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The role of controlling nutritional status score in predicting postthrombotic syndrome in patients with lower extremity deep venous thrombosis

Thrombosis Journal volume 23, Article number: 19 (2025) Cite this article

Abstract

This study aimed to explore the efficacy of Prognostic Nutritional Index (PNI), Controlling Nutritional Status (CONUT), and Nutritional Risk Index (NRI) in predicting postthrombotic syndrome (PTS) in patients with lower extremity deep vein thrombosis (DVT) based on peripheral blood samples. We reviewed and analyzed patients with lower extremity DVT in our hospital from June 2020 to December 2023. The receiver operating characteristic (ROC) curve identified the best nutritional scoring system for a logistic regression model. Restricted cubic spline (RCS) analysis examined the nonlinear link between the CONUT score and PTS risk, using knots at the 10th, 50th, and 90th percentiles of the CONUT score.The study investigated 246 cases of lower extremity DVT, PTS occurred in 59 patients (23.2%). Multifactorial analysis indicated that body mass index (BMI), prior varicose veins, recurrent venous thromboembolism (VTE), and CONUT score were independent risk factors for patients with DVT developing PTS (P < 0.05). In the multivariate analysis model, a CONUT score of > 4.5 was independently associated with PTS (P < 0.001). RCS analysis demonstrated a significant nonlinear relationship (P for nonlinearity = 0.028), with the risk of PTS increasing with CONUT scores up to an inflection point of 7, after which the risk plateaued. Our study suggest that an independent correlation was found between CONUT score and PTS in patients with lower extremity DVT.

Introduction

Deep venous thrombosis (DVT) involves the formation of a blood clot in one or more deep veins and often occurs in the arms or legs, with a higher prevalence in the lower limbs [1]. Between 20% and 50% of patients with DVT will develop postthrombotic syndrome (PTS), the most common chronic complication in patients with venous thromboembolism (VTE) [2]. PTS leads to symptoms, such as pain and swelling in the affected limb, and can progress to intractable venous ulcers in severe cases. Studies have indicated that the impact of PTS on quality of life may exceed that of chronic lung diseases and diabetes, with severe PTS having effects comparable to congestive heart disease and cancer [3]. Moreover, treatments are often ineffective once PTS has developed [4]. Therefore, identifying risk factors and developing effective prevention strategies is crucial. However, current diagnostic approaches for PTS and research into its risk factors showed a lack of biomarkers for predicting PTS. Thus, reliable biomarkers that can be easily assessed in clinical settings are urgently needed to predict the risk of PTS.

The relationship between nutritional status and disease prognosis has increasingly garnered attention. Malnutrition, linked to immunosuppression, increases susceptibility to infections [5] and is a high-risk factor for adverse outcomes in numerous chronic diseases. For instance, it is associated with higher mortality rates and ischemic strokes in elderly patients with atrial fibrillation [6]. Conversely, nutritional excess and/or obesity can signify a chronic, low-grade inflammatory state [7], increasing the risk of metabolic diseases, autoimmune disorders, and cardiovascular diseases [8], impacting prognosis in conditions, such as hypertension, heart failure, and atrial fibrillation [9]. Approximately 50–60% of patients with VTE have triggering factors, such as surgery, cancer, trauma, or paralysis [10], with most displaying underlying inflammatory states [11]. This increased risk of malnutrition and immune abnormalities closely correlates with the onset and progression of DVT [12]. Patients with DVT have low serum albumin levels [13]. Malatino et al. [13] found significantly lower serum albumin levels in patients with DVT patients compared with those without DVT. Additionally, low albumin levels are related to a hypercoagulable state [14], which may partially drive the pathogenesis of PTS. Studies indicate a significantly higher risk of PTS in obese patients compared with nonobese individuals [15]. Thus, nutritional status may influence PTS. However, the exact mechanism of how nutrition status affects PTS incidence in patients with DVT is unknown.

Nutritional indicators, such as the Prognostic Nutritional Index (PNI) [16], Controlling Nutritional Status (CONUT) score [17], and Nutritional Risk Index (NRI) [18] are increasingly used to assess nutritional status. These indexes are calculated using different commonly available and routinely measured laboratory parameters, which can be useful tools for determining the prognosis of patients with various diseases [5, 9, 13, 19, 20].

Recent studies have shown that higher CONUT scores and lower PNI values are independent predictors of DVT risk for various conditions, such as postoperative outcomes in pancreatic tumors [13], gastrointestinal cancers [21], and COVID-19 infection [22]. However, whether immunonutritional markers, such as the CONUT score, PNI, and NRI can accurately predict PTS risk in patients with DVT is unknown. This study aimed to evaluate the utility of CONUT, NRI, and PNI in assessing nutritional status at the early stages of DVT and predicting PTS risk, providing a basis for implementing effective PTS prevention strategies.

Materials and methods

Study population

We collected data from patients diagnosed with lower extremity DVT at Ningbo University’s First Affiliated Hospital between June 2020 and December 2023. The criteria for inclusion were [1] patients diagnosed with lower extremity DVT by using color Doppler ultrasonography (DUS); [2] aged ≥ 18 years; [3] a complete 2-year follow-up. Proximal DVT is defined as thrombosis involving the iliac vein and/or the common femoral vein, which may or may not extend to the inferior vena cava, with or without pulmonary embolism (PE). The exclusion criteria were [1] incomplete clinical data or lost to follow-up during clinical observation; [2] diagnosis of lower extremity arterial diseases or dermatological conditions not related to venous diseases; and [3] treatment with pharmacomechanical catheter-directed thrombolysis, catheter-directed thrombolysis, percutaneous mechanical thrombectomy, and/or stent placement. For 2 years, the patients were followed up at 6, 12, and 24 months after DVT diagnosis.

The study adhered to the Declaration of Helsinki (revised 2013). The First Affiliated Hospital of Ningbo University provided ethical approval for this project (Approval Number: 2024075RS). Informed consent was waived for this retrospective study.

Data collection

We collected the following demographic and patient-related characteristics at baseline from electronic medical records: sex, age, body mass index (BMI), smoking status, and comorbidities (hypertension, diabetes, coronary heart disease, stroke, PE, and prior varicose veins), risk factors of DVT (hospitalization for surgery, active cancer, trauma/fracture, hospitalization due to nonsurgical illness, and recurrent VTE), laboratory parameters (neutrophil count, lymphocyte count, monocyte count, and total cholesterol levels), DVT-related characteristics (limbs of DVT and DVT location).

We also recorded the baseline characteristics of DVT, as well as its signs and symptoms (pain, cramps, heaviness, itching, paresthesia, pretibial edema, skin induration, hyperpigmentation, venous ectasia, redness, venous ulcers, and pain on calf compression). The aforementioned potential risk factors for DVT are defined as factors occurring within the 3 months preceding DVT onset. Based on the American Cancer Society, active cancer includes tumors that are treated with chemotherapy or radiation therapy, have metastasized to other organs, and/or have reached an advanced stage of the disease. Comorbidities are defined as diseases or clinical conditions coexisting with DVT at baseline.

Nutritional assessment using common scoring systems

We used three scoring systems to assess nutritional status in patients with DVT: CONUT score, NRI, and PNI. CONUT scores range from 0 to 12, where a higher score indicates poorer nutritional status. The scores are determined by serum albumin levels, cholesterol levels, and lymphocyte counts [17](Table 1). PNI is computed as follows: 10 × serum albumin level (g/dL) + 0.005 × total lymphocyte count (number/mm3). A higher PNI suggests a greater risk of malnutrition [23]. The NRI is calculated using the equation: NRI = (1.519 × serum albumin, g/dL) + (41.7 × weight [kg]/ideal body weight [IBW; kg]) [18]. The ideal weight for men and women is computed using the Lorentz formula: height (cm) − 100 − (height [cm] − 150)/4 and height (cm) − 100 − (height [cm] − 150)/2. Lower NRI indicated increased malnutrition risk [24]. Through receiver operating characteristic (ROC) curves, the sensitivity and specificity of CONUT, PNI, and NRI scoring systems were tested for their ability to predict PTS in patients with lower extremity DVT. The optimal nutritional assessment system for patients with DVT was determined by calculating and comparing the area under the ROC curve.

Table 1 Calculation of the CONUT score
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PTS assessment

We reviewed outpatient follow-up records and conducted telephone follow-ups at 6, 12, and 24 months after DVT diagnosis. PTS was assessed using the Villalta scoring scale that includes five patient-reported symptoms (pain, heaviness, cramps, paresthesia, and itching) and six clinically observed signs (pretibial edema, redness, hyperpigmentation, skin induration, venous ectasia, and pain on calf compression). Each symptom and sign were assigned scores of 0 (none) to 3 (severe). PTS was considered in patients with lower extremity DVT with a Villalta score of ≥ 5 or a venous ulcer during follow-up. PTS severity was classified as none (0–4), mild [5,6,7,8,9], moderate [10,11,12,13,14], and severe (> 14) [25].

Statistical analyses

Statistical analyses were conducted using IBM SPSS Statistics version 23.0 and R 4.2.3. Continuous variables were tested for normality. Normal distributions were expressed as mean + standard deviation, and Student’s t-test was used to determine significant differences between groups. Nonnormal distributions were expressed as medians (Q1, Q3), and the Mann–Whitney U test was used to compare the differences between groups. Categorical variables were expressed as frequency (%), and Fisher’s exact test was used to examine the differences. Multivariate logistic regression analysis included the optimal nutritional scoring system determined by the ROC curve analysis. We identified the independent risk factors for PTS in patients with lower extremity DVT by using uni- and multivariate logistic regression analyses. Moreover, the association between the CONUT score and the odds of PTS was evaluated using a restricted cubic spline (RCS) model with knots placed at the 10th, 50th, and 90th percentiles of the CONUT score distribution, allowing for a flexible assessment of potential nonlinear relationships. A two-sided P < 0.05 was considered statistically significant.

Results

Patient characteristics

We included 246 patients, with baseline demographic and clinical characteristics summarized in Table 2. Figure 1 shows the study flowchart. The participants were 111 men and 135 women with a median age of 67 years (range, 26–92). The median BMI was 23.07 kg/m2. During the follow-up period, 57 patients (23.2%) developed PTS. Compared with patients without PTS, those who developed PTS had higher rates of recurrent VTE and prior varicose veins, with thrombi occurring more frequently in the proximal veins. Additionally, lymphocyte count and serum albumin and cholesterol levels were lower in patients with PTS patients (P < 0.05; Table 2).

Table 2 Baseline characteristics of patients with DVT
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Fig. 1
figure 1

Flow diagram of the selection process

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Postthrombotic symptoms and signs at follow-Up

During the follow-up period, 57 of 246 patients were diagnosed with PTS, resulting in a 23.2% cumulative incidence rate. Among them, 50 (87.7%), 4 (7%), and 3 patients (5.3%) had mild, moderate, and severe PTS symptoms, respectively. Among the severe cases, two (3.5%) had venous ulcers. Pretibial edema (35.1%), pain (21.1%), and heaviness (17.5%) were the most common symptoms and signs in patients with PTS (Table 3).

Table 3 Postthrombotic symptoms and signs at 2 year of follow-up
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Comparison of the three nutritional scoring systems

Nutritional status was determined using CONUT, RNI, and PNI scores. Nutritional status was significantly correlated with PTS, regardless of the nutritional assessment system used (P < 0.05) (Table 4). Patients with PTS had significantly higher baseline CONUT scores compared with those without PTS (6.11 ± 1.91 vs. 4.80 ± 2.05, P < 0.001). RNI (96.49 ± 10.26 vs. 99.60 ± 10.49, P = 0.049) and PNI scores (40.54 ± 5.68 vs. 43.82 ± 6.56, P = 0.001) in patients with PTS were significantly lower than in those without (Table 4). ROC curves were plotted for CONUT, RNI, and PNI scores as PTS predictors, with areas under the curve of 0.691, 0.517, and 0.649, respectively (Fig. 2), indicating that the CONUT system can better evaluate the nutritional status and predict PTS effects in patients with DVT.

Table 4 Relationship between CONUT score, NRI score, PNI score and PTS
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Fig. 2
figure 2

Receiver operating curves (ROC) of three nutritional scoring systems CONUT (controlling nutritional status), NRI (nutrition risk index), and PNI (prognostic nutritional index) in postoperative complications in patients with bronchiectasis

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Risk factors for PTS development

PTS risk factors were determined by using multi- and univariate logistic regression analyses (Table 5). Univariate analysis showed that BMI, prior varicose vein, recurrent VTE, DVT location, and CONUT score were significantly associated with PTS. Further multivariate logistic regression analysis confirmed that BMI (OR, 1.119; 95% CI, 1.017–1.231; P = 0.021), prior varicose vein (OR, 2.601; 95% CI, 1.020–6.632; P = 0.045), recurrent VTE (OR, 2.862; 95% CI, 1.279–6.401; P = 0.010), and CONUT score (OR, 1.407; 95% CI, 1.200–1.650; P < 0.001) were independent risk factors for developing PTS in patients with DVT. In the multivariate analysis model, a CONUT score of > 4.5 was independently associated with PTS (OR, 5.870; 95% CI, 2.612–13.199; P < 0.001).

Table 5 Univariate and multivariate analyses of risk factors associated with PTS
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Nonlinear relationship between CONUT score and PTS development

The RCS model demonstrated a significant nonlinear association between the CONUT score and the odds of PTS in patients with lower extremity DVT (P for nonlinearity = 0.028, Fig. 3). The risk of PTS increased steadily with higher CONUT scores up to the inflection point at a score of 7, after which the association plateaued. Patients with a CONUT score above 7 showed no further significant increase in PTS risk.

Fig. 3
figure 3

The restricted cubic spline (RCS) model illustrates the association between CONUT score and the odds of developing postthrombotic syndrome (PTS) in patients with lower extremity deep venous thrombosis (DVT). The red solid line represents the odds ratio (OR), with the shaded area denoting the 95% confidence interval (CI). The dashed horizontal line at OR = 1 indicates no association, while the dashed vertical line at a CONUT score of 7 marks the inflection point, used as the reference value

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Discussion

Our study shows that the CONUT score effectively predicts PTS. Among 246 patients with lower extremity DVT, the cumulative incidence of PTS at a 2-year follow-up was 23.2%, which was consistent with previous findings [26]. Our study is the first to demonstrate a significant correlation between nutritional status and PTS following DVT. Previous studies have identified BMI, varicose veins, and prior thrombosis as high-risk factors for PTS, which were also confirmed in our study. Nutritional status remained an independent risk factor for predicting PTS even after adjusting for these factors.

PTS is a common complication involving lower extremity DVT and is often accompanied by peripheral venous circulation disorders and complications (including varicose veins, skin damage, ulcers, etc.), which affect the patient’s nutrition due to dietary restrictions and closely correlate with enhanced systemic inflammation [27]. Previous studies have investigated the expression of nutritional parameters in patients with venous thrombosis and their association with the development of PTS [28,29,30]. A large prospective cohort study has shown that obesity (BMI > 30 kg/m2) increases PTS risk [15]. Kahn et al. [30]also showed that the Villalta score for PTS increases by 0.14 for every 1 kg/m2 increase in BMI. The serum albumin levels of patients with DVT were significantly lower than those without DVT [13]. Previous studies have reported lower lymphocyte count in VTE patients compared with healthy controls [31]. Lower lymphocyte count indicates an increased risk of inflammation, which can reduce albumin synthesis, leading to oxidative damage and exacerbation of inflammation [13]. The pathology of DVT and PTS is largely influenced by inflammation at various stages [32]. During PTS development, these nutrition-related biomarker levels may change due to increased inflammation, although research on this is currently limited. Our study analyzed the clinical data from 246 patients with lower extremity DVT. This study is the first to link nutritional status to PTS risk in patients with DVT, with nutritional status being an independent risk factor for PTS.

The CONUT, and PNI scoring systems were correlated with PTS. However, the CONUT score may be slightly better because of the inclusion of more parameters. The CONUT score quantifies protein, lipid metabolism, and immunity based on serum albumin levels, total lymphocyte count, and cholesterol levels [17]. Albumin is an anti-inflammatory and antioxidant factor [33], and decreased albumin levels increase the activity of vascular cell adhesion molecule-1 in endothelial cells and weaken its anti-inflammatory function, leading to further endothelial damage. Additionally, reduced albumin levels increase free phospholipid choline concentration, stimulating lipid and coagulation factor synthesis, increasing blood viscosity, and causing a hypercoagulable state [34]. The hypercoagulable state and endothelial wall function deterioration may be related to the development of PTS. Idicula et al. showed that serum albumin levels can be used to predict ischemic stroke prognosis, with higher levels associated with better functional outcomes and lower mortality rates [35]. Moreover, lymphocyte count reflects the body’s immune and inflammatory status, with a lower lymphocyte count indicating a compromised immune response and increased inflammation risk. Patients with DVT usually have abnormal lymphocyte counts. Furthermore, several studies confirmed the association between lymphopenia and poor prognosis in various cancers and cardiovascular diseases [36]. Due to chronic inflammation and other factors, patients with DVT are more prone to develop cholesterol metabolism abnormalities, leading to decreased total cholesterol levels [32, 37, 38]. A meta-analysis showed that patients with rheumatoid arthritis with abnormal cholesterol levels were at risk of atherosclerotic plaques, resulting from endothelial dysfunction [39]. Thus, utilizing these three indicators comprehensively can provide a more comprehensive picture of the nutrition status of patients with DVT.

In our multivariate analyses, BMI, prior varicose veins, recurrent VTE, and CONUT score were identified as independent risk factors for PTS. The formation mechanism of PTS is complex, and numerous studies have reported on the related risk factors, but the results were inconsistent. BMI, prior varicose veins, and recurrent VTE were risk factors in current research, which were consistent with our findings [12, 15, 30]. The association between age, sex, proximal thrombosis, and PTS incidence remains controversial. The duration of anticoagulant treatment and compression therapy with elastic stockings did not affect PTS risk in our study, consistent with other studies [40]. Interestingly, mild PTS had a higher prevalence in this study, with PTS severity being lower than the average [41], which may be related to the positive effect of anticoagulation and compression therapy in alleviating clinical symptoms in patients. In conclusion, considering the diversity and variability of PTS risk factors, integrating the assessment of nutritional status in patients with DVT can help clinicians develop effective individualized management strategies for PTS.

This study has several limitations. First, it is a retrospective analysis conducted at a single institution with a relatively small sample size. Indicators such as the PNI, RNI, and CONUT score provide useful insights into patients’ inflammatory and nutritional status but fail to capture other critical factors influencing DVT and PTS development. For example, PTS is strongly associated with systemic inflammation [32]. Prior research [42] has shown that patients with PTS exhibit elevated plasma levels of matrix metalloproteinases (MMP-1, MMP-8) and pro-inflammatory cytokines like TNF-α and IL-6. However, the study’s retrospective nature precluded the assessment of these inflammatory markers, potentially underestimating the role of systemic inflammation. Future prospective studies should address this limitation.Additionally, the observational design does not account for the effects of nutritional interventions on DVT prognosis, including dietary composition, nutritional intake, or environmental factors such as living conditions, occupation, and lifestyle. Evidence suggests that healthy diets and favorable environments significantly influence inflammation, metabolism, and immune function [43,44,45] potentially affecting DVT incidence and PTS progression. Due to data limitations, these variables were excluded from the analysis, which may restrict the findings’ interpretability. Finally, patients receiving combined pharmacological treatments (e.g.,immunosuppressants, anticoagulants, anti-inflammatory drugs) may experience altered inflammatory status, influencing PTS outcomes. Future research should incorporate comprehensive dietary assessments, environmental exposures, and medication usage into prospective study designs to enhance prognostic accuracy.

Conclusion

The CONUT score comprehensively assesses the patient’s nutritional status and is an independent predictor of postthrombotic syndrome. Clinicians should use the CONUT score to screen for malnourished patients and provide appropriate nutritional support to reduce PTS.

The CONUT score is an independent predictor of PTS in patients with lower extremity DVT, with a threshold of 7 indicating a marked increase in risk. Beyond this threshold, the risk plateaus, suggesting diminishing returns of further nutritional decline on PTS development. This underscores the importance of early identification and intervention for at-risk patients. Routine use of the CONUT score in clinical practice can guide targeted nutritional support and potentially mitigate PTS risk.

Data availability

No datasets were generated or analysed during the current study.

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Funding

This work was financially supported by the Natural Science Foundation of Zhejiang Province, China (No. LBY23H180003) and the Medical and Health Technology of Zhejiang Province (No. 2023KY1058,2024KY1546).

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Author notes

  1. Shanhong Lin and Ning Zhu contributed equally to this work.

Authors and Affiliations

  1. Department of Ultrasound, The First Affiliated Hospital of Ningbo University, 59 Liuting Road, Ningbo, 315010, Zhejiang, China

    Shanhong Lin & Shengmin Zhang

  2. Department of Respiratory and Critical Care Medicine, Key Laboratory of Respiratory Disease of Ningbo, The First Affiliated Hospital of Ningbo University, Ningbo, China

    Ning Zhu

Authors
  1. Shanhong Lin
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  2. Ning Zhu
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  3. Shengmin Zhang
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Contributions

S.L. and N.Z.: conceptualization, data curation, formal analysis, investigation, methodology, project administration, resources, supervision, validation, visualization, writing–original draft, writing–review & editing.S.Z.: conceptualization, formal analysis, investigation, methodology, project administration, resources, supervision, validation, visualization, writing–original draft, writing–review & editing. All authors reviewed the manuscript.

Corresponding author

Correspondence to Shengmin Zhang.

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Ethics approval and consent to participate

This study was approved by the medical ethics committee of First Affiliated Hospital of Ningbo University (NO.2024-075RS). The investigations were carried out following the rules of the Declaration of Helsinki. The requirement for written informed consent was exempted because of the retrospective nature.

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The authors declare no competing interests.

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Lin, S., Zhu, N. & Zhang, S. The role of controlling nutritional status score in predicting postthrombotic syndrome in patients with lower extremity deep venous thrombosis. Thrombosis J 23, 19 (2025). https://doiorg.publicaciones.saludcastillayleon.es/10.1186/s12959-025-00701-3

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  • DOI: https://doiorg.publicaciones.saludcastillayleon.es/10.1186/s12959-025-00701-3

Keywords

Thrombosis Journal

ISSN: 1477-9560

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