
==== Front
Int J Surg
Int J Surg
JS9
International Journal of Surgery (London, England)
1743-9191
1743-9159
Lippincott Williams & Wilkins Hagerstown, MD

38833358
IJS-D-24-00983
10.1097/JS9.0000000000001670
00015
3
Original Research
Long-term outcomes and risk factors for early bacterial infection after pediatric liver transplantation: a prospective cohort study
Sun Xicheng MD asunxckjwn@163.com

Sun Xiaowei PhD sunxiaowei_sz@163.com
b
Zhou Tao MD aemperorztxy@126.com

Li Peiying PhD blipeiying@renji.com

Wang Bingran MD adr_wangbingran@163.com

Pan Qi MD ayxcbxxpanqi@sina.com

Zhou Aiwei MD azhouaiwei97@163.com

Qian Yongbing MD aqianyb79@hotmail.com

Liu Yongbo PhD acliuyongbo@renji.com

Liu Yuan MD ad*liuyuanbird@163.com

Xia Qiang MD, PhD ace*xiaqiang@shsmu.edu.cn

a Department of Liver Surgery, Renji Hospital, Shanghai Jiao Tong University School of Medicine
b Clinical Research Center, Renji Hospital, Shanghai Jiao Tong University School of Medicine
c Shanghai Institute of Transplantation
d Shanghai Immune Therapy Institute
e Shanghai Engineering Research Center of Transplantation and Immunology, Shanghai, People’s Republic of China
* Corresponding author. Address: Renji Hospital, Shanghai Jiao Tong University School of Medicine, 160 Pujian Road, Shanghai 200127, People’s Republic of China. Tel.: +86 21 683 839 29. E-mail: liuyuanbird@163.com (Y. Liu), and Tel.: +86 21 683 837 75. E-mail: xiaqiang@shsmu.edu.cn (Q. Xia).
9 2024
4 6 2024
110 9 54525462
18 3 2024
9 5 2024
Copyright © 2024 The Author(s). Published by Wolters Kluwer Health, Inc.
2024
https://creativecommons.org/licenses/by-nc-nd/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution-Non Commercial-No Derivatives License 4.0 (CCBY-NC-ND), where it is permissible to download and share the work provided it is properly cited. The work cannot be changed in any way or used commercially without permission from the journal. http://creativecommons.org/licenses/by-nc-nd/4.0/

Background:

Liver transplantation (LT) is the most efficient treatment for pediatric patients with end-stage liver diseases, while bacterial infection is the leading reason for post-transplant mortality. The present study is to explore the outcomes and risk factors of early bacterial infection (within 1 months) after pediatric LT.

Methods:

In this prospective cohort study, 1316 pediatric recipients [median (IQR) age: 9.1 (6.3–28.0) months; male: 48.0%; median (IQR) follow-up time: 40.6 (29.1–51.4) months] who received LT from September 2018 to April 2022 were included. Bacterial culture samples such as sputum, abdominal drainage, blood, and so on were collected when recipients were presented with infective symptoms. Kaplan–Meier analysis was applied to estimate the long-term survival rates and logistic regression was used to identify independent risk factors. To explore the role of pretransplant rectal swab culture (RSC) in reducing post-transplant bacterial infection rate, 188 infant LT recipients [median (IQR) age: 6.8 (5.5–8.1) months; male: 50.5%] from May 2022 to September 2023 were included. Log-binomial regression was used to measure the association of pretransplant RSC screening and post-transplant bacterial infection. The ‘Expectation Maximization’ algorithm was used to impute the missing data.

Results:

Bacterial infection was the primary cause for early (38.9%) and overall mortality (35.6%) after pediatric LT. Kaplan–Meier analysis revealed inferior 1-year and 5-year survival rates for recipients with post-transplant bacterial infection (92.6 vs. 97.1%, 91.8 vs. 96.4%, respectively; P<0.001). Among all detected bacteria, Staphylococcus spp. (34.3%) and methicillin-resistant coagulase-negative Staphylococci (43.2%) were the dominant species and multidrug resistant organisms, respectively. Multivariable analysis revealed that infant recipients [adjusted odds ratio (aOR) 1.49; 95% CI: 1.01–2.20], male recipients (aOR, 1.43; 95% CI: 1.08–1.89), high graft-to-recipient weight ratio (aOR, 1.64; 95% CI: 1.17–2.30), positive post-transplant RSC (aOR, 1.45; 95% CI: 1.04–2.02) and nasopharyngeal swab culture (aOR 2.46; 95% CI: 1.72–3.52) were independent risk factors for early bacterial infection. Furthermore, RSC screening and antibiotic prophylaxis before transplantation could result in a relatively lower post-transplant infection rate, albeit without statistical significance (adjusted RR, 0.53; 95% CI: 0.25–1.16).

Conclusion:

In this cohort study, post-transplant bacterial infection resulted in an inferior long-term patient survival rate. The five identified independent risk factors for post-transplant bacterial infection could guide the prophylaxis strategy of post-transplant bacterial infection in the future. Additionally, pretransplant RSC might decrease post-transplant bacterial infection rate.

Keywords:

bacterial infection
pediatric liver transplantation
rectal swab culture
risk factor
OPEN-ACCESSTRUE
SDCT
==== Body
pmcIntroduction

Highlights

The long-term patient and graft survival rates were significantly lower in pediatric liver transplantation recipients with post-transplant bacterial infection compared with those without bacterial infection.

The five identified independent risk factors for pediatric post-transplant bacterial infection could guide the prophylaxis strategy for post-transplant bacterial infection.

Pretransplant rectal swab culture might decrease post-transplant bacterial infection rate.

Liver transplantation (LT) is considered as the most efficient treatment for end-stage liver diseases in children. With the development of surgical techniques and perioperative management, over 75–90% of recipients can survive up to 5 years after transplantation1–3. Based on the analysis of mortality after transplantation, bacterial infection was found as the leading cause, accounting for ~21% of the overall post-LT mortality4–8. The incidence of bacterial infection after LT ranged from 20 to 80%8. Compared to adult LT recipients, pediatric LT recipients are more susceptible to early infection due to pretransplant malnutrition, the complexity of operative procedures, and an immature immune system6,7,9–13. Studies that included adult LT recipients had revealed that pretransplant status, massive pleural effusion, or ascites, diabetes mellitus, low serum albumin level, operative blood loss, and postoperative cytomegalovirus infection were associated with post-transplant bloodstream infection (BSI)14–18. Moreover, prolonged perioperative hospitalization, use of extensive-spectrum antibiotics and the placement of central venous or artery catheters made LT recipients increasingly vulnerable to multidrug-resistant organisms (MDROs) infection, which was associated with higher post-LT morbidity and mortality9,10,19. Therefore, identifying the risk factors associated with post-transplant infection could assist physicians in distinguishing susceptible recipients and implementing individualized anti-infection strategies. However, previous studies have been limited to BSIs and no studies have investigated the impact and risk factors of overall bacterial infection after pediatric LT.

Taking advantage of the large pediatric LT sample size, as well as the comprehensive data on individual characteristics, medical history, and follow-up data from the Ren Ji Pediatric Liver Transplantation (RJPLT) cohort, this study aimed to 1) explore the association of post-transplant bacterial infection with long-term outcomes and identify independent risk factors for early bacterial infection (within 1 months) after pediatric LT; 2) investigate the role of pretransplant RSC screening in decreasing early bacterial infection after pediatric LT.

Methods

This study was approved by the Clinical Research Ethics Committee of Ren Ji Hospital and registered on Chinese Clinical Trial Registry. Participants or their legal guardians were required to provide written informed consent before inclusion. None of the organs were procured from executed prisoners and organs were procured after informed consent with full record in the China Organ Transplant Response System (https://www.cot.org.cn/). The study followed the Strengthening the Reporting of Cohort Studies in Surgery (STROCSS, Supplemental Digital Content 1, http://links.lww.com/JS9/C698) criteria20.

Study design, setting, and population

The present study was carried out based on the prospective RJPLT (Ren Ji Pediatric Liver Transplantation) cohort, which was designed to investigate the associations of demographical and perioperative characteristics with post-transplant outcomes (such as post-transplant complications and mortality). From September 2018 to September 2023, a total of 1748 consecutive cases of pediatric LT (all of them were younger than 18 years) were conducted in Ren Ji Hospital, Ren Ji University School of Medicine. After exclusion, a total of 1711 pediatric recipients were included. Among them, 1316 pediatric recipients were included in the post-transplant Bacterial Infection Study (from September 2018 to April 2022) to investigate the long-term outcomes and risk factors for bacterial infection after pediatric LT (Fig. 1). Additionally, to evaluate the role of pretransplant rectal swab culture (RSC) screening in reducing the post-transplant infection rate, 188 infant recipients (age <12 months) with biliary atresia as the primary disease from the RJPLT cohort were enrolled in the pretransplant RSC Screening Study (from May 2022 to September 2023), which was further divided into RSC and non-RSC group depending on whether pretransplant RSC was conducted (Fig. 1). RSC screening-positive recipients were considered to have pathogen colonization and antibiotics were administered when infective symptoms (such as fever, chills, sweats, cough, consolidation in chest radiograph, and so on) were manifested.

Figure 1 Flowchart of the subject selection and classification. RJPLT, ** Pediatric Liver Transplantation; RSC, rectal swab culture.

Data collection and variable definitions

Perioperative clinical and laboratory data were collected through an electronic follow-up system, which was used to record information on demographic characteristics, medical history, laboratory tests, immunosuppressive strategy, physical development, complications, and treatments. Preoperative variables including age at the time of transplantation, sex, growth retardation (defined as 2 SD below the average height or weight for the same age group), indication for LT, history of abdominal surgery and pretransplant laboratory examinations [albumin (ALB), alanine aminotransferase (ALT), total bilirubin (TB), creatinine and international normalized ratio (INR)] were collected. Pediatric end-stage liver disease (PELD) scores for recipients <12 years21, model for end-stage liver disease (MELD) scores for recipients ≥12 years22 at the time of transplant and creatinine clearance (CCr) (based on Cockcroft-Gault equation)23 were calculated. Surgery-associated variables including blood type (ABO) incompatibility, graft type, LT type, graft-to-recipient weight ratio (GRWR), bile duct anastomosis type, massive blood loss, and blood product transfusion. After LT, data on bacterial infection, length of hospital and ICU stay, acute and chronic rejection (including clinical acute rejection and biopsy-proven acute rejection)24, and grade III–IV complications according to the Dindo–Clavien classification were collected25.

Follow-up strategy

Enrolled participants were required to take follow-up blood and imaging tests every week within 3 months after transplantation, every 2 weeks within 6 months, and every one or 2 months thereafter. The last follow-up time of this cohort study was 1 December 2023.

Outcomes and definitions

In the post-transplant Bacterial Infection Study, the primary endpoint was the patient mortality and the influence of early bacterial infection on graft survival was additionally evaluated. In the pretransplant RSC Screening Study, the primary endpoint was early culture-proven bacterial infection (within 1 months after the LT)26 while the early gram-negative bacteria (GNB) infection was also assessed. A multidisciplinary team including an expert in transplant infection was responsible for the diagnosis and treatment of post-transplant infection. Patients received microbial culture when presenting infection signs as mentioned above. Samples for culture included sputum (when recipients manifested fever, cough, sputum production, and were suspected of having pneumonia), thoracentesis fluid (when pleuritic chest pain and massive pleural fluid were presented), abdominal drainage fluid (when recipients were presented with fever, abdominal pain, tenderness, or were suspected of biliary leaks, intestinal perforation), central vein catheter tips (when central vein catheter was placed for more than 7 days after LT and patient manifested fever, chills, or purulent discharge from the site of catheter placement), peripheral vein bloodstream (when recipients manifested the signs of bacteremia such as chills, hypotensive, tachycardic, and febrile), urine (when recipients were presented with dysuria, frequency, and urgency) and wound discharge (when wound pain and purulent secretion appeared). Based on the sites of infection, early post-transplant bacterial infections were classified into lower respiratory tract infections (LRTIs), intra-abdominal infections (IAIs), BSIs, wound infections, and urinary tract infections26. BSIs were further classified into primary BSIs, catheter-related bloodstream infections (CR-BSIs), and secondary BSIs27. RSC and nasopharyngeal swab culture (NPSC) were routinely conducted when recipients were transferred to the ICU after transplantation.

Statistical analysis

Continuous data were expressed as median (interquartile range, IQR) and compared with the Mann–Whitney U test. Categorical data were expressed as number (percentage, %) and compared with the χ 2 test or Fisher’s exact test as appropriate.

Survival rates were calculated using the Kaplan–Meier estimation with log-rank test. Univariable and multivariable Cox proportional hazards regression analyses were used to investigate the independent association of post-transplant bacterial infection with patient mortality or graft loss. Variables with P-value <0.1 in univariable analyses (Figure S1, Supplemental Digital Content 1, http://links.lww.com/JS9/C699) were included in the multivariable Cox regression model.

To screen factors associated with post-transplant bacterial infection, univariable, and multivariable logistic regression were conducted. In this process, the following quantitative variables were converted to qualitative variables: Age <12 months (defined as infant recipient)7, ALB <30 g/l, ALT >5 upper limit of normal value (ULN), TB >3 ULN, CCr <80 ml/min, INR >1.5 and GRWR ≥4%28. Variables with P-value <0.1 in the univariable analysis and clinically relevant factors based on previous studies were introduced into a multivariable logistic regression model to identify the independent risk factors for post-transplant bacterial infection. To address the problem of multiple comparisons, false discovery rate (FDR) correction was used, and FDR-adjusted P=values were calculated. Sensitivity analysis without incomplete observations was further conducted to test the robustness of the identified risk factors.

In the analyses of the associations between pretransplant RSC screening and post-transplant bacterial as well as GNB infection, univariable and multivariable log-binomial regression were used to estimate the relative risk (RR) of the pretransplant RSC screening for post-transplant infection. The initial multivariable log-binomial regression included the same confounders as the multivariable logistic regression model, except for the infant recipient and indication. We used propensity score methods to balance the baseline characteristics between the RSC and non-RSC screening groups. The individual propensity score was estimated with a multivariable logistic regression model, which included the same covariates as the multivariable log-binomial regression model. The primary analysis was conducted using the propensity score weighting method (using stabilized inverse probability weight in a simple log-binomial regression model). We then applied 1:1 nearest-neighbor propensity score matching within a caliper radius equal to a SD of 0.1 and propensity score adjustment (propensity score considered as an additional covariate in a multivariable log-binomial regression model) to test the robustness of the results.

Missing data are reported (Figure S2, Supplemental Digital Content 1, http://links.lww.com/JS9/C699) and the ‘Expectation Maximization’ algorithm was used to impute the missing data29. All statistical analyses were performed with R, version 4.1.0 (R Foundation for Statistical Computing). Nominal two-sides P<0.05 were considered statistically significant.

Results

General characteristics of enrolled pediatric LT recipients in the bacterial infection study

A total of 1316 recipients who received primary LT with a median (IQR) follow-up time of 40.6 (29.1–51.4) months were included in the post-transplant Bacterial Infection Study (Fig. 1). Among them, 269 recipients [median (IQR) follow-up time: 39.8 (25.2–48.6) months] with positive bacterial culture constructed the infection group, while the other 1047 recipients [median (IQR) follow-up time: 40.8 [29.6–52.1] months] were assigned to the noninfection group (Fig. 1). Demographic and perioperative characteristics are summarized in Table 1. The median (IQR) age at the time of transplantation was 9.1 (6.3–28.0) months, with cholestatic liver disease (82.4%) as the primary indication (Table 1). Living donor liver transplantation (LDLT) was the dominant operation type (77.2%). The median (IQR) PELD score before transplantation was 15 (6–23) for recipients younger than 12 years and the median (IQR) MELD score was 11 (4.25–14.75) for those older than 12 years (Table 1).

Table 1 Baseline characteristics of recipients in bacterial infection study.

Characteristic	Total (n=1316)	Noninfection group (n=1047)	Infection group (n=269)	P c	
Age, months	9.1 (6.3–28.0)	10.0 (6.4–29.9)	7.2 (5.7–19.1)	<0.001	
Sex (male)	632 (48.0)	484 (46.2)	148 (55.0)	0.010	
Growth retardation	611 (46.4)	478 (45.7)	133 (49.4)	0.266	
Indication				0.055	
 Cholestatic liver disease	1084 (82.4)	850 (81.2)	234 (87.0)		
 Metabolic liver disease	134 (10.2)	111 (1.6)	23 (8.6)		
 Others	98 (7.5)	86 (8.2)	12 (4.5)		
History of abdominal surgery	850 (64.6)	667 (63.7)	183 (68.0)	0.186	
ALB <30 g/l	247 (18.8)	186 (17.8)	61 (22.7)	0.066	
ALT >5ULN	337 (25.6)	257 (24.6)	80 (29.7)	0.082	
TB >3 ULN	534 (40.6)	413 (39.5)	121 (45.00)	0.099	
CCr <80 ml/min	641 (48.7)	508 (48.5)	133 (49.4)	0.787	
INR >1.5	417 (31.7)	323 (30.9)	94 (34.9)	0.198	
PELD scorea	15 (6–23)	14 (5–23)	17 (8–24)	0.032	
MELD scoreb	11 (4.25–14.75)	11 (4.25–14.75)	10 (4–15.25)	1.000	
Blood type incompatibility	56 (4.3)	40 (3.8)	16 (6.0)	0.123	
LT type				0.119	
 LDLT	1016 (77.2)	815 (77.8)	201 (74.7)		
 Split DDLT	132 (10.0)	96 (9.2)	36 (13.4)		
 Whole-liver DDLT	168 (12.8)	136 (13.0)	32 (11.9)		
Graft type (left lateral segment)	1047 (79.6)	827 (79.0)	220 (81.8)	0.310	
GRWR ≥4%	292 (22.2)	205 (19.6)	87 (32.3)	<0.001	
Reduced-size graft	193 (14.7)	151 (14.4)	42 (15.6)	0.622	
Bile duct anastomosis				0.206	
 Duct-to-duct	186 (14.1)	157 (15.0)	29 (1.8)		
 Old RY HJ	696 (52.9)	547 (52.2)	149 (55.4)		
 New RY HJ	434 (33.0)	343 (32.8)	91 (33.8)		
Massive blood loss	156 (11.9)	111 (1.6)	45 (16.7)	0.006	
Blood product transfusion	1024 (77.8)	802 (76.6)	222 (82.5)	0.037	
Positive post-transplant RSC	257 (19.5)	189 (18.1)	68 (25.3)	0.008	
Positive post-transplant NPSC	189 (14.4)	127 (12.1)	62 (23.1)	<0.001	
Data are presented as number (percentage) or median (interquartile range). Due to rounding, the percentage might differ from the data presented, and percentages might not be a total of 100.

a PELD (pediatric end-stage liver disease) scores were calculated for 1290 recipients in the Bacterial Infection Study (265 in the infection group and 1025 in the noninfection group) who were less than 12 years old.

b MELD (model for end-stage liver disease) scores were calculated for 26 recipients in the Bacterial Infection Study (4 in the infection group and 22 in the noninfection group) who were not less than 12 years old.

c P<0.05 was considered statistically significant.

ALB, albumin; ALT, alanine aminotransferase; CCr, creatinine clearance; GRWR, graft-to-recipient weight ratio; HJ, hepaticojejunostomy; INR, international normalized ratio; LDLT, living donor; LT, DDLT, deceased donor; LT, liver transplantation; LT, RY, Roux-en-Y; NPSC, nasopharyngeal swab culture; RSC, rectal swab culture; TB, total bilirubin.

Influence of post-transplant bacterial infection on the long-term outcomes

Analysis for reasons of post-transplant mortality indicated that bacterial infection was the primary reason for the early (38.9%) and overall (35.6%) mortality after pediatric LT (Fig. 2A–B). Recipients free of bacterial infection exhibited superior 1-year and 5-year survival rates than those suffering from bacterial infection (97.1 vs. 96.4%; 92.6 vs. 91.8%; P<0.001) (Fig. 2C), so as the graft survival rates (1-year: 96.9 vs. 96.1%; 5-year: 91.4 vs. 89.9%; P<0.001) (Fig. 2D). Multivariable Cox regression analysis indicated that post-transplant bacterial infection independently impaired the patient [adjusted hazards ratio (aHR), 1.88; 95% CI: 1.05–3.37] and graft survival (aHR, 2.01; 95% CI: 1.18–3.41) (Fig. 2C-D), so as the GNB infection [for patient survival: aHR (95% CI): 3.22 (1.73–5.98); for graft survival: aHR (95% CI): 3.42 (1.96–5.98)] (Figure S3A-B, Supplemental Digital Content 1, http://links.lww.com/JS9/C699). Intriguingly, gram-positive bacteria (GPB) and MDRO infections were not correlated with patient mortality and graft loss (Figure S3C-F, Supplemental Digital Content 1, http://links.lww.com/JS9/C699). The median (IQR) days of the hospital (2318-35 vs. 1815-22; P<0.001) and ICU (65-8 vs. 54-6; P<0.001) stay after LT were longer for recipients with post-transplant bacterial infection. Compared with recipients free of bacterial infection, higher incidence of grade III–IV complications (19.0 vs. 7.1%, P<0.001) including exploratory laparotomy (10.4 vs. 2.1%, P<0.001) and retransplantation (1.9 vs. 0.3%, P=0.012) were found in the infection group (Table S1, Supplemental Digital Content 1, http://links.lww.com/JS9/C699).

Figure 2 Causes of mortality after pediatric liver transplantation and survival analyses of the pediatric LT recipients. (A) Overall causes of mortality after pediatric LT (liver transplantation). (B) Causes of mortality after pediatric LT within the first month. (C-D) Kaplan–Meier analysis of the patient (C) and graft (D) survival rates in pediatric recipients with or without bacterial infection after LT. Notes: Multivariable Cox regression model for investigating the association of post-transplant bacterial infection with the all-cause patient mortality (C) adjusted for indication, LT type, massive blood loss, positive post-transplant RSC (rectal swab culture), length of ICU stay, length of hospital stay, grade III–IV complication and acute rejection. Multivariable Cox regression model for investigating the association of post-transplant bacterial infection with the all-cause graft loss (D) adjusted for total bilirubin > 3 ULN (upper limit of normal value), blood type incompatibility, LT type, graft type, massive blood loss, positive post-transplant RSC, length of ICU stay, length of hospital stay, grade III–IV complication, acute and chronic rejection. PTLD, post-transplant lymphoproliferative disorder; PGD, primary graft dysfunction (including primary nonfunctional and initial poor function); ARDS, acute respiratory distress syndrome; cHR, crude hazard ratio; aHR, adjusted hazard ratio.

Independent risk factors for post-transplant bacterial infection

Univariable logistic regression analyses revealed that infant recipients (age <12 months), male sex, noncholestatic liver disease, deceased donor liver transplantation (DDLT), GRWR ≥4%, massive blood loss and blood product transfusion during operation, positive post-transplant RSC and NPSC were associated with post-transplant bacterial infection (Figure S4, Supplemental Digital Content 1, http://links.lww.com/JS9/C699). Five independent risk factors for post-transplant bacterial infection were identified in the multivariable analysis: infant recipients [adjusted OR (aOR), 1.49; 95% CI: 1.01–2.20], male sex (aOR, 1.43; 95% CI: 1.08–1.89), GRWR ≥4% (aOR, 1.64; 95% CI: 1.17–2.30), positive post-transplant RSC (aOR, 1.45; 95% CI: 1.04–2.02) and NPSC screening (aOR, 2.46; 95% CI: 1.72–3.52) (Fig. 3). The FDR-corrected P-values for associations between multiple risk factors and post-transplant bacterial infection were presented in Table S2 (Supplemental Digital Content 1, http://links.lww.com/JS9/C699). Sensitivity analysis without incomplete observations yielded similar results (Table S3, Supplemental Digital Content 1, http://links.lww.com/JS9/C699).

Figure 3 Multivariable logistic regression analysis for investigating the risk factors of post-transplant bacterial infection. Notes: Independent risk factors (P-value <0.05) for post-transplant bacterial infection were colored burgundy, and insignificant variables (P-value ≥0.05) are colored deep sky blue. Ref indicated the reference used in the multivariable logistic regression. aOR, adjusted odds ratio; ALB, albumin; ALT, alanine aminotransferase; ULN, upper limit of normal value; TB, total bilirubin; DDLT, deceased donor liver transplantation; LDLT, living donor liver transplantation; GRWR, graft-to-recipient weight ratio; RY, Roux-en-Y; HJ, hepaticojejunostomy; RSC, rectal swab culture; NPSC, nasopharyngeal swab culture.

Microbial spectrum of post-transplant bacterial infection

The overall bacterial and MDRO infection rates within 1 month after pediatric LT were 20.4 and 5.2%, respectively (Fig. 4A), with comparable overall infection rates of GPB and GNB (12.6 and 10.9%, respectively) (Fig. 4C). Staphylococcus spp. (34.3%) and Klebsiella spp. (13.0%) were predominantly detected bacteria after LT (Fig. 4B and Table S4, Supplemental Digital Content 1, http://links.lww.com/JS9/C699), while methicillin-resistant coagulase-negative Staphylococci (MR-CNS, 43.2%) and carbapenem-resistant Klebsiella pneumoniae (CRKP, 24.7%) were the primary MDROs (Fig. 4D and Table S5, Supplemental Digital Content 1, http://links.lww.com/JS9/C699). The lower respiratory tract was the most common infected site (8.8%), followed by the abdomen (5.6%) and bloodstream [primary BSI (5.5%), CR-BSI (4.6%), secondary BSI (0.4%)] (Fig. 4A). The microbial composition of post-transplant infection varied among different sites (Fig. 4B). Staphylococcus aureus (21.1%) and Klebsiella pneumoniae (18.3%) were two major detected pathogens in the lower respiratory tract, while the culture of abdominal drainage indicated that Enterococcus spp. (25.8%) and Acinetobacter baumanii (12.4%) were the primary pathogens in IAI. Coagulase-negative Staphylococci (CNS) were the dominant strains in the primary BSI (35.3%) and CR-BSI (50%) (Fig. 4B and Table S4, Supplemental Digital Content 1, http://links.lww.com/JS9/C699). Post-transplant RSC and NPSC screening indicated that 19.5 and 14.4% of recipients were found with bacterial colonization in the digestive tract and upper respiratory tract, and GNB (98.0%) including Escherichia coli (51.1%) and Klebsiella pneumoniae (39.6%) were the most commonly detected bacteria in the digestive tract (Fig. 4C).

Figure 4 Incidences and microbial spectrums of post-transplant bacterial and MDRO infection. (A) Bacterial and MDRO (multidrug-resistant organism) infection rates in different sites after pediatric liver transplantation. (B) Microbial composition of bacteria in different infection sites after pediatric liver transplantation. (C) GPB (gram-positive bacteria) and GNB (gram-negative bacteria) infection rates in different sites after pediatric liver transplantation. (D) Microbial composition of MDROs in different infection sites after pediatric liver transplantation. LRTI, lower respiratory tract infection; IAI, intra-abdominal infection; BSI, bloodstream infection; CR-BSI, catheter-related bloodstream infection; RSC, rectal swab culture; NPSC, nasopharyngeal swab culture; E. coli, Escherichia coli; S. maltophilia, Stenotrophomonas maltophilia; CNS, coagulase-negative staphylococci; S. aureus, Staphylococcus aureus; MRSA, methicillin-resistant S. aureus; MR-CNS, methicillin-resistant CNS; CRE, carbapenem-resistant Enterobacteriaceae; VRE, vancomycin-resistant Enterococcus; CR-AB, carbapenem-resistant Acinetobacter baumanii; ESBL, extended-spectrum β-lactamase.

Effectiveness of pretransplant RSC screening and antibacterial prophylaxis on post-transplant bacterial infection

Since bacterial colonization is an independent risk factor for post-transplant infection, we further explored whether pretransplant screening could reduce the post-transplant infection rate. A total of 188 infant recipients [median (IQR) age, 6.8 (5.5–8.1) months] with biliary atresia were enrolled in the RSC Screening Study. Sixty-three recipients [median (IQR) age, 6.2 (5.3–7.6) months; 35 (55.6%) males] who accepted pretransplant RSC screening constructed the RSC group, while the rest of the 125 recipients [median (IQR) age, 7.1 (5.9–8.3) months; 60 (48.0%) males] were assigned to the non-RSC group (Fig. 1 and Table 2). Bacterial colonization was found in 11.1% (7/63) patients before transplantation via RSC screening, with CRKP as the only detected pathogen. The overall bacterial and GNB infection rates after transplantation were insignificantly reduced in the RSC group compared with the non-RSC group (18.4 vs. 24.8%; 14.3 vs. 19.1%, respectively). Crude and multivariable analyses also indicated a lower relative risk of post-transplant bacterial [crude RR (cRR) (95% CI): 0.71 (0.34–1.51); adjusted RR (aRR) (95% CI): 0.44 (0.18–1.07)] and GNB infection [cRR (95% CI): 0.74 (0.32–1.71); aRR (95% CI): 0.42 (0.15–1.14)] in the RSC screening group, although not statistically significant (Table 3). Consistent results were found after balancing the baseline characteristics (overall bacterial: RR, 0.53; 95% CI: 0.25–1.16; GNB infection: RR, 0.54; 95% CI: 0.23–1.30) and the results were also found robust in propensity score matching and propensity score-adjusted model (Figure S5, Supplemental Digital Content 1, http://links.lww.com/JS9/C699 and Table 3).

Table 2 Baseline characteristics of the pediatric recipients in the RSC screening study before and after propensity score weighting.

	Unweighted recipients	Weighted recipients	
Characteristic	Non-RSC screening (n=125)	RSC screening (n=63)	P a	Non-RSC screening (w=121.6)	RSC screening (w=65.8)	P a	
Age, months	7.1 (5.9–8.3)	6.2 (5.3–7.6)	0.010	6.8 (5.5–8.1)	6.2 (5.5–7.8)	0.746	
Sex (male)	60 (48.0)	35 (55.6)	0.328	62.7 (51.6)	36.8 (55.9)	0.624	
Growth retardation	40 (32.0)	14 (22.2)	0.162	36.0 (29.6)	20.9 (31.8)	0.809	
History of abdominal surgery	107 (85.6)	46 (73)	0.036	97.8 (80.5)	55.4 (84.3)	0.515	
ALB<30 g/l	17 (13.6)	8 (12.7)	0.864	15.9 (13.1)	8.0 (12.1)	0.866	
ALT > 5ULN	42 (33.6)	26 (41.3)	0.302	44.6 (36.7)	23.8 (36.3)	0.959	
TB >3 ULN	68 (54.4)	33 (52.4)	0.793	66.9 (55.0)	35.4 (53.8)	0.895	
CCr <80 ml/min	62 (49.6)	32 (50.8)	0.877	57.8 (47.6)	33.2 (50.5)	0.744	
INR > 1.5	42 (33.6)	27 (42.9)	0.214	41.3 (33.9)	24.4 (37.1)	0.695	
Blood type incompatibility	21 (16.8)	11 (17.5)	0.909	19.6 (16.1)	8.4 (12.7)	0.550	
LT type			1.000			0.638	
 LDLT	115 (92.0)	59 (93.7)		112.6 (92.6)	59.6 (90.6)		
 Split DDLT	7 (5.6)	3 (4.8)		6.8 (5.6)	5.6 (8.6)		
 Whole-liver DDLT	3 (2.4)	1 (1.6)		2.2 (1.8)	0.5 (0.8)		
Graft type (left lateral segment)	122 (97.6)	62 (98.4)	1.000	119.3 (98.2)	65.2 (99.2)	0.472	
GRWR ≥4%	68 (54.4)	29 (46.0)	0.278	62.7 (51.6)	33.6 (51.1)	0.961	
Reduced-size graft	11 (8.8)	11 (17.5)	0.081	14.1 (11.6)	7.8 (11.9)	0.954	
Bile duct anastomosis			<0.001			0.997	
 Duct-to-duct	1 (0.8)	1 (1.6)		1.6 (1.4)	0.9 (1.3)		
 Old RY HJ	98 (78.4)	32 (50.8)		85.2 (70.0)	45.7 (69.5)		
 New RY HJ	26 (20.8)	30 (47.6)		34.8 (28.6)	19.2 (29.2)		
Massive blood loss	4 (3.2)	6 (9.5)	0.139	5.6 (4.6)	3.3 (5.1)	0.881	
Blood product transfusion	112 (89.6)	50 (79.4)	0.055	105.6 (86.9)	57.5 (87.5)	0.901	
Positive post-transplant RSC	17 (13.6)	8 (12.7)	0.864	17.0 (14.0)	8.5 (12.9)	0.858	
Positive post-transplant NPSC	29 (23.2)	17 (27)	0.569	29.6 (24.3)	17.9 (27.2)	0.720	
Data are presented as number (percentage). Due to rounding, the percentage might differ from the data presented, and percentages might not be a total of 100.

a P<0.05 was considered statistically significant.

ALB, albumin; ALT, alanine aminotransferase; CCr, creatinine clearance; GRWR, graft-to-recipient weight ratio; HJ, hepaticojejunostomy; INR, international normalized ratio; LDLT, living donor; LT, liver transplantation; LT; DDLT, deceased donor LT; NPSC, nasopharyngeal swab culture; RSC, rectal swab culture; RY, Roux-en-Y; TB, total bilirubin.

Table 3 Analyses of associations between pretransplant RSC screening and post-transplant bacterial infection.

Analysis	Bacterial infection	GNB infection	
No. of events/no. of patients at risk (%)	
 Non-RSC screening	31/125 (24.8)	23/125 (18.4)	
 RSC screening	12/63 (19.1)	9/63 (14.3)	
Crude analysis	
 cRR (95% CI)	0.71 (0.34–1.51)	0.74 (0.32–1.71)	
 P-value	0.377	0.48	
Multivariable analysis	
 aRR (95% CI)a	0.44 (0.18–1.07)	0.42 (0.15–1.14)	
 P-value	0.071	0.087	
Propensity-score analyses — RR (95% CI)	
 With inverse probability weightingb	0.53 (0.25–1.16)	0.54 (0.23–1.30)	
 With matchingc	0.54 (0.20–1.45)	0.48 (0.16–1.43)	
 With adjustmentd	0.51 (0.22–1.17)	0.49 (0.19–1.25)	
a Shown is the adjusted relative risk (aRR) from the multivariable log-binomial model, with adjustment for age, sex, growth retardation, albumin<30 g/l, alanine aminotransferase > 5 ULN (upper limit of normal value), total bilirubin > 3 ULN, liver transplantation type, graft-to-recipient weight ratio ≥4%, size reduction, bile duct anastomosis, massive blood loss, blood product transfusion, post-transplant RSC (rectal swab culture), post-transplant nasopharyngeal swab culture. The analysis included all of the 188 patients.

b Shown is the RR from the log-binomial model weighting by the stabilized inverse probability according to the propensity score. The analysis included all of the patients (w=187.4 for total recipients. Among them, w=65.8 for the RSC screening group and w=121.6 for the non-RSC screening group).

c Shown is the RR from the log-binomial model with matching according to the propensity score. The analysis included 108 patients (49 with RSC screening and 49 without RSC screening).

d Shown is the RR from a multivariable log-binomial model with additional adjustment for the propensity score. The analysis included all of the 188 patients.

cRR, crude RR; GNB, gram-negative bacteria.

Discussion

To the best of our knowledge, this is the first study to report an association between post-transplant bacterial infections and long-term outcomes in pediatric LT recipients. Our findings indicated inferior 1-year and 5-year survival rates in pediatric recipients with post-transplant bacterial infection. Staphylococcus spp. and Klebsiella spp. were the dominant pathogens detected after pediatric LT, whereas MR-CNS and CRKP were the primary MDROs. Five independent clinical factors, including infant recipients, male sex, GRWR ≥4%, positive post-transplant RSC and NPSC were independently associated with post-transplant infection. Our study provides a comprehensive depiction of the bacterial spectrum of early bacterial infection after pediatric LT and proposes that prophylaxis against independent risk factors may reduce the post-transplant infection rate.

In the present study, the overall bacterial infection rate in the early stages after pediatric LT was 20.4%, of which over one fourth was MDRO infection (5.2%). Among all the detected pathogens, MR-CNS were the primary MRDOs after pediatric LT, accounting for 43.2% of all MRDO infections, followed by carbapenem-resistant Enterobacteriaceae (32.1%) and methicillin-resistant staphylococcus aureus (MRSA) (11.1%). MDRO infections have been identified as an independent risk factor for post-LT mortality. Compared to recipients of other solid organs (heart, lung, and kidney), LT patients have the highest risk of MRSA infection, with a 30-day mortality as high as 21%30,31. Clinical factors such as invasive procedures, biliary complications, and broad-spectrum antimicrobial use were found to be associated with post-transplant MRSA infection32. Recently, genome screening of LT recipients with MRSA infection revealed that grafts lacking mannose-binding lectin, pannexin 1 or IL-33, which hinted at a deficiency in innate immunity, could increase the risk of post-transplant MRSA infection and mortality33,34. As ~6.7% of MRSA colonization was detected in nasal swab screening, active surveillance screening and prophylaxis were proposed to reduce the overall MRDO-related infection and mortality35.

Five clinical factors were found to be independent risk factors for bacterial infection after pediatric LT: infant recipients, male sex, GRWR ≥4%, positive post-transplant RSC and NPSC. In our study, infant recipients suffered 1.6 times of risk for bacterial infections compared with that of adolescents (24.2 vs. 15.3%). Infant LT recipients usually experience longer operative times and more difficult perioperative management, which makes them an independent risk factor for post-transplant BSI and overall infections (including bacterial, viral, and fungal infections)27,36,37. Moreover, recipient and graft incompatibility is more frequent in infant recipients owing to limited abdominal space and retarded development. Recipients who received grafts with GRWR ≥4% were more likely to develop large-for-size (LFS) syndrome, which is fatal in pediatric LT recipients38. A nationwide analysis of 10 000 pediatric LT cases in Japan revealed that LFS graft was associated with increased early mortality, hepatic necrosis, and massive hydrothorax39,40. LFS syndrome was accompanied by impaired hepatic microcirculation and poor oxygen supply to the graft due to compression of the large graft and insufficient portal blood flow41. The release of inflammatory factors from the ischemic graft caused severe hemodynamic changes and jeopardized the defensive barriers for bacteria, which facilitated the bacteria translocation. Therefore, appropriate pretransplant evaluation of infant LT recipients is crucial and reduced-size grafts or anatomical mono-segment grafts were encouraged if LFS is suspected.

Gram-negative MDROs have emerged as the predominant pathogens after LT42. Among them, CRKP infection could lead to an almost sevenfold increase in post-LT mortality and is a strong predictor for inferior patient survival43. The infection rates of post-transplant CRKP in LT recipients varied from 6.6 to 28%44. In our study, CRKP accounted for 24.7% of overall MDRO infections after pediatric LT. The lower respiratory tract (48.4%) was the dominant infection site of CRKP, followed by the abdominal cavity (33.3%) and bloodstream (22.7%). Risk factors associated with CRKP infection after LT include renal replacement therapy, extended operation time, prolonged ICU stay, CRKP colonization, and surgical complications42,45. Previous reports have revealed that colonization might be a strong predictor of post-transplant CRKP infection and mortality46–48. Therefore, screening for CRKP and individualized prophylaxis strategies could be an efficient method to reduce the post-transplant CRKP infection rate. We performed pretransplant RSC screening in 63 infants with biliary atresia. We observed a reduction in the overall post-transplant infection rate in the RSC screening cohort. Furthermore, among the seven CRKP carriers before LT, only one patient developed a post-transplant CRKP infection after receiving antibacterial prophylaxis, which was much lower than that reported previously. Therefore, detailed screening and prophylactic strategies for LT recipients with CRKP colonization before transplantation hold promise for reducing the CRKP infection rate and CRKP-related mortality after LT.

Strengths and limitations

The study has several strengths. First, it had a prospective design and a longitudinal follow-up, which allowed us to provide evidence of the inference of causality between post-transplant infection and long-term outcomes. Second, we comprehensively depicted the microbial spectrum and independent risk factors for post-transplant infection, which could guide prophylactic strategies for post-transplant infection. However, this study has several limitations. Although this is the largest single-center cohort study to data, the lack of information on external validation may have generated a selection bias. Multicenter validation involving recipients of different ethnic backgrounds is recommended. Second, only recipients with culture-proven bacterial infections were assigned to the infection group, which may have resulted in an underestimation of the post-transplant bacterial infection rate. However, any variation in the examined bacteria would have resulted in a nondifferential misclassification of bacterial infections independent of the outcome. The existence of such a misclassification would have led to an underestimation of the strength of the observed association between post-transplant bacterial infection and long-term survival rate. Third, although the overall incidence of post-transplant bacterial and GNB infection in the RSC group was lower than that in the non-RSC group, the difference was not statistically significant. Further prospective studies with larger sample sizes are needed to corroborate our findings. Lastly, we did not include data on COVID-19 infection in the analyses. However, previous studies reported that exposure to COVID-19 before LT does not affect post-transplant patients and graft survival49. COVID-19 infection is unlikely to be an unmeasured confounder in the present study. Thus, it is unlikely that the effect of COVID-19 infection would influence the observed associations of bacterial infection with long-term outcomes. Nevertheless, further studies with detailed COVID-19 infection were still warranted.

Conclusion

Overall bacterial infection resulted in inferior long-term outcomes after pediatric LT. Clinical factors including infant recipients, male sex, GRWR ≥4%, positive post-transplant RSC, and NPSC were independent risk factors for bacterial infection after pediatric LT. Our results indicated that prophylaxis to the aforementioned independent risk factors may reduce the overall post-transplant infection rate.

Ethical approval

This study was approved by the Clinical Research Ethics Committee of Renji Hospital (KY2022-117B).

Consent

Participants or their legal guardians were required to provide written informed consent before inclusion.

Source of funding

This study was supported by the National Natural Science Foundation of China (82241221), Innovative research team of high-level local universities in Shanghai (SHSMU-ZLCX20211600), Science and Technology Innovation Plan of Shanghai Science and Technology Commission (21410750400).

Author contribution

X.C.S. and Y.L.: have full access to all of the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis; Y.L. and Q.X.: conception and design; X.C.S., X.W.S., Y.L., and T.Z.: drafting of the manuscript; Y.L., Q.X., and P.L.: critical review of the manuscript for important intellectual content; X.C.S., X.W.S., and T.Z.: statistical analysis; Q.X. and Y.L.: obtained funding; T.Z., B.W., A.Z., Y.Q., Y.B.L., Y.L., Q.X.: administrative, technical, or material support; Y.L. and Q.X.: supervision. All authors contributed in acquisition, analysis, or interpretation of data.

Conflicts of interest disclosure

The authors declare that they have no conflicts of interest.

Research registration unique identifying number (UIN)

The research was registered at ChiCTR (ChiCTR2000035792, https://www.chictr.org.cn/hvshowproject.html?id=49108&v=1.1).

Guarantor

Qiang Xia.

Data availability statement

Data will be shared with bona fide researchers who submit a research proposal approved by the independent review board. Individual recipient data will be shared in data sets in a de-identified and anonymized format. Any researchers requiring original data could contact the corresponding author.

Provenance and peer review

Not commissioned, externally peer-reviewed.

Supplementary Material

Sun Xicheng, Sun Xiaowei, and Zhou Tao contributed equally to this article (co-first authors).

Sponsorships or competing interests that may be relevant to content are disclosed at the end of this article.

Supplemental Digital Content is available for this article. Direct URL citations are provided in the HTML and PDF versions of this article on the journal’s website, www.lww.com/international-journal-of-surgery.

Published online 4 June 2024
==== Refs
References

1 Kasahara M Umeshita K Eguchi S . Outcomes of pediatric liver transplantation in Japan: a report from the registry of the Japanese Liver Transplantation Society. Transplantation 2021;105 :2587–2595.33982916
2 Bowring MG Massie AB Chu NM . Projected 20- and 30-year outcomes for pediatric liver transplant recipients in the United States. J Pediatr Gastroenterol Nutr 2020;70 :356–363.31880667
3 Elisofon SA Magee JC Ng VL . Society of pediatric liver transplantation: Current registry status 2011-2018. Pediatr Transplant 2020;24 :e13605.31680409
4 Baumann U Karam V Adam R . Prognosis of children undergoing liver transplantation: a 30-year European study. Pediatrics 2022;150 :e2022057424.36111446
5 Akbulut S Sahin TT Yilmaz S . Prognostic factors in pediatric early liver retransplantation. Liver Transpl 2021;27 :940–941.33619814
6 Spada M Riva S Maggiore G . Pediatric liver transplantation. World J Gastroenterol 2009;15 :648–674.19222089
7 Shepherd RW Turmelle Y Nadler M . Risk factors for rejection and infection in pediatric liver transplantation. Am J Transplant 2008;8 :396–403.18162090
8 Taylor SA Venkat V Arnon R . Improved outcomes for liver transplantation in patients with biliary atresia since pediatric end-stage liver disease implementation: analysis of the society of pediatric liver transplantation registry. J Pediatr 2020;219 :89–97.32005543
9 Cuenca AG Kim HB Vakili K . Pediatric liver transplantation. Semin Pediatr Surg 2017;26 :217–223.28964477
10 Lee EJ Vakili K . Pediatric liver transplantation. In: Shapiro R, Sarwal MM, Raina R, Sethi SK, eds. Pediatric Solid Organ Transplantation: A Practical Handbook. Springer Nature Singapore; 2023:415–427.
11 Mohan N Vohra M . Challenges in pediatric liver transplant. In: Vohra V, Gupta N, Jolly AS, Bhalotra S, eds. Peri-operative Anesthetic Management in Liver Transplantation. Springer Nature Singapore; 2023:471–479.
12 Paganelli M . Liver transplantation in critically ill children. In: Jouvet P, Alvarez F, eds. Liver Diseases in the Pediatric Intensive Care Unit: A Clinical Guide. Springer International Publishing; 2021:143–160.
13 Pawłowska J . The importance of nutrition for pediatric liver transplant patients. Clin Exp Hepatol 2016;2 :105–108.28856271
14 Møller DL Sørensen SS Wareham NE . Bacterial and fungal bloodstream infections in pediatric liver and kidney transplant recipients. BMC Infect Dis 2021;21 :541.34103013
15 Yamazhan T Bulut Avşar C Zeytunlu M . Infections developing in patients undergoing liver transplantation: recipients of living donors may be more prone to bacterial/fungal infections. Turk J Gastroenterol 2020;31 :894–901.33626002
16 Shoji K Funaki T Kasahara M . Risk factors for bloodstream infection after living-donor liver transplantation in children. Pediatr Infect Dis J 2015;34 :1063–1068.26121201
17 Zhong L Men TY Li H . Multidrug-resistant gram-negative bacterial infections after liver transplantation - spectrum and risk factors. J Infect Mar 2012;64 :299–310.
18 Liu N Yang G Dang Y . Epidemic, risk factors of carbapenem-resistant Klebsiella pneumoniae infection and its effect on the early prognosis of liver transplantation. Front Cell Infect Microbiol 2022;12 :976408.36275019
19 Giannella M Freire M Rinaldi M . Development of a risk prediction model for carbapenem-resistant enterobacteriaceae infection after liver transplantation: a multinational cohort study. Clin Infect Dis 2021;73 :e955–e966.33564840
20 Mathew G Agha R Albrecht J . STROCSS 2021 . strengthening the reporting of cohort, cross-sectional and case-control studies in surgery. Int J Surg 2021;96 :106–165.
21 Barshes NR Lee TC Udell IW . The pediatric end-stage liver disease (PELD) model as a predictor of survival benefit and posttransplant survival in pediatric liver transplant recipients. Liver Transpl Mar 2006;12 :475–480.
22 Kamath PS Kim WR . The model for end-stage liver disease (MELD). Hepatology 2007;45 :797–805.17326206
23 Cockcroft DW Gault MH . Prediction of creatinine clearance from serum creatinine. Nephron 1976;16 :31–41.1244564
24 Xue F Gao W Qin T . Immune cell function assays in the diagnosis of infection in pediatric liver transplantation: an open-labeled, two center prospective cohort study. Transl Pediatr 2021;10 :333–343.33708519
25 Dindo D Demartines N Clavien PA . Classification of surgical complications: a new proposal with evaluation in a cohort of 6336 patients and results of a survey. Ann Surg Aug 2004;240 :205–213.
26 Fagiuoli S Colli A Bruno R . Management of infections pre- and post-liver transplantation: report of an AISF consensus conference. J Hepatol 2014;60 :1075–1089.24384327
27 Kim YE Choi HJ Lee HJ . Assessment of pathogens and risk factors associated with bloodstream infection in the year after pediatric liver transplantation. World J Gastroenterol Mar 2022;28 :1159–1171.
28 Ersoy Z Kaplan S Ozdemirkan A . Effect of graft weight to recipient body weight ratio on hemodynamic and metabolic parameters in pediatric liver transplant: a retrospective analysis. Exp Clin Transplant 2017;15 :53–56.28260433
29 Łuczyńska G Pena-Pereira F Tobiszewski M . Expectation-maximization model for substitution of missing values characterizing greenness of organic solvents. Molecules 2018;23 :1292.29843437
30 Paulsen G Blum S Danziger-Isakov L . Epidemiology and outcomes of pretransplant methicillin-resistant Staphylococcus Aureus screening in pediatric solid organ transplant candidates. Pediatr Transplant 2018:e13246.29888518
31 Singh N Paterson DL Chang FY . Methicillin-resistant Staphylococcus aureus: the other emerging resistant gram-positive coccus among liver transplant recipients. Clin Infect Dis 2000;30 :322–327.10671336
32 Ziakas PD Pliakos EE Zervou FN . MRSA and VRE colonization in solid organ transplantation: a meta-analysis of published studies. Am J Transplant 2014;14 :1887–1894.25040438
33 Lombardo-Quezada J Sanclemente G Colmenero J . Mannose-binding lectin-deficient donors increase the risk of bacterial infection and bacterial infection-related mortality after liver transplantation. Am J Transplant 2018;18 :197–206.28649744
34 Li H Yu X Shi B . Reduced pannexin 1-IL-33 axis function in donor livers increases risk of MRSA infection in liver transplant recipients. Sci Transl Med 2021;13 :eaaz6169.34380770
35 Russell DL Flood A Zaroda TE . Outcomes of colonization with MRSA and VRE among liver transplant candidates and recipients. Am J Transplant 2008;8 :1737–1743.18557723
36 Bouchut JC Stamm D Boillot O . Postoperative infectious complications in paediatric liver transplantation: a study of 48 transplants. Paediatr Anaesth 2001;11 :93–98.11123739
37 Rhee KW Oh SH Kim KM . Early bloodstream infection after pediatric living donor living transplantation. Transplant Proc 2012;44 :794–796.22483498
38 Addeo P Noblet V Naegel B . Large-for-size orthotopic liver transplantation: a systematic review of definitions, outcomes, and solutions. J Gastrointest Surg 2020;24 :1192–1200.31919740
39 Shen Z Wang Z Jiang Y . Early outcomes of implanting larger-sized grafts in deceased donor liver transplantation. ANZ J Surg 2020;90 :1352–1357.32691510
40 Eguchi S Umeshita K Soejima Y . An analysis of 10,000 cases of living donor liver transplantation in japan: special reference to the graft-versus-recipient weight ratio and donor age. Ann Surg Jan 2024;279 :94–103.
41 Tanaka A Tanaka K Tokuka A . Graft size-matching in living related partial liver transplantation in relation to tissue oxygenation and metabolic capacity. Transpl Int 1996;9 :15–22.8748406
42 Phichaphop C Apiwattanakul N Techasaensiri C . High prevalence of multidrug-resistant gram-negative bacterial infection following pediatric liver transplantation. Medicine (Baltimore) 2020;99 :e23169.33158003
43 Kalpoe JS Sonnenberg E Factor SH . Mortality associated with carbapenem-resistant Klebsiella pneumoniae infections in liver transplant recipients. Liver Transpl 2012;18 :468–474.22467548
44 Pereira MR Scully BF Pouch SM . Risk factors and outcomes of carbapenem-resistant Klebsiella pneumoniae infections in liver transplant recipients. Liver Transpl 2015;21 :1511–1519.26136397
45 Giannella M Bartoletti M Morelli MC . Risk factors for infection with carbapenem-resistant Klebsiella pneumoniae after liver transplantation: the importance of pre- and posttransplant colonization. Am J Transplant 2015;15 :1708–1715.25754742
46 Lübbert C Becker-Rux D Rodloff AC . Colonization of liver transplant recipients with KPC-producing Klebsiella pneumoniae is associated with high infection rates and excess mortality: a case-control analysis. Infection 2014;42 :309–316.24217959
47 Giannella M Bartoletti M Campoli C . The impact of carbapenemase-producing Enterobacteriaceae colonization on infection risk after liver transplantation: a prospective observational cohort study. Clin Microbiol Infect 2019;25 :1525–1531.31039445
48 Takemura Y Hibi T Shinoda M . Methicillin-resistant Staphylococcus aureus carriers are vulnerable to bloodstream infection after living donor liver transplantation. Clin Transplant 2019;33 :e13753.31692105
49 Langford BJ So M Simeonova M . Antimicrobial resistance in patients with COVID-19: a systematic review and meta-analysis. Lancet Microbe 2023;4 :e179–e191.36736332
