Asploro Journal of Biomedical and Clinical Case Reports
ISSN: 2582-0370
Article Type: Original Article
DOI: 10.36502/2024/ASJBCCR.6352
Asp Biomed Clin Case Rep. 2024 Jun 21;7(2):143-50
Association of Preoperative Red Cell Distribution Width with Postoperative Outcomes in Liver Transplantation Recipients
Siying Wang1*
1Department of Anesthesiology, West China Hospital, Sichuan University, Chengdu, China
Corresponding Author: Siying Wang
Address: Department of Anesthesiology, Sichuan University West China Hospital, 37 Guoxuexiang, Chengdu, Sichuan, 610041 China.
Received date: 20 May 2024; Accepted date: 14 June 2024; Published date: 21 June 2024
Citation: Wang S. Association of Preoperative Red Cell Distribution Width with Postoperative Outcomes in Liver Transplantation Recipients. Asp Biomed Clin Case Rep. 2024 Jun 21;7(2):143-50.
Copyright © 2024 Wang S. This is an open-access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium provided the original work is properly cited.
Keywords: Liver Transplantation, Red Blood Cell Distribution, Propensity Score Matching
Abstract
Background: The 1-year mortality rate after liver transplantation is approximately 8%-20%. It is important to explore risk factors associated with postoperative outcomes in liver transplantation recipients (LTRs). Red cell distribution width (RDW) is an indicator that assesses the variability in the volume of red blood cells in circulation. RDW is not only related to inflammatory levels and nutritional status but also associated with postoperative outcomes in surgical patients. However, the relationship between preoperative RDW and postoperative outcomes in LTRs remains unclear. Therefore, we designed a retrospective observational study to investigate the impact of preoperative RDW levels on postoperative outcomes in LTRs.
Methods: We retrospectively collected clinical data of patients who underwent allogeneic liver transplantation at West China Hospital, Sichuan University, from January 2016 to December 2020. The primary outcome was 1-year mortality. Secondary outcomes included 30-day mortality, long-term survival, early postoperative graft dysfunction, acute kidney injury, renal replacement therapy, pulmonary complications, duration of postoperative mechanical ventilation, length of ICU stay, and length of hospital stay. Patients were divided into two groups: RDW ≤ 14.5% and RDW > 14.5%. We selected 14 covariates and used propensity score matching (PSM) to adjust for baseline characteristics. Postoperative outcomes and long-term survival were analyzed after PSM. Receiver operating characteristics (ROC) curves and subgroup analyses were also performed.
Results: A total of 661 patients who underwent liver transplantation surgery were screened for this study. Finally, 438 patients were included in the statistical analysis. After PSM, there were no statistically significant differences in postoperative mortality and complications between the RDW ≤ 14.5% group and the RDW > 14.5% group (P > 0.05). The comparison of long-term survival between the two groups also showed no statistical difference (hazard ratio = 0.67, 95% confidence interval: 0.28-1.61, P = 0.358). Subgroup analyses showed consistent results. The ROC curve indicated that the predictive ability of preoperative RDW levels for 1-year mortality is moderate (area under the ROC curve 0.661).
Conclusion: Preoperative RDW levels do not affect postoperative mortality and the incidence of complications in LTRs. However, these results still need further research for verification.
Introduction
Liver transplantation (LT) is one of the most important treatments for end-stage liver disease. The 1-year mortality rate of liver transplantation recipients (LTRs) has been reported to range from 8% to 20% [1-3]. Severe postoperative complications are also very common. Therefore, it is important to further improve the outcomes of LTRs.
Red cell distribution width (RDW), a parameter in the complete blood count test, measures the variation in red blood cell volumes. RDW is used for the diagnosis of anemia but has also been reported to be associated with inflammatory and nutritional status [4-6]. In addition, elevated RDW has been reported to be related to worse outcomes in surgical patients [7-16]. However, the association between preoperative RDW and postoperative outcomes in LTRs remains uncertain. Thus, we designed a retrospective study to investigate the association between preoperative RDW and postoperative outcomes in LTRs.
Methods
We performed a retrospective observational study on patients undergoing liver transplantation (LT) at West China Hospital between January 2016 and December 2020. This study was approved by the institutional review board of West China Hospital of Sichuan University. Individual consent was waived due to the retrospective design of the study.
Patients aged 18 years or older who underwent donor-after-brain-death liver transplantation were included. Exclusion criteria were as follows: history of LT, combined liver and other organ transplantation, and unavailable preoperative RDW. The patients were divided into two groups based on the normal RDW critical value: RDW ≤ 14.5% and RDW > 14.5%. Follow-up was concluded on February 28, 2022.
We reviewed the electronic medical records of all patients who underwent LT at West China Hospital of Sichuan University. We collected follow-up data from the Chinese Liver Transplant Registry and the hospital information system.
The primary outcome was 1-year mortality. The secondary outcomes included 30-day mortality, long-term survival, incidences of early allograft dysfunction (EAD), acute kidney injury (AKI), pulmonary complications, renal replacement therapy (RRT), duration of mechanical ventilation, postoperative length of ICU stay, and postoperative length of hospital stay.
R software version 4.2.2 and GraphPad Prism software version 9.0.2 were used for analyses. The results are presented as mean ± SD or median [interquartile range] for continuous variables and number (percentage) for categorical variables. The normality of the distribution was tested by the Kolmogorov-Smirnov test. Continuous variables were tested by Student’s t-test or Mann-Whitney U test. Categorical variables were tested by Pearson’s chi-squared test or Fisher’s exact test.
Propensity score matching (PSM) was used to adjust potentially confounding baseline variables [17]. The propensity score of each variable was calculated by logistic regression analysis. Fourteen variables were used for matching: LTR’s age, gender, body mass index (BMI), Model for End-stage Liver Disease (MELD) score, Child-Pugh grade, hepatocellular carcinoma (HCC), comorbidities (hypertension, diabetes, chronic obstructive pulmonary disease, chronic kidney disease), donor’s age, BMI, Graft-to-Recipient Weight Ratio (GRWR), and cold ischemic time. Patients were matched at a ratio of 1:1 using the nearest neighbor method with a caliper of 0.1. A standardized mean difference (SMD) < 0.1 indicates good balance of matched variables.
Long-term survival of the propensity-matched patients was depicted using a Kaplan-Meier curve and compared using the log-rank test. The analyses of 1-year mortality and 30-day mortality were also conducted in subgroups of patients with different ages, genders, BMIs, and HCC status. Receiver operating characteristics (ROC) curves were depicted and the area under the ROC curve (AUC) was calculated.
A P-value < 0.05 was considered statistically significant. Patients with missing data for variables used in PSM were excluded from analyses.
Results
Of the 661 patients who underwent LT between January 2016 and December 2020 at West China Hospital of Sichuan University, 438 patients were finally included in the analyses (Fig-1). Table-1 shows the baseline characteristics. The median age was 50 (interquartile range) [18, 73]. Most patients were male (78.8%), and 49.8% of patients were diagnosed with HCC. The median preoperative RDW was 16.1% (interquartile range [11.4%, 35.5%]). 71.2% of patients had a preoperative RDW > 14.5%. Before PSM, there were statistically significant differences in MELD score, Child-Pugh grade, diagnoses of HCC, and diabetes between the two groups. PSM was used to match two groups of patients across 14 covariates. Finally, 176 patients were successfully matched (88 patients in each group), as shown in Fig-1. After PSM, there were no statistical differences between the two groups in terms of baseline characteristics (P > 0.05), and the balance of each covariate was good (SMD < 0.1), as shown in Table-1.
Fig-1: Flowchart of the study
Table-1: Baseline characteristics before and after PSM

Before PSM, patients in the RDW > 14.5% group had significantly higher 1-year mortality, incidence of AKI, RRT, and pulmonary complications compared to patients in the RDW ≤ 14.5% group (P < 0.05). Additionally, the duration of postoperative mechanical ventilation, the length of ICU stay, and the length of postoperative hospital stay were all significantly longer in the RDW > 14.5% group. After PSM, there were no statistical differences in the postoperative 1-year mortality, postoperative 30-day mortality, EAD, AKI, RRT, and pulmonary complications between the two groups. Additionally, there were no statistical differences in the duration of postoperative mechanical ventilation, the length of ICU stay, and the length of postoperative hospital stay (P > 0.05), as shown in Table-2.
Table-2: Postoperative outcomes before and after PSM

Subgroup analyses were conducted based on the recipient’s gender, age, BMI, and diagnosis of HCC. The results showed that in each subgroup, there were no statistically significant differences in 1-year mortality and 30-day mortality between patients in the preoperative RDW ≤ 14.5% group and the RDW > 14.5% group (P > 0.05), as shown in Table-3.
Table-3
The long-term survival between the two groups after PSM also showed no statistical differences (hazard ratio = 0.67, 95% confidence interval (CI): 0.28-1.61, P = 0.358), as shown in Fig-2.
Fig-2: Kaplan-Meier curve
The area under the ROC curve (AUC) for preoperative RDW values to predict 1-year mortality in LTRs was 0.661 (AUC = 0.661, 95% CI: 0.54-0.79, P = 0.025), as shown in Fig-3. The optimal cutoff value of preoperative RDW for predicting 1-year mortality was 14.15%, with a sensitivity of 34.81% and a specificity of 94.44%.
Fig-3: ROC curve
Discussion
This study retrospectively analyzed the association between preoperative RDW and outcomes in LTRs. We found that preoperative RDW does not affect mortality or the incidence of complications. After PSM adjustment for potential confounders, there were no statistical differences in primary or secondary outcomes between the RDW ≤ 14.5% group and RDW > 14.5% group. Subgroup analyses showed consistent results. The ROC curve demonstrated that the predictive ability of preoperative RDW levels for 1-year mortality is moderate.
This study found that the preoperative RDW level in LTRs is not related to postoperative outcomes. There have been few studies on the association between preoperative RDW and prognosis in LTRs. Caire et al. retrospectively collected clinical and follow-up data from 96 patients who underwent liver transplantation surgery [18]. The results showed that the preoperative RDW level of patients who survived one year was significantly lower than that of patients who died within one year after surgery (16.6% vs. 20.6%, 95% CI: 1.9-5.9%, P < 0.001). Although this study also analyzed the association between preoperative RDW levels and prognosis in LTRs, there were significant differences in baseline data, and no adjustments were made. Thus, the results of this study may be affected by confounding factors. In contrast, our study had a larger sample size, and we applied PSM to adjust for baseline data. Our study found that the preoperative RDW level is not correlated with prognosis and has moderate predictive ability for prognosis in LTRs, which may be due to: (1) The prognosis of LTRs is closely related to preoperative baseline data (including recipient factors, donor factors, quality of the donated liver, etc.), but our study has already used the PSM method to adjust baseline data; (2) Although preoperative RDW can reflect the patient’s preoperative inflammatory status and nutritional level, the impact of this single indicator on the prognosis of LTRs may be limited; (3) The 30-day mortality and 1-year mortality after liver transplant surgery in our center are both low, and the sample size of this study was reduced after PSM. Thus, there may be insufficient statistical power; (4) The perioperative management of LTRs in our center is standardized, so differences in postoperative mechanical ventilation time, ICU stay time, and hospital stay time may not be significant.
RDW and other perioperative inflammatory biomarkers (such as neutrophil-to-lymphocyte ratio, lymphocyte-to-monocyte ratio, platelet-to-lymphocyte ratio, and systemic immune-inflammation index) are common test parameters that are easily accessible and relatively inexpensive for clinicians. In recent years, there have been many studies exploring the association between these perioperative inflammatory biomarkers and the prognosis of LTRs, but the results are not consistent [19-25]. This may be because these markers only reflect part of the patient’s inflammatory status, and the predictive value of a single biomarker is limited. Future research could consider exploring the predictive value of a combination of multiple biomarkers. Secondly, these inflammatory biomarkers may be affected by many other factors, such as infections, blood diseases, medications, and blood transfusion treatments. Therefore, the impact of RDW and other inflammatory biomarkers on the prognosis of LTRs still needs further research to verify.
Conclusion
Preoperative RDW levels do not affect postoperative mortality or the incidence of complications in LTRs. However, these results still need further research for verification.
Disclosure
Relevant data were collected from the Chinese Liver Transplant Registry and Hospital Information System.
Conflict of Interest
The author has read and approved the final version of the manuscript. The author has no conflicts of interest to declare.
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