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Vol. 29. Issue 4. (In progress)
(July - August 2024)
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Vol. 29. Issue 4. (In progress)
(July - August 2024)
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Impact of preoperative nonselective beta-blocker use on acute kidney injury after living donor liver transplantation: Propensity score analysis
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Hye-Won Jeonga, Jae Hwan Kimb, Sang-bin Hanb, Hye-Mee Kwonb, In-Gu Junb, Jun-Gol Songb,
Corresponding author
jungol.song@amc.seoul.kr

Corresponding author.
, Gyu-Sam Hwangb
a Department of Anesthesiology and Pain Medicine, Chonnam National University Hospital, Gwangju, Korea
b Department of Anesthesiology and Pain Medicine, Laboratory for Cardiovascular Dynamics, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Korea
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Tables (4)
Table 1. Perioperative characteristics and postoperative outcomes of the study population.
Table 2. Perioperative characteristics of the study population after PS-matching and IPTW analysis.
Table 3. Multivariate logistic regression analysis for acute kidney injury after living donor liver transplantation.
Table 4. Predictive value of preoperative NSBBs for acute kidney injury after living donor liver transplantation.
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Abstract
Introduction and Objectives

Acute kidney injury (AKI) is prevalent and has deleterious effects on postoperative outcomes following liver transplantation (LT). The impact of nonselective beta-blockers (NSBBs) in patients with liver cirrhosis remains controversial. This study investigated the association between preoperative NSBB use and AKI after living donor LT (LDLT).

Patients and Methods

We evaluated 2,972 adult LDLT recipients between January 2012 and July 2022. The patients were divided into two groups based on the preoperative NSBB use. Propensity score matched (PSM) and inverse probability of treatment weighting (IPTW) analyses were performed to evaluate the association between preoperative NSBB use and postoperative AKI. Multiple logistic regression analyses were also used to identify the risk factors for AKI.

Results

The overall incidence of AKI was 1,721 (57.9%) cases. The NSBB group showed a higher incidence of AKI than the non-NSBB group (62.4% vs. 56.7%; P = 0.011). After PSM and IPTW analyses, no significant difference in the incidence of AKI was found between the two groups (Odds ratio, OR 1.13, 95% confidence interval, CI 0.93–1.37, P = 0.230, PSM analysis; OR 1.20, 95% CI 0.99–1.44, P = 0.059, IPTW analysis). In addition, preoperative NSBB use was not associated with AKI after multivariate logistic regression analysis (OR 1.16, 95% CI 0.96–1.40, P = 0.118).

Conclusions

Preoperative NSBB use was not associated with AKI after LDLT. Further studies are needed to validate our results.

Keywords:
Nonselective beta-blockers
Living donor liver transplantation
Acute kidney injury
Propensity score
Abbreviations:
ABOi
AKI
BBs
BMI
CI
CKD
eGFR
FFP
HCV
HR
HRS
IPTW
IQR
LT
LC
LDLT
MELD
NSBBs
OR
PT-INR
PRS
pRBCs
PSM
SBP
sCr
Full Text
1Introduction

Acute kidney injury (AKI) is a frequent complication after liver transplantation (LT), with detrimental effects on patient outcomes. Studies have reported a wide range of incidence rates for post-LT AKI, ranging from 17% to over 90% [1,2]. Additionally, rates for renal replacement therapy have been reported to range from 8 to 20% [3,4]. Post-LT AKI has been consistently shown to impact post-transplant outcomes. Even mild AKI following LT increased the risk of post-LT chronic kidney disease (CKD) and decreased patient and graft survival rates [3,5–7]. Therefore, it would be beneficial to identify and mitigate the risk factors that can deteriorate renal function to improve postoperative outcomes after LT.

Nonselective beta-blockers (NSBBs) have been the mainstay treatment for portal hypertension in patients with liver cirrhosis (LC) [8]. Response to NSBB therapy is associated with a lower risk of portal hypertension-related complications, including variceal rebleeding, ascites, and spontaneous bacterial peritonitis (SBP), as well as improved survival rates [9,10]. However, recent studies have raised concerns about the potential negative impact of NSBB therapy in patients with end-stage liver disease [11–14]. The cardio-inhibitory effects of NSBBs may reduce the cardiac compensatory reserve, which is essential for renal and hepatic perfusion [14,15], leading to renal failure and poor survival in patients with liver cirrhosis with ascites [16–18].

Although the impact of NSBBs on AKI has been investigated in various patient populations [12,13,19,20], there is a lack of research on the influence of preoperative NSBB use on the incidence of postoperative AKI in LT recipients. Therefore, we investigated the association between preoperative NSBB use and postoperative AKI in living donor LT (LDLT) recipients. We hypothesized that preoperative NSBB therapy in LDLT recipients might have a negative impact on renal outcomes after LDLT.

2Patients and methods2.1Patients

The Institutional Review Board of Asan Medical Center approved this study (protocol number: 2023–0561) and waived the need for informed consent due to the retrospective nature of the study. We reviewed the electronic medical records of all patients who underwent LT at Asan Medical Center between January 2012 and July 2022. This study included adult patients (≥18 years) who underwent LDLT. Patients with a preoperative serum creatinine (sCr) level > 1.4 mg/dL, those diagnosed with CKD or hepatorenal syndrome (HRS), or those receiving hemodialysis at baseline were excluded from the study. The remaining patients were divided into two groups based on their preoperative NSBB use for at least one month. At our center, LT candidates who may benefit from NSBBs are selected by hepatologists and prescribed NSBBs for both primary and secondary prophylaxis against variceal bleeding, as well as for the potential prevention of further decompensation [21–24].

2.2Clinical data

Clinical data were extracted from an electronic medical records system, including demographic data, donor-related variables, perioperative laboratory results, intraoperative records containing details of anesthetic management and surgical procedures, and postoperative outcomes. The demographic data included preoperative characteristics of recipients, including beta-blocker use, patient age, sex, and body mass index (BMI); comorbidities, such as diabetes mellitus, hypertension, and coronary arterial disease; liver disease characteristics, such as the etiology of LC (hepatitis B virus, hepatitis C virus [HCV], alcoholic LC, and other disease), Model for End-Stage Liver Disease (MELD) score, Child-Pugh-Turcotte score; SBP; intractable ascites; dual donor grafts; and ABO incompatibility (ABOi). Donor-related variables included donor age, sex, and total fatty change. Laboratory data included prothrombin time–international normalized ratio (PT-INR), albumin, total bilirubin, creatinine, and estimated glomerular filtration rate (eGFR). Intraoperative data included severe post-reperfusion syndrome (PRS), volume and type of fluids (crystalloid and colloid), volume of blood components (packed red blood cells [pRBCs] and fresh frozen plasma [FFP]), massive transfusion, inotrope/vasopressor use, urine output, anesthetic time, cold ischemic time, warm ischemic time, total ischemic time, graft-to-recipient weight ratio, bio-pump use, and intraoperative embolization. PRS was defined as a decrease in mean arterial pressure by more than 30% compared to the pre-reperfusion level, persisting for at least 1 min within the initial 5 min following the reperfusion of the liver graft [25]. In addition, PRS was considered severe if there was a requirement for over 30 μg of epinephrine during the reperfusion phase [26]. Massive transfusion was defined as transfusion of ≥10 pRBC units within 24 h, or >4 pRBC units in 1 h [27].

2.3Primary and secondary outcomes

The primary outcome of this study is postoperative AKI, which was diagnosed according to the Kidney Disease Improving Global Outcome criteria. AKI was defined as an increase in sCr by ≥0.3 mg/dL within 48 h postoperatively or an increase in sCr to ≥1.5 times the baseline value within postoperative day 7 [28]; baseline sCr was measured the day before LT as our routine protocol for LDLT recipients [29]. More specifically, stage 1 was defined as an increase in sCr to 1.5–1.9 times baseline or an increase in sCr by ≥0.3 mg/dL. Stage 2 was defined as an increase in sCr to 2.0–2.9 times baseline, while stage 3 was defined as an increase in sCr to 3.0 times baseline or an increase in sCr to ≥4.0 mg/dl, or the initiation of renal replacement therapy [28].

Secondary outcomes include 1-year graft failure and mortality, overall graft failure, and overall mortality. Graft failure was defined as re-transplantation or death. We reviewed electronic medical records and the regularly updated Asan Organ Transplantation Center registry to determine graft failure and mortality incidence.

2.4Statistical analysis

Continuous variables are reported as mean ± standard deviation or median with interquartile range (IQR), and categorical variables are reported as frequencies with percentages. According to the use of preoperative NSBBs, patients were divided into the NSBB and non-NSBB groups. Between-group comparisons were conducted using the Student t-test or the Mann–Whitney U test for continuous variables, and the Chi-square test or the Fisher exact test for categorical variables, as appropriate.

Propensity scores (PSs) were calculated to balance confounding variables and reduce selection bias between the NSBB and non-NSBB groups, using logistic regression based on all preoperative data, including demographic variables, donor-related variables, and laboratory variables listed in Table 1. Model discrimination was evaluated using C statistics (c-statistics = 0.650), and calibration was assessed using Hosmer–Lemeshow statistics (P = 0.166). The baseline characteristics of the NSBB group and non-NSBB group were balanced using propensity score matched (PSM) analysis and inverse probability of treatment weighting (IPTW) analyses. However, there were disparities in some important intraoperative variables, such as severe PRS, massive transfusion, and anesthetic time between the NSBB and non-NSBB groups after PS matching. Given that these variables could confound the relationship between preoperative NSBB use and post-LT AKI, we made additional adjustments for these variables in both PSM and IPTW analyses.

Table 1.

Perioperative characteristics and postoperative outcomes of the study population.

  Non-NSBB (n = 2331)  NSBB (n = 641)  Total (n = 2972)  P-value 
Demographic variables
Age (years)  55.0 (50.0–61.0)  55.0 (50.0–60.0)  55.0 (50.0–60.0)  0.898 
Sex, male  1706 (73.2%)  487 (76.0%)  2193 (73.8%)  0.171 
Body mass index (kg/m224.1 (21.9–26.3)  24.4 (22.4–26.6)  24.2 (22.0–26.4)  0.004 
Diabetes mellitus  544 (23.3%)  204 (31.8%)  748 (25.2%)  <0.001 
Hypertension  448 (19.2%)  123 (19.2%)  571 (19.2%)  1.000 
Coronary arterial disease  177 (7.6%)  69 (10.8%)  246 (8.3%)  0.012 
Etiology
Hepatitis B virus  1338 (57.4%)  374 (58.3%)  1712 (57.6%)  0.701 
Hepatitis C virus  153 (6.6%)  36 (5.6%)  189 (6.4%)  0.436 
Alcoholic  551 (23.6%)  161 (25.1%)  712 (24.0%)  0.469 
Other disease  352 (15.1%)  90 (14.0%)  442 (14.9%)  0.545 
MELD score  11.0 (8.0–16.0)  11.0 (9.0–15.0)  11.0 (8.0–16.0)  0.061 
Child-Pugh-Turcotte score  7.0 (6.0–9.0)  7.0 (6.0–9.0)  7.0 (6.0–9.0)  0.805 
Child-Pugh-Turcotte grade         
917 (39.3%)  243 (37.9%)  1160 (39.0%)  0.541
B and C  1414 (60.7%)  398 (62.1%)  1812 (61.0%) 
Spontaneous bacterial peritonitis  56 (2.4%)  24 (3.7%)  80 (2.7%)  0.085 
Dual donor grafts  150 (6.4%)  51 (8.0%)  201 (6.8%)  0.204 
ABO incompatibility  556 (23.9%)  178 (27.8%)  734 (24.7%)  0.047 
Donor-related variables
Age (years)  28.0 (23.0–35.0)  28.0 (22.0–35.0)  28.0 (23.0–35.0)  0.537 
Sex, male  1542 (66.2%)  417 (65.1%)  1959 (65.9%)  0.637 
Total fatty change (%)  1.0 (0.0– 5.0)  1.0 (0.0–5.0)  1.0 (0.0– 5.0)  0.716 
Laboratory variables
PT-INR  1.3 (1.1–1.5)  1.3 (1.2–1.5)  1.3 (1.1–1.5)  <0.001 
Albumin (g/dL)  3.2 (2.8–3.6)  3.1 (2.8–3.4)  3.2 (2.8–3.6)  0.002 
Total bilirubin (mg/dL)  1.4 (0.7–2.9)  1.4 (0.8–2.3)  1.4 (0.8–2.8)  0.777 
Creatinine (mg/dL)  0.7 (0.6–0.9)  0.8 (0.6–0.9)  0.7 (0.6–0.9)  0.373 
eGFR (mL/min/1.73 m290.0 (76.0–90.0)  90.0 (76.0–90.0)  90.0 (76.0–90.0)  0.581 
Intraoperative variables
Severe post-reperfusion syndrome  183 (7.9%)  74 (11.5%)  257 (8.6%)  0.004 
Crystalloid (L)  6.3 (4.9–8.0)  6.4 (5.0–8.2)  6.3 (4.9–8.0)  0.160 
Albumin (L)  3.0 (2.0–4.0)  3.2 (2.4–4.5)  3.0 (2.0–4.1)  <0.001 
Red blood cell transfusion (units)  5.0 (1.0–11.0)  6.0 (2.0–12.0)  6.0 (1.0–11.0)  0.001 
FFP transfusion (units)  4.0 (0.0–10.0)  6.0 (2.0–12.0)  5.0 (0.0–10.0)  <0.001 
Massive transfusion  684 (29.3%)  227 (35.4%)  911 (30.7%)  0.004 
Total urine output (mL)  1750.0 (1280.0–2430.0)  1790.0 (1330.0–2390.0)  1750.0 (1290.0–2420.0)  0.630 
Anesthetic time (hr)  13.2 (12.1–14.7)  13.5 (12.3–15.1)  13.2 (12.2–14.8)  0.001 
Cold ischemic time (min)  81.0 (65.0–98.0)  82.0 (67.0–97.0)  81.0 (66.0–98.0)  0.313 
Warm ischemic time (min)  38.0 (30.0–46.0)  38.0 (31.0–48.0)  38.0 (30.0–46.0)  0.112 
Total ischemic time (hr)  2.0 (1.7–2.4)  2.1 (1.7–2.4)  2.0 (1.7–2.4)  0.143 
Graft-to-recipient weight ratio  1.1 (0.9–1.2)  1.0 (0.9–1.2)  1.1 (0.9–1.2)  0.444 
Bio-pump use  257 (11.0%)  69 (10.8%)  326 (11.0%)  0.908 
Intraoperative embolization  469 (20.1%)  156 (24.3%)  625 (21.0%)  0.023 
Surgical outcomes
Acute kidney injury  1321 (56.7%)  400 (62.4%)  1721 (57.9%)  0.011 
Acute kidney injury grade (1/2/3)  904 (38.8%) / 338 (14.5%) / 79 (3.4%)  252 (39.3%) / 123 (19.2%) / 25 (3.9%)  1156 (38.9%) / 461 (15.5%) / 104 (3.5%)  0.009 
Graft failure at 1 year  94 (4.0%)  21 (3.3%)  115 (3.9%)  0.445 
Mortality at 1 year  80 (3.4%)  16 (2.5%)  96 (3.2%)  0.289 
Overall graft failure  263 (11.3%)  65 (10.1%)  328 (11.0%)  0.456 
Overall mortality  246 (10.6%)  55 (8.6%)  301 (10.1%)  0.164 

Values are expressed as mean ± standard deviation, median (interquartile range), or number of patients (%), as appropriate. NSBB, Nonselective beta blocker; MELD score, Model for end-stage liver disease score; PT-INR, prothrombin time–international normalized ratio; eGFR, estimated glomerular filtration rate; FFP, fresh frozen plasma.

The association between preoperative NSBB use and post-LT outcomes was evaluated using multivariate logistic regression and Cox proportional hazard regression analyses. Multivariate logistic regression analysis was used to identify the factors associated with post-LT AKI. Variables with P-values <0.1 in the univariate analysis were included in the multivariate analysis. Multivariate Cox regression analysis was used to assess the factors associated with 1-year graft failure and mortality, overall graft failure, and overall mortality. Backward elimination was used to develop the final model, and adjusted odds ratio (OR) or hazard ratio (HR) was calculated.

All P-values <0.05 were considered statistically significant. Data manipulation and statistical analyses were performed using SPSS 22.0 (IBM Corp., Armonk, NY, USA) and R 3.5.1 (R Foundation for Statistical Computing, Vienna, Austria).

2.5Ethical statement

The Institutional Review Board of Asan Medical Center approved this study (protocol number: 2023-0561).

3Results

We included 2972 adult LDLT recipients in this study, and the median follow-up time was 4.7 years (IQR 2.3–7.5 years). Based on preoperative NSBB use, the 2972 patients were divided into the non-NSBB group (n = 2331) and the NSBB group (n = 641). The duration and dosage for patients in the NSBB group were as follows: For propranolol, the median duration of use was 142 days (IQR 67–456 days) with a median dosage of 40 mg/day (IQR 20–40 mg/day). For carvedilol, the median duration was 93 days (IQR 45–178 days) with a median dosage of 12.5 mg/day (IQR 6.2–13.2 mg/day). Table 1 shows their preoperative and intraoperative data and surgical outcomes. The NSBB group included a higher proportion of patients with diabetes mellitus and coronary arterial disease. They had a higher BMI, a longer PT-INR, and lower albumin levels than the non-NSBB group. Additionally, they were more likely to undergo ABOi LT. Intraoperatively, these patients experienced a higher incidence of severe PRS, required more albumin infusions, had a greater need for pRBC and FFP transfusions, underwent embolization of the remaining portosystemic shunts performed by interventional radiologists more frequently, and had a longer anesthetic time. Among the 2972 LDLT recipients, the incidence of AKI was 57.9% (n = 1721). The incidence of 1-year graft failure and mortality was 3.9% (n = 115) and 3.2% (n = 96), respectively. The graft failure and overall mortality rates were 11.0% (n = 328) and 10.1% (n = 301), respectively. When comparing the incidence of AKI, there was a statistically significant difference between the two groups (62.4% in the NSBB group and 56.7% in the non-NSBB group, P = 0.011). Specifically, in the non-NSBB group, 38.8% (n = 904) patients had AKI stage 1, 14.5% (n = 338) had stage 2, and 3.4% (n = 79) had stage 3. In contrast, the NSBB group had 39.3% (n = 252) cases in Stage 1, 19.2% (n = 123) in Stage 2, and 3.9% (n = 25) in Stage 3 (P = 0.009).

Table 2 shows preoperative and intraoperative characteristics of PSM patients (1:1 to 1:3 matched set, n = 2329 total set, n = 1703 in non-NSBB group and n = 626 in NSBB group). After PS matching, no significant differences were observed in demographic, donor-related, and preoperative laboratory variables between NSBB and non-NSBB groups. The incidence of post-LT AKI was 62.5% (n = 391) in the NSBB group and 57.8% (n = 984) in the non-NSBB group after PSM analysis.

Table 2.

Perioperative characteristics of the study population after PS-matching and IPTW analysis.

  PS-matching analysisIPTW analysis
  Non-NSBB(n = 1703)  NSBB(n = 626)  SMD  Non-NSBB(n = 2331)  NSBB(n = 641)  SMD 
Demographic variables
Age (years)  55.1 ± 8.3  54.7 ± 8.2  0.043  54.4 ± 9.0  54.4 ± 8.5  0.007 
Sex, male  1295 (76.0%)  476 (76.0%)  <0.001  1722 (73.9%)  481 (75.0%)  0.026 
Body mass index (kg/m224.6 ± 3.5  24.8 ± 3.6  0.057  24.4 ± 3.6  24.5 ± 3.5  0.045 
Diabetes mellitus  485 (28.5%)  195 (31.2%)  0.058  588 (25.2%)  165 (25.7%)  0.011 
Hypertension  320 (18.8%)  120 (19.2%)  0.010  448 (19.2%)  122 (19.0%)  0.007 
Coronary arterial disease  137 (8.0%)  63 (10.1%)  0.070  193 (8.3%)  53 (8.2%)  0.003 
Etiology
Hepatitis B virus  973 (57.1%)  365 (58.3%)  0.024  1334 (57.2%)  386 (60.2%)  0.060 
Hepatitis C virus  119 (7.0%)  36 (5.8%)  0.051  154 (6.6%)  34 (5.2%)  0.058 
Alcoholic  417 (24.5%)  157 (25.1%)  0.014  559 (24.0%)  154 (24.0%)  0.002 
MELD score  11.0 (8.0–16.0)  11.0 (9.0–15.0)  0.008  11.0 (8.0–16.0)  11.0 (9.0–15.0)  0.021 
Child-Pugh-Turcotte score  7.0 (6.0–9.0)  7.0 (6.0–9.0)  0.010  7.0 (6.0–9.0)  7.0 (6.0–9.0)  0.016 
Intractable ascites  586 (34.4%)  211 (33.7%)  0.015  771 (33.1%)  204 (31.8%)  0.028 
Dual donor grafts  104 (6.1%)  47 (7.5%)  0.056  159 (6.8%)  44 (6.8%)  0.001 
ABO incompatibility  445 (26.1%)  170 (27.2%)  0.023  575 (24.7%)  161 (25.1%)  0.010 
Donor-related variables
Age (years)  28.9 ± 8.4  29.1 ± 8.6  0.017  29.3 ± 8.7  29.1 ± 8.5  0.014 
Sex, male  1110 (65.2%)  408 (65.2%)  <0.001  1536 (65.9%)  427 (66.6%)  0.014 
Total fatty change (%)  1.0 (0.0–5.0)  1.0 (0.0–5.0)  0.040  1.0 (0.0–5.0)  1.0 (0.0–5.0)  0.022 
Laboratory variables
PT-INR  1.3 (1.2–1.5)  1.3 (1.2–1.5)  0.079  1.3 (1.1–1.5)  1.3 (1.2–1.5)  0.066 
Albumin (g/dL)  3.2 ± 0.6  3.1 ± 0.5  0.086  3.2 ± 0.6  3.1 ± 0.5  0.086 
Total bilirubin (mg/dL)  1.4 (0.8–2.7)  1.4 (0.8–2.3)  0.071  1.4 (0.8–2.9)  1.4 (0.8–2.3)  0.090 
Creatinine (mg/dL)  0.8 ± 0.2  0.8 ± 0.2  0.051  0.8 ± 0.2  0.8 ± 0.2  0.062 
eGFR (mL/min/1.73 m289.7 ± 18.2  90.2 ± 18.3  0.025  89.8 ± 18.7  89.9 ± 18.4  0.002 
Intraoperative variables
Severe post-reperfusion syndrome  135 (7.9%)  72 (11.5%)  0.121  183 (7.9%)  70 (11.0%)  0.106 
Crystalloid (L)  6.4 (4.9–8.0)  6.4 (5.0–8.2)  0.025  6.4 (4.9–8.0)  6.3 (5.0–8.1)  0.010 
Albumin (L)  3.0 (2.0–4.3)  3.2 (2.4–4.4)  0.006  3.0 (2.0–4.0)  3.2 (2.4–4.5)  0.025 
Red blood cell transfusion (units)  5.0 (2.0–11.0)  6.0 (2.0–12.0)  0.056  5.0 (1.0–11.0)  6.0 (2.0–13.0)  0.049 
FFP transfusion (units)  5.0 (0.0–10.0)  6.0 (2.0–12.0)  0.075  4.0 (0.0–10.0)  6.0 (2.0–12.0)  0.064 
Massive transfusion  504 (29.6%)  220 (35.1%)  0.119  691 (29.7%)  224 (35.0%)  0.114 
Total urine output (mL)  1720.0 (1260.0–2430.0)  1790.0 (1330.0–2390.0)  0.005  1750.0 (1280.0–2430.0)  1790.0 (1345.0–2440.0)  0.011 
Anesthetic time (hr)  13.6 ± 2.2  13.8 ± 2.3  0.118  13.5 ± 2.2  13.8 ± 2.2  0.108 
Cold ischemic time (min)  83.6 ± 25.7  84.7 ± 26.2  0.042  83.6 ± 25.9  83.7 ± 26.3  0.004 
Warm ischemic time (min)  38.0 (30.0–47.0)  38.0 (31.0–47.0)  0.046  38.0 (30.0–46.0)  38.0 (31.0–47.0)  0.020 
Total ischemic time (hr)  2.1 ± 0.5  2.1 ± 0.6  0.054  2.1 ± 0.5  2.1 ± 0.6  0.012 
Graft-to-recipient weight ratio  1.1 ± 0.2  1.1 ± 0.2  0.013  1.1 ± 0.2  1.1 ± 0.2  0.002 
Intraoperative embolization  354 (20.8%)  151 (24.1%)  0.080  473 (20.3%)  156 (24.4%)  0.098 

Values are expressed as mean ± standard deviation, median (interquartile range), or number of patients (%), as appropriate. PS, propensity score; IPTW analysis, inverse probability of treatment weighted analysis; NSBB, Nonselective beta blocker; SMD, standardized mean difference; MELD score, Model for end-stage liver disease score; PT-INR, prothrombin time–international normalized ratio; eGFR, estimated glomerular filtration rate; FFP, fresh frozen plasma.

In the univariate logistic regression analysis, preoperative NSBB use was associated with post-LT AKI (OR 1.27, 95% confidence interval, CI 1.06–1.52, P = 0.009) (Table 3). However, after adjusting variables related to AKI, preoperative NSBB use was not associated with post-LT AKI (OR 1.16, 95% CI 0.96–1.40, P = 0.118). However, BMI (OR 1.10, 95% CI 1.07–1.12, P < 0.001), HCV (OR 1.48, 95% CI 1.07–2.07, P = 0.020), MELD score (OR 1.04, 95% CI 1.03–1.06, P < 0.001), intractable ascites (OR 1.22, 95% CI 1.02–1.45, P = 0.026), and anesthetic time (OR 1.22, 95% CI 1.16–1.28, P < 0.001) were associated with post-LT AKI. Furthermore, preoperative NSBB use was not significantly associated with post-LT AKI in PSM analysis (OR 1.13, 95% CI 0.93–1.37, P = 0.230) and IPTW analysis (OR 1.20, 95% CI 0.99–1.44, P = 0.059) (Table 4).

Table 3.

Multivariate logistic regression analysis for acute kidney injury after living donor liver transplantation.

UnivariateMultivariate
OR  95% CIP-value  OR  95% CIP-value 
Preoperative NSBBs use  1.27  1.06  1.52  0.009  1.16  0.96  1.40  0.118 
Age (years)  1.00  1.00  1.01  0.368         
Sex, male  0.99  0.84  1.17  0.939         
Body mass index  1.10  1.07  1.12  <0.001  1.10  1.07  1.12  <0.001 
Diabetes mellitus  1.04  0.88  1.23  0.678         
Hypertension  1.04  0.86  1.25  0.682         
Etiology                 
Hepatitis B virus  0.83  0.72  0.96  0.015         
Hepatitis C virus  1.65  1.21  2.28  0.002  1.48  1.07  2.07  0.020 
Alcoholic  1.19  1.00  1.41  0.048         
MELD score  1.06  1.04  1.07  <0.001  1.04  1.03  1.06  <0.001 
Intractable ascites  1.37  1.18  1.61  <0.001  1.22  1.02  1.45  0.026 
ABO incompatibility  1.03  0.87  1.22  0.733         
Donor Age (years)  1.00  0.99  1.01  0.678         
Donor Sex, male  1.05  0.90  1.23  0.500         
Donor Total fatty change (%)  1.01  1.00  1.02  0.253         
Severe post-reperfusion syndrome  1.31  1.01  1.72  0.045         
Massive transfusion  2.01  1.70  2.37  <0.001         
Vasopressor use  0.94  0.74  1.20  0.642         
Anesthetic time (hr)  1.26  1.21  1.31  <0.001  1.22  1.16  1.28  <0.001 
Total ischemic time (hr)  1.34  1.17  1.54  <0.001         
Graft-to-recipient weight ratio  0.59  0.43  0.79  <0.001         
Bio-pump use  1.80  1.41  2.31  <0.001         
Intraoperative embolization  1.19  1.00  1.43  0.055         

NSBBs, Nonselective beta-blockers; MELD score, Model for end-stage liver disease score; OR, odds ratio; CI, confidence interval.

Table 4.

Predictive value of preoperative NSBBs for acute kidney injury after living donor liver transplantation.

  Unadjusted  Multivariable adjusteda  Propensity score-matchedbIPTW analysisb
  Event/n  OR  95% CI  P-value    OR  95% CI  P-value    Event/n  OR  95% CI  P-value  OR  95% CI  P-value 
Acute kidney injury  NSBB  400/641  1.27  1.06–1.52  0.009    1.16  0.96–1.40  0.118    391/626  1.13  0.93–1.37  0.230  1.20  0.99–1.44  0.059 
  Non-NSBB  1321/2331              984/1703         
a

Adjusted by all variables in Table 3.

b

Adjusted by severe post-reperfusion syndrome, anesthetic time (hr), and massive transfusion after propensity score matching. NSBB, Nonselective beta blocker; OR, odds ratio; CI, confidence interval.

No significant difference was observed in the incidence of 1-year graft failure and mortality, overall graft failure, or overall mortality between the NSBB group and the non-NSBB group (all P-values >0.05) (Table 1). Cox proportional regression analysis revealed that preoperative NSBB use was not associated with 1-year graft failure and mortality, overall graft failure, or overall mortality (HR 0.81, 95% CI 0.50–1.30, P = 0.373; HR 0.72, 95% CI 0.42–1.23, P = 0.233; HR 0.86, 95% CI 0.66–1.13, P = 0.283; HR 0.77, 95% CI 0.58–1.04, P = 0.085, respectively). In PSM analysis, preoperative NSBB use was not associated with 1-year graft failure and mortality, overall graft failure, or overall mortality (HR 0.78, 95% CI 0.48–1.27, P = 0.315; HR 0.69, 95% CI 0.39–1.20, P = 0.186; HR 0.85, 95% CI 0.64–1.13, P = 0.264; HR 0.76, 95 % CI 0.56–1.03, P = 0.076, respectively). In IPTW analysis, preoperative NSBB use was not associated with 1-year graft failure and mortality, overall graft failure, or overall mortality (HR 0.68, 95% CI 0.42–1.12, P = 0.133; HR 0.60, 95% CI 0.35–1.06, P = 0.078; HR 0.86, 95% CI 0.64–1.14, P = 0.288; HR 0.76, 95% CI 0.56–1.03, P = 0.080).

4Discussion

LDLT recipients who used NSBBs preoperatively had a higher incidence of post-LT AKI than those who did not. However, no significant association was found between preoperative NSBB use and post-LT AKI in multivariate, PSM, and IPTW analyses. In addition, no significant association was found between preoperative NSBB use and 1-year graft failure and mortality, overall graft failure, or overall mortality.

NSBBs have played a fundamental role in preventing portal hypertension-related complications in patients with cirrhosis for decades. LT candidates benefit from NSBBs for both primary and secondary prophylaxis against variceal bleeding, as well as for the potential prevention of further decompensation and death [21–24]. However, NSBBs may be harmful, particularly in patients with decompensated LC [11,30,31]. Mechanically, in decompensated LC, activation of the sympathetic nervous system leads to increased left ventricle systolic function, as an adaptive mechanism to maintain renal perfusion. Beta-blockade may blunt this sympathetic overdrive, lowering cardiodynamic reserve and renal perfusion pressure, resulting in impaired renal function [16–18,32]. Although AKI frequently occurs after LT and has deleterious effects on long-term outcomes [1–3,5–7], the impact of preoperative NSBB use on post-LT AKI has not been evaluated.

Studies have reported conflicting results about the effects of NSBBs on renal function in patients with LC. A retrospective cohort study reported that NSBB use was neither associated with a deterioration of renal function nor an increase in AKI incidence in patients with LC with gastroesophageal varices [20]. Their findings are consistent with ours, but their study mostly included patients with compensated LC. Another retrospective study reported that NSBBs increased the risk for HRS and AKI in patients with cirrhosis and SBP [13]. However, the association was assessed only through Pearson's chi-square test. In addition, a nested case-control study of LT candidates reported that NSBBs significantly increased AKI in patients with ascites while they decreased AKI in patients without ascites [19]. However, their case and control groups were matched using a limited set of variables: age, sCr, MELD-Na scores at baseline, and follow-up duration. All these mentioned studies focused on patients with LC prior to their operations. However, the development of post-LT AKI is influenced not only by preoperative factors but also by the factors encountered during the surgical process. Therefore, our research carries clinical significance as the first to investigate the association between preoperative NSBBs use and post-LT AKI in LDLT recipients. We used multivariate, PSM, and IPTW analyses to adjust for a wide range of preoperative and intraoperative variables to assess the association between preoperative NSBB use and the development of AKI after LT.

Patients undergoing various surgeries have shown inconsistent outcomes on the impact of preoperative beta blockers (BBs) on postoperative AKI. A large multicenter cohort study found no significant association between preoperative BBs within 24 h of elective coronary artery bypass surgery and perioperative outcomes, including renal failure in PSM analysis [33]. In another study including ASA 1–2 patients undergoing non-cardiac surgery, preoperative BBs were significantly associated with postoperative AKI in univariate analysis but not in multivariate analysis [34]. Acute BBs use independently predicted postoperative AKI in hypertensive patients undergoing non-suprainguinal vascular surgery, likely due to kidney ischemic injury from global perioperative hypotension [35]. Lastly, regular preoperative use of anti-adrenergic agents (alpha and/or beta-blockers) was independently associated with the development of AKI after non-cardiac surgeries in both multivariate and PSM analyses [36]. However, these studies reported the incidence rates of postoperative AKI to be 2–6%, significantly lower than the 17–90% observed in LT recipients. This discrepancy can be attributed to the unique circumstances associated with LC patients, often complicated by cirrhotic cardiomyopathy. Furthermore, the large intraoperative hemodynamic fluctuations that can occur during LT due to factors such as inferior vena cava clamping, PRS, massive bleeding, or massive transfusions may contribute to this discrepancy. Therefore, findings from other surgeries may not be directly applicable to LT recipients.

Post-LT AKI has been reported to be related to MELD, BMI, HCV, intractable ascites, and anesthetic time [37–40]. Therefore, our findings of the factors associated with post-LT AKI in the multivariate analysis are consistent with those of previous studies. Meanwhile, no significant differences were observed between preoperative NSBB use and 1-year graft failure and mortality, overall graft failure, or overall mortality in our study. Many studies have explored the impact of NSBBs on survival in patients with LC with conflicting results [11,13,30,41,42]. Furthermore, a recent study reported that the incidences of graft failure were 8.7%, 14.2%, 19.4%, and 42.0% for adult LDLT, and the incidences of mortality were 7.8%, 13.3%, 18.6%, and 35.9% for adult LT at 1,3,5, and 10 years, respectively [43]. Notably, our results showed a lower incidence of postoperative graft failure and mortality, suggesting that a larger sample size may be needed for more robust conclusions.

Our study has several limitations. First, its retrospective nature may introduce confounding factors and selection bias. We used multivariate, PSM, and IPTW analyses to mitigate these issues. Second, this research was conducted in a single center, one of the world's leading LT institutions, with an experienced surgical and perioperative management team, which may have affected postoperative outcomes, including AKI. Therefore, care should be given when generalizing our findings. Therefore, while this study provides valuable insights, further multicenter, prospective research is needed to confirm and expand upon our findings.

5Conclusions

In conclusion, no significant association between preoperative NSBB use and postoperative AKI was observed after multivariate, PSM, and IPTW analyses in LDLT. These results suggest that preoperative NSBB use is not a significant risk factor for AKI following LDLT.

Author contributions

Conceptualization: HWJ, JGS, GSH. Data curation: HWJ, JGS, JHK, SBH, HMK, IGJ. Formal analysis: HWJ, JGS, JHK, SBH, HMK, IGJ. Funding acquisition: did not receive any specific. grant. Investigation: HWJ, JGS. Methodology: HWJ, JGS. Project administration: HWJ, JGS. Resources: HWJ, JGS, GSH. Software: HWJ, JGS. Supervision: HWJ, JGS, GSH. Validation: HWJ, JGS. Visualization: HWJ, JGS. Writing - original draft: HWJ, JGS. Writing - review & editing: HWJ, JGS,GSH. All the authors have read and approved the final manuscript.

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