Publications > Journals > Journal of Clinical and Translational Hepatology > Article Full Text


Predictive Value of Inflammation Biomarkers in Patients with Portal Vein Thrombosis

  • Jian-Bo Han#,
  • Qing-Hua Shu#,
  • Yu-Feng Zhang* and
  • Yong-Xiang Yi*
 Author information
Journal of Clinical and Translational Hepatology 2021;():-

DOI: 10.14218/JCTH.2020.00159


Background and Aims

To investigate the usefulness of inflammation biomarkers to serve as a predictors of portal vein thrombosis (PVT) postoperatively (post) in patients with portal hypertension after splenectomy and periesophagogastric devascularization.


A total of 177 liver cirrhosis patients were recruited from January 2013 to December 2017. They were divided into a PVT group (n=71) and a non-PVT group (n=106), according to ultrasound examination findings at 7-day post. Inflammation biomarkers involving platelet-to-lymphocyte ratio (PLR), neutrophil-to-lymphocyte ratio (NLR), monocyte-to-lymphocyte ratio (MLR), red blood cell distribution width-to-platelet ratio(RPR), mean platelet volume-to-platelet ratio (MPR) preoperatively (pre) and at 1, 3, 7-days post were recorded.


The univariate logistic regression analysis indicated that PLR (pre) (odds ratio (OR)=3.963, 95% confidence interval (CI)=2.070–7.587, p<0.000), MLR (pre) (OR=2.760, 95% CI=1.386–5.497, p=0.004), PLR (post-day 7) (OR=3.345, 95% CI=1.767–6.332, p=0.000) were significantly associated with the presence of PVT. The multivariate logistic regression analysis results indicated that PLR (pre) (OR=3.037, 95% CI=1.463–6.305, p=0.003), MLR (pre) (OR=2.188, 95% CI=1.003–4.772, p=0.049), PLR(post-day 7) (OR=2.166, 95% CI=1.053–4.454, p=0.036) were independent factors for predicting PVT.


The PLR (pre), MLR (pre), and PLR (post-day 7) are predictors of portal vein thrombosis post in patients with portal hypertension after splenectomy and periesophagogastric devascularization.


Inflammation biomarker, Thrombosis, Splenectomy, Portal vein


Splenectomy and periesophagogastric devascularization is one of the main procedures for the management of portal hypertension and hypersplenism, especially for patients with variceal bleeding. The incidence of portal vein thrombosis (PVT) after such surgery can be as high as 6.3%∼39.0%.1 PVT is characterized by partial or total occlusion of the portal vein, with the presence of solid intraluminal material. It can elevate the resistance to portal inflow as the portal venous pressure is increased. Consequently, liver function becomes deteriorated due to the decreased blood flow to the liver. It also shows increased rate of re-bleeding and aggravated progression of bleeding.2,3 The rate of bleeding in liver cirrhosis patients with PVT is higher than in those without PVT.4 Besides these harmful effects, PVT even influences the eligibility for liver transplantation, since it makes the operative technique more complicated and decreases the 1-year survival rate of the recipient.5,6

Vascular endothelial injury, blood flow alteration, and prothrombotic condition are the three major determinants of venous thrombosis, described as Virchow’s triad.7 Previous research has indicated that a higher model for end-stage liver disease (MELD) score, wider splenic vein diameter, increased antithrombin III concentration and prolonged prothrombin time are risk factors of PVT after splenectomy in patients with liver cirrhosis.811

However, an accumulation of evidence suggests that systemic inflammatory response is associated with the development of venous thrombosis.1217 Some inflammation biomarkers involving platelet-to-lymphocyte ratio (PLR), lymphocyte-to-monocyte ratio (LMR), and neutrophil-to-lymphocyte ratio (NLR) have been demonstrated to be useful in predicting venous thromboembolism (deep vein thrombosis of the lower limbs and/or pulmonary embolism or cerebral vein thrombosis).1821 Another series of an index involving the monocyte-to-lymphocyte ratio (MLR), NLR, prognostic nutritional index (PNI), red blood cell distribution width-to-platelet ratio (RPR), and mean platelet volume-to-platelet ratio (MPR) consists of inflammation response biomarkers associated with the prognostic of inflammatory disease, viral infection disease, coronary artery disease, and malignant tumor.1824 However, whether these inflammation biomarkers are able to detect the probability of PVT formation is still unclear.

In previous studies, inflammation biomarkers were not dynamically observed, and the surgery itself may cause the ongoing inflammatory response resulting in change of these markers. In this study, inflammatory biomarkers were detected at certain times before and after surgery. We aimed to determine whether these inflammation biomarkers could serve as predictors of PVT in liver cirrhosis patients with portal hypertension after splenectomy and periesophagogastric devascularization.



We conducted a retrospective analysis of the patients consecutively admitted to the Hospital for portal hypertension, who had been diagnosed according to the following criteria: hypersplenism (platelet count <100×109/L) or gastroesophageal varices between the dates of January 2013 to December 2017 (Fig. 1). All selected patients had undergone splenectomy combined with periesophagogastric devascularization. Exclusion criteria were as follows: 1) liver tumor; 2) liver cirrhosis patients associated with preoperative PVT; 3) liver cirrhosis patients associated with congenital thrombotic disease or hematopoietic disease; 4) use of anticoagulation or anti-inflammation drugs; 5) severe organ dysfunction; or 6) incomplete clinical information. Before surgical procedures, all patients or their relatives provided informed consent and the investigation was carried out in line with the principles of the Declaration of Helsinki (as revised in Fortaleza, Brazil, October 2013). The Ethics Committee of the Second Hospital of Nanjing approved the study protocol.

Flow diagram of the study population.
Fig. 1  Flow diagram of the study population.

PVT, portal vein thrombosis.

Laboratory tests

Blood specimens were collected from the peripheral vein. Data collected from blood tests included assessment of liver function, renal function, coagulation parameters, etiology of liver disease, and blood morphology. Electrocardiography, chest radiography, ultrasound examination, endoscopy of the upper gastrointestinal tract, and contrast-enhanced spiral computed tomography were performed on each patient before the operation. Cirrhosis was confirmed by pathological investigation postoperatively (post). The severity of cirrhosis was evaluated by the MELD and Child-Turcotte-Pugh (CTP) scores. Blood tests, including assessment of liver function, renal function, blood coagulation, and blood morphology, were conducted again on days 1, 3, and 7 after the operation. Two independent radiologists evaluated the presence and extent of PVT, velocity of portal blood flow of PVT preoperatively (pre) and at day 7 post by color Doppler ultrasound examination. Besides, the basic demographic and clinical characteristics (age, gender, body mass index), etiology of liver cirrhosis, and emergency surgery were also recorded.


PLR was defined as the absolute platelet count divided by lymphocyte count (109/L). NLR was the ratio of absolute neutrophils count to lymphocyte count (109/L). MLR was calculated as absolute monocyte count divided by lymphocyte ratio count (109/L), and the MPR as mean platelet volume divided by platelet count (109/L). While RPR referred to the ratio of red cell distribution width to platelet count (109/L). PNI was calculated as albumin (g/L) + 5× total lymphocyte count (109/L).20


Although the standard surgical procedure of splenectomy with periesophagogastric devascularization has been commonly described, we still need to make a brief statement. The open operation was performed by using an extended left subcostal incision. The routine splenectomy was firstly performed, and then periesophagogastric devascularization was performed. Firstly, the gastric branch of the right gastric vein near the gastric angular incisura and small branches of the gastric coronary veins were disconnected. Secondly, the esophageal branch (i.e. esophageal branch of the gastric coronary vein; high esophageal branch of the gastric coronary vein; aberrant high esophageal branch of the gastric coronary vein) was disconnected and suture-ligated, involving up to 10 cm of the esophageal inferior segment. The gastric posterior veins and short gastric veins were disconnected, and then the left subphrenic vein was also disconnected. In addition, the corresponding arteries, including the left gastric artery, left gastroepiploic artery, gastric posterior artery, and left subphrenic artery, were also ligated.

Statistical analysis

The measurement data were presented as mean±standard deviation (normal distribution). Statistically significant differences were evaluated with Student’s t-test (normal distribution). Qualitative data were summarized as n (%), and statistically significant differences were evaluated using the chi-square test. Receiver operating characteristic curves were constructed to assess the indicative values of the inflammation biomarkers. The areas under the curves (AUCs) were calculated with 95% confidence intervals (CIs). The Youden index was applied to determine the optimal cutoff value for every indicator. Significant variables of PVT from univariate analysis were included in multivariate analysis when performing forward stepwise logistic regression modeling. Data were analyzed by SPSS version 16 (SPSS Inc., Chicago, IL, USA). A p-value of less than 0.05 was considered statistically significant.


We collected data for 223 patients with splenectomy. In total, 46 patients were excluded for the following reasons: hematopoietic disease (n=6); liver tumor (n=9); PVT pre (n=17); no portal vein evaluation pre and post (n=14). Finally, 177 patients who meet the criteria were enrolled in this study. The patients were divided into the PVT group (n=71) and the non-PVT group (n=106) according to the finding of PVT post. Baseline characteristics and clinical and laboratory parameters of the two groups are presented in Table 1. There were no significant differences between the two groups, with respect to gender, body mass index, etiology of liver cirrhosis, emergency surgery, portal blood flow velocity, CTP score, and MELD score.

Table 1

Demographic and clinical characteristics of the study population at baseline

VariablePVT, n=71Non-PVT, n=106p-value
Age in years45.90±9.5049.36±10.480.027
Gender, male/female51/2068/380.286
Etiology, hepatitis B/others62/987/190.348
Emergency surgery, yes/no23/4826/800.252
Velocity of portal blood flow in cm/s18.33±4.8717.85±5.340.598
Thickness of spleen in mm61.56±12.5958.31±15.280.184
Longitudinal diameter of spleen in mm184.84±31.55169.81±22.870.053
CTP score, A/B/C53/18/075/31/00.570
MELD score10.94±2.3710.77±2.360.639
PT in s15.83±2.0415.56±2.250.423
TBIL in µmol/L22.88±13.2023.52±11.640.732
DBIL in µmol/L9.24±5.4910.95±6.760.079
ALB in g/L37.21±5.0736.43±5.510.345
GLB in g/L25.77±4.7927.13±6.920.152
AKP in U/L145.61±53.1485.42±40.410.348
GGT in U/L143.38±47.89134.29±73.390.299
BUN in mmol/L5.65±2.366.73±7.480.244
Cr in µmol/L65.54±15.4262.97±18.620.341

Significant differences in basic characteristics of the patients, including age (p=0.027), PLR (p=0.007), NLR (p=0.035), MLR (p=0.037), and lymphocyte count (p=0.002), were observed between the two groups. On day 3 post, the PLR of the PVT group was higher than that of the non-PVT group (p=0.027). In day 7 post, PLR (p=0.001), MLR (p=0.023), PLT (p=0.030), and lymphocyte count (p=0.009) were significantly different among the groups. The data are illustrated in Table 2.

Table 2

Characteristics of inflammation biomarkers at pre and post-days 1, 3, and 7

VariablesPVT (pre)Non-PVT (pre)P-valuePVT (post-D1)Non-PVT (post-D1)p-valuePVT (post-D3)Non-PVT (post-D3)p-valuePVT (post-D7)Non-PVT (post-D7)p-value
WBC as 109/L2.60±2.402.66±1.750.86717.61±6.9216.96±6.800.53713.64±4.7514.03±5.040.60811.30±4.2011.65±4.960.628
Neutrophils as 109/L1.82±2.141.69±1.410.60915.55±6.5315.06±6.470.62311.21±4.4011.49±4.700.6888.45±3.678.64±4.450.770
Lymphocytes as 109/L0.51±0.250.67±0.370.0020.69±0.450.65±0.370.5260.84±0.430.93±0.510.2661.00±0.411.19±0.520.009
Monocytes as 109/L0.22±0.140.23±0.140.7201.29±0.761.20±0.630.4031.37±0.651.36±0.630.9271.45±0.691.39±0.670.552
PLT as 109/L44.39±25.6843.74±24.900.86983.01±29.7282.69±30.020.944143.35±54.45130.39±64.600.162275.17±122.08233.98±123.300.030

Youden index analysis showed the optimal cutoff points for NLR (pre), PLR (post-day 3), MLR (post-day 7), and PLT (post-day 7) were 3.7, 139, 1.055, and 263.5, respectively. The cutoff value for PLR (pre) was 70.5, with a sensitivity of 0.714 and a specificity of 0.614. The cutoff value for MLR (pre) was 0.295, with a sensitivity of 0.783 and a specificity of 0.434. The cutoff value for PLR (post-day 7) was 230.5, with a sensitivity of 0.657 and a specificity of 0.647 (Table 3). Receiver operating characteristic curve analysis identified the AUC for PLR (pre), MLR (pre), PLR (post-day 7), and PLR (pre) combined with MLR (pre) as 0.665, 0.618, 0.655, and 0.697, respectively (Fig. 2). Obviously, they were all better than the AUC values for NLR (pre) (0.600), PLR (post-day 3) (0.595), MLR (post-day 7) (0.607), and PLT (post-day 7) (0.604).

Table 3

Receiver operating characteristics curve of predictive variables for patients with PVT

VariableCutoff valueAUC (95%CI)Sensitivity, %Specificity, %p-value
NLR (pre)3.70.600 (0.515–0.685)32.985.80.025
PLR (pre)70.50.665 (0.585–0.746)71.461.40.000
MLR (pre)0.2950.618 (0.534–0.703)78.343.40.008
PLR (post-day 3)1390.595 (0.508–0.682)73.1480.037
PLR (post-day 7)230.50.655 (0.571–0.739)65.764.70.001
MLR (post-day 7)1.0550.607 (0.523–0.692)75.445.60.017
ROC curve analysis for predicting PVT by PLR (pre), MLR (pre), PLR (post-D7) and combined markers in the estimation cohort.
Fig. 2  ROC curve analysis for predicting PVT by PLR (pre), MLR (pre), PLR (post-D7) and combined markers in the estimation cohort.

ROC, receiver operating characteristic.

The univariate logistic regression analysis indicated that age [odds ratio (OR)=1.958, 95% CI=1.051–3.647, p=0.034], NLR (pre) (OR=2.969, 95% CI=1.417–6.220, p=0.004), PLR (pre) (OR=3.963, 95% CI=2.070–7.587, p<0.000), MLR (pre) (OR=2.760, 95% CI=1.386–5.497, p=0.004), PLR (post-day 3) (OR=2.615, 95% CI=1.342–5.098, p=0.005), PLR (post-day 7) (OR=3.345, 95% CI=1.767–6.332, p=0.000), MLR (post-day 7) (OR=2.567, 95% CI=1.312–5.022, p=0.006), and PLT (post-day 7) (OR=2.437, 95% CI=1.313–4.527, p=0.005) were significantly associated with the presence of PVT.

Multivariate logistic regression analysis was conducted to verify the predictive value of the factors including age, NLR (pre), PLR (pre), MLR (pre), PLR (post-day 3), PLR (post-day 7), MLR (post-day 7), and PLT (post-day 7). The results indicated that PLR (pre) (OR=3.037, 95% CI=1.463–6.305, p=0.003), MLR (pre) (OR=2.188, 95% CI=1.003–4.772, p=0.049), and PLR (post-day 7) (OR=2.166, 95% CI=1.053–4.454, p=0.036) were independent factors for predicting PVT (Table 4).

Table 4

Predictive variables of portal vein thrombosis by univariate and multivariate analyses

VariableUnivariate analysis
Multivariate analysis
OR (95% CI)p-valueOR (95% CI)p-value
Age (≤50 vs. >50 years)1.958 (1.051–3.647)0.034
NLR (pre) (>3.7 vs. ≤3.7)2.969 (1.417–6.220)0.004
PLR (pre) (>70.5 vs. ≤70.5)3.963 (2.070–7.587)0.0003.037 (1.463–6.305)0.003
MLR (pre) (>0.295 vs. ≤0.295)2.760 (1.386–5.497)0.0042.188 (1.003–4.772)0.049
PLR (post-day 3) (>139 vs. ≤139)2.615 (1.342–5.098)0.005
PLR (post-day 7) (>230.5 vs. ≤230.5)3.345 (1.767–6.332)0.0002.166 (1.053–4.454)0.036
MLR (post-day 7) (>1.055 vs. ≤1.055)2.567 (1.312–5.022)0.006

According to the cutoff values for PLR (pre) and MLR (pre), the patients were divided into the following three groups: PLR (pre) ≤70.5 with MLR (pre) ≤0.295; PLR (pre) ≤70.5 with MLR (pre) > 0.295 or PLR (pre) >70.5 with MLR (pre) ≤0.295; and, PLR (pre) >70.5 with MLR (pre) > 0.295. PLR (pre) ≤70.5 with MLR (pre) ≤0.295 was selected as reference. Multivariate logistic regression analysis was performed and showed that PLR (pre) >70.5 and MLR (pre) >0.295 were associated with the greatest predictive value between the three groups (Table 5).

Table 5

Multivariate logistic regression analysis of predictive variables

PLR (pre) ≤70.5 and MLR (pre) ≤0.295
PLR (pre) >70.5 and MLR (pre) ≤0.2952.7501.008–7.5020.048
PLR (pre) ≤70.5 and MLR (pre) >0.295
PLR (pre) >70.5 and MLR (pre) >0.2958.1483.005–22.093<0.000


PVT after splenectomy and periesophagogastric devascularization is a life-threatening complication for its serious consequences involving the increased rate of re-bleeding, complicated liver transplantation technique, and deterioration of liver function.25 The relationship between venous thromboembolism and inflammation response has been controversial, with it being unknown whether inflammation is casual in the development of venous thrombosis or instead a consequence of venous thrombosis. A growing body of data suggests that inflammation plays a vital role in the pathogenesis of venous thromboembolism.1317 The inflammatory process can influence coagulation from the following three aspects: down-regulation of physiological anticoagulant pathways, inhibition of fibrin removal, and initiation of coagulation activation.26 This would result in the shift of hemostatic balance toward a prothrombotic state. Besides, inflammation may increase the damage of endothelial cells. Some inflammatory biomarkers, such as PLR, NLR, and LMR, have been confirmed as useful predictive measures of deep vein thrombus.2730

There is no significant difference with respect to pre platelet count and monocyte count between the PVT group and the non-PVT group. Elevated levels of pre PLR and MLR in the PVT group primarily result from a decreased number of lymphocytes compared with that in the control group. The lymphocyte is the major cell component of the immune system that represents the immunomodulatory pathway and plays a crucial role in regulating systemic inflammation.31 As systemic inflammation worsens, peripheral lymphocyte count becomes reduced as a result of cell apoptosis, necrosis, and redistribution. In hepatitis B virus-related acute-on-chronic liver failure, systemic inflammation is the result of depletion in circulating lymphocytes.32 The lymphocyte count in the PVT group of our study was lower than that of the control group, indicating suppressed immunity. We hypothesized that the intestinal lumen bacterial products penetrated into the circulation in patients with advanced cirrhosis and portal hypertension due to depressed immunity. The combination of bacterial distribution and suppressed immunity ultimately may result in more critical portal vein and systemic inflammation in the PVT group. The inflammation of the vessel wall will initiate thrombus formation.

The elevated level of PLR (post-day 7) may primarily result from an increased platelet count and a decreased lymphocyte count compared to counts in the control group. We found the platelet count to be increasing gradually after splenectomy, and the platelet count of the PVT group in the 7-day post group to be significantly higher than that of the non-PVT group; there were no significant differences for that between the groups at pre and post-day 1 or post-day 3. Evidence suggest that platelets play a less important role in venous thrombosis than in arterial thrombosis. This was supported by the findings from pathological analysis, which showed the arterial thrombi to mainly consist of platelets and the venous thrombi to mainly consist of red blood cells and fibrin, at least initially. The involvement of platelets in the formation of venous thrombosis is slight at an early stage; at a later stage, platelets appear to play a slightly more major role because the subsequent layers of venous thrombi contain some platelets.14 To concretely determine the roles of platelets in the formation of venous thrombosis more research is needed. This may be helpful for clinicians to determine when and which anticoagulation therapy should be recommended. The result indicates that taking an anti-platelet drug from the post-day 7 time point should be an alternative.

The use of anticoagulation for PVT is strongly recommended because of the fact that spontaneous recanalization of PVT rarely happens; however, this therapy is associated with anticoagulation-related bleeding. Which subgroup of patients who undergo surgery and will benefit most from anticoagulant therapy remains an unresolved issue. Early selection of appropriate patients is critical. The two inflammation biomarkers, pre PLR and MLR, are significantly associated with a diagnosis of PVT. Further analysis demonstrated that with a combination index of pre PLR >70.5 and MLR >0.295, the risk of PVT increased 8.148-fold compared with that of PLR ≤70.5 and MLR≤ 0.295. Patients with PLR >70.5 and MLR >0.295 are at high risk for development of post PVT. The increased PLR and MLR preoperatively may reflect a serious thrombus burden. As the thrombus burden becomes aggravated, the risk of PVT becomes increased. This contributes to enhancing our ability to identify the high-risk population and provide a bias for clinic intervention at an early stage. Resveratrol has been demonstrated to reduce the incidence of PVT after splenectomy in an animal model, via a regulation of platelet function and induction of platelet apoptosis.33 Besides that, statins have been used as anti-thrombotic therapy for their anti-inflammatory effect.34 This type of therapy could decrease the rate of venous thrombosis via the reduction of proinflammatory cytokines and chemokines. However, the current guideline of anticoagulation management did not recommend the treatment of inhibiting inflammation. This study may help to suggest the role of anti-inflammation therapy as an optimal prophylactic strategy. The identification of inflammation markers relevant to the formation of PVT could provide definite targets for future therapy.

In this study, we found that PLR (pre), MLR (pre), and PLR (post-day7) are predictors of PVT post in patients undergoing splenectomy and periesophagogastric devascularization. Some potential limitations of this study should be noted. Firstly, this is a retrospective study performed in a single-center, and additional prospective and multicenter studies are needed. Secondly, the portal vein was assessed only on the seventh day after surgery. Dynamic observation of portal vein is proposed, as changes of inflammation biomarkers may represent an after-effect. Thirdly, former research confirmed that the anatomic extent of deep vein thrombosis was associated with changes of inflammation marker levels;12 the PVT group was not divided into any subgroups according to the extent of PVT.



area under the curve


confidence interval




model for end-stage liver disease


monocyte-to-lymphocyte ratio


mean platelet volume-to-platelet ratio


neutrophil-to-lymphocyte ratio


odds ratio


platelet-to-lymphocyte ratio




prognostic nutritional index






portal vein thrombosis


red blood cell distribution width-to-platelet ratio


white blood cell



The authors would like to thank all the individuals who participated in this study.

Data sharing statement

All data are available upon request.


This work was supported by the Nanjing Medical Science and Technology Development Fund (Grant numbers YKK17169).

Conflict of interest

The authors have no conflict of interests related to this publication.

Authors’ contributions

Study concept and design (YXY, YFZ), acquisition of data (JBH, QHS), analysis and interpretation of data (JBH, QHS, YFZ, YXY), drafting of the manuscript (JBH, QHS), critical revision of the manuscript for important intellectual content (JBH, QHS), administrative, technical, or material support, study supervision (YXY, YFZ).


  1. Webster GJ, Burroughs AK, Riordan SM. Review article: portal vein thrombosis — new insights into aetiology and management. Aliment Pharmacol Ther 2005;21(1):1-9 View Article
  2. Stine JG, Shah PM, Cornella SL, Rudnick SR, Ghabril MS, Stukenborg GJ, et al. Portal vein thrombosis, mortality and hepatic decompensation in patients with cirrhosis: A meta-analysis. World J Hepatol 2015;7(27):2774-2780 View Article
  3. Qi X, Su C, Ren W, Yang M, Jia J, Dai J, et al. Association between portal vein thrombosis and risk of bleeding in liver cirrhosis: A systematic review of the literature. Clin Res Hepatol Gastroenterol 2015;39(6):683-691 View Article
  4. Dell’Era A, Iannuzzi F, Fabris FM, Fontana P, Reati R, Grillo P, et al. Impact of portal vein thrombosis on the efficacy of endoscopic variceal band ligation. Dig Liver Dis 2014;46(2):152-156 View Article
  5. Lendoire J, Raffin G, Cejas N, Duek F, Barros Schelotto P, et al. Liver transplantation in adult patients with portal vein thrombosis: risk factors, management and outcome. HPB (Oxford) 2007;9(5):352-356 View Article
  6. Qi X, Dai J, Jia J, Ren W, Yang M, Li H, et al. Association between portal vein thrombosis and survival of liver transplant recipients: a systematic review and meta-analysis of observational studies. J Gastrointestin Liver Dis 2015;24(1):51-59 View Article
  7. Kyrle PA, Eichinger S. Deep vein thrombosis. Lancet 2005;365(9465):1163-1174 View Article
  8. Zocco MA, Di Stasio E, De Cristofaro R, Novi M, Ainora ME, Ponziani F, et al. Thrombotic risk factors in patients with liver cirrhosis: correlation with MELD scoring system and portal vein thrombosis development. J Hepatol 2009;51(4):682-689 View Article
  9. Danno K, Ikeda M, Sekimoto M, Sugimoto T, Takemasa I, Yamamoto H, et al. Diameter of splenic vein is a risk factor for portal or splenic vein thrombosis after laparoscopic splenectomy. Surgery 2009;145(5):457-464 View Article
  10. Kawanaka H, Akahoshi T, Kinjo N, Konishi K, Yoshida D, Anegawa G, et al. Impact of antithrombin III concentrates on portal vein thrombosis after splenectomy in patients with liver cirrhosis and hypersplenism. Ann Surg 2010;251(1):76-83 View Article
  11. Li MX, Zhang XF, Liu ZW, Lv Y. Risk factors and clinical characteristics of portal vein thrombosis after splenectomy in patients with liver cirrhosis. Hepatobiliary Pancreat Dis Int 2013;12(5):512-519 View Article
  12. Rabinovich A, Cohen JM, Cushman M, Kahn SR. Association between inflammation biomarkers, anatomic extent of deep venous thrombosis, and venous symptoms after deep venous thrombosis. J Vasc Surg Venous Lymphat Disord 2015;3(4):347-353.e1 View Article
  13. Riva N, Donadini MP, Ageno W. Epidemiology and pathophysiology of venous thromboembolism: similarities with atherothrombosis and the role of inflammation. Thromb Haemost 2015;113(6):1176-1183 View Article
  14. Saghazadeh A, Hafizi S, Rezaei N. Inflammation in venous thromboembolism: Cause or consequence?. Int Immunopharmacol 2015;28(1):655-665 View Article
  15. Vazquez-Garza E, Jerjes-Sanchez C, Navarrete A, Joya-Harrison J, Rodriguez D. Venous thromboembolism: thrombosis, inflammation, and immunothrombosis for clinicians. J Thromb Thrombolysis 2017;44(3):377-385 View Article
  16. Branchford BR, Carpenter SL. The role of inflammation in venous thromboembolism. Front Pediatr 2018;6:142 View Article
  17. Saghazadeh A, Rezaei N. Inflammation as a cause of venous thromboembolism. Crit Rev Oncol Hematol 2016;99:272-285 View Article
  18. Budzianowski J, Pieszko K, Burchardt P, Rzeźniczak J, Hiczkiewicz J. The role of hematological indices in patients with acute coronary syndrome. Dis Markers 2017;2017:3041565 View Article
  19. Cai J, Wang K, Han T, Jiang H. Evaluation of prognostic values of inflammation-based makers in patients with HBV-related acute-on-chronic liver failure. Medicine (Baltimore) 2018;97(46):e13324 View Article
  20. Kinoshita A, Onoda H, Imai N, Iwaku A, Oishi M, Fushiya N, et al. Comparison of the prognostic value of inflammation-based prognostic scores in patients with hepatocellular carcinoma. Br J Cancer 2012;107(6):988-993 View Article
  21. Sun Y, Zhang L. The clinical use of pretreatment NLR, PLR, and LMR in patients with esophageal squamous cell carcinoma: evidence from a meta-analysis. Cancer Manag Res 2018;10:6167-6179 View Article
  22. Cetinkaya E, Senol K, Saylam B, Tez M. Red cell distribution width to platelet ratio: new and promising prognostic marker in acute pancreatitis. World J Gastroenterol 2014;20(39):14450-14454 View Article
  23. Cai YJ, Dong JJ, Dong JZ, Chen Y, Lin Z, Song M, et al. A nomogram for predicting prognostic value of inflammatory response biomarkers in decompensated cirrhotic patients without acute-on-chronic liver failure. Aliment Pharmacol Ther 2017;45(11):1413-1426 View Article
  24. Li Y, Zhao Y, Feng L, Guo R. Comparison of the prognostic values of inflammation markers in patients with acute pancreatitis: a retrospective cohort study. BMJ Open 2017;7(3):e013206 View Article
  25. Violi F, Ferro D. Clotting activation and hyperfibrinolysis in cirrhosis: implication for bleeding and thrombosis. Semin Thromb Hemost 2013;39(4):426-433 View Article
  26. Levi M, van der Poll T, Büller HR. Bidirectional relation between inflammation and coagulation. Circulation 2004;109(22):2698-2704 View Article
  27. Artoni A, Abbattista M, Bucciarelli P, Gianniello F, Scalambrino E, Pappalardo E, et al. Platelet to lymphocyte ratio and neutrophil to lymphocyte ratio as risk factors for venous thrombosis. Clin Appl Thromb Hemost 2018;24(5):808-814 View Article
  28. Ming L, Jiang Z, Ma J, Wang Q, Wu F, Ping J. Platelet-to-lymphocyte ratio, neutrophil-to-lymphocyte ratio, and platelet indices in patients with acute deep vein thrombosis. Vasa 2018;47(2):143-147 View Article
  29. Zhu X, Yao Y, Yao C, Jiang Q. Predictive value of lymphocyte to monocyte ratio and monocyte to high-density lipoprotein ratio for acute deep vein thrombosis after total joint arthroplasty: a retrospective study. J Orthop Surg Res 2018;13(1):211 View Article
  30. Akboga YE, Bektas H, Anlar O. Usefulness of platelet to lymphocyte and neutrophil to lymphocyte ratios in predicting the presence of cerebral venous sinus thrombosis and in-hospital major adverse cerebral events. J Neurol Sci 2017;380:226-229 View Article
  31. Mo C, Zeng Z, Deng Q, Ding Y, Xiao R. Imbalance between T helper 17 and regulatory T cell subsets plays a significant role in the pathogenesis of systemic sclerosis. Biomed Pharmacother 2018;108:177-183 View Article
  32. Wu W, Yan H, Zhao H, Sun W, Yang Q, Sheng J, et al. Characteristics of systemic inflammation in hepatitis B-precipitated ACLF: Differentiate it from No-ACLF. Liver Int 2018;38(2):248-257 View Article
  33. Xu M, Xue W, Ma Z, Bai J, Wu S. Resveratrol reduces the incidence of portal vein system thrombosis after splenectomy in a rat fibrosis model. Oxid Med Cell Longev 2016;2016:7453849 View Article
  34. Sexton T, Wallace EL, Smyth SS. Anti-thrombotic effects of statins in acute coronary syndromes: At the intersection of thrombosis, inflammation, and platelet-leukocyte interactions. Curr Cardiol Rev 2016;12(4):324-329 View Article
  • Journal of Clinical and Translational Hepatology
  • pISSN 2225-0719
  • eISSN 2310-8819

Predictive Value of Inflammation Biomarkers in Patients with Portal Vein Thrombosis

Jian-Bo Han, Qing-Hua Shu, Yu-Feng Zhang, Yong-Xiang Yi
  • Reset Zoom
  • Download TIFF