Predictors and Outcomes of Acute Kidney Injury after Cardiac Surgery.
AKI reflects structural injury preceding an abrupt loss of kidney function, leading to either an increase in SCr or a decrease in urinary output (Petaja et al., 2016; Shaw, 2012). The glomerular filtration rate (GFR) is the most accurate representation of renal function, and it may be estimated using SCr and timed urine collection (Petaja et al., 2016). However, using a 24-hour urine creatinine clearance is inconvenient and time-consuming, and both SCr and urinary output have been traditionally used as surrogate indicators of renal function (Machodo, Nakazone, & Maia, 2014; Petaja et al., 2016). Hourly urine output is frequently unreliable, and AKI based on SCr criteria has better validity than oliguria criteria (O'Neal, Shaw, & Billings, 2016). Several studies even focused on SCr alone to determine AKI (Birnie et al., 2014; Chan et al., 2017; Hansen et al., 2015; Machado et al., 2014). However, establishing the diagnosis of AKI using only SCr without urine output is not without issues, and may lead to both under-diagnosed and over-diagnosed AKI (Englberger et al., 2011; Petaja et al., 2016).
Various definitions of AKI have been used in the past (Petaja et al., 2017). The Acute Dialysis Quality Initiative (ADQI) was first created to develop evidence-based guidelines for the treatment and prevention of AKI. This was later named the RIFLE criteria, with RIFLE being an acronym for risk, injury, failure, loss, and end stage renal disease (ESRD) (Bellomo, Ronco, Kellum, Mehta, & Palevsky, 2004). This expert workgroup introduced the term 'AKI' to replace acute renal failure and proposed the diagnosis of AKI based on either increased SCr, decreased GFR, or decreased urinary output. Three stages of AKI severity (mild, moderate, and severe) and two outcome stages contingent on the required duration for RRT (loss of renal function and ESRD) were recommended (Bellomo RIFLE criteria have been extensively validated, but studies show they have limited application for some patient populations and with certain causes of AKI (Hocine et al., 2016; Shaw, 2012).
The Acute Kidney Injury Network (AKIN) was later formed to improve the understanding of AKI and classified AKI into three stages without retaining any outcome stages (Mehta et al., 2007; Shaw, 2012). AKIN criteria eliminated the use of GFR all together and added an absolute SCr in addition to a relative SCr increase in AKI Stage 1 (Mehta et al., 2007). These criteria defined changes within 48 hours instead of the seven days in RIFLE criteria. AKIN criteria improved the recognition of patients with AKI superimposed on underlying chronic kidney disease (CKD) (Park, 2017). In an attempt to resolve differences between the RIFLE and AKIN guidelines, the Kidney Disease: Improving Global Outcomes (KDIGO) clinical practice guideline for AKI was developed (KDIGO AKI Work Group, 2012; Stevens & Levin, 2013). KDIGO AKI staging is based on absolute SCr elevation within 48 hours, relative SCr elevation within seven days after surgery, and urinary output within the first 6 to 12 hours (KDIGO AKI Work Group, 2012). KDIGO staging criteria are believed to be suitable for the definition of CS-AKI, and to more accurately reflect the mortality and RRT risks associated with CS-AKI (Park, 2017).
The pathophysiology of CS-AKI is complex and may be attributed to kidney-related or surgery-related factors (O'Neal at al., 2016; Shaw, 2012). Kidney-related contributors are categorized as pre-renal, intrinsic, and post-renal factors. Inadequate renal perfusion, such as atherosclerosis, hypotension, and hypoxemia, are main pre-renal mechanisms (Park, 2017). Tissue ischemia, systemic inflammation, or direct toxin exposure are related to intrinsic renal factors (O'Neal et al., 2016; Thiele et al., 2015). Venous congestion after surgery is an example of a post-renal cause of CS-AKI (O'Neal et al., 2016).
Surgical-related factors may be divided into preoperative, intraoperative, and postoperative risk factors (O'Neal et al., 2016). Well-established preoperative risk factors include demographics, nephrotoxic medications or substances, preexisting CKD, underlying medical conditions, and cardiac disease (O'Neal et al., 2016). Specific risk factors include advanced age, female gender, ethnicity, obesity, hypertension (HT), diabetes mellitus (DM), diuretic/angiotensin converting enzyme inhibitor (ACEI) drugs, peripheral arterial disease (PAD), cerebrovascular accident (CVA), chronic obstructive pulmonary disease (COPD), CKD, anemia, cardiomegaly, decreased left ventricular function (LVF), congestive heart failure (CHF), valvular heart disease, and contrast media (O'Neal et al., 2016; Petaja et al., 2017; Shaw, 2012). The types of surgery and cardiopulmonary bypass (CPB) are operative etiologies, whereas intra-aortic balloon pump (IABP) and blood product administration are operative and postoperative risk factors (O'Neal et al., 2016; Shaw, 2012). Other postoperative risk factors include inotropic use, embolic events, other postoperative complications, and the use of antibiotics and non-steroidal anti-inflammatory drugs (Park, 2017).
CS-AKI increases the risk of in-hospital mortality and morbidity, including sepsis, coagulopathy, mechanical ventilation, RRT, and ICU and hospital LOS based on the RIFLE and AKIN criteria (Corredor et al., 2016; Shaw, 2012). Additional studies have reported on incidence, morbidity, and mortality based on KDIGO criteria (Birnie et al., 2014; Engoren, Habib, Arslanian-Engoren, Kheterpal, & Schwann, 2014; Han et al., 2015; Hansen et al., 2015; Machado et al.,2014). For example, any stage of CS-AKI increased the postoperative stay, infection, and pulmonary complications, and result in an almost 5fold increase in the odds of in-hospital mortality (Birnie et al., 2014). Patients who do not require immediate postoperative RRT will have progression of AKI requiring RRT later, and they also have a higher intermediate and long-term mortality (Engoran et al., 2014; Han et al., 2015; Hansen et al., 2015; Machado et al., 2014). Engoran and colleagues (2014) reported increased 30-day and long-term mortality at 6 months to 6.3 years associated with all stages of AKI. Early-onset (within four days) and late-onset (within 30 days) CS-AKI have also been associated with increased 5-year risk of myocardial infarction (MI), CHF, CVA, and all-cause mortality (Hansen et al., 2015).
Several risk stratification scores were developed to identify those at risk for CS-AKI. Petaja and colleagues (2017) found that patients with CSAKI received more blood products and vasoactive agents, and that significant predictors for CS-AKI in multivariable logistic regression included age, body mass index (BMI), PAD, CKD, urgent surgery, low hematocrit (Hct), vasodilators, and postoperative diuretic treatment. Han and colleagues (2015) found that the EuroScore value, cardiopulmonary bypass (CPB) duration, and ICU LOS were predictors for any stage of CS-AKI in patients with elevated SCr. Birnie and colleagues (2014) reported predictors for any stage of CS-AKI based on KDIGO criteria, which included older age, male sex, BMI greater than 35 kg/[m.sup.2], current smokers, higher dyspnea categories, DM, PAD, HT, lower hemoglobin (Hb), lower estimated GFR, catheter to surgery within 24 hours, triple vessel disease, poor left ventricular ejection fraction (EF), emergency/salvage operations, and more complex surgery.
CS-AKI remains an important healthcare issue despite ongoing research over the past two decades. The lack of effective preventive measures, early recognition, and treatment for ongoing CS-AKI continue to be major contributors to the high incidence and poor outcomes of CS-AKI (Birnie et al., 2014; Thiele et al., 2014). Inconsistent definitions in the past have impeded the development of a consensus recommendations (Birnie et al., 2014). Most recent studies on CS-AKI adhere to KDIGO value criteria, but temporal identification remains heterogeneous, varying between 2 to 30 postoperative days (Birnie et al., 2014; Chan et al., 2017; Engoren et al., 2014; Hansen et al., 2014; O'Neal et al., 2016; Petaja et al., 2017). Consistent areas of investigation and findings on CS-AKI based on KDIGO criteria are still lacking, especially in predictors and prognosis of less severe CS-AKI (Birnie et al., 2012). The purpose of the present study was to explore predictors and outcomes of all CS-AKI stages based on the KDIGO value criteria throughout the length of hospital admission.
Methods and Sample
This study used a retrospective chart review of patients who had cardiothoracic surgery at a community hospital in a Midwestern city of a large healthcare system between June 2011 and December 2016. The study was approved by the relevant Institutional Review Boards and Human Rights Review Committees. During the study period, 1,053 patients underwent cardiac surgery. Only patients without known ESRD who were treated with HD were included in the study. The study excluded 38 patients with ESRD on HD, one patient with CKD Stage 5 not yet on HD, and five patients with operative mortality; the final study population included 1,009 patients.
Data collection was performed by a registered nurse who had been trained to collect data for the Society of Thoracic Surgeons (STS) Adult Cardiac Surgery National Database at the study facility (Shahian et al., 2013). The data collection process has undergone yearly independent auditing from the STS National Database throughout the years. Data on known predisposing risk factors for AKI in the general population were obtained, including age, gender, weight, height, smoking history, DM, HT, hyperlipidemia, PAD, SCr, ESRD on HD, decreased left-ventricular EF, COPD, and other related or contributing factors based on the STS database (see Table 1) (Shahian et al., 2013). Data collection also included possible operative risks (left internal mammary artery usage, CPB, and intraoperative transfusion) and postoperative risks for CS-AKI (reintubation, prolonged ventilation, highest postoperative SCr, pneumonia, intubation duration, and postoperative transfusion). Acute respiratory failure (ARF) was defined as prolonged intubation greater than 48 hours or reintubation. Preoperative SCr was that obtained within 24 hours before cardiac surgery, and peak postoperative SCr was the highest SCr at any time during hospital admission. No information was available regarding when peak postoperative SCr levels were obtained.
Patients' heights and weights were used to calculate BMIs. Pre-existing CKD was determined from estimated GFR (eGFR) calculated from preoperative SCr using the re-expressed 4variable Modification of Diet in Renal Disease (MDRD) Study equation for SCr (mg/dL): GFR = 175 x standardized [SCr.sub.-1.154] x ]age.sup.-0203] x 1.212 (if black) x 0.742 (if female) (Earley, Miskulin, Lamb, Levey, & Uhlig, 2012; Levey et al., 2007). CKD stages were defined from the eGFR as follows: CKD Stage 1 with GFR greater than 90 mL/ min/1.73[m.sup.2], CKD Stage 2 with GFR = 60 to 89 mL/min/1.73[m.sup.2], CKD Stage 3 with GFR = 30 to 59 mL/min/1.73 [m.sup.2], CKD Stage 4 with GFR = 15 to 29 mL/min/1.73 [m.sup.2], and CKD Stage 5 with GFR less than 15 mL/min/1.73[m.sup.2] (KDIGO, 2013). AKI for this study was calculated from the preoperative and highest postoperative SCr during the hospital stay using preoperative and highest postoperative SCr using KDIGO value criteria as follows: AKI Stage 1, including patients with absolute increased SCr equal to or greater than 0.3 mg/dL or relative increased SCr x 1.5 to 1.9 baseline; AKI Stage 2, including those with relative increased SCr x 2 to 2.9 baseline; and AKA Stage 3, including those with relative increased SCr 3x baseline or SCr equal to or greater than 4 mg/dL, or those with initiation of RRT (KDIGO AKI Work Group, 2012). In patients under 18 years of age, a decrease in eGFR less than 35 mL/min/1.73 [m.sup.2] is also considered AKI Stage 3 (KDIGO AKI Work Group, 2012).
Descriptive and bivariate analyses were conducted using the Statistical Package for Social Sciences (SPSS) version 25 (International Business Machine Corporation, 2017), including the one-way analysis of valiance (ANOVA), Kruskal-Wallis test, and the [chi square] tests of independence. Data were examined for the contribution of possible causes for CS-AKI, such as predisposing, operative, and postoperative factors. Bivariate analyses were performed to initially address the relationship between hypothesized risk factors and CS-AKI. For continuous outcomes, a one-way ANOVA was conducted to compare variability in the outcome by AKI staging. However, when concerns over the assumptions of a one-way ANOVA arose, the Kruskal-Wallis test was typically conducted. For all discrete outcomes, the [chi square] tests of independence was conducted to identify whether observed frequencies vary by AKI staging.
The relationship between the risk factors and AKI staging were also explored and evaluated using ordinal logistic regression using Statistical Analysis System (SAS) 9.4 (Statistical Analysis System Institute, Inc., 2017). Ordinal logistic regression allows researchers to evaluate the influence of a set of predictors on an outcome variable measured on an ordinal scale (Tabachnick & Fidell, 2007). Due to the exploratory characteristic of this study, all variables were entered into an initial regression model and evaluated in turn for removal using significance tests, odd ratios for their substantial contribution, and amenability to regression analysis. For an example of the latter, some variables that exhibited too much collinearity (e.g., variance inflation factor [VIF] greater than 10) were subsequently eliminated from the model for their high level of redundancy. The Wald and likelihood ratio tests were used to evaluate the statistical contribution of each predictor with alpha set to 0.5, while an odds ratio of less than 1.50 was used as a guide to identify variables with a trivial contribution to predicting CS-AKI. Prior to interpretation, model diagnostics were inspected to ensure the validity of the result, including whether the variable selection method had an influence over the composition of the final mode.
Demographic and clinical variables were presented in three categories; preoperative (see Table 1), operative (see Table 2), and postoperative factors (see Table 3). The overall incidence of CS-AKI in this study was 30.3% for AKI Stage 1, 7.1% for AKI Stage 2, and 7.9% for AKI Stage 3. Forty-nine patients (4.9%) required RRT.
* Preoperative factors (see Table 1) statistically associated with CSAKI included age, BMI, Hct, albumin, race, smoking history, HT, DM, CKD, COPD, CHF, and previous percutaneous coronary intervention (PCI).
* Operative factors (see Table 2) statistically associated with CS-AKI included type of surgery, CPB, circulatory arrest, intraoperative blood transfusion, CPB time, and time in the OR.
* Postoperative factors (see Table 3) statistically associated with all-stage CS-AKI were acute respiratory failure (prolonged intubation greater than 48 hours/reintubation), reoperation for postoperative bleeding, postoperative transfusion, coma/encephalopathy, postoperative atrial fibrillation, and pneumonia.
Results of the final logistic regression model are displayed in Table 4. Among the preoperative, operative, and postoperative predictors, smoker status, hypertension, CPB, acute respiratory failure, postoperative blood product administration, and coma/ encephalopathy performed well as a set of predictors. The likelihood ratio test indicated that the set of predictors performed significantly better than the null model ([chi square] = 198.274, df=12, p=0.000). Akaike information criterion (AIC) also indicated that the final regression model performed better than the null ([AIC.sub.model] = 1357.346 and [AIC.sub.null] =1531.619).
Among the preoperative factors, smoking history and hypertension shared a salient association with AKI staging. Under the proposed model, smoking was associated with CS-AKI across all AKI stages. Patients who smoked were 2.058 times the odds of being classified by the model as Stage 0 than higher stages compared to nonsmokers. Smokers were less likely to suffer from CS-AKI, and smoking did not increase the odds of developing higher AKI stages. While holding all other variables constant, patients with HT were 3.071 times more likely to be classified into a higher AKI stage than patients without hypertension. The influence of hypertension was not consistent across all AKI stages because freeing the coefficient to vary across stages caused convergence failures.
CPB was the only operative variable that tenably contributed to higher AKI staging in the model. Patients having CPB were 2.358 times more likely to experience higher AKI stages than patients who had not undergone CPB. Among postoperative factors, ARF, postoperative blood transfusion, and coma/encephalopathy contributed to the risk of having CS-AKI. In general, postoperative factors tended to exhibit the largest associations with higher AKI staging. Participants who had ARF were likely to suffer all AKI stages. For example, the risk for AKI Stage 1 or higher was 2.183 higher for patients with ARF compared to those without ARF, and the risk continued to escalate for AKI Stage 2 compared to AKI Stage 1 (OR=3.441, p=0.000) and AKI Stage 3 compared to AKI Stage 2 (OR=4.840, p=0.000). Likewise, patients receiving postoperative blood transfusion were 1.927 times more likely to be classified into higher AKI stages by the regression model than those who did not receive post-operative blood transfusion, with the highest risk escalation for AKI Stage 3 (OR=8.850, p=0.000). Patients with a coma/encephalopathy were 5.051 times more likely to develop higher AKI stages than patients who had not experienced coma/encephalopathy.
Postoperative outcomes of patients with CS-AKI are shown in Table 5. Patients who developed CS-AKI had significantly increased ICU LOS, postoperative LOS, and hospital LOS, and were less likely to be discharged home. Patients with CS-AKI also had a higher postoperative mortality. Although the LOS typically increases with CS-AKI, correlation values indicate there is very little change between adjacent stages, which could have been attributed to a large variation in LOS for all AKI stages. For example, while postoperative LOS is expected to increase by one day between patients without CS-AKI and patients with AKI Stage 1 (see Table 5), there is also a lot of variation within each stage (0 to 42 days for patients without CS-AKI and 0 to 44 days for those with AKI Stage 1). AKI Stage 1 did not exert any influence on postoperative mortality (OR=1.360). However, the percentage of mortality rose substantially as AKI increased from AKI Stage 1: the odds of dying were 12.600 times higher for those with AKI Stage 2 and much higher for those with AKI Stage 3 (OR=59.564) compared to those without CS-AKI. As for discharge status, the difference was small between patients without CS-AKI and those with AKI Stage 1 (OR=1.854), but more noticeable for AKI Stage 2 (OR=3.468) and AKI Stage 3 (OR=8.886).
The incidence of CS-AKI in this study was high and is consistent with other studies reporting a prevalence of CS-AKI, up to 40% using both the RIFLE and AKIN criteria (Corredor et al., 2016). However, the incidence in this study is different from others who used KDIGO criteria. (Birnie et al. 2014; Chan et al., 2017; Petaja et al., 2017). The reason for a higher incidence of CS-AKI in this study may be related to a lack of specific time when the peak SCr was obtained, and some values could have been sampled beyond the first 7th postoperative day. Patients with late AKI possibly secondary to other causes unrelated to cardiac surgery might have been included in the present study. Hansen and colleagues (2015) reported that this overestimation may be as high as 8% of the overall incidence. Fortunately, most cases of CS-AKI (70% to 80%) in the present study and others were AKI Stage 1 and did not impact patient outcomes as significantly as would be expected from higher AKI stages.
Similar to prior studies, CS-AKI was associated with several preoperative, operative, and postoperative factors; although, there were more associated factors in the present study than in others (Birnie et al., 2014; Han et al., 2015; Shaw, 2012). There were as many as 23 factors in this study that were associated with CS-AKI, including age, race, smoking history, diabetes, hypertension, COPD, Hct, albumin, CKD, previous PCI, previous CHF, time in OR, CPB, circulato ry arrest, intraoperative blood transfusion, postoperative ARF, postoperative transfusion, reoperation for postoperative bleeding, coma/encephalopathy, postoperative CVA, postoperative atrial fibrillation (POAF), and pneumonia. However, the sequential regression analysis in this study found that only smoking history, hypertension, CPB, reintubation, and coma/ encephalopathy were concurrent predictors for CS-AKI stages. Acute respiratory failure and postoperative blood transfusion were contributing factors to CS-AKI across all AKI stages, whereas HT, CPB, and coma/encephalopathy were predictors for higher AKI stages, and smoking history was predictive of only lower AKI stages. The present study is also different from other studies that stratified risk factors for all stages of CS-AKI (Birnie et al., 2014; Han et al., 2015; Petaja et al., 2017). In one study, the EuroScore value, CPB duration, and ICU LOS were predictors for any-stage of CS-AKI (Han et al., 2015). Another study developed and validated predictors for any-stage CSAKI; reported predictors for CS-AKI included older age, male sex, BMI greater than 35 kg/m2, current smokers, higher dyspnea categories, DM, PAD, HT, lower Hb, lower eGFR, cardiac catheterization within 24 hours before surgery, triple vessel disease, poor EF, and more complex or emergency surgery (Birnie et al., 2014). Several of these predictors were also found to have similar predictive values in a study by Petaja and associates (2017), including age, BMI, PAD, CKD, urgent surgery, low Hct, vasodilators, and postoperative diuretic.
In this study, CS-AKI adversely affected all postoperative outcomes, including increased ICU LOS, postoperative LOS, hospital LOS, and inhospital mortality, but reduced the likelihood of home discharge. The need for postoperative and the longterm need for RRT in this study is similar to others (Petaja et al., 2017; Thiele et al., 2014). The increased postoperative LOS and mortality in the present study are similar to findings reported by Birnie and associates (2014), but are different in that our study did not reveal increases in postoperative infection or other pulmonary complications. The increased postoperative mortality in the present study corresponds to one report that revealed higher mortality in patients with AKI Stages 2 and 3 (Engoren et al., 2014). However, this finding is different from the study by Birnie and associates (2014) who reported increased mortality across all stages of CS-AKI; the likelihood of dying was 4.6 times higher for patients with AKI Stage 1, 8.0 times for patients with AKI Stage 2, and 81.2 times higher for patients with AKI Stage 3.
Strengths and Limitations
The primary strength of this study is the ability to assess predictors and outcomes of all CS-AKI stages based on KDIGO criteria. The study was limited because it involved a crosssectional, retrospective chart review, and documentation errors are possible. The chart review was performed by only one nurse, which limits assessment of accuracy, reliability, and validity of the medical record review. However, the nurse was trained and experienced in this type of data collection. The study utilized only SCr without including urinary output criteria to stage AKI, and this may have under-diagnosed CS-AKI in some patients (Petaja et al., 2017). Using the highest postoperative SCr during the hospital stay in this study without having postoperative SCr at 48 hours or at Day 7 was also a limiting factor. Two hundred eighty-six (286) post-cardiac surgery patients with AKI Stages 1-3 (28.5%) were hospitalized longer than seven days after surgery, and several of them might potentially have had late AKI not meeting a strict KDIGO criteria. Future studies that include SCr samples at 48 hours and at Day 7, and hourly urine output during the first postoperative day should help clarify these limitations. Nevertheless, assessing postoperative outcomes of CS-AKI using only KDIGO criteria alone will still miss many late-occur ring CS-AKIs, which have as devastating prognosis as the early events (Hansen et al., 2015)
The diagnosis of AKI based on SCr may be too late to apply any preventive measures because SCr level does not begin to increase until one to three days after AKI has already been established (Shaw, 2012). Specific serum and urine protein biomarkers that are released as early as within 2 hours of AKI may be more superior in recognizing and managing CS-AKI (Shaw, 2012). These biomarkers include neutrophil gelatinase-associated lipocalin (NGAL), Cystatin C (CyC), kidney injury molecule-1 (KIM-1), tissue inhibitor of metalloproteinase-2 (TIMP-2), and insulin-like growth factor binding protein 7 (IGFBP7) (Shaw, 2012). Currently, specific treatments for AKI are lacking, but preventative measures may include maintenance of adequate hemodynamics, sufficient fluid resuscitation, avoiding nephrotoxic agents and optimizing preoperative hemoglobin levels, avoiding excessive transfusions, maintaining sufficient urine output and acid-base and electrolyte homeostasis, and early initiation of RRT (O'Neal et al., 2016; Shaw, 2012). More studies utilizing these serum and urine protein biomarkers are needed (Shaw, 2012).
In summary, the present study reaffirms the common prevalence of CS-AKI and demonstrates its independent devastating contribution to LOS, morbidity, mortality, and patient discharge home after cardiac surgery. Improved recognition of early CS-AKI, as well as effective therapies and preventative measures for this complication, requires ongoing research.
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Joanne Thanavaro, DNP, RN, AGACNPBC, AGPCNP-BC, DCC, FAANP, is the Associate Dean of Graduate Nursing Education, the Director of Advanced Practice Nursing, and an Associate Professor of Nursing, St. Louis University School of Nursing. St. Louis, MO.
John Taylor, PhD, is an Assistant Professor, St. Louis University School of Nursing. St. Louis, MO.
Linda Vitt, BSN, RN, is the Clinical Data Coordinator, SSMHealth St. Louis Network, St. Louis, MO.
Mary S. Guignon, BA, RN, MHA, is the Team Leader--Clinical Outcomes Department, SSM Health St. Louis Network, St. Louis, MO.
Statement of Disclosure: The authors reported no actual or potential conflict of interest in relation to this continuing nursing education activity.
Note: The Learning Outcome, additional statements of disclosure, and instructions for CNE evaluation can be found on page 41.
Table 1 Demographics, Preoperative Factors, and Acute Kidney Injury After Cardiac Surgery (CS-AKI) CS-AKI No CS-AKI AKI Stage 1 Incidence 54.8% (n=550) 30.3% (n=304) Preoperative Factors Age (Years) 62.29 [+ or -] 12.31 66.40 [+ or -] 12.11 Body mass index 29.26 [+ or -] 6.16 30.80 [+ or -] 6.91 (kg/[m.sup.2]) Preoperative hematocrit 38.85 [+ or -] 4.68 38.13 [+ or -] 4.84 (%) Preoperative albumin 3.63 [+ or -] 0.47 3.59 [+ or -] 0.46 (g/dL) Race (White) 457 (83.1%) 241 (79.5%) Smoking 131 (23.8%) 41 (13.5%) Diabetes mellitus 159 (28.9%) 110 (36.2%) Hyperlipidemia 442 (80.4%) 262 (86.2%) Hypertension 468 (85.1%) 286 (94.1%) COPD Mild 138 (25.1%) 70 (2.0%) Moderate 39 (7.1%) 18 (5.9%) Severe 33 (6.0%) 26 (8.6%) Obstructive sleep apnea 78 (14.2%) 54 (17.8%) Peripheral arterial 66 (12.0%) 36 (11.8%) disease Cerebrovascular accident 87 (15.8%) 49 (16.1%) Preoperative CKD Stage 1 138 (25.1%) 14 (4.6%) Stage 2 290 (52.7%) 52 (17.1%) Stage 3 122 (22.2%) 238 (78.3%) Beta blocker treatment 508 (92.4%) 273 (89.8%) ACE I treatment 224 (40.7%) 143 (47.0%) Lipid treatment 244 (44.4%) 159 (52.3%) Preoperative AF 104 (18.9%) 60 (19.7%) PCI Previous PCI 152 (27.6%) 99 (32.6%) Present PCI 113 (20.5%) 66 (21.7%) Previous CABS 13 (2.4%) 11 (3.4%) Ml after catheterization 173 (31.5%) 96 (31.6%) Previous CHF 232 (42.2%) 146 (48.0%) Recent CHF 154 (28.0%) 85 (28.0%) Number of vessels 1-vessel 59 (10.7%) 42 (13.8%) 2-vessel 88 (16.0%) 40 (13.2%) 3-vessel 167 (30.4%) 108 (35.5%) [greater than or equal 50 (9.1%) 26 (8.6%) to] 50% Left Main artery disease IABP 30 (5.5%) 17 (5.6%) CS-AKI AKI Stage 2 AKI Stage 3 Incidence 7.1% (at=71) 7.9% (n=79) Preoperative Factors Age (Years) 69.38 [+ or -] 10.89 65.38 [+ or -] 10.89 Body mass index 32.78 [+ or -] 7.59 30.95 [+ or -] 6.50 (kg/[m.sup.2]) Preoperative hematocrit 36.00 [+ or -] 4.32 35.30 [+ or -] 4.43 (%) Preoperative albumin 3.50 [+ or -] 0.44 3.36 [+ or -] 0.56 (g/dL) Race (White) 52 (73.2%) 55 (69.6%) Smoking 9 (12.7%) 13 (16.5%) Diabetes mellitus 34 (47.9%) 37 (46.8%) Hyperlipidemia 61 (85.9%) 64 (81.0%) Hypertension 70 (98.6%) 75 (94.9%) COPD Mild 17 (23.9%) 22 (27.8%) Moderate 12 (16.9%) 8 (10.1%) Severe 6 (8.5%) 10 (12.7%) Obstructive sleep apnea 9 (12.7%) 11 (13.9%) Peripheral arterial 8 (11.3%) 14 (17.7%) disease Cerebrovascular accident 18 (25.4%) 18 (22.8%) Preoperative CKD Stage 1 1 (1.4%) 0 (0.0%) Stage 2 3 (4.2%) 0 (0.0%) Stage 3 67 (94.4%) 79 (100.0%) Beta blocker treatment 65 (91.5%) 72 (91.1%) ACE I treatment 37 (52.1%) 31 (39.2%) Lipid treatment 38 (53.5%) 37 (46.80%) Preoperative AF 19 (26.8%) 20 (25.3%) PCI Previous PCI 23 (32.4%) 35 (44.3%) Present PCI 23 (23.9%) 21 (26.6%) Previous CABS 3 (3.6%) 5 (8.8%) Ml after catheterization 21 (29.6%) 31 (39.2%) Previous CHF 34 (47.9%) 51 (64.6%) Recent CHF 19 (26.8%) 42 (53.2%) Number of vessels 1-vessel 13 (18.3%) 13 (16.5%) 2-vessel 8 (11.3%) 8 (10.1%) 3-vessel 24 (33.8%) 24 (30.4%) [greater than or equal 1 (8.5%) 7 (7.9%) to] 50% Left Main artery disease IABP 2 (1.4%) 4 (5.1%) CS-AKI Incidence Preoperative Factors Statistic (df) P Age (Years) 13.34 (3, 1000) 0.000 Body mass index 8.649 (3, 998) 0.000 (kg/[m.sup.2]) Preoperative hematocrit 18.79 (3, 1000) 0.000 (%) Preoperative albumin 8.77 (3, 972) 0.000 (g/dL) Race (White) 10.74 (3) 0.013 Smoking 16.20 (3) 0.001 Diabetes mellitus 18.93 (3) 0.000 Hyperlipidemia 5.31 (3) 0.151 Hypertension 26.98 (3) 0.000 COPD Mild 35.96 (12) 0.000 Moderate Severe Obstructive sleep apnea 2.45 (3) 0.485 Peripheral arterial 2.32 (3) 0.509 disease Cerebrovascular accident 6.05 (3) 0.109 Preoperative CKD Stage 1 44.32 (9) 0.000 Stage 2 Stage 3 Beta blocker treatment 1.65 (3) 0.648 ACE I treatment 5.99 (3) 0.112 Lipid treatment 6.02 (3) 0.111 Preoperative AF 3.79 (3) 0.286 PCI Previous PCI 9.86 (3) 0.020 Present PCI 1.75 (3) 0.626 Previous CABS 7.00 (3) 0.072 Ml after catheterization 2.20 (3) 0.533 Previous CHF 14.77 (3) 0.002 Recent CHF 22.24 (3) 0.000 Number of vessels 1-vessel 11.01 (9) 0.275 2-vessel 3-vessel [greater than or equal 0.09 (3) 0.993 to] 50% Left Main artery disease IABP 2.25 (3) 0.523 Notes: Counts and relative frequencies are displayed for categorical preoperative factors, and p-values are based upon the [chi square] test of independence. Means and standard deviations are displayed for continuous factors, and p-values are based upon a one-way analysis of variance F-test. ACEI = angiotensin converting enzyme inhibitor, AF = atrial fibrillation, CABS = coronary artery bypass surgery, CHF = congestive heart failure, CKD = chronic kidney disease, COPD = chronic obstructive pulmonary disease, CS AKI = acute kidney injury after cardiac surgery, df= degrees of freedom, IABP = intra-aortic balloon pump, PCI = percutaneous coronary intervention. Table 2 Operative Factors and Acute Kidney Injury After Cardiac Surgery (CS-AKI) No CS-AKI AKI Stage 1 Operative Factors 54.8% (n=550) 30.3% (n=304) Type of surgery CABS 198 (36.0%) 106 (34.9%) Valve 206 (37.5%) 117 (38.5%) Combined 132 (24.0%) 66 (21.7%) Others 14 (2.5%) 15 (4.9%) Cardiopulmonary bypass 482 (88.6%) 300 (93.8%) Circulatory arrest 1 (0.2%) 6 (2.0%) LIMA graft 229 (41.6%) 121 (39.8%) Intraoperative 149 (26.6%) 128 (42.1%) transfusion Cardiopulmonary bypass 96.0 (0.0 to 247.0) 98.0 (0.0 to 316.0) time ([dagger]) Cross-clamp time 81.0 (0.0 to 199.0) 79.0 (0.0 to 212.0) ([dagger]) Time in operating room 5.61 [+ or -] 1.35 5.79 [+ or -] 1.44 AKI Stage 2 AKI Stage 3 Operative Factors 7.1% (at=71) 7.9% (n=79) Type of surgery CABS 18 (25.4%) 20 (25.3%) Valve 37 (52.1%) 31 (39.2%) Combined 16 (22.5%) 22 (27.8%) Others 0 (0.0%) 6 (7.6%) Cardiopulmonary bypass 82 (98.8%) 54 (96.4%) Circulatory arrest 0 (0.0%) 5 (6.3%) LIMA graft 26 (36.6%) 25 (31.6%) Intraoperative 30 (42.3%) 56 (70.9%) transfusion Cardiopulmonary bypass 102.0 (0 to 349) 114.0 (0.0 to 361.0) time ([dagger]) Cross-clamp time 81.0 (30.0 to 204.0) 88.0 (35.0 to 305.0) ([dagger]) Time in operating room 6.03 [+ or -] 1.54 6.34 [+ or -] 1.80 Operative Factors Statistic (df) P Type of surgery CABS 18.17 (9) 0.033 Valve Combined Others Cardiopulmonary bypass 16.32 (3) 0.001 Circulatory arrest 24.83 (3) 0.000 LIMA graft 3.25 (3) 0.354 Intraoperative 66.39 (3) 0.000 transfusion Cardiopulmonary bypass 15.83 (3) 0.001 time ([dagger]) Cross-clamp time 7.06 (3) 0.070 ([dagger]) Time in operating room 7.26 (3, 1000) 0.000 Notes: Counts and relative frequencies are displayed for categorical intra-operative factors, and p-values are based upon the [chi square] test of independence. Mea and standard deviations are displayed for continuous factors, and p-values are based upon a one-way analysis of variance F-test unless noted otherwise. CABS = coronary artery bypass surgery, LIMA = left internal mammary artery, df= degrees of freedom. ([dagger]) Medians and ranges are displayed and significance testing was conducted using the Kruskal-Wallis Htest. Table 3 Postoperative Factors and Acute Kidney Injury After Cardiac Surgery (CS-AKI) No CS-AKI AKI Stage 1 Postoperative Factors 54.8% (n=550) 30.3% (n=304) Prolonged ventilation/ 42 (7.6%) 39 (12.8%) reintubation Reoperation for 9 (1.6%) 5 (1.6%) postoperative bleeding Coma/encephalopathy 9 (1.6%) 17 (5.6%) Infection 6 (1.1%) 8 (2.6%) Postoperative atrial 126 (22.9%) 105 (34.5%) fibrillation Pneumonia 16 (2.9%) 18 (5.9%) AKI Stage 2 AKI Stage 3 Postoperative Factors 7.1% (n=71) 7.9% (n=79) Prolonged ventilation/ 15 (21.1%) 51 (64.6%) reintubation Reoperation for 0 (0.0%) 5 (6.3%) postoperative bleeding Coma/encephalopathy 10 (14.1%) 27 (34.2%) Infection 1 (1.4%) 3 (3.8%) Postoperative atrial 30 (42.3%) 34 (43.0%) fibrillation Pneumonia 9 (12.7%) 25 (31.6%) Postoperative Factors Statistic (df) P Prolonged ventilation/ 182.28 (3) 0.000 reintubation Reoperation for 10.04 (3) 0.018 postoperative bleeding Coma/encephalopathy 132.31 (3) 0.000 Infection 4.62 (3) 0.202 Postoperative atrial 27.77 (3) 0.000 fibrillation Pneumonia 94.67 (3) 0.000 Notes: Counts and relative frequencies are displayed for categorical preoperative factors, and p-values are based upon the %2 test of independence. Medians and ranges are displayed for the continuous factor, and the associated p-value based upon the Kruskal-Wallis H test. Table 4 Sequential Logistic Regression of Predictors for Acute Kidney Injury after Cardiac Surgery (CS-AKI) Predictors CS-AKI Stage Slopes Preoperative risk factors Smoker 0 vs. 1 [less than or 0.721 equal to] Smoker 1 [greater than or equal 0.390 to] vs. 2 [less than or equal to] Smoker 2 [greater than or equal 0.304 to] vs. 3 Hypertension -- -1.122 Operative risk factors Cardiopulmonary bypass -- -0.857 Postoperative risk factors Prolonged ventilation/ 0 vs. 1 [less than or -0.781 reintubation equal to] Prolonged ventilation/ 1 [greater than or equal -1.236 reintubation to] vs. 2 [less than or equal to] Prolonged ventilation/ 2 [greater than or equal -1.577 reintubation to] vs. 3 Postoperative blood 0 vs. 1 [less than or 0.656 product equal to] Postoperative blood 1 [greater than or equal 1.122 product to] vs. 2 [less than or equal to] Postoperative blood 2 [greater than or equal 2.182 product to] vs. 3 Coma/encephalopathy -- -1.621 Predictors S.E. Wald P OR Preoperative risk factors Smoker 0.215 11.258 0.001 0.486 Smoker 0.317 1.506 0.220 0.677 Smoker 0.393 0.596 0.440 0.738 Hypertension 0.298 14.214 0.000 3.071 Operative risk factors Cardiopulmonary bypass 0.313 7.512 0.006 2.358 Postoperative risk factors Prolonged ventilation/ 0.258 9.139 0.003 2.183 reintubation Prolonged ventilation/ 0.277 19.845 0.000 3.441 reintubation Prolonged ventilation/ 0.346 20.784 0.000 4.840 reintubation Postoperative blood 0.179 13.390 0.000 1.927 product Postoperative blood 0.251 19.993 0.000 3.067 product Postoperative blood 0.445 24.046 0.000 8.850 product Coma/encephalopathy 0.324 25.048 0.000 5.051 Table 5 Postoperative Outcomes for Patients Developing Acute Kidney Injury After Cardiac Surgery (CS-AKI) No CS-AKI AKI Stage 1 54.8% (n=550) 30.3% (n=304) ICU LOS (hour) 90.2 (0 to 673.1) 102.5 (0 to 1013.5) Postoperative LOS (day) 7.0 (0 to 42.0) 8.0 (0 to 44.0) Hospital LOS (day) 7.0 (0 to 70.0) 9.0 (0 to 46.0) Postoperative mortality 4 (0.7%) 3 (1.0%) Discharge Home 468 (85.6%) 230 (76.2%) Extended care 51 (9.3%) 39 (12.9%) Nursing home 21 (3.8%) 25 (8.3%) Others 7 (1.3%) 8 (2.6%) AKI Stage 2 7.1% (at=71) ICU LOS (hour) 145.6 (48.2 to 960.0) Postoperative LOS (day) 10.0 (5.0 to 40.0) Hospital LOS (day) 11.0 (5.0 to 40.0) Postoperative mortality 6 (8.5%) Discharge Home 41 (63.1%) Extended care 17 (26.2%) Nursing home 7 (10.8%) Others 0 (0.0%) AKI Stage 3 7.9% (n=79) Statistic (df) ICU LOS (hour) 256.5 (44.1 to 1198.6) 186.25 (3) Postoperative LOS (day) 16.0 (2.0 to 76.0) 164.08 (3) Hospital LOS (day) 19.0 (2.0 to 77.0) 140.04 (3) Postoperative mortality 24 (30.4%) 182.94 (3) Discharge Home 22 (40.0%) 87.93 (9) Extended care 18 (32.7%) Nursing home 9 (16.4%) Others 6 (10.9%) P ICU LOS (hour) 0.000 Postoperative LOS (day) 0.000 Hospital LOS (day) 0.000 Postoperative mortality 0.000 Discharge Home 0.000 Extended care Nursing home Others Notes: Counts and relative frequencies are displayed for categorical preoperative factors, and p-values are based upon the %2 test of independence. Medians and ranges are displayed for the continuous factors, and the associated p-value based upon the Kruskal-Wallis H test. ICU = intensive care unit, df= degrees of freedom, LOS = length of stay.
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|Author:||Thanavaro, Joanne; Taylor, John; Vitt, Linda; Guignon, Mary S.|
|Publication:||Nephrology Nursing Journal|
|Date:||Jan 1, 2019|
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