary bypass (CPB) time ≥120 min, which were similar to previous AKI risk models. Other risk factors in our model include preoperative anaemia, intraoperative red blood cell transfusion and lowest haematocrit during CPB, which have not been described previously. The clinical score ranged from 0 to 14 points with three major risk categories. The AKI frequencies are as follows: 0-4 points (18%), 5-8 points (39%) and 9-14 points (64%). The area under the receiver operating curve (ROC) for the test cohort was 0.70 (95% CI 0.68-0.72), similar to the validation cohort (0.75; 95% CI 0.70-0.80).
CONCLUSIONS: In conclusion, the risk model is valid in predicting AKI post-cardiac surgery and can be used for the early diagnosis and treatment of AKI.