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Prognostic nutritional index predicts clinical outcomes in patients with cerebral venous sinus thrombosis



Lower prognostic nutritional index (PNI) is related to the poor prognosis of cardiovascular diseases. However, little is known about PNI and its relationship with the prognosis of cerebral venous sinus thrombosis (CVST).


CVST patients were retrospectively identified from January 2013 till June 2019. Patients in the acute / subacute phase were selected as subjects. Poor prognosis was defined as a modified Rankin Scale (mRS) of 3–6. Multivariate logistic regression analysis was used to confirm if lower PNI was associated with a poor prognosis.


A total of 297 subjects with follow-up data were enrolled. Thirty-three (11.1%) had a poor outcome. Multivariate logistic regression analysis suggested that PNI was an important predictive factor of poor outcome in acute/subacute CVST (odds ratio, 0.903; 95% CI, 0.833–0.978; P = 0.012). The optimal cut-off value for predicting the poor prognosis of PNI was 44.2. Kaplan-Meier analysis and log-rank test suggested that the lower the PNI value, the higher the mortality rate (P < 0.001). In addition, the nomogram that was set up showed that lower PNI was an index of poor prognosis. The c-index for acute/subacute patients with CVST was 0.872.


Lower PNI is correlated with a higher risk of adverse clinical outcomes in patients with acute/subacute CVST.

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Cerebral venous sinus thrombosis (CVST) is a special type of cerebrovascular disease, which is characterized by cerebral venous reflux obstruction and intracranial hypertension caused by the disturbance of cerebrospinal fluid absorption. It is generally believed that the annual incidence of CVST is 2–5 cases / million, accounting for 0.5–1% of all strokes [1,2,3,4,5,6]. A recent report suggested a much higher incidence (13 cases / million every years) [7]. The inducing risk factors, clinical characteristics, and neuroimaging features of CVST are extremely diverse, which cause challenges to the prognosis [8]. Therefore, it is clinically significant to carry out early risk stratification at the time of onset.

Malnutrition has been proven to be an independent prognostic index of incidence and mortality in patients with various cancers, myocardial infarction (MI) as well as acute ischemic stroke (AIS) [9,10,11]. The PNI is a novel and comprehensive nutritional-inflammatory score that reflects the immunological nutritional status based on serum albumin concentration and lymphocyte count. Several studies have found that PNI is related to poor prognosis and increased mortality in patients with malignant diseases, MI and AIS [12,13,14]. Nevertheless, this correlation between PNI and prognosis in CVST patients has not been studied yet. Acute/subacute CVST is characterized by a sudden onset and rapid progression, which is of great significance to study [15]. Therefore, the aim of this study was to assess the outcome and predictive role of PNI in patients with acute/subacute CVST.

Material and methods

Patient selection

A follow-up study was conducted from January 2013 till June 2019 at the Henan CVST Registry in the First Affiliated Hospital of Zhengzhou University (Henan, China). The diagnosis of CVST complied with international standards [4, 5], based on clinical symptoms, patient history, and neuroimaging results (computed tomographic (CT), magnetic resonance venography (MRV) or digital subtraction angiography (DSA)). The acute period defined as the time from onset to hospital admission was less than 7 days. Whereas subacute period is defined as the time from onset to hospital admission was less than 30 days [16, 17]. The exclusion criteria as follows: (1) patients without complete clinical data; (2) time from onset to admission over 30 days [15]; (3) patients less than 18 years old; (4) patients with severe hepatic or renal diseases; (5) patients lost to follow-up. The registry study was approved by the Ethics Committee of the First Affiliated Hospital of Zhengzhou University.

Data collection

Demographic data and information such as age, gender, risk factors, clinical manifestations, laboratorial parameters and imageological examination were gathered and analyzed. Albumin concentration (ALB) and the absolute lymphocyte count (ALC) were assessed 24 h after admission.

Definition of PNI

Similar to previous studies, PNI was calculated using 5 lymphocyte count (10 9 /L) + albumin concentration (g/L) [18].

Outcome assessment

The outcome was assessed by modified Rankin Scale (mRS) during routine follow-up, which was performed over the phone after 3 months of discharge. The adverse prognosis was defined as mRS of 3–6. Telephone interviewers were unaware of baseline data.

Statistical analysis

Statistical analysis was performed using SPSS 22.0. Continuous data were represented as mean ± SD, which were analyzed by independent Student’s t-test or Mann-Whitney U test, whichever was appropriate. Categorical variables were presented as numbers and percentages, which were compared by the χ2 test or Fisher exact test. Multivariate logistic regression analysis was used to analyze the association between PNI and clinical outcomes. The receiver operating characteristic (ROC) analysis was carried out to evaluate the ability of PNI in predicting clinical prognosis. The patients were dichotomized with the cut-off PNI value. The mortality rate in high and low PNI value groups was compared with the help of the log-rank test and plotted with the use of the Kaplan-Meier method. On this basis, a nomogram of independent predictive factors was established by using RMS software. The results were significant for Two-tailed P < 0.05.


Study subject characteristics

Out of 324 patients who were diagnosed with CVST within 30 days of onset to admission and enrolled in the database, 27 patients were excluded: 15 patients younger than 18 years old, 8 patients without complete clinical data and 4 patients lost to follow-up. Therefore, 297 patients were included in the final analysis. The comparison of baseline characteristics and treatment details of included and excluded patients, showed no difference except for age (Table S1).

Characteristics of patients with good and poor prognosis

During the follow-up period, 33 patients (11.1%) had poor functional outcomes, including 26 patients who died (8.8%). The baseline characteristics of the two groups are shown in Table 1. The PNI (49.3 ± 6.3 versus 42.3 ± 6.1, P < 0.001) of the poor outcome group considerably decreased. Patients with poor outcomes were older (34.2 ± 11.6 versus 44.4 ± 16.3; P < 0.001) compared with the good outcome group. In addition, coma, focal neurological deficits, involvement of straight sinus, and intracerebral hemorrhage in neuroimaging manifestations were more common in patients with adverse prognosis. The lymphocyte count and albumin concentration in subjects with adverse outcomes were lower than those with good outcomes (P < 0.001).

Table 1 Baseline characteristics according to the clinical functional outcome

Analysis between PNI and long-term prognosis

As presented in Table 2, multivariate logistic regression analysis suggested that PNI (odds ratio, 0.903; 95% CI, 0.833–0.978; P = 0.012) remained significantly correlated with the functional outcome after the adjustment of potential confounders including age, gender, presence of coma, focal neurological deficits, intracerebral hemorrhage, and straight sinus. According to the ROC curve of laboratory parameters to predict poor results shown in Fig. 1, when 44.2 was set as the cut-off point, PNI showed the best predictive value with the receiver operating characteristic analysis and area under the curve (AUC) of 0.75 (sensitivity: 75.8% and specificity: 69.7%), which showed the highest AUC value than those of ALC (AUC 0.71; 95% CI, 0.63–0.79) and ALB (AUC 0.69; 95% CI, 0.59–0.79). It indicated that PNI provides a stronger predictive power of poor outcome than its constituent parts. The mRS distribution is shown in Fig. 2. Overall, patients with lower PNI had worse scores on the mRS than higher PNI patients. Kaplan-Meier analysis and log-rank test suggested that the lower the PNI value, the higher the mortality rate (P < 0.001) (Fig. 3).

Table 2 Multivariate logistic regression analysis of predictors for poor clinical outcome in CVST patients
Fig. 1
figure 1

Receiver operating characteristic curves for the clinical functional outcome. Predictive values of ALC, ALB and PNI for the poor outcome. Area under the curve 0.71(95% CI, 0.63–0.79) for ALC, 0.69 (95% CI, 0.59–0.79) for ALB and 0.75(95% CI, 0.66–0.84) for PNI. ALC: absolute lymphocyte count, ALB: albumin concentration and PNI: prognostic nutritional index

Fig. 2
figure 2

The mRS distribution for patients with PNI>44.2 and PNI ≤ 44.2 at the last follow-up. mRS, modified Rankin Scale; PNI: prognostic nutritional index

Fig. 3
figure 3

Kaplan-Meier curves of patients stratified according to the PNI value. The Kaplan-Meier curves showed a significant difference between the PNI>44.2 and PNI ≤ 44.2 categories (Log-rank test = 32.71, P < 0.001). PNI: prognostic nutritional index

Nomograms to predict the prognosis

In addition, age, coma, intracranial hemorrhage, straight sinus involvement and PNI were included in the nomogram of the study (Fig. 4) by stepwise logistic regression analysis. The new model showed that older age, coma,  intracerebral hemorrhage, straight sinus, and lower PNI were indicators of poor prognosis. The c-index of the model was 0.872. These findings were similar to those of the previous multivariate logistic model.

Fig. 4
figure 4

Nomograms of acute/subacute patients with CVST to predict the outcome


In the International Study on Cerebral Vein and Dural Sinus Thrombosis (ISCVT), male gender, age > 37 years old, mental status disturbance, coma, thrombosis of the deep venous system, intracranial hemorrhage, malignancy, and infection of the central nervous system were independently associated with adverse outcomes at the last follow-up [19]. The VENOST study is the largest national multicenter study. Compared with previous studies, the clinical and imaging results are consistent; however, the susceptibility factors are different. The incidence of puerperium is high, and the use of oral contraceptives is not a common risk factor. The prognosis of malignant tumors, advanced age and hemorrhagic infarction is worse [20]. Our study showed that PNI was a significant and independent predictor of poor prognosis in non-chronic CVST patients.

The current research supports the link between inflammation and the incidence of CVST [21, 22]. A number of studies appeared to reinforce the biological plausibility behind inflammation and the prognosis of cerebral venous thrombosis [23, 24]. The lymphocyte count is an indicator that mediates cellular immunity. It is worth noting that some studies supported the use of lymphocyte count as a prognostic indicator. Lymphocytes are involved in the cellular immunity of various cancers and are related to cancer prognosis [25]. In addition, a previous study has shown that lymphocyte count is a predictive factor of adverse outcomes in patients with AIS [26]. In animal models, immunosuppression induced by stroke could lead to lymphopenia and changes in the ratio of helper T cells [27, 28].

Similarly, in human studies, it has also been observed that peripheral blood lymphocytes decreased after stroke, particularly in the acute phase [29, 30]. Therefore, lower lymphocyte count may be a predictor of adverse outcome. The relationship between lymphocyte count and the outcome of CVST has been confirmed in previous studies, such as platelet to lymphocyte ratio (PLR), lymphocyte to monocyte ratio (LMR) and neutrophil to lymphocyte ratio (NLR) [17, 31, 32].

Hypoalbuminemia is a comprehensive result of inflammation and insufficient intake of protein and calories in patients with chronic diseases. In different clinical settings, hypoalbuminemia has been shown to be a sign of poor prognosis [33,34,35]. Considering that albumin is a negative acute-- phase protein, its synthesis rate is affected by nutrition and inflammation [36]. More evidence shows that as the severity of inflammation increases, serum albumin levels gradually decrease [37, 38]. Albumin combined with nitric oxide (NO) free radicals has anticoagulant and antithrombotic effects. Due to the increase in the concentration of free lysophospholipids, hypoalbuminemia may affect blood viscosity and the function of endothelial cells [39]. However, serum albumin is not a good indicator of nutrition observation because it is greatly affected by fluid transfer [33]. Many different factors affect serum albumin levels and have shown a lack of sensitive and specific indicators of nutritional status [40].

As for PNI, it combines the lymphocyte count and albumin concentration, reflecting the nutrition, inflammation and immunity status. Therefore, compared with the factors mentioned above, PNI is more stable and representative. PNI was originally reported to be used to evaluate the immune and nutritional status of patients undergoing gastrointestinal tract surgery [18, 41, 42]. Subsequently, PNI has been widely used in prognostic evaluation of a variety of cancers and transplant operations, as well as for patients with various diseases such as myocardial infarction, acute type A aortic dissections and AIS patients receiving intravenous thrombolysis (IVT) [12, 13, 43, 44].

This study further showed that lower PNI increased the risk of poor outcomes in acute/subacute patients with CVST. Additionally, the findings from nomograms by stepwise logistic regression analyses suggested that age, coma, intracerebral hemorrhage, straight sinus involvement, and PNI were also predictors of adverse outcomes in acute/subacute patients with CVST, which further supported the results from multivariate logistic regression analyses. Therefore, the PNI created by combining serum albumin concentration and lymphocyte counts has the ability to assess the nutritional, inflammatory and immune status of patients with acute/subacute CVST. Considering that patients with lower PNI scores in this study have a significantly higher incidence of poor prognosis, it can be considered that appropriate evaluation and implementation of measures to improve nutritional status will help improve the outcome of patients with acute/subacute CVST. Further prospective studies are required to verify this hypothesis.

PNI is easy to obtain because it is calculated using objective laboratory test data. This makes it easy for our achievements to be translated into daily practice. However, several potential limitations should be acknowledged in the present study. Firstly, it is a single center study, and the sample size included in this study is relatively small. This association in the present study also needs to be confirmed and verified in larger multicenter prospective cohort studies. Secondly, compared with arterial stroke, it is difficult to determine the exact onset time in patients with CVST.


In summary, our study suggested that lower PNI was a potential risk factor in unfavorable functional outcome of patients with acute/subacute CVST.

Availability of data and materials

Study data are available from the corresponding author upon request.



Cerebral venous sinus thrombosis


Lower prognostic nutritional index


Modified Rankin Scale


Myocardial infarction


Acute ischemic stroke


Intravenous thrombolysis


Computed tomographic


Magnetic resonance venography


Digital subtraction angiography


Albumin concentration


Absolute lymphocyte count


Receiver operating characteristic


The receiver operating characteristic analysis and area under the curve


International Study on Cerebral Vein and Dural Sinus Thrombosis


Platelet to lymphocyte ratio


Lymphocyte to monocyte ratio


Neutrophil to lymphocyte ratio


Nitric oxide


Cerebral venous thrombosis


Odds ratio


Confidence interval


  1. Filippidis A, Kapsalaki E, Patramani G. Fountas KN cerebral venous sinus thrombosis: review of the demographics, pathophysiology, current diagnosis, and treatment. Neurosurg Focus. 2009;27(5):E3.

    Article  PubMed  Google Scholar 

  2. Medel R, Monteith SJ, Crowley RW. Dumont AS a review of therapeutic strategies for the management of cerebral venous sinus thrombosis. Neurosurg Focus. 2009;27(5):E6.

    Article  PubMed  Google Scholar 

  3. Chik Y, Gottesman RF, Zeiler SR, Rosenberg J. Llinas RH differentiation of transverse sinus thrombosis from congenitally atretic cerebral transverse sinus with CT. Stroke. 2012;43(7):1968–70.

    Article  PubMed  PubMed Central  Google Scholar 

  4. Saposnik G, Barinagarrementeria F, Brown RD Jr, Bushnell CD, Cucchiara B, Cushman M, et al. Diagnosis and management of cerebral venous thrombosis: a statement for healthcare professionals from the American Heart Association/American Stroke Association. Stroke. 2011;42(4):1158–92.

    Article  PubMed  Google Scholar 

  5. Ferro JM, Bousser MG, Canhao P, Coutinho JM, Crassard I, Dentali F, et al. European stroke organization guideline for the diagnosis and treatment of cerebral venous thrombosis - endorsed by the European academy of neurology. European Stroke J. 2017;2(3):195–221.

    Article  Google Scholar 

  6. Coutinho JM, Zuurbier SM, Aramideh M. Stam J the incidence of cerebral venous thrombosis: a cross-sectional study. Stroke. 2012;43(12):3375–7.

    Article  PubMed  Google Scholar 

  7. Devasagayam S, Wyatt B, Leyden J. Kleinig T cerebral venous sinus thrombosis incidence is higher than previously thought: a retrospective population-based study. Stroke. 2016;47(9):2180–2.

    Article  PubMed  Google Scholar 

  8. Gulati D, Strbian D. Sundararajan S cerebral venous thrombosis: diagnosis and management. Stroke. 2014;45(2):e16–8.

    Article  PubMed  Google Scholar 

  9. Zhang X, Pang L, Sharma SV, Li R, Nyitray AG, Edwards BJ Malnutrition and overall survival in older patients with cancer. Clin Nutr. 2020.

  10. Adejumo AC, Adejumo KL, Adegbala OM, Enwerem N, Ofosu A, Akanbi O, et al. Inferior outcomes of patients with acute myocardial infarction and comorbid protein-energy malnutrition. JPEN J Parenter Enteral Nutr. 2020;44(3):454–62.

    Article  CAS  PubMed  Google Scholar 

  11. Cai ZM, Wu YZ, Chen HM, Feng RQ, Liao CW, Ye SL, et al. Being at risk of malnutrition predicts poor outcomes at 3 months in acute ischemic stroke patients. Eur J Clin Nutr. 2020;74(5):796–805.

    Article  PubMed  Google Scholar 

  12. Wang SH, Zhai ST. Lin H role of prognostic nutritional index in patients with gastric cancer: a meta-analysis. Minerva Med. 2016;107(5):322–7.

    PubMed  Google Scholar 

  13. Chen QJ, Qu HJ, Li DZ, Li XM, Zhu JJ, Xiang Y, et al. Prognostic nutritional index predicts clinical outcome in patients with acute ST-segment elevation myocardial infarction undergoing primary percutaneous coronary intervention. Sci Rep. 2017;7(1):3285.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  14. Xiang W, Chen X, Ye W, Li J, Zhang X. Xie D prognostic nutritional index for predicting 3-month outcomes in ischemic stroke patients undergoing thrombolysis. Front Neurol. 2020;11:599.

    Article  PubMed  PubMed Central  Google Scholar 

  15. Li S, Liu K, Gao Y, Zhao L, Zhang R, Fang H, et al. Prognostic value of systemic immune-inflammation index in acute/subacute patients with cerebral venous sinus thrombosis. Stroke Vasc Neurol. 2020;5(4):368–73.

    Article  PubMed  PubMed Central  Google Scholar 

  16. Meng R, Wang X, Hussain M, Dornbos D 3rd, Meng L, Liu Y, et al. Evaluation of plasma D-dimer plus fibrinogen in predicting acute CVST. International journal of stroke : official journal of the International Stroke Society. 2014;9(2):166–73.

    Article  Google Scholar 

  17. Li S, Liu K, Zhang R, Gao Y, Fang H, Liu X, et al. Lower lymphocyte to monocyte ratio is a potential predictor of poor outcome in patients with cerebral venous sinus thrombosis. Stroke Vasc Neurol. 2019;4(3):148–53.

    Article  PubMed  Google Scholar 

  18. Onodera T, Goseki N. Kosaki G [prognostic nutritional index in gastrointestinal surgery of malnourished cancer patients]. Nihon Geka Gakkai Zasshi. 1984;85(9):1001–5.

    CAS  PubMed  Google Scholar 

  19. Ferro JM, Canhao P, Stam J, Bousser MG, Barinagarrementeria F. Investigators I prognosis of cerebral vein and dural sinus thrombosis: results of the international study on cerebral vein and Dural sinus thrombosis (ISCVT). Stroke. 2004;35(3):664–70.

    Article  PubMed  Google Scholar 

  20. Duman T, Demirci S, Uluduz D, Kozak HH, Demir S, Misirli CH, et al. Cerebral venous sinus thrombosis as a rare complication of systemic lupus Erythematosus: subgroup analysis of the VENOST study. Journal of Stroke Cerebrovascular Dis. 2019;28(12):104372.

    Article  Google Scholar 

  21. Goeijenbier M, van Wissen M, van de Weg C, Jong E, Gerdes VE, Meijers JC, et al. Review: viral infections and mechanisms of thrombosis and bleeding. J Med Virol. 2012;84(10):1680–96.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  22. Rashad S, Niizuma K, Sato-Maeda M, Fujimura M, Mansour A, Endo H, et al. Early BBB breakdown and subacute inflammasome activation and pyroptosis as a result of cerebral venous thrombosis. Brain Res. 1699;2018:54–68.

    Google Scholar 

  23. Wang L, Duan J, Bian T, Meng R, Wu L, Zhang Z, et al. Inflammation is correlated with severity and outcome of cerebral venous thrombosis. J Neuroinflammation. 2018;15(1):329.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  24. Aguiar DSD, Pereira-Santos MC, Serra-Caetano A, Lucas NL, Sousa AL, Gabriel D, et al. Blood biomarkers associated with inflammation predict poor prognosis in cerebral venous thrombosis:: a multicenter prospective observational study. Eur J Neurol 2020.

  25. Kobayashi N, Usui S, Kikuchi S, Goto Y, Sakai M, Onizuka M, et al. Preoperative lymphocyte count is an independent prognostic factor in node-negative non-small cell lung cancer. Lung Cancer. 2012;75(2):223–7.

    Article  PubMed  Google Scholar 

  26. Xiao J, Qiu QW, Qin C, Tao R, Qiao SY, Chen M, et al. Dynamic changes of peripheral blood lymphocyte subsets in acute ischemic stroke and prognostic value. Brain Behav. 2020:e01919.

  27. Prass K, Meisel C, Hoflich C, Braun J, Halle E, Wolf T, et al. Stroke-induced immunodeficiency promotes spontaneous bacterial infections and is mediated by sympathetic activation reversal by poststroke T helper cell type 1-like immunostimulation. J Exp Med. 2003;198(5):725–36.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  28. Prass K, Braun JS, Dirnagl U, Meisel C. Meisel a stroke propagates bacterial aspiration to pneumonia in a model of cerebral ischemia. Stroke. 2006;37(10):2607–12.

    Article  PubMed  Google Scholar 

  29. Haeusler KG, Schmidt WU, Fohring F, Meisel C, Helms T, Jungehulsing GJ, et al. Cellular immunodepression preceding infectious complications after acute ischemic stroke in humans. Cerebrovasc Dis. 2008;25(1–2):50–8.

    Article  CAS  PubMed  Google Scholar 

  30. Vogelgesang A, Grunwald U, Langner S, Jack R, Broker BM, Kessler C, et al. Analysis of lymphocyte subsets in patients with stroke and their influence on infection after stroke. Stroke. 2008;39(1):237–41.

    Article  PubMed  Google Scholar 

  31. 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;380:226–9.

    Article  PubMed  Google Scholar 

  32. 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):808–14.

    Article  PubMed  Google Scholar 

  33. Franch-Arcas G. The meaning of hypoalbuminaemia in clinical practice. Clin Nutr. 2001;20(3):265–9.

    Article  CAS  PubMed  Google Scholar 

  34. Oduncu V, Erkol A, Karabay CY, Kurt M, Akgun T, Bulut M, et al. The prognostic value of serum albumin levels on admission in patients with acute ST-segment elevation myocardial infarction undergoing a primary percutaneous coronary intervention. Coron Artery Dis. 2013;24(2):88–94.

    Article  PubMed  Google Scholar 

  35. Bielewicz J, Kurzepa J, Czekajska-Chehab E, Kamieniak P, Daniluk B, Bartosik-Psujek H, et al. Worse neurological state during acute ischemic stroke is associated with a decrease in serum albumin levels. J Mol Neurosci. 2016;58(4):493–6.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  36. Kirsch R, Frith L, Black E. Hoffenberg R regulation of albumin synthesis and catabolism by alteration of dietary protein. Nature. 1968;217(5128):578–9.

    Article  CAS  PubMed  Google Scholar 

  37. Ishida S, Hashimoto I, Seike T, Abe Y, Nakaya Y. Nakanishi H serum albumin levels correlate with inflammation rather than nutrition supply in burns patients: a retrospective study. J Med Investig. 2014;61(3–4):361–8.

    Article  Google Scholar 

  38. Eckart A, Struja T, Kutz A, Baumgartner A, Baumgartner T, Zurfluh S, et al. Relationship of nutritional status, inflammation, and serum albumin levels during acute illness: a prospective study. Am J Med. 2020;133(6):713–22 e717.

    Article  CAS  PubMed  Google Scholar 

  39. Joles JA, Willekes-Koolschijn N. Koomans HA Hypoalbuminemia causes high blood viscosity by increasing red cell lysophosphatidylcholine. Kidney Int. 1997;52(3):761–70.

    Article  CAS  PubMed  Google Scholar 

  40. Levitt DG. Levitt MD human serum albumin homeostasis: a new look at the roles of synthesis, catabolism, renal and gastrointestinal excretion, and the clinical value of serum albumin measurements. Int J Gen Med. 2016;9:229–55.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  41. Nozoe T, Ninomiya M, Maeda T, Matsukuma A, Nakashima H. Ezaki T prognostic nutritional index: a tool to predict the biological aggressiveness of gastric carcinoma. Surg Today. 2010;40(5):440–3.

    Article  PubMed  Google Scholar 

  42. Buzby GP, Mullen JL, Matthews DC, Hobbs CL. Rosato EF prognostic nutritional index in gastrointestinal surgery. Am J Surg. 1980;139(1):160–7.

    Article  CAS  PubMed  Google Scholar 

  43. Kim CY, Kim SY, Song JH, Kim YS, Jeong SJ, Lee JG, et al. Usefulness of the preoperative prognostic nutritional index score as a predictor of the outcomes of lung transplantation: a single-institution experience. Clin Nutr. 2019;38(5):2423–9.

    Article  PubMed  Google Scholar 

  44. Lin Y, Chen Q, Peng Y, Chen Y, Huang X, Lin L, et al. Prognostic nutritional index predicts in-hospital mortality in patients with acute type a aortic dissection. Heart Lung. 2021;50(1):159–64.

    Article  PubMed  Google Scholar 

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The work was supported by the Grants from the Science and Technology Department of the Henan Province (No. 152102310058 to Dr. Bo Song).

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YMX and BS: conception, design and administrative support. JWZ and KL: provision of study materials or patients. SL and HBL: collection and assembly of data. YG, LZ, HF, JW, SLS and YSL: data analysis and interpretation. Manuscript writing: All authors. Final approval of manuscript: All authors.

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Correspondence to Bo Song or Yuming Xu.

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Zhao, J., Liu, K., Li, S. et al. Prognostic nutritional index predicts clinical outcomes in patients with cerebral venous sinus thrombosis. BMC Neurol 21, 404 (2021).

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  • Prognostic nutritional index
  • Cerebral venous sinus thrombosis
  • Acute/subacute
  • Prognosis
  • Risk factors