Abstract
BACKGROUND
Red blood cell distribution width (RDW) is associated with the development and progression of various diseases.
AIM
To explore the association between pretreatment RDW and short-term outcomes after laparoscopic pancreatoduodenectomy (LPD).
METHODS
A total of 804 consecutive patients who underwent LPD at our hospital between March 2017 and November 2021 were retrospectively analyzed. Correlations between pretreatment RDW and clinicopathological characteristics and short-term outcomes were investigated.
RESULTS
Patients with higher pretreatment RDW were older, had higher Eastern Cooperative Oncology Group scores and were associated with poorer short-term outcomes than those with normal RDW. High pretreatment RDW was an independent risk factor for postoperative complications (POCs) (hazard ratio = 2.973, 95% confidence interval: 2.032-4.350, P < 0.001) and severe POCs of grade IIIa or higher (hazard ratio = 3.138, 95% confidence interval: 2.042-4.824, P < 0.001) based on the Clavien-Dino classification system. Subgroup analysis showed that high pretreatment RDW was an independent risk factor for Clavien-Dino classification grade IIIb or higher POCs, a comprehensive complication index score ≥ 26.2, severe postoperative pancreatic fistula, severe bile leakage and severe hemorrhage. High pretreatment RDW was positively associated with the neutrophil-to-lymphocyte ratio and platelet-to-lymphocyte ratio and was negatively associated with albumin and the prognostic nutritional index.
CONCLUSION
Pretreatment RDW was a special parameter for patients who underwent LPD. It was associated with malnutrition, severe inflammatory status and poorer short-term outcomes. RDW could be a surrogate marker for nutritional and inflammatory status in identifying patients who were at high risk of developing POCs after LPD.
Keywords: Biomarker, Laparoscopic pancreatoduodenectomy, Postoperative complication, Red blood cell distribution width, Short-term outcomes
Core Tip: Pretreatment red blood cell distribution width was a special parameter for patients who underwent laparoscopic pancreatoduodenectomy. It was associated with malnutrition, severe inflammatory status and poorer short-term outcomes. Pretreatment red blood cell distribution width could be a surrogate marker for nutritional and inflammatory status in identifying patients who were at high risk of developing postoperative complications after laparoscopic pancreatoduodenectomy.
INTRODUCTION
With the development of laparoscopic instruments and the accumulation and progress of surgical experience, laparoscopic pancreatoduodenectomy (LPD) has been widely performed in high-volume medical centers[1-3]. However, as one of the most challenging abdominal surgeries with high complexity, LPD is associated with a high incidence of postoperative complications (POCs), and the incidence of POCs after LPD ranges from 30% to 50%[1,3,4]. POCs could lead to higher costs and longer hospital stays for patients undergoing surgery[5,6]. Meanwhile, recent studies have demonstrated that POCs have a negative impact on the long-term outcomes of patients with malignant tumors, including hepatocellular carcinoma[7] and colorectal liver metastasis[8]. Consequently, increased attention has been placed on identifying risk factors for the development of POCs in efforts to improve both the short- and long-term outcomes for patients undergoing surgery.
Traditionally, operation-related parameters, such as pancreas texture and blood loss, are considered risk factors for POCs after pancreatoduodenectomy[9,10]. In recent studies, nutritional and inflammatory factors such as prognostic nutritional index (PNI), neutrophil-to-lymphocyte ratio (NLR) and platelet-to-lymphocyte ratio (PLR) have been found to be associated with the development of POCs after surgery[11-13]. Malnutrition and systemic inflammatory responses play crucial roles in the development of POCs by causing tissue friability, decreasing the production of proinflammatory molecules and weakening the blood vessel wall, thereby impacting the immune response and wound healing after surgery[14,15].
Red blood cell distribution width (RDW) is a parameter reflecting the degree of heterogeneity of erythrocyte volume and is used for estimating the pathogenesis of anemia[16]. Recent studies revealed that RDW could be an indicator of malnutrition and systemic inflammation and was associated with the development of many disorders[17-19]. For instance, higher RDW was found to be associated with critical illness for patients with coronavirus disease 2019 infection[20]. Recent studies revealed that high RDW was associated with the development of POCs after operation, including esophagectomy[21] and cardiac surgery[22]. However, no previous studies have reported the relationship between high pretreatment RDW and short-term outcomes in patients undergoing LPD. This study aimed to explore the association between high pretreatment RDW and short-term outcomes and identify risk factors for POCs after LPD. In addition, the correlation between high pretreatment RDW and malnutrition and immune response was investigated to reveal how high RDW reflects the frequent incidence of POCs after LPD.
MATERIALS AND METHODS
Patients
Between March 2017 and November 2021, a total of 832 consecutive patients who underwent LPD at Shandong Provincial Hospital Affiliated to Shandong First Medical University were initially identified and enrolled in this study. Of these, 11 patients who were aged < 18 or > 80 years old and 17 patients with insufficient clinical data [3 for RDW pretreatment data, 2 for C-reactive protein (CRP), 5 for prothrombin time (PT), 3 for operative time and 4 for total lymphocyte count] were excluded. Eventually, 804 patients were included in this study. This study obtained ethics approval from the ethics committee of Shandong Provincial Hospital Affiliated to Shandong First Medical University and was performed in accordance with the Declaration of Helsinki (as revised in 2013). Written informed consent was obtained from each participant in the study.
Data collection
The clinicopathological profiles of the 804 patients were collected, including age, sex, body mass index (BMI), smoking and alcohol consumption history, comorbidities (diabetes mellitus, hypertension and pancreatitis), Eastern Cooperative Oncology Group (ECOG) score, up-abdominal operation history, preoperative biliary drainage, pathology, American Society of Anesthesiologists physical status, preoperative laboratory data, surgery-related parameters and postoperative outcomes. Preoperative laboratory data included alanine aminotransferase (ALT), aspartate aminotransferase (AST), alkaline phosphatase (ALP), γ-glutamyl transferase (GGT), hemoglobin, RDW, platelet count, neutrophil cell count, lymphocyte count, total bilirubin (TBIL), albumin, CRP and PT. Surgery-related parameters included operative time, blood loss and intraoperative blood transfusion. Postoperative outcomes included POCs, postoperative pancreatic fistula (POPF), bile leakage (BL), hemorrhage, intra-abdominal infection and delayed gastric emptying (DGE). Patients were divided into two groups according to the institutional standard value of pretreatment RDW: High (> 15.4) and normal (≤ 15.4) RDW groups.
Definition of POCs
POCs were graded according to the Clavien-Dino classification (CDc) system[23]. The comprehensive complication index was also used for assessing POCs[24]. POPF was defined according to the criteria provided by the International Study Group of Pancreatic Surgery. DGE and hemorrhage were defined according to the International Study Group of Pancreatic Surgery criteria[25,26]. The diagnosis of BL was determined according to the definitions provided by the International Study Group of Liver Surgery[27].
Statistical analysis
Categorical variables are expressed as numbers (n) and proportions (%), and continuous variables are expressed as the mean ± SD. The χ2 test and Fisher’s exact test were used to compare categorical variables between two groups. The Mann-Whitney U test was used for continuous variables. Logistic regression analysis was used to identify risk factors for POCs. Variables with P < 0.1 in the univariate analysis were regarded as potential risk factors and were included in the multivariate analysis. The odds ratios (ORs) with 95% confidence intervals (95%CIs) were recorded. The NLR, PLR, and PNI were calculated as follows: NLR = absolute neutrophil count/absolute lymphocyte count; PLR = absolute platelet count/absolute lymphocyte count[28]; PNI = 10 × serum albumin (g/dL) + 0.005 × total lymphocyte count in peripheral blood (/mm3)[29]. Finally, Pearson’s correlation coefficients were calculated to evaluate the relationship between RDW and nutritional (albumin and PNI) and inflammatory (NLR and PLR) factors. All statistical tests were two-sided, and P < 0.05 was defined as statistically significant. SPSS version 26.0 (SPSS Inc., Chicago, IL, United States) was employed in the statistical analysis.
RESULTS
Association between pretreatment RDW and clinical features for patients who underwent LPD
Out of 804 patients, 231 (28.7%) had a higher pretreatment RDW level (≥ 15.4), including 146 males and 85 females. The clinicopathological data of the patients are shown in Table 1. Compared with those with normal pretreatment RDW, patients in the high RDW group were significantly older and had a higher ECOG score and more preoperative biliary drainage (all P < 0.05). Meanwhile, higher RDW was associated with lower BMI and more malignant tumors (all P < 0.05). There were no significant differences in sex, alcohol consumption, smoking, comorbidities, upper-abdominal operation history or American Society of Anesthesiologists status between the two groups (all P > 0.05). For the laboratory data, compared with those with normal pretreatment RDW, patients in the high RDW group had higher preoperative ALT, AST, ALP, GGT, TBIL, CRP, leucocyte count, platelet level, NLR, and PLR (all P > 0.05). Meanwhile, higher RDW was associated with lower albumin, leucocyte and lymphocyte counts, hemoglobin levels and PNI (all P < 0.05). There were no significant differences in PT between the two groups (P > 0.05).
Table 1.
Baseline characteristics of patients who underwent laparoscopic pancreaticoduodenectomy, n (%)
|
Variables
|
Total (n = 804)
|
Red blood cell distribution width
|
P value
|
|
|
< 15.4 (n = 573)
|
≥ 15.4 (n = 231)
|
|||
| Age, years | ||||
| < 65 | 478 (59.5) | 353 (61.6) | 125 (54.1) | 0.050 |
| ≥ 65 | 326 (40.5) | 220 (38.4) | 106 (45.9) | |
| Sex | 0.325 | |||
| Male | 529 (65.8) | 383 (66.8) | 146 (63.2) | |
| Female | 275 (34.2) | 190 (33.2) | 85 (36.8) | |
| Body mass index, kg/m2 | ||||
| < 25 | 500 (62.2) | 341 (59.5) | 159 (68.8) | 0.014 |
| ≥ 25 | 304 (37.8) | 232 (40.5) | 72 (31.2) | |
| Drinking | 0.489 | |||
| No | 553 (68.8) | 390 (68.1) | 163 (70.6) | |
| Yes | 251 (31.2) | 183 (31.9) | 68 (29.4) | |
| Smoking | 0.983 | |||
| No | 526 (65.4) | 375 (65.4) | 151 (65.4) | |
| Yes | 278 (34.6) | 198 (34.6) | 80 (34.6) | |
| ECOG score | 0.029 | |||
| 0-1 | 734 (91.3) | 531 (92.7) | 203 (87.9) | |
| 2 | 70 (8.7) | 42 (7.3) | 28 (12.1) | |
| Comorbidity | ||||
| Hypertension | 218 (27.1) | 156 (27.2) | 62 (26.8) | 0.911 |
| Pancreatitis | 65 (8.1) | 52 (9.1) | 13 (5.6) | 0.105 |
| Diabetes mellitus | 157(19.5) | 119 (20.8) | 38 (16.5) | 0.162 |
| Upper-abdominal operation history | 0.717 | |||
| No | 759 (94.4) | 542 (94.6) | 217 (93.9) | |
| Yes | 45 (5.6) | 31 (5.4) | 14 (6.1) | |
| Preoperative biliary drainage | 0.009 | |||
| No | 682 (84.8) | 498 (86.9) | 184 (79.7) | |
| Yes | 122 (15.2) | 75 (13.1) | 47 (20.3) | |
| Pathology | < 0.001 | |||
| Malignant tumor | 618 (76.9) | 414 (72.3) | 204 (88.3) | |
| Benign tumor | 186 (23.1) | 159 (27.7) | 27 (11.7) | |
| ASA physical status | 0.083 | |||
| II | 514 (63.9) | 377 (65.8) | 137 (59.3) | |
| III | 290 (36.1) | 196 (34.2) | 94 (40.7) | |
| ALT, U/L, mean ± SD | 134.91 ± 144.16 | 122.26 ± 134.32 | 166.31 ± 162.17 | < 0.001 |
| < 40 | 257 (32.0) | 214 (37.3) | 43 (18.6) | < 0.001 |
| ≥ 40 | 547 (68.0) | 359 (62.7) | 188 (81.4) | |
| AST, U/L, mean ± SD | 104.40 ± 134.09 | 92.11 ± 128.77 | 134.89 ± 142.22 | < 0.001 |
| < 35 | 549 (68.3) | 349 (60.9) | 31 (13.4) | < 0.001 |
| ≥ 35 | 255 (31.7) | 224 (39.1) | 200 (86.6) | |
| ALP, U/L, mean ± SD | 345.49 ± 305.36 | 287.75 ± 263.95 | 488.72 ± 351.25 | < 0.001 |
| < 140 | 268 (33.3) | 239 (41.7) | 29 (12.6) | < 0.001 |
| ≥ 140 | 536 (66.7) | 334 (58.3) | 202 (87.4) | |
| GGT, U/L, mean ± SD | 511.57 ± 559.77 | 115.90 ± 529.70 | 667.70 ± 601.57 | < 0.001 |
| < 54 | 217 (27.0) | 195 (34.0) | 22 (9.5) | < 0.001 |
| ≥ 54 | 587 (73.0) | 378 (66.0) | 209 (90.5) | |
| TBIL, μmol/L, mean ± SD | 125.95 ± 141.75 | 87.95 ± 109.20 | 220.19 ± 167.27 | < 0.001 |
| < 235.0 | 547 (68.0) | 449 (78.4) | 98 (42.4) | < 0.001 |
| ≥ 235.0 | 257 (32.0) | 124 (21.6) | 133 (57.6) | |
| Albumin, g/L, mean ± SD | 39.55 ± 5.65 | 40.74 ± 5.28 | 36.60 ± 5.47 | < 0.001 |
| < 35 | 152 (18.9) | 60 (10.5) | 92 (39.8) | < 0.001 |
| ≥ 35 | 652 (81.1) | 513 (89.5) | 139 (60.2) | |
| CRP, mg/L, mean ± SD | 12.72 ± 21.03 | 12.14 ± 21.65 | 14.14 ± 19.39 | < 0.001 |
| < 10 | 564 (70.1) | 425 (74.2) | 139 (60.2) | < 0.001 |
| ≥ 10 | 240 (29.9) | 148 (25.8) | 92 (39.8) | |
| PT, second, mean ± SD | 12.32 ± 1.39 | 12.26 ± 1.32 | 12.47 ± 1.54 | 0.105 |
| < 14 | 730 (90.8) | 523 (91.3) | 207 (89.6) | 0.460 |
| ≥ 14 | 74 (9.2) | 50 (8.7) | 24 (10.4) | |
| Hemoglobin, g/L, mean ± SD | 126.52 ± 18.88 | 131.65 ± 16.46 | 113.80 ± 18.49 | < 0.001 |
| < 115 | 192 (23.9) | 79 (13.8) | 113 (48.9) | < 0.001 |
| ≥ 115 | 612 (76.1) | 494 (86.2) | 118 (51.1) | |
| Leucocytes, 109/L, mean ± SD | 6.37 ± 2.64 | 6.13 ± 2.43 | 6.96 ± 3.03 | < 0.001 |
| < 9.5 | 722 (89.8) | 521 (90.9) | 201 (87.0) | |
| ≥ 9.5 | 82 (10.2) | 52 (9.1) | 30 (13.0) | 0.097 |
| Lymphocyte, 109/L, mean ± SD | 1.55 ± 0.60 | 1.64 ± 0.59 | 1.33 ± 0.57 | < 0.001 |
| < 3.2 | 797 (99.1) | 567 (99.0) | 230 (99.6) | 0.680 (F) |
| ≥ 3.2 | 7 (0.9) | 6 (1.0) | 1 (0.4) | |
| Platelet, 109/L, mean ± SD | 258.893 ± 88.76 | 249.92 ± 75.82 | 281.27 ± 111.84 | < 0.001 |
| < 350 | 698 (86.8) | 518 (90.4) | 180 (77.9) | < 0.001 |
| ≥ 350 | 106 (13.2) | 55 (9.6) | 51 (22.1) | |
| NLR, mean ± SD | 3.23 ± 2.94 | 2.70 ± 2.46 | 4.54 ± 3.56 | < 0.001 |
| PLR, mean ± SD | 197.51 ± 101.20 | 187.46 ± 95.80 | 222.45 ± 109.82 | < 0.001 |
| PNI, mean ± SD | 46.94 ± 6.766 | 48.26 ± 6.35 | 43.69 ± 6.64 | < 0.001 |
ECOG: Eastern Cooperative Oncology Group; ASA: American Society of Anesthesiologists; ALT: Alanine aminotransferase; AST: Aspartate aminotransferase; ALP: Alkaline phosphatase; GGT: γ-glutamyl transferase; TBIL: Total bilirubin; CRP: C-reactive protein; PT: Prothrombin time; NLR: Neutrophil-to-lymphocyte ratio; PLR: Platelet-to-lymphocyte ratio; PNI: Prognostic nutritional index.
Intra- and postoperative outcomes
The average operative time was 329.14 ± 91.77 minutes. Patients in the high RDW group had more cases of blood transfusion (P < 0.05), and there were no significant differences in operative time and blood loss between the two groups (Table 2, all P > 0.05). The postoperative outcomes were shown in Table 2. A total of 383 (47.6%) patients developed POCs, 166 (20.6%) patients had severe POCs (CDc grade ≥ IIIa) and the postoperative mortality was 1.7% (14 patients). The average comprehensive complication index (CCI) score was 20.0 ± 25.5. Patients in the high RDW group had a higher incidence of POCs, more severe POCs, higher CCI scores and longer hospital stay (all P < 0.05). In addition, high RDW was associated with a higher incidence of BL, hemorrhage, POPF, intra-abdominal infection and longer hospital stay (all P < 0.05). There was no significant difference in DGE between the two groups (P > 0.05).
Table 2.
Surgical details and short-term outcomes of patients who underwent laparoscopic pancreatoduodenectomy, n (%)
|
Variables
|
Total (n = 804)
|
Red blood cell distribution
|
P value
|
|
|
< 15.4 (n = 573)
|
≥ 15.4 (n = 231)
|
|||
| Operative time, minute, mean ± SD | 329.14 ± 91.77 | 325.39 ± 92.03 | 338.44 ± 90.65 | 0.068 |
| Blood loss, mL, mean ± SD | 156.20 ± 155.38 | 155.13 ± 160.75 | 158.85 ± 141.47 | 0.759 |
| Blood transfusion | < 0.001 | |||
| No | 576 (71.6) | 454 (79.2) | 122 (52.8) | |
| Yes | 228 (28.4) | 119 (20.8) | 109 (47.2) | |
| Postoperative morbidity | < 0.001 | |||
| No | 421 (52.4) | 327 (57.1) | 94 (40.7) | |
| Yes | 383 (47.6) | 246 (42.9) | 137 (59.3) | |
| Any POPF | 213 (26.5) | 132 (23.0) | 81 (35.1) | < 0.001 |
| POPF, grade B/C | 83 (10.3) | 44 (7.7) | 39 (16.9) | < 0.001 |
| BL | 119 (14.8) | 70 (12.2) | 49 (21.2) | 0.001 |
| BL, grade B/C | 89 (11.1) | 40 (7.0) | 49 (21.2) | < 0.001 |
| DGE | 185 (23.0) | 126 (22.0) | 59 (25.5) | 0.279 |
| DGE, grade B/C | 62 (7.7) | 43 (7.5) | 19 (8.2) | 0.729 |
| Hemorrhage | 113 (14.1) | 69 (12.0) | 44 (19.0) | 0.010 |
| Hemorrhage, B/C | 82 (10.2) | 47 (8.2) | 35 (15.2) | 0.003 |
| Intra-abdominal infection | 140 (17.4) | 90 (15.7) | 50 (21.6) | 0.045 |
| Clavien-Dino classification | < 0.001 | |||
| 0 | 421 (52.4) | 327 (57.1) | 94 (40.7) | |
| I | 53 (6.6) | 38 (6.6) | 15 (6.5) | |
| II | 164 (20.4) | 102 (17.8) | 62 (26.8) | |
| IIIa | 117 (14.6) | 80 (14.0) | 37 (16.0) | |
| IIIb | 12 (1.5) | 8 (1.4) | 4 (1.7) | |
| IVa | 16 (2.0) | 11 (1.9) | 5 (2.2) | |
| IVb | 7 (0.9) | 3 (0.5) | 4 (1.7) | |
| V | 14 (1.7) | 4 (0.7) | 10 (4.3) | |
| CCI score, mean ± SD | 20.0 ± 25.5 | 17.2 ± 23.5 | 26.9 ± 28.9 | < 0.001 |
| < 26.2 | 519 (64.6) | 396 (69.1) | 123 (53.2) | < 0.001 |
| ≥ 26.2 | 285 (35.4) | 177 (30.9) | 108 (46.8) | |
| Hospital stay, day, mean ± SD | 13.65 ± 11.98 | 13.13 ± 10.44 | 14.93 ± 15.09 | 0.027 |
POPF: Postoperative pancreatic fistula; BL: Bile leakage; DGE: Delayed gastric emptying; CCI: Comprehensive complication index.
Risk factors for POCs after LPD and subgroup analysis
The risk factors for POCs after LPD were further explored. For any CDc grade POCs, univariate analysis showed that preoperative biliary drainage, intraoperative blood transfusion, RDW, platelet level, AST, ALT, GGT, ALP, TBIL, albumin, and CRP were potential risk factors (all P < 0.05, Table 3). Multivariate analysis indicated that the independent risk factors for POCs were preoperative biliary drainage [hazard ratio (HR) = 2.160, 95%CI: 1.387-3.364, P = 0.001], ALP (HR = 1.979, 95%CI: 1.130-3.464, P = 0.017), RDW (HR = 2.973, 95%CI: 2.032-4.350, P < 0.001) and albumin (HR = 1.735, 95%CI: 1.130-2.662, P = 0.012) (Table 3). Furthermore, for CDc grade IIIa or higher POCs, univariate analysis showed that sex, age, ECOG score, diabetes mellitus, intraoperative blood transfusion, RDW, hemoglobin, leucocytes, AST, ALT, GGT, TBIL, albumin, and CRP were potential risk factors (all P < 0.05, Table 3). Multivariate analysis indicated that the independent risk factors for POCs were diabetes mellitus (HR = 1.773, 95%CI: 1.054-2.983, P = 0.031) and RDW (HR = 3.138 95%CI: 2.042-4.824, P < 0.001) (Table 3).
Table 3.
Logistic analysis for exploration of risk factors of any postoperative complications of patients who underwent laparoscopic pancreatoduodenectomy
| Variables |
Univariate analysis1
|
Multivariate analysis1
|
Univariate analysis2
|
Multivariate analysis2
|
||||
|
OR (95%CI)
|
P value
|
OR (95%CI)
|
P value
|
OR (95%CI)
|
P value
|
OR (95%CI)
|
P value
|
|
| Sex | 0.766 | 0.095 | 0.528 | |||||
| Male | 1.000 | 1.000 | 1.000 | |||||
| Female | 0.957 (0.714-1.281) | 0.729 (0.502-1.057) | 0.872 (0.570-1.334) | |||||
| Age | 0.268 | 0.046 | 0.209 | |||||
| < 65 | 1.000 | 1.000 | 1.000 | |||||
| ≥ 65 | 1.173 (0.885-1.555) | 1.417 (1.006-1.998) | 1.266 (0.876-1.829) | |||||
| Pathology | 0.203 | 0.117 | ||||||
| Benign tumors | 1.000 | 1.000 | ||||||
| Malignant tumors | 1.239 (0.891-1.723) | 1.411 (0.918-2.169) | ||||||
| ECOG score | 0.245 | 0.010 | 0.107 | |||||
| 0-1 | 1.000 | 1.000 | 1.000 | |||||
| 2 | 1.339 (0.819-2.190) | 2.005 (1.179-3.410) | 1.637 (0.898-2.982) | |||||
| Preoperative biliary drainage | 0.047 | 0.419 | ||||||
| Yes | 1.000 | 1.000 | 0.001 | 1.000 | ||||
| No | 1.488 (1.005-2.205) | 2.160 (1.387-3.364) | 1.227 (0.747-2.017) | |||||
| Hypertension | 0.510 | 0.802 | ||||||
| No | 1.000 | 1.000 | ||||||
| Yes | 1.110 (0.813-1.516) | 1.051 (0.714-1.545) | ||||||
| Diabetes mellitus | 0.568 | 0.012 | 0.031 | |||||
| No | 1.000 | 1.000 | 1.000 | |||||
| Yes | 1.107 (0.781-1.569) | 1.887 (1.150-3.096) | 1.773 (1.054-2.983) | |||||
| Pancreatitis | 0.194 | 0.633 | ||||||
| No | 1.000 | 1.000 | ||||||
| Yes | 1.402 (0.842-2.335) | 1.159 (0.633-2.119) | ||||||
| Abdominal surgery history | 0.276 | 0.170 | ||||||
| No | 1.000 | 1.000 | ||||||
| Yes | 1.400(0.765-2.564) | 1.596 (0.818-3.144) | ||||||
| Smoking | 0.511 | 0.253 | ||||||
| No | 1.000 | 1.000 | ||||||
| Yes | 1.103 (0.824-1.476) | 1.228 (0.863-1.747) | ||||||
| Alcohol consumption | 0.258 | 0.272 | ||||||
| No | 1.000 | 1.000 | ||||||
| Yes | 1.188 (0.881-1.602) | 1.224 (0.854-1.756) | ||||||
| BMI | 0.115 | 0.271 | ||||||
| < 25 | 1.000 | 1.000 | ||||||
| ≥ 25 | 1.259 (0.945-1.676) | 1.222 (0.855-1.747) | ||||||
| Operation time | 1.001 (0.999-1.002) | 0.484 | 1.001 (0.999-1.003) | 0.408 | ||||
| Blood loss | 1.000 (0.999-1.001) | 0.956 | 1.000 (0.998-1.001) | 0.533 | ||||
| Intraoperative blood transfusion | 0.004 | 0.890 | 0.096 | 0.660 | ||||
| No | 1.000 | 1.000 | 1.000 | 1.000 | ||||
| Yes | 1.572 (1.154-2.140) | 1.025 (0.722-1.455) | 1.364 (0.946-1.966) | 1.102 (0.715-1.700) | ||||
| ASA score | 0.475 | 0.496 | ||||||
| II | 1.000 | 1.000 | ||||||
| III | 1.111 (0.833-1.481) | 1.130 (0.795-1.606) | ||||||
| RDW | < 0.001 | < 0.001 | < 0.001 | < 0.001 | ||||
| < 15.4 | 1.000 | 1.000 | 1.000 | 1.000 | ||||
| ≥ 15.4 | 3.537 (2.553-4.900) | 2.973 (2.032-4.350) | 3.603 (2.525-5.141) | 3.138 (2.042-4.824) | ||||
| Hemoglobin, g/L | 0.212 | 0.024 | 0.426 | |||||
| < 115 | 1.000 | 1.000 | 1.000 | |||||
| ≥ 115 | 0.813 (0.588-1.125) | 0.647 (0.443-0.944) | 0.823 (0.509-1.331) | |||||
| Leucocytes, 109/L | 0.250 | 0.047 | 0.533 | |||||
| < 9.5 | 1.000 | 1.000 | 1.000 | |||||
| ≥ 9.5 | 1.308 (0.827-2.068) | 1.675 (1.006-2.789) | 1.198 (0.679-2.113) | |||||
| Platelet, 109/L | 0.003 | 0.093 | 0.996 | |||||
| < 350 | 1.000 | 1.000 | 1.000 | |||||
| ≥ 350 | 1.894 (1.247-2.878) | 1.493 (0.935-2.383) | 1.001 (0.605-1.657) | |||||
| Lymphocyte, 109/L | 0.225 | 0.612 | ||||||
| < 3.2 | 1.000 | 1.000 | ||||||
| ≥ 3.2 | 2.771 (0.534-14.368) | 1.532 (0.295-7.968) | ||||||
| AST, U/L | 0.002 | 0.190 | 0.016 | 0.649 | ||||
| < 35 | 1.000 | 1.000 | 1.000 | 1.000 | ||||
| ≥ 35 | 1.610 (1.191-2.177) | 1.617 (0.788-3.320) | 1.618 (1.094-2.393) | 1.229 (0.505-2.991) | ||||
| ALT, U/L | 0.042 | 0.731 | 0.035 | 0.651 | ||||
| < 40 | 1.000 | 1.000 | 1.000 | 1.000 | ||||
| ≥ 40 | 1.363 (1.011-1.837) | 1.140 (0.541-2.403) | 1.516 (1.031-2.231) | 1.226 (0.508-2.959) | ||||
| GGT, U/L | 0.004 | 0.186 | 0.006 | 0.454 | ||||
| < 45 | 1.000 | 1.000 | 1.000 | 1.000 | ||||
| ≥ 45 | 1.601 (1.166-2.199) | 1.511 (0.820-2.785) | 1.809 (1.182-2.770) | 1.335 (0.626-2.848) | ||||
| ALP, U/L | 0.058 | 0.017 | 0.220 | |||||
| < 140 | 1.000 | 1.000 | 1.000 | |||||
| ≥ 140 | 1.330 (0.990-1.787) | 1.979 (1.130-3.464) | 1.262 (0.871-1.829) | |||||
| TBIL, umol/L | 0.002 | 0.624 | < 0.001 | 0.152 | ||||
| < 235 | 1.000 | 1.000 | 1.000 | 1.000 | ||||
| ≥ 235 | 1.605 (1.191-2.163) | 1.099 (0.754-1.601) | 2.172 (1.531-3.082) | 1.551 (0.850-2.829) | ||||
| Albumin, g/L | < 0.001 | 0.012 | < 0.001 | 0.149 | ||||
| ≥ 35 | 1.000 | 1.000 | 1.000 | 1.000 | ||||
| < 35 | 2.598 (1.794-3.764) | 1.735 (1.130-2.662) | 2.628 (1.781-3.879) | 1.417 (0.883-2.274) | ||||
| CRP, mg/L | 0.002 | 0.197 | 0.001 | 0.205 | ||||
| < 10 | 1.000 | 1.000 | 1.000 | 1.000 | ||||
| ≥ 10 | 1.599 (1.180-2.168) | 1.265 (0.885-1.807) | 1.797 (1.260-2.564) | 1.308 (0.863-1.983) | ||||
| PT, second | 0.760 | 0.277 | ||||||
| < 14 | 1.000 | 1.000 | ||||||
| ≥ 14 | 0.928 (0.574-1.499) | 0.736 (0.424-1.278) | ||||||
Any morbidity, Clavien-Dino classification grade I or higher.
Severe morbidity, Clavien-Dino classification grade IIIa or higher.
OR: Odds ratio; CI: Confidence interval; ECOG: Eastern Cooperative Oncology Group; BMI: Body mass index; ASA: American Society of Anesthesiologists; RDW: Red blood cell distribution width; ALT: Alanine aminotransferase; AST: Aspartate aminotransferase; ALP: Alkaline phosphatase; GGT: γ-glutamyl transferase; TBIL: Total bilirubin; CRP: C-reactive protein; PT: Prothrombin time.
In subgroup analysis (Table 4), we found that RDW was still an independent risk factor for CDc grade IIIb or higher POCs (HR = 2.127, 95%CI: 1.116-4.055, P = 0.022) and CCI score ≥ 26.2 (HR = 1.680, 95%CI: 1.185-2.382, P = 0.004). In addition, RDW was found to be risk factors for severe BL (HR = 3.401, 95%CI: 1.979-5.845, P < 0.001), severe POPF (HR = 2.246, 95%CI: 1.320-3.820, P = 0.003) and severe hemorrhage (HR = 1.794, 95%CI: 1.050-3.063, P = 0.032). RDW was not an independent risk factor for intra-abdominal infection (HR = 1.201, 95%CI: 0.793-1.817, P = 0.387) or severe DGE (HR = 1.130, 95%CI: 0.573-2.226, P = 0.725).
Table 4.
Subgroup analysis of risk factors for the development of postoperative complications of grades IIIa or higher, grades IIIb or higher according to the Clavien-Dino classification, and specific types of postoperative complications, including severe bile leakage, severe postoperative pancreatic fistula, delayed gastric emptying, hemorrhage, and intra-abdominal infection in patients who underwent laparoscopic pancreatoduodenectomy
| POCs | Variables |
Univariate analysis
|
Multivariate analysis
|
||
|
OR (95%CI)
|
P value
|
OR (95%CI)
|
P value
|
||
| CDc grade IIIb or higher | ECOG score, 2 vs 0-1 | 3.415 (1.659-7.028) | 0.001 | 4.169 (1.895-9.174) | < 0.001 |
| Preoperative biliary drainage, yes vs no | 0.225 (0.054-0.940) | 0.041 | 0.138 (0.032-0.600) | 0.008 | |
| Smoking, yes vs no | 1.735 (0.970-3.101) | 0.063 | 1.496 (0.727-3.079) | 0.274 | |
| Drinking, yes vs no | 1.712 (0.952-3.078) | 0.072 | 1.650 (0.791-3.440) | 0.182 | |
| ALP, ≥ 140 U/L vs < 140 U/L | 1.783 (0.896-3.546) | 0.099 | 1.614 (0.717-3.634) | 0.247 | |
| RDW, ≥ 15.4 vs < 15.4 | 2.326 (1.298-4.169) | 0.005 | 2.127 (1.116-4.055) | 0.022 | |
| Lymphocyte, ≥ 3.2 × 109/L vs < 3.2 × 109/L | 6.383 (1.206-33.775) | 0.029 | 6.536 (1.068-39.978) | 0.042 | |
| CRP, ≥ 10 mg/L vs < 10 mg/L | 1.836 (1.020-3.302) | 0.043 | 1.400 (0.741-2.646) | 0.300 | |
| Severe POPF (grade B and C) | Age, ≥ 65 years vs < 65 years | 1.756 (1.113-2.772) | 0.016 | 1.435 (0.889-2.316) | 0.139 |
| ECOG score, 2 vs 0-1 | 2.671 (1.433-4.981) | 0.002 | 2.878 (1.435-5.774) | 0.003 | |
| Operative time | 0.997 (0.994-1.000) | 0.026 | 0.996 (0.993-0.999) | 0.006 | |
| RDW, ≥ 15.4 vs < 15.4 | 2.442 (1.539-3.875) | < 0.001 | 2.246 (1.320-3.820) | 0.003 | |
| Hemoglobin, ≥ 115 g/L vs < 115 g/L | 0.544 (0.335-0.882) | 0.014 | 0.856 (0.495-1.481) | 0.579 | |
| Leucocytes, ≥ 9.5 × 109/L vs < 9.5 × 109/L | 1.755 (0.924-3.334) | 0.086 | 1.609 (0.815-3.177) | 0.170 | |
| Albumin, < 35 g/L vs ≥ 35 g/L | 1.885 (1.130-3.143) | 0.015 | 1.153 (0.641-2.074) | 0.643 | |
| PT, ≥ 14 seconds vs < 14 seconds | 0.343 (0.106-1.115) | 0.075 | 0.229 (0.067-0.783) | 0.019 | |
| Severe BL | Diabetes mellitus, yes vs no | 3.110 (1.408-6.870) | 0.005 | 2.484 (1.105-5.583) | 0.028 |
| Smoking, yes vs no | 2.010 (1.289-3.133) | 0.002 | 1.660 (0.959-2.874) | 0.070 | |
| Drinking, yes vs no | 1.580 (1.005-2.484) | 0.048 | 1.200 (0.687-2.097) | 0.522 | |
| BMI ≥ 24 kg/m2 vs < 24 kg/m2 | 2.442 (1.439-4.143) | 0.001 | 1.988 (1.143-3.456) | 0.015 | |
| Intra-operative blood transfusion, yes vs no | 1.660 (1.050-2.625) | 0.030 | 1.210 (0.707-2.072) | 0.487 | |
| RDW, ≥ 15.4 vs < 15.4 | 3.587 (2.287-5.628) | < 0.001 | 3.401 (1.979-5.845) | < 0.001 | |
| Hemoglobin, ≥ 115 g/L vs < 115 g/L | 0.648 (0.401-1.048) | 0.077 | 0.824 (0.448-1.515) | 0.533 | |
| TBIL, ≥ 235 μmol/L vs < 235 μmol/L | 2.188 (1.402-3.417) | 0.001 | 1.326 (0.776-2.264) | 0.302 | |
| Albumin, < 35 g/L vs ≥ 35 g/L | 2.326 (1.434-3.774) | 0.001 | 1.290 (0.721-2.309) | 0.391 | |
| CRP, ≥ 10 mg/L vs < 10 mg/L | 1.527 (0.967-2.413) | 0.069 | 1.138 (0.679-1.907) | 0.623 | |
| Severe hemorrhage | ECOG score, 2 vs 0-1 | 2.715 (1.455-5.066) | 0.002 | 2.832 (1.447-5.540) | 0.002 |
| Smoking, yes vs no | 1.937 (1.223-3.068) | 0.005 | 1.437 (0.820-2.517) | 0.206 | |
| Drinking, yes vs no | 2.064 (1.299-3.278) | 0.002 | 1.858 (1.047-3.297) | 0.034 | |
| RDW, ≥ 15.4 vs < 15.4 | 1.998 (1.252-3.189) | 0.004 | 1.794 (1.050-3.063) | 0.032 | |
| GGT, ≥ 45 U/L vs < 45 U/L | 1.735 (0.969-3.108) | 0.064 | 1.215 (0.640-2.307) | 0.551 | |
| Albumin, < 35 g/L vs ≥ 35 g/L | 1.792 (1.067-3.008) | 0.027 | 1.022 (0.559-1.869) | 0.944 | |
| CRP, ≥ 10 mg/L vs < 10 mg/L | 1.582 (0.986-2.536) | 0.057 | 1.181 (0.699-1.997) | 0.534 | |
| Intra-abdominal infection | Age, ≥ 65 vs < 65 | 1.539 (1.067-2.220) | 0.021 | 1.363 (0.928-2.001) | 0.114 |
| ECOG score, 2 vs 0-1 | 1.887 (1.076-3.310) | 0.027 | 1.725 (0.957-3.109) | 0.070 | |
| Hypertension, yes vs no | 1.577 (1.069-2.326) | 0.022 | 1.365 (0.909-2.052) | 0.134 | |
| Drinking, yes vs no | 1.603 (1.100-2.338) | 0.014 | 1.556 (1.052-2.301) | 0.027 | |
| RDW, ≥ 15.4 vs < 15.4 | 1.483 (1.008-2.180) | 0.045 | 1.201 (0.793-1.817) | 0.387 | |
| Leucocytes, ≥ 9.5 × 109/L vs < 9.5 × 109/L | 1.618 (0.942-2.779) | 0.081 | 1.247 (0.703-1.817) | 0.450 | |
| TBIL, ≥ 235 μmol/L vs < 235 μmol/L | 1.426 (0.977-2.081) | 0.066 | 1.585 (1.027-2.446) | 0.038 | |
| CRP, ≥ 10 mg/L vs < 10 mg/L | 1.675 (1.147-2.448) | 0.008 | 1.304 (0.868-1.960) | 0.202 | |
| Severe DGE | Pathology, malignant tumors vs benign tumors | 1.652 (0.944-2.892) | 0.079 | 1.058 (0.548-2.042) | 0.886 |
| Preoperative biliary drainage, yes vs no | 0.365 (0.130-1.024) | 0.055 | 0.421 (0.144-1.236) | 0.155 | |
| Pancreatitis, yes vs no | 2.748 (1.354-5.578) | 0.005 | 2.555 (1.158-5.639) | 0.020 | |
| Intra-operative blood transfusion, yes vs no | 1.931 (1.137-3.279) | 0.015 | 1.667 (0.901-3.082) | 0.103 | |
| ASA, III vs I-II | 1.683 (0.935-3.031) | 0.083 | 1.893 (1.028-3.487) | 0.041 | |
| RDW, ≥ 15.4 vs < 15.4 | 1.105 (0.629-1.940) | 0.729 | 1.130 (0.573-2.226) | 0.725 | |
| Operative time | 1.003 (1.000-1.005) | 0.028 | 1.002 (0.999-1.005) | 0.212 | |
| Lymphocyte, ≥ 3.2 × 109/L vs < 3.2 × 109/L | 4.913 (0.933-25.861) | 0.060 | 4.019 (0.696-23.193) | 0.120 | |
| ALP, ≥ 140 U/L vs < 140 U/L | 2.131 (1.265-3.588) | 0.004 | 2.913 (1.538-5.518) | 0.001 | |
| Albumin, < 35 g/L vs ≥ 35 g/L | 2.201 (1.251-3.871) | 0.006 | 3.065 (1.568-5.992) | 0.001 | |
| CCI ≥ 26.2 | Intra-operative blood transfusion, yes vs no | 1.489(1.087-2.041) | 0.013 | 1.150 (0.816-1.621) | 0.425 |
| Preoperative biliary drainage, yes vs no | 0.695 (0.456-1.060) | 0.091 | 0.573 (0.368-0.891) | 0.014 | |
| RDW, ≥ 15.4 vs < 15.4 | 1.964 (1.436-2.687) | < 0.001 | 1.680 (1.185-2.382) | 0.004 | |
| Leucocytes, ≥ 9.5 × 109/L vs < 9.5 × 109/L | 1.854 (1.171-2.936) | 0.008 | 1.740 (1.076-2.815) | 0.024 | |
| Albumin, < 35 g/L vs ≥ 35 g/L | 1.918 (1.341-2.743) | < 0.001 | 1.511 (1.017-2.244) | 0.041 | |
| Platelet, ≥ 350 × 109/L vs 350 × 109/L | 1.472 (0.973-2.229) | 0.067 | 1.241 (0.798-1.930) | 0.337 | |
POCs: Postoperative complications; OR: Odds ratio; CI: Confidence interval; CDc: Clavien-Dino classification; ECOG: Eastern Cooperative Oncology Group; BMI: Body mass index; ASA: American Society of Anesthesiologists; RDW: Red blood cell distribution width; ALT: Alanine aminotransferase; AST: Aspartate aminotransferase; ALP: Alkaline phosphatase; GGT: γ-glutamyl transferase; TBIL: Total bilirubin; CRP: C-reactive protein; PT: Prothrombin time; POPF: Postoperative pancreatic fistula; BL: Bile leakage; DGE: Delayed gastric emptying; CCI: Comprehensive complication index.
Relationship between red blood cell width distribution and nutritional and inflammatory factors
Previous studies demonstrated that RDW was an indicator of inflammation and malnutrition. We postulated that systemic inflammation and malnutrition might be involved in the high RDW of these patients. Consequently, the relationship between RDW and PNI, albumin, NLR and PLR was analyzed. As shown in Figure 1, higher RDW was positively associated with NLR (r2 = 0.258, P < 0.001) and PLR (r2 = 0.359, P < 0.001) and was negatively associated with albumin (r2 = -0.440, P < 0.001) and PNI (r2 = -0.442, P < 0.001).
Figure 1.
Relationship between pretreatment red blood cell distribution width and nutritional and inflammatory status. A-D: Negative correlation between pretreatment red cell distribution width and albumin (r2 = -0.440, P < 0.001) (A) and prognostic nutritional index (r2 = -0.442, P < 0.001) (B); and positive correlation between pretreatment red cell distribution width and neutrophil-to-lymphocyte ratio (r2 = 0.258, P < 0.001) (C) and platelet-to-lymphocyte ratio (r2 = 0.359, P < 0.001) (D) in peripheral blood in patients who underwent laparoscopic pancreatoduodenectomy. RDW: Red cell distribution width; PNI: Prognostic nutritional index.
DISCUSSION
The high incidence of POCs after LPD is one of the main concerns of surgeons, and exploring the risk factors for POCs is thus vitally important. In this study, we found that higher RDW at the time of admission was associated with poorer short-term outcomes after LPD. In the subgroup analysis, high pretreatment RDW was still an independent risk factor for severe POCs and specific types of POCs. In addition, RDW was found to be associated with nutritional and inflammatory markers, including PNI, albumin, PLR, and NLR, which indicated that it could be a surrogate biomarker for nutritional and inflammatory markers in predicting the development of POCs after surgery.
RDW, reflecting the degree of heterogeneity of erythrocyte volume, is a simple and easily obtained parameter that is conventionally used in estimating the pathogenesis of anemia[16]. Nevertheless, recent evidence revealed that RDW was associated with the development and progression of multiple diseases[16]. RDW was associated with mortality of cardiovascular diseases, including coronary artery disease, coronary artery ectasia, atrial fibrillation, etc.[30]. RDW could be a prognostic factor for various gastrointestinal cancers, including colorectal cancer[31], pancreatic cancer[32] and gastric cancer[33]. However, only a few studies have focused on the relationship between RDW and short-term outcomes after surgery. Aali-Rezaie et al[34] revealed that a higher preoperative RDW was associated with mortality, any in-hospital medical complications and readmission following revision arthroplasty. Higher RDW was also found to be associated with a higher prevalence of systemic morbidity after laryngectomy[35]. For gastrointestinal surgery, higher pretreatment RDW was reported to be a risk factor for POCs after esophagectomy[21] and hepatectomy[36], and no earlier studies have reported the association between high pretreatment RDW and short-term outcomes after LPD. In this study, using a large cohort of patients, we demonstrated that higher pretreatment RDW was associated with poorer short-term outcomes after LPD.
The underlying mechanisms of the negative impact of RDW on short-term outcomes after surgery have not been fully elucidated. Actually, it is not clear whether RDW is a “cause” or just an “effect” of POCs. Several factors could lead to higher RDW, including nutritional deficiencies, shortening of telomere length, oxidative stress, inflammation, venous thromboembolism and increased erythrocyte mechanical fragility. Some of these conditions were also risk factors for the development of POCs after surgery. Malnutrition, such as iron and folic acid deficiency, could induce increased RDW by impairing the production and survival of erythrocytes[37]. Inflammation could lead to higher RDW by inhibiting the synthesis or activity of erythropoietin, lowering erythrocyte survival and impairing iron metabolism[16]. Short or critically short telomeres could induce increased RDW by causing cell senescence of the hematopoietic progenitors, which could lead to impaired maturation and increased replicative stress of the erythroid lineage[38]. Recently, the impact of red blood cell biology on the development of nonhematological disorders has also been reported, especially in cardiovascular disorders. It was reported that anisocytosis could accelerate atherogenesis by promoting the expansion of the lipid core and the ulceration of the fibrous cap, inhibiting endothelium-dependent nitric oxide-mediated vasodilation, increasing blood viscosity and impairing blood flow[39-41]. However, few studies have reported the potential causal association between anisocytosis and other noncardiovascular disorders, and the pathophysiological mechanisms for the impact of RDW on the development of these disorders cannot be fully explained at this point in time. Further studies are needed to elucidate the potential mechanisms.
Nutritional (e.g., albumin level, BMI and PNI) and inflammatory factors (e.g., PLR, NLR, and CRP) have been demonstrated to be closely associated with the development of POCs after operation and could be predictive markers for POCs[42-44]. RDW was considered to be a general health status and could be a reflection of nutritional and inflammatory status. Consequently, the association between RDW and nutritional and inflammatory status was further explored in our study. We found that higher RDW was associated with higher preoperative CRP, platelet level, NLR and PLR, while it was associated with lower albumin and hemoglobin level. Meanwhile, line regression analysis showed that higher pretreatment RDW was associated with malnutrition (lower albumin and PNI) and severe inflammatory status (higher NLR and PLR). These results support that RDW could be a reflection of patients’ preoperative nutritional and inflammatory status and affect short-term outcomes after LPD. Consequently, RDW may be regarded as a surrogate marker of nutritional and inflammatory factors in selecting patients who are at high risk of developing POCs after surgery.
The strength of our study was its large sample size of patients who underwent LPD. However, our study has several limitations worth noting. First, this was a retrospective study from a single institution. Although comprehensive statistical analysis was performed to improve the reliability of our findings, the results may still be influenced by selection bias, and there was a lack of external validation for them. In addition, the patients included in this study were selected from a relatively long study period, and the improvement of treatment strategy and perioperative management could lead to a historical bias.
CONCLUSION
In conclusion, this study found that elevated pretreatment RDW was a special parameter for patients who underwent LPD. It was associated with malnutrition, severe inflammatory status and poorer short-term outcomes. RDW could be a surrogate marker for nutritional and inflammatory status in identifying patients who were at high risk of developing POCs after LPD. However, further multi-institution, international studies with a larger cohort should be conducted to consolidate our findings.
Footnotes
Institutional review board statement: This study obtained ethics approval from the ethics committee of Shandong Provincial Hospital Affiliated to Shandong First Medical University and was performed in accordance with the Declaration of Helsinki (No. 2024-498). All patients signed an informed consent form.
Informed consent statement: Patients were not required to give informed consent to the study because the analysis used anonymous data that were obtained after each patient agreed to treatment by written consent.
Conflict-of-interest statement: All the authors report no relevant conflicts of interest for this article.
STROBE statement: The authors have read the STROBE Statement-checklist of items, and the manuscript was prepared and revised according to the STROBE Statement-checklist of items.
Provenance and peer review: Unsolicited article; Externally peer reviewed.
Peer-review model: Single blind
Specialty type: Gastroenterology and hepatology
Country of origin: China
Peer-review report’s classification
Scientific Quality: Grade C
Novelty: Grade B
Creativity or Innovation: Grade B
Scientific Significance: Grade B
P-Reviewer: Lin WJ S-Editor: Wang JJ L-Editor: A P-Editor: Zhang XD
Contributor Information
Xian-Rang Cao, Department of Liver Transplantation and Hepatobiliary Surgery, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan 250021, Shandong Province, China.
Yin-Long Xu, Department of Liver Transplantation and Hepatobiliary Surgery, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan 250021, Shandong Province, China.
Jia-Wei Chai, Department of Breast and Thyroid Surgery, Shandong Provincial Maternal and Child Health Care Hospital, Jinan 250014, Shandong Province, China.
Kai Zheng, Department of Liver Transplantation and Hepatobiliary Surgery, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan 250021, Shandong Province, China.
Jun-Jie Kong, Department of Liver Transplantation and Hepatobiliary Surgery, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan 250021, Shandong Province, China.
Jun Liu, Department of Liver Transplantation and Hepatobiliary Surgery, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan 250021, Shandong Province, China.
Shun-Zhen Zheng, Department of Liver Transplantation and Hepatobiliary Surgery, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan 250021, Shandong Province, China. zsz5512920@hotmail.com.
Data sharing statement
No additional data are available.
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