DOI: https://doi.org/10.21203/rs.3.rs-29665/v1
This study aimed to identify the incidence rate of Acute kidney injury (AKI) in our center, assess risk factors for one-year mortality, and predict short- and long-term survival after heart transplantation (HTx).
This single-center, retrospective study from October 2009 to Jan 2020 analyzed the pre-, intra-, and postoperative characteristics of 87 patients who underwent HTx. AKI was defined according to the Kidney Disease: Improving Global Outcomes (KDIGO) criteria. Risk factors were analyzed by multivariable logistic regression models. The log-rank test was used to compare long-term survival.
Twenty-six (36.1%) patients developed AKI. The one-year mortality rates in HTx patients with and without AKI were 26.92% and 10.87%, respectively (P > 0.05). Recipients who required renal replacement therapy (RRT) had a one-year mortality rate of 53.85% compared to 10.87% in those without AKI or RRT (P = 0.003). A long cardiopulmonary bypass (CPB) time (OR: 1.622, 95% CI: 1.014 to 2.595, P = 0.044) was positively related to the occurrence of AKI. A high intraoperative urine volume (OR: 0.566, 95% CI: 0.344 to 0.930, P = 0.025) was negatively correlated with AKI. AKI requiring RRT (HR, 6.402; 95% CI, 2.014–20.355, P = 0.002) was a risk factor for death. Overall survival in patients without AKI at 1, 3, and 5 years was higher than that in patients with AKI (P > 0.05).
AKI is common after HTx and adversely impacts early mortality. A long CPB time and low intraoperative urine volume maybe associated with the occurrence of AKI. AKI requiring RRT could contribute powerful prognostic information to predict short-term survival.
Heart transplantation (HTx) is a generally successful procedure for patients with end-stage heart failure, improving their survival and quality of life [1]. Acute kidney injury (AKI) is a frequent complication following HTx. With an incidence ranging from 14–76%, it is a significant contributor to high morbidity and mortality [2–7]. There are various causes of AKI, such as renal hypoperfusion, prolonged cardiopulmonary bypass (CPB), and nephrotoxicity of immunosuppressive drugs [8]. Therefore, there is a need to identify high-risk factors, reduce the life-threatening outcomes of AKI, and enhance the long-term survival rates in HTx patients.
Scoring systems for the quantification of AKI have been applied in clinical studies. These criteria included the Risk/Injury/Failure/Loss/End-stage (RIFLE) criteria, the Acute Kidney Injury Network (AKIN) criteria, and the Kidney Disease: Improving Global Outcomes (KDIGO) criteria [9–11]. Based on these criteria, AKI can be defined and staged. It is important to note that despite different performances of different scoring systems, a mild to modest form of AKI does not play a significant role in predicting poor long-term outcomes [12]. However, patients who develop severe AKI frequently receive renal replacement therapy (RRT) as a salvage treatment. The need for RRT has been reported to be one of the most important predictors of a poor prognosis after HTx [13]. Although some clinical outcomes associated with AKI requiring RRT have been described, its impact on long-term survival has not been addressed.
The aims of this study were to (1) evaluate the incidence of AKI after HTx in our center by using the KDIGO criteria, (2) identify risk factors for AKI and mortality after HTx, and (3) explore long-term survival in AKI patients requiring RRT.
Patient population
The data of all HTx patients at Tianjin First Center Hospital between October 2009 and Dec 2019 were retrospectively examined. Patients who died within 24 h as well as those who underwent multiorgan transplantation were excluded. Patients were followed in the outpatient department. Eighty-seven HTxs were performed in our center, of which 72 were included in the analysis. Patients were excluded if they underwent combined heart-kidney transplantation (n=8) or were lost to follow-up (n=7).
Perioperative management
A biatrial technique was performed in the HTx procedure. All patients received methylprednisolone intraoperatively (500 mg when the aortic cross clamp was released) followed by 120 mg q8h intravenous for the first 24 h, 120mg q12h for the second 24h, 120 mg once daily for the third 24h and basiliximab (20 mg loading dose in the operating room and 20 mg the fourth day). On the fourth day postoperation, tacrolimus and mycophenolate mofetil was started at an oral dose of 1.5 mg and 500mg twice daily, respectively. Tacrolimus and mycophenolate mofetil were prescribed for the rest of their lives. Further, dosing was based on tacrolimus whole-blood trough concentrations at 6 a.m (12 h post-dose). A whole-blood tacrolimus trough concentration between 7 and 15 ng/ml was considered in the first 3 months and thereafter tapered towards 5-10 ng/ml. Accompanying immunosuppression comprised corticosteroids, prednisolone was started 28mg orally on the fourth day postoperation, followed by 24mg once daily and tapered off to 8mg once daily orally.
Outcome measure
AKI was classified according to the KDIGO criteria [11]. The KDIGO criteria recognize 3 stages of AKI severity based on serum creatinine (SCr) levels and urine output. The definition of AKI was based on peak creatinine within 7 days postoperation. The administration of loop diuretics is a commonly used method in the postoperative period and in the early management of AKI, at least in patients with volume overload and/or oliguria. Indications for RRT were stage 3 AKI combined with one of the following: hyperkalemia, severe hypervolemia, uncorrectable metabolic acidosis or serious uremia.
Continuous variables are presented as mean±standard deviation, while categorical or integer variables are presented as number and percentage. To compare values between two groups, Student’s t test was used for normally distributed numerical variables, and Wilcoxon rank test for nonnormally ones. One-way analysis of covariance (ANOVA) or Kruskal-Wallis test was used for comparisons more than two groups. When there was a statistical significance among groups, SNK method was used to perform comparison between groups. Categorical or integer parameters compared by Fisher’s exact test or Chi-square test. Other continuous variables were expressed as median and interquartile (25th to 75th percentile) range and compared by Mann-Whitney U-test or Kruskal-Wallis test. Survival analysis was performed using log-rank test. Cox proportional hazards model were used to identify variables independently associated with mortality. All statistical procedures were performed using SAS 9.4 (SAS Institute Inc. Cary, NC, USA) and GraphPad Prism 5.0 (GraphPad Software Inc., La Jolla, USA). A two-tailed P value < 0.05 was considered statistically significant.
Table 1 shows the demographics and perioperative characteristics of the HTx recipients stratified into 3 groups by the estimated glomerular filtration rate (eGFR). Patients in the GFR < 30 ml/min/1.73 m2 group were older than those in the eGFR > 60 ml/min/1.73 m2 group (P < 0.001), and the creatinine levels and frequency of chronic kidney disease were higher in the GFR < 30 ml/min/1.73 m2 group than in the other groups (P < 0.001); P = 0.021). However, there was no difference in body mass index (BMI) or left ventricular ejection fraction (LVEF) among the groups (P = 0.408 and 0.122, respectively). In addition, the three groups had a similar frequency of dilated cardiomyopathy (DCM), coronary artery disease (CAD), valve disease, and pre-percutaneous coronary intervention (PCI) (P = 0.091, 0.682, 0.793 and 0.398, respectively). Intraoperatively, patients in the GFR < 30 ml/min/1.73 m2 group had a longer duration of CPB and more blood loss than the patients in the other groups, but there was no statistical significance (P > 0.05). Although there was decreased urine volume during the operation and an increased frequency of application of intra-aortic balloon pump with venoarterial extracorporeal membrane oxygenation (IABP/ECMO) in the GFR < 30 ml/min/1.73 m2 group (P = 0.005 and 0.009), there was no difference in time to discharge, death within 1 year, or the incidence of AKI between the groups (P > 0.05). Figure 1 shows the Kaplan-Meier curves for HTx recipients stratified into 3 groups by eGFR. There were no differences in long-term survival among the 3 groups stratified by eGFR (P = 0.621).
Of the 72 HTx recipients who were enrolled, 26 patients fulfilled the criteria for AKI, and 46 patients were assigned to the non-AKI group (Table 2). Although there was no difference in most perioperative variables, the urine volume during the operation was lower in the AKI group than in the non-AKI group (P = 0.019). In addition, the frequency of RRT was higher in the AKI group than in the non-AKI group (P < 0.001). However, there was no difference in the overall 5-year survival rates between the two groups (P = 0.0643) (Fig. 2).
Table 3 shows the demographics and perioperative characteristics of 72 HTx recipients stratified into 3 groups by post-HTx RRT. There was an increased frequency of patients with a chronic kidney disease history in the AKI with RRT group (P = 0.022). Intraoperatively, the AKI with RRT group had a longer CPB time, lower urine volume and a higher frequency of IABP/ECMO than the other groups (P = 0.004, 0.049, and < 0.001, respectively). Postoperatively, there were significant differences in urine volume, mechanical ventilation rate and mortality within 1 year. During follow-up, the survival rate was 62.72 ± 19.82% in the AKI with RRT group, while the survival rate was 92.01 ± 3.04% in the non-AKI without RRT group (Fig. 3).
The multivariable model for AKI and perioperative predictors of mortality are summarized in Table 4. A relatively long CPB time (OR: 1.622, 95% CI: 1.014 to 2.595, P = 0.044) was positively related to the occurrence of AKI. An increased intraoperative urine volume (OR: 0.566, 95% CI: 0.344 to 0.930, P = 0.025) was negatively correlated with AKI. The risk for death was 6.402 times increased in the AKI patients with RRT after HTx (P = 0.002).
In our retrospective analysis, we found that AKI was a frequent complication of HTx, with an incidence of 36.1%. We also showed that a relatively short CPB time and increased intraoperative urine volume could prevent the occurrence of AKI. Furthermore, AKI requiring RRT was an independent risk factor for mortality after HTx. Finally, AKI requiring RRT was associated with an increased risk for short-term mortality but not long-term mortality.
Severe AKI is an important independent contributor to mortality in the HTx population. Accumulating evidence indicates that AKI requiring RRT could be a strong predictor of adverse clinical outcomes. In Renata’s study, patients with AKI, especially those requiring RRT (46.9%), had higher hospital mortality (16%) than those without AKI [14]. However, after hospital discharge, AKI was not associated with poor long-term outcomes. With a median follow-up after hospital discharge of 6.7 years, overall survival at 1, 5, and 10 years was 95.4%, 85.1%, and 75.4% and 85.2%, 69.8% and 63.5% among patients with AKI stages 2 and 3, respectively [14]. Fortrie’s findings showed that one-year mortality rates in patients without AKI and with AKI stages 1, 2, and 3 were 4.8%, 7.6%, 11.8%, and 14.7%, respectively.7 In an extensive follow-up of 471 HTx patients over a period up to 26 years, no association was found between the development of AKI and long-term mortality or chronic RRT dependence [15]. In this study, we found that one-year mortality in patients with AKI was 26.92%, and the incidence rate of AKI requiring RRT was 50%. Moreover, overall survival in patients without AKI at 1, 3, and 5 years was higher than that in AKI patients.
In contrast to the high overall incidence of AKI, the need for RRT in our study was 18.05%. This is similar to previous studies reporting a need for RRT in 6–29% of patients [2, 4, 6]. A recent analysis indicated that AKI requiring RRT had a 1-year mortality rate of 59.2% [16]. In Boyle’s study, AKI requiring RRT was associated with a mortality rate of 50% compared to 1.4% in patients without AKI [17]. We estimated an increased risk for mortality, with a hazard ratio of 6.402 in AKI patients requiring RRT. These results could be explained by the fact that patients with severe AKI are less likely to achieve full recovery of kidney function, even with RRT, than patients with mild AKI. In fact, some AKI patients requiring RRT develop at least one other serious complication (sepsis, graft failure, or acute myocardial infarction), which can lead to early mortality during the postoperative care period. In our study, there was a nonsignificant tendency toward an increase in long-term mortality in AKI patients requiring RRT, which is consistent with previous reports.3 Therefore, the impact of RRT appears to be lost at long-term follow-up. This result indicated that recovery of kidney function prior to hospital discharge was associated with decreased long-term mortality risk.
The interactions between the heart and kidney systems have become a matter of great concern [18]. The difference between arterial driving pressure and venous outflow pressure must remain sufficiently large for adequate renal blood flow and glomerular filtration. The low-resistance nature of the renal vasculature and parenchyma and the very low oxygen tension in the outer medulla also explain the unique sensitivity of the kidneys to hypotension-induced injury [2, 19]. Thus, both hemodynamic instability and antecedent hypotension should be considered in the consultative evaluation of a patient with developing AKI.
Several factors have been suggested to contribute to the development of postoperative AKI. In general, the most common cause in the early postoperative period is ischemic-reperfusion injury [20]. Intraoperatively, maintenance of a mean arterial pressure (MAP) > 60–65 mmHg, reduction in CPB time, minimization of blood transfusion and avoidance of nephrotoxic agents may prevent AKI [2, 21]. Moreover, increased central venous pressure (CVP) was associated with a reduced GFR and all-cause mortality. Right atrial pressure strongly predicts the development of AKI early after HTx and can be used as an early AKI indicator [22]. Finally, postoperatively, chloride-restricted fluid management was associated with less AKI and RRT [23]. In our opinion, a relatively short CPB time and increased intraoperative urine volume play important roles in preventing the occurrence of AKI after HTx.
The performance and usefulness of different AKI scoring systems with regard to mortality vary greatly [24]. The KDIGO criteria are widely applied in the analysis of AKI in HTx patients. However, the emphasis on SCr and urine volume may exaggerate the severity of AKI. In addition, according to the RIFLE criteria, AKI encompasses the entire spectrum of the syndrome, from minor changes in renal function to the requirement of RRT. Thus, AKI does not simply represent acute renal failure but is a more general description [25]. Since the AKIN criteria are not sensitive enough to capture all episodes of AKI in cardiac surgery patients, they are not widely used for HTx patients [26]. We consider to evaluate this issue in future clinical trials.
A growing body of evidence suggests a disconnect between SCr and adverse outcomes in certain clinical circumstances. SCr can be influenced by volume overload, nutrition, steroids, and muscle trauma; thus, relying solely on SCr for the diagnosis of AKI can be problematic, especially in critically ill patients [27]. In fact, low to moderate SCr levels are anticipated and tolerated and seem unrelated to significant renal injury [28]. Kidney tubular injury biomarkers, such as neutrophil gelatinase-associated lipocalin (NGAL), N-acetyl-β-D-glucosaminidase (NAG), plasma cystatin-C (CyC) and kidney injury molecule 1 (KIM-1), can predict the development of AKI [8, 29]. Additionally, NGAL has shown a promising correlation with irreversible renal dysfunction. Thus, these novel biomarkers of early kidney damage represent a new dimension in improving the accuracy of AKI and its treatment targets for the future.
We acknowledge that several limitations exist in this study. The inherent limitation is that it was a retrospective, single-center study that enrolled a small number of patients. Furthermore, the small sample size made it difficult to detect small effects and prevented the use of multivariate analysis. In addition, patients were relatively old and likely to suffer from comorbid conditions, such as diabetes mellitus and hypertension. These comorbidities may interfere with the analysis of the long-term survival rates in AKI requiring RRT. Finally, the indication for dialysis is standardized; however, to some extent, it depends on the physician treating the individual patient, which may have acted as a confounder in our study.
Our study suggests that AKI is a frequent complication of HTx, and the results demonstrated that AKI requiring RRT following HTx was independently associated with an increased risk for short-term mortality. However, AKI patients had a relatively good long-term prognosis, with the recovery of renal function. Therefore, the results of this study highlight that risk factor identification may assist in implementing strategies to prevent or limit the progression of AKI, which, in turn, may improve survival.
AKI: Acute kidney injury; HTx: Heart transplantation; KDIGO: Kidney Disease: Improving Global Outcomes; RRT: Renal replacement therapy; CPB: Cardiopulmonary bypass; RIFLEL: Risk/Injury/Failure/Loss/End-stage; AKIN: Acute Kidney Injury Network; SCr: Serum creatinine; ANOVA: One-way analysis of covariance; eGFR: estimated glomerular filtration rate; BMI: Body mass index; LVEF: Left ventricular ejection fraction; DCM: Dilated cardiomyopathy; CAD: Coronary artery disease; PCI: percutaneous coronary intervention; IABP: Intra-aortic balloon pump; ECMO: Extracorporeal membrane oxygenation; NGAL: Neutrophil gelatinase-associated lipocalin; NAG: N-acetyl-β-D-glucosaminidase; CyC: Cystatin-C (CyC); KIM-1: Kidney injury molecule 1; OR: Odds ratio; HR: Hazard ratio; CI: Confidence interval.
Acknowledgments
We thank Dr. HJ He for her assistance in statistical analysis.
Authors’ contributions
Xiangrong Kong designed the study and critically reviewed the manuscript. Yiyao Jiang participated in the data collection, data analysis and drafted the initial draft of the manuscript. All authors read and approved the final manuscript.
Funding
This work was supported by grants from the National Natural Science Foundation of China (81800214), Natural Science Foundation of Anhui Province (1808085QH236).
Availability of data and materials
The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.
Ethics approval and consent to participate
The study was approved by the Institutional Ethical Review Board of Tianjin First Center Hospital. The need for patient consent was waived due to the retrospective study design.
Consent for publication
Not applicable.
Competing interests
The authors declare that they have no competing interests.
Table 1. Demographics and Perioperative Characteristics of the HTx Recipients Stratified by eGFR.
|
|
Overall (n=72) |
eGFR (ml/min/1.73 m2) |
P value |
||
|
<30 (n=18) |
30-59 (n=46) |
≥60 (n=8) |
|||
|
Demographic data |
|||||
|
Age, years |
53.90±12.18 |
59.94±10.25 |
54.28±9.52 |
38.13±16.93 |
0.002* |
|
Sex, men, n (%) |
60(83.33) |
12 (66.67) |
41 (89.13) |
7 (87.50) |
0.073 |
|
BMI (kg/m2) |
24.27±3.80 |
23.27±3.20 |
24.51±3.96 |
25.12±4.17 |
0.408 |
|
History of alcohol |
19(26.39) |
7 (38.89) |
10 (21.74) |
2 (25.00) |
0.284 |
|
History of smoking |
46(63.89) |
10 (55.56) |
30 (65.22) |
6 (75.00) |
0.320 |
|
Hypertension |
28(38.89) |
10 (55.56) |
15 (32.61) |
3 (37.50) |
0.201 |
|
Diabetes mellitus |
27(37.50) |
8 (44.44) |
16 (34.78) |
3 (37.50) |
0.605 |
|
Chronic kidney disease |
16(22.22) |
9 (50.00) |
5 (10.87) |
2 (25.00) |
0.021* |
|
Pretransplant characteristics |
|||||
|
DCM |
1(1.39) |
0(0) |
1(2.17) |
0(0) |
0.091 |
|
CAD |
22(30.56) |
6(33.33) |
14(30.43) |
2(25.00) |
0.682 |
|
Valve disease |
11(15.28) |
3(16.67) |
7(15.22) |
1(12.50) |
0.793 |
|
Pre-PCI |
6(8.33) |
2(11.11) |
4(8.70) |
0(0) |
0.398 |
|
ICD implantation |
3(4.17) |
2(11.11) |
1(2.17) |
0(0) |
0.113 |
|
EF pre-HTx (%) |
26(21,30) |
30(24,33) |
25(22,30) |
25(20,29) |
0.122 |
|
Creatinine (mg/dL) |
1.13(0.95,1.27) |
1.65(1.33,1.88) |
1.09(0.95,1.21) |
0.78(0.66,0.87) |
<0.001* |
|
Intraoperative characteristics |
|||||
|
CPB duration (min) |
225(195,264.5) |
240(195,300) |
225(195,255) |
209(172.5,225) |
0.256 |
|
Blood transfusion (ml) |
1440(1050,1930) |
1450(1100,2000) |
1440(1100,1900) |
1570(1000,2250) |
0.999 |
|
Infusion (ml) |
1800 (1350,2412.5) |
1895(1505,2400) |
1750(1350,2600) |
1550 (1120,1862.5) |
0.392 |
|
Blood loss (ml) |
1500(1000,2100) |
1500(1000,2500) |
1000(1000,2000) |
1250(1000,2250) |
0.795 |
|
Urine volume (ml) |
1700(1200,2300) |
1275(770,1650) |
2000(1200,2500) |
2075(1700,2550) |
0.005* |
|
IABP/ECMO |
5(6.94) |
4 (22.22) |
1 (2.17) |
0(0) |
0.009* |
|
Postoperative characteristics |
|||||
|
AKI stage |
|||||
|
NO-AKI |
46(63.89) |
13(72.22) |
28(60.87) |
5(62.50) |
0.502 |
|
Stage 1 |
9(12.50) |
1(5.56) |
7(15.22) |
1(12.50) |
0.948 |
|
Stage 2 |
7(9.72) |
1(5.56) |
4(8.70) |
2(25.00) |
|
|
Stage 3 |
10(13.89) |
3(16.67) |
7(15.22) |
0(0) |
|
|
Urine volume |
|||||
|
1st Day after operation |
2145 (1970,2732.5) |
2042.5 (1965,2482) |
2170 (1940,2730) |
2785 (2065,3492.5) |
0.180 |
|
2nd Day after operation |
2100 (1762.5,2475) |
1967.5 (1425,2505) |
2112.5 (1815,2425) |
2355 (1822.5,2707.5) |
0.321 |
|
3rd Day after operation |
2102.5 (1790,2445) |
2090(1440,2560) |
2102.5 (1860,2390) |
2187.5 (1742.5,2417.5) |
0.956 |
|
Mechanical ventilation (min) |
1850(960,2400) |
2310(1800,4860) |
1320(960,2220) |
990(780,1845) |
0.045* |
|
RRT |
13(18.06) |
5(27.78) |
8(17.39) |
0(0) |
0.096 |
|
Time to discharge (days) |
25.5(22,33) |
25.5(21,33) |
26.5(23,33) |
23.5(17,26) |
0.282 |
|
Death within 1 year |
12(16.67) |
4(22.22) |
7(15.22) |
1(12.50) |
0.474 |
|
Follow-up days |
623(302,1296) |
397.5 (299,798) |
728.5 (305,1342) |
1583 (381.5,2043) |
0.071 |
* P<0.05; eGFR was calculated using the Chronic Kidney Disease Epidemiology collaboration equation. HTx, Heart transplantation; eGFR, estimated glomerular filtration rate; BMI, body mass index; DCM, dilated cardiomyopathy; CAD, coronary arterial disease; Pre-PCI, previous percutaneous coronary intervention; ICD, implantable cardioverter defibrillator; CPB, cardiopulmonary bypass; RRT, renal replacement therapy. Numbers in brackets are interquartile ranges (IQRs). ANOVA was applied to the BMI variable because of its normal distribution. The Kruskal-Wallis test was used to compare other variables.
Table 2. Demographics and Perioperative Characteristics of HTx Recipients Stratified by AKI.
|
|
AKI (n=26) |
Non-AKI (n=46) |
P value |
|
Demographic data |
|||
|
Age, years |
54.38±13.18 |
53.63±11.72 |
0.581 |
|
< 60 |
16(61.54) |
27(58.7) |
0.815 |
|
≥60 |
10(38.46) |
19(41.3) |
|
|
Sex, men, n (%) |
24(92.31) |
36(78.26) |
0.127 |
|
BMI (kg/m2) |
25.20±4.46 |
23.75±3.31 |
0.121 |
|
History of alcohol |
6(23.08) |
13(28.26) |
0.634 |
|
History of smoking |
18(69.23) |
28(60.87) |
0.481 |
|
Hypertension |
13(50.00) |
15(32.61) |
0.149 |
|
Diabetes mellitus |
11(42.31) |
16(34.78) |
0.529 |
|
Chronic kidney disease |
9(34.62) |
7(15.22) |
0.059 |
|
Pretransplant characteristics |
|||
|
DCM |
7(26.92) |
23(50.00) |
0.058 |
|
CAD |
11(42.31) |
11(23.91) |
0.106 |
|
Valve disease |
5(19.23) |
6(13.04) |
0.486 |
|
Pre-PCI |
3(11.54) |
3(6.52) |
0.463 |
|
ICD implantation |
0(0) |
3(6.52) |
0.187 |
|
EF pre-HTx (%) |
28(25,30) |
25(20,30) |
0.279 |
|
Creatinine (mg/dL) |
1.10(0.95,1.22) |
1.15(0.95,1.30) |
0.460 |
|
GFR (ml/min/1.73m2) |
39.82(36.24,46.54) |
38.98(29.62,46.93) |
0.446 |
|
<30 |
5(19.23) |
13(28.26) |
0.698 |
|
30-59 |
18(69.23) |
28(60.87) |
|
|
≥60 |
3(11.54) |
5(10.87) |
|
|
Intraoperative characteristics |
|||
|
CPB duration (min) |
247.5(210,270) |
215(183,240) |
0.033* |
|
Blood transfusion (ml) |
1485(1000,1900) |
1420(1100,1960) |
0.865 |
|
Infusion (ml) |
2020(1320,3000) |
1750(1400,2100) |
0.278 |
|
Blood loss (ml) |
1600(1000,2500) |
1250(1000,2000) |
0.240 |
|
Urine volume (ml) |
1500(1000,2000) |
2000(1300,2600) |
0.019* |
|
IABP/ECMO |
5(19.23) |
0(0) |
0.002* |
|
Postoperative characteristics |
|||
|
Urine volume |
|||
|
1st Day after operation |
2136.5(1785,2965) |
2145(2010,2520) |
0.582 |
|
2nd Day after operation |
1952.5(1525,2425) |
2117.5(1845,2505) |
0.286 |
|
3rd Day after operation |
2032.5(1318,2225) |
2162.5(1970,2615) |
0.015* |
|
RRT |
13(50.00) |
0(0) |
<0.001* |
|
Mechanical ventilation (min) |
2190(1140,4560) |
1245(960,2160) |
0.041* |
|
Time to discharge (days) |
27.5(22,41) |
25(22,32) |
0.533 |
|
Death within 1 year |
7(26.92) |
5(10.87) |
0.0813* |
|
Follow-up days |
503(64,1398) |
727(354,1250) |
0.450 |
* P<0.05; ANOVA was applied to the BMI variable because of its normal distribution. The Kruskal-Wallis test was used to compare other variables.
Table 3 Demographics and Perioperative Characteristics of HTx Recipients Stratified by RRT
|
|
Non-AKI without RRT (n=46) |
AKI without RRT (n=13) |
AKI with RRT (n=13) |
P value |
|
Demographic data |
||||
|
Age, years |
53.63±11.72 |
49.62±15.91 |
59.15±7.71 |
0.286 |
|
< 60 |
27(58.70) |
9(69.23) |
7(53.85) |
0.929 |
|
≥60 |
19(41.30) |
4(30.77) |
6(46.15) |
|
|
Sex, men, n (%) |
36(78.26) |
13(100) |
11(84.62) |
0.315 |
|
BMI (kg/m2) |
23.75±3.31 |
25.35±5.06 |
25.04±3.96 |
0.296 |
|
History of alcohol |
13(28.26) |
1(7.69) |
5(38.46) |
0.810 |
|
History of smoking |
28(60.87) |
9(69.23) |
9(69.23) |
0.516 |
|
Hypertension |
15(32.61) |
7(53.85) |
6(46.15) |
0.239 |
|
Diabetes mellitus |
16(34.78) |
4(30.77) |
7(53.85) |
0.296 |
|
Chronic kidney disease |
7(15.22) |
3(23.08) |
6(46.15) |
0.022* |
|
Pretransplant characteristics |
||||
|
DCM |
23(50.00) |
4(30.77) |
3(23.08) |
0.057 |
|
CAD |
11(23.91) |
4(30.77) |
7(53.85) |
0.048* |
|
Valve disease |
6(13.04) |
2(15.38) |
3(23.08) |
0.395 |
|
Pre-PCI |
3(6.52) |
3(23.08) |
0(0) |
0.892 |
|
ICD implantation |
3(6.52) |
0(0) |
0(0) |
0.223 |
|
EF pre-HTx (%) |
25(20,30) |
25(25,28) |
29(25,33) |
0.188 |
|
Creatinine (mg/dL) |
1.15(0.95,1.30) |
1.08(0.94,1.17) |
1.11(1.00,1.27) |
0.261 |
|
GFR (ml/min/1.73 m2) |
38.98(29.62,46.93) |
44.30(38.58,52.38) |
38.23(29.21,40.45) |
0.065 |
|
<30 |
13(28.26) |
0(0) |
5(38.46) |
0.816 |
|
30-59 |
28(60.87) |
10(76.92) |
8(61.54) |
|
|
≥60 |
5(10.87) |
3(23.08) |
0(0) |
|
|
Intraoperative characteristics |
||||
|
CPB duration (min) |
215(183,240) |
210(200,240) |
270(255,325) |
0.004* |
|
Blood transfusion (ml) |
1420(1100,1960) |
1440(1000,1700) |
1500(1300,2500) |
0.363 |
|
Infusion (ml) |
1750(1400,2100) |
1980(1400,2950) |
2060(1250,3050) |
0.553 |
|
Blood loss (ml) |
1250(1000,2000) |
1000(1000,2000) |
2000(1600,3000) |
0.081 |
|
Urine volume (ml) |
2000(1300,2600) |
1600(1000,2000) |
1200(820,2000) |
0.049* |
|
IABP/ECMO |
0(0) |
0(0) |
5(38.46) |
<0.001* |
|
Postoperative characteristics |
||||
|
Urine volume |
||||
|
1st Day after operation |
2145(2010,2520) |
2440(1975,3010) |
1965(1195,2375) |
0.066 |
|
2nd Day after operation |
2117.5(1845,2505) |
2220(1850,2765) |
1525(1060,2235) |
0.041* |
|
3rd Day after operation |
2162.5(1970,2615) |
2110(2000,2300) |
1885(255,2130) |
0.013* |
|
Mechanical ventilation (min) |
1245(960,2160) |
1140(840,1860) |
4320(2220,6240) |
<0.001* |
|
Time to discharge (days) |
25(22,32) |
24(22,28) |
33(22,64) |
0.278 |
|
Death within 1 year |
5(10.87) |
0(0) |
7(53.85) |
0.003* |
|
Follow-up days |
727(354,1250) |
1398(309,2135) |
64(22,556) |
0.005* |
* P<0.05; ANOVA was applied to the BMI variable because of its normal distribution. The Kruskal-Wallis test was used to compare other variables
Table 4.1 Multivariate model for AKI.
|
|
OR |
95% CI |
P value |
|
|
CPB time |
1.622 |
1.014 |
2.595 |
0.044* |
|
Intraoperative urine volume |
0.566 |
0.344 |
0.930 |
0.025* |
Table 4.2 Perioperative predictors of death
|
|
HR |
95% CI |
P value |
|
|
Age, years ≥60 |
2.776 |
0.833 |
9.252 |
0.096 |
|
AKI requiring RRT |
6.402 |
2.014 |
20.355 |
0.002* |
* P<0.05; OR, odds ratio; HR, hazard ratio; CI, confidence interval; CPB, cardiopulmonary bypass; AKI, acute kidney injury; RRT, renal replacement therapy.