The Pattern of Longitudinal Change in Serum Creatinine and 90-Day Mortality After Major Surgery.

OBJECTIVE: Calculate mortality risk that accounts for both severity and recovery of postoperative kidney dysfunction using the pattern of longitudinal change in creatinine. BACKGROUND: Although the importance of renal recovery after acute kidney injury (AKI) is increasingly recognized, the complex association that accounts for longitudinal creatinine changes and mortality is not fully described. METHODS: We used routinely collected clinical information for 46,299 adult patients undergoing major surgery to develop a multivariable probabilistic model optimized for nonlinearity of serum creatinine time series that calculates the risk function for 90-day mortality. We performed a 70/30 cross validation analysis to assess the accuracy of the model. RESULTS: All creatinine time series exhibited nonlinear risk function in relation to 90-day mortality and their addition to other clinical factors improved the model discrimination. For any given severity of AKI, patients with complete renal recovery, as manifested by the return of the discharge creatinine to the baseline value, experienced a significant decrease in the odds of dying within 90 days of admission compared with patients with partial recovery. Yet, for any severity of AKI, even complete renal recovery did not entirely mitigate the increased odds of dying, as patients with mild AKI and complete renal recovery still had significantly increased odds for dying compared with patients without AKI [odds ratio: 1.48 (95% confidence interval: 1.30-1.68)]. CONCLUSIONS: We demonstrate the nonlinear relationship between both severity and recovery of renal dysfunction and 90-day mortality after major surgery. We have developed an easily applicable computer algorithm that calculates this complex relationship.

Acute and Chronic Kidney Disease and Cardiovascular Mortality After Major Surgery.

OBJECTIVE: The aim of the study was to determine the long-term cardiovascular-specific mortality in patients with acute kidney injury (AKI) or chronic kidney disease (CKD) after major surgery. BACKGROUND: In surgical patients, pre-existing CKD and postoperative AKI are associated with increases in all-cause mortality. METHODS: In a single-center cohort of 51,457 adult surgical patients undergoing major inpatient surgery, long-term cardiovascular-specific mortality was modeled using a multivariable subdistributional hazards model while treating any other cause of death as a competing risk and accounting for the progression to end-stage renal disease (ESRD) after discharge. Pre-existing CKD and ESRD, and postoperative AKI were the main independent predictors. RESULTS: Before the admission, 4% and 8% of the cohort had pre-existing ESRD and CKD not requiring renal replacement therapy, respectively. During hospitalization, 39% developed AKI. At 10-year follow-up, adjusted cardiovascular-specific mortality estimates were 6%, 11%, 12%, 19%, and 27% for patients with no kidney disease, AKI with no CKD, CKD with no AKI, AKI with CKD, and ESRD, respectively (P < 0.001). This association remained after excluding 916 patients who progressed to ESRD after discharge, although it was significantly amplified among them. Compared with patients having no kidney disease, adjusted hazard ratios for cardiovascular mortality were significantly higher among patients with kidney disease, ranging from 1.95 (95% confidence interval, 1.80-2.11) for patients with de novo AKI to 5.70 (95% confidence interval, 5.00-6.49) for patients with pre-existing ESRD. CONCLUSIONS: Both AKI and CKD were associated with higher long-term cardiovascular-specific mortality compared with patients having no kidney disease.

Mortality and Cost of Acute and Chronic Kidney Disease after Vascular Surgery.

BACKGROUND: Both acute kidney injury (AKI) and chronic kidney disease (CKD) are common yet underappreciated risk factors for adverse perioperative outcomes. We hypothesize that AKI and CKD are associated with similar increases in 90-day mortality and cost in patients undergoing major vascular surgery. METHODS: We used multivariable regression analyses to evaluate the associations between AKI and CKD and incremental 90-day mortality and hospital cost in a single-center cohort of 3646 adult patients undergoing major vascular surgery. We defined AKI using Kidney Disease: Improving Global Outcomes criteria as change in creatinine ≥ 0.3 mg/dL or ≥ 50% increase from the reference value. CKD was determined from medical history. Regression models were adjusted for demographic and socioeconomic characteristics, comorbid conditions, surgery type, and postoperative complications. RESULTS: The prevalence of kidney disease among vascular surgery patients is high with 49% of patients developing AKI during hospitalization and 17% presenting with CKD on admission. In risk-adjusted logistic regression analysis, perioperative AKI (odds ratio 2.2, 95% confidence interval 1.5-3.3) was the most significant predictor of 90-day mortality. The risk-adjusted average cost was significantly higher for patients with any type of kidney disease. The incremental cost of having any type of kidney disease ranged from $9100 to $19,100, even after adjustment for underlying comorbidities and other postoperative complications. CONCLUSIONS: Kidney disease after major vascular surgery is associated with significant increases in 90-day mortality and cost with the highest risk observed among patients with AKI regardless of previous CKD.

Cost and Mortality Associated With Postoperative Acute Kidney Injury.

OBJECTIVE: To determine the incremental hospital cost and mortality associated with the development of postoperative acute kidney injury (AKI) and with other associated postoperative complications. BACKGROUND: Each year 1.5 million patients develop a major complication after surgery. Postoperative AKI is one of the most common postoperative complications and is associated with an increase in hospital mortality and decreased survival for up to 15 years after surgery. METHODS: In a single-center cohort of 50,314 adult surgical patients undergoing major inpatient surgery, we applied risk-adjusted regression models for cost and mortality using postoperative AKI and other complications as the main independent predictors. We defined AKI using consensus Risk, Injury, Failure, Loss and End-Stage Renal Disease criteria. RESULTS: The prevalence of AKI was 39% among 50,314 patients with available serum creatinine. Patients with AKI were more likely to have postoperative complications and had longer lengths of stay in the intensive care unit and the hospital. The risk-adjusted average cost of care for patients undergoing surgery was $42,600 for patients with any AKI compared with $26,700 for patients without AKI. The risk-adjusted 90-day mortality was 6.5% for patients with any AKI compared with 4.4% for patients without AKI. Serious postoperative complications resulted in increased cost of care and mortality for all patients, but the increase was much larger for those patients with any degree of AKI. CONCLUSIONS: Hospital costs and mortality are strongly associated with postoperative AKI, are correlated with the severity of AKI, and are much higher for patients with other postoperative complications in addition to AKI.

Application of Machine Learning Techniques to High-Dimensional Clinical Data to Forecast Postoperative Complications.

OBJECTIVE: To compare performance of risk prediction models for forecasting postoperative sepsis and acute kidney injury. DESIGN: Retrospective single center cohort study of adult surgical patients admitted between 2000 and 2010. PATIENTS: 50,318 adult patients undergoing major surgery. MEASUREMENTS: We evaluated the performance of logistic regression, generalized additive models, naïve Bayes and support vector machines for forecasting postoperative sepsis and acute kidney injury. We assessed the impact of feature reduction techniques on predictive performance. Model performance was determined using the area under the receiver operating characteristic curve, accuracy, and positive predicted value. The results were reported based on a 70/30 cross validation procedure where the data were randomly split into 70% used for training the model and the 30% for validation. MAIN RESULTS: The areas under the receiver operating characteristic curve for different models ranged between 0.797 and 0.858 for acute kidney injury and between 0.757 and 0.909 for severe sepsis. Logistic regression, generalized additive model, and support vector machines had better performance compared to Naïve Bayes model. Generalized additive models additionally accounted for non-linearity of continuous clinical variables as depicted in their risk patterns plots. Reducing the input feature space with LASSO had minimal effect on prediction performance, while feature extraction using principal component analysis improved performance of the models. CONCLUSIONS: Generalized additive models and support vector machines had good performance as risk prediction model for postoperative sepsis and AKI. Feature extraction using principal component analysis improved the predictive performance of all models.

Cardiovascular-Specific Mortality and Kidney Disease in Patients Undergoing Vascular Surgery.

IMPORTANCE: Acute kidney injury (AKI) affects as many as 40% of patients undergoing surgery and is associated with increased all-cause mortality. Chronic kidney disease (CKD) is a well-known risk factor for cardiovascular mortality. OBJECTIVE: To determine the association between kidney disease and long-term cardiovascular-specific mortality after vascular surgery. DESIGN, SETTING, AND PARTICIPANTS: A single-center cohort of 3646 patients underwent inpatient vascular surgery from January 1, 2000, to November 30, 2010, at a tertiary care teaching hospital. To determine cause-specific mortality for patients undergoing vascular surgery, a proportional subdistribution hazards regression analysis was used to model long-term cardiovascular-specific mortality while treating any other cause of death as a competing risk. Kidney disease constituted the main covariate after adjusting for baseline patient characteristics, surgery type, and admission hemoglobin level. Final follow-up was completed July 2014 to assess survival through January 31, 2014, and data were analyzed from June 1, 2014, to September 7, 2015. MAIN OUTCOMES AND MEASURES: Perioperative AKI, presence of CKD, and overall and cause-specific mortality. RESULTS: Among the 3646 patients undergoing vascular surgery, perioperative AKI occurred in 1801 (49.4%) and CKD was present in 496 (13.6%). The top 2 causes among the 1577 deaths in our cohort were cardiovascular disease (845 of 1577 [53.6%]) and cancer (173 of 1577 [11.0%]). Adjusted cardiovascular mortality estimates at 10 years were 17%, 31%, 30%, and 41%, respectively, for patients with no kidney disease, AKI without CKD, CKD without AKI, and AKI with CKD. Adjusted hazard ratios (95% CIs) for cardiovascular mortality were significantly elevated among patients with AKI without CKD (2.07 [1.74-2.45]), CKD without AKI (2.01 [1.46-2.78]), and AKI with CKD (2.99 [2.37-3.78]) and were higher than those for other risk factors, including increasing age (1.03 per 1-year increase; 1.02-1.04), emergent surgery (1.47; 1.27-1.71), and admission hemoglobin levels lower than 10 g/dL (1.39; 1.14-1.69) compared with a hemoglobin level of 12 g/dL or higher. CONCLUSIONS AND RELEVANCE: Perioperative AKI is common in patients undergoing vascular surgery and is associated with a high risk for cardiovascular-specific mortality comparable to that seen with CKD. These findings reinforce the importance of preoperative and postoperative risk stratification for kidney disease and the implementation of strategies now available to help prevent perioperative AKI.

Preoperative assessment of the risk for multiple complications after surgery.

BACKGROUND: The association between preoperative patient characteristics and the number of major postoperative complications after a major operation is not well defined. METHODS: In a retrospective, single-center cohort of 50,314 adult surgical patients, we used readily available preoperative clinical data to model the number of major postoperative complications from none to ≥3. We included acute kidney injury; prolonged stay (>48 hours) in an intensive care unit; need for prolonged (>48 hours) mechanical ventilation; severe sepsis; and cardiovascular, wound, and neurologic complications. Risk probability scores generated from the multinomial logistic models were used to develop an online calculator. We stratified patients based on their risk of having ≥3 postoperative complications. RESULTS: Patients older than 65 years (odds ratio 1.5, 95% confidence interval, 1.4-1.6), males (odds ratio 1.2, 95% confidence interval, 1.2-1.3), patients with a greater Charlson comorbidity index (odds ratio 3.9, 95% confidence interval, 3.6-4.2), patients requiring emergency operation (odds ratio 3.5, 95% confidence interval, 3.3.-3.7), and patients admitted on a weekend (odds ratio 1.4, 95% confidence interval, 1.3-1.5) were more likely to have ≥3 postoperative complications than they were to have none. Patients in the medium- and high-risk categories were 3.7 and 6.3 times more likely to have ≥3 postoperative complications, respectively. High-risk patients were 5.8 and 4.4 times more likely to die within 30 and 90 days of admission, respectively. CONCLUSION: Readily available, preoperative clinical and sociodemographic factors are associated with a greater number of postoperative complications and adverse surgical outcomes. We developed an online calculator that predicts probability of developing each number of complications after a major operation.