The association between thrombotic and inflammatory biomarkers and lower-extremity peripheral artery disease

A systematic review of the neutrophil to lymphocyte and platelet to lymphocyte ratios in patients with lower extremity arterial disease

Lower extremity arterial disease (LEAD) is caused by atherosclerotic plaque in the arterial supply to the lower limbs. The neutrophil to lymphocyte and platelet to lymphocyte ratios (NLR, PLR) are established markers of systemic inflammation which are related to inferior outcomes in multiple clinical conditions, though remain poorly described in patients with LEAD. This review was carried out in accordance with PRISMA guidelines. The MEDLINE database was interrogated for relevant studies. Primary outcome was the prognostic effect of NLR and PLR on clinical outcomes following treatment, and secondary outcomes were the prognostic effect of NLR and PLR on disease severity and technical success following revascularisation. There were 34 studies included in the final review reporting outcomes on a total of 19870 patients. NLR was investigated in 21 studies, PLR was investigated in two studies, and both NLR & PLR were investigated in 11 studies. Relating to increased levels of systemic inflammation, 20 studies (100%) reported inferior clinical outcomes, 13 (92.9%) studies reported increased disease severity, and seven (87.5%) studies reported inferior technical results from revascularisation. The studies included in this review support the role of elevated NLR and PLR as key components influencing the clinical outcomes, severity, and success of treatment in patients with LEAD. The use of these easily accessible, cost effective and routinely available markers is supported by the present review.

Construction of a novel lower-extremity peripheral artery disease subtype prediction model using unsupervised machine learning and neutrophil-related biomarkers

Lower-extremity peripheral artery disease (LE-PAD) is a prevalent circulatory disorder with risks of critical limb ischemia and amputation. This study aimed to develop a prediction model for a novel LE-PAD subtype to predict the severity of the disease and guide personalized interventions. Additionally, LE-PAD pathogenesis involves altered immune microenvironment, we examined the immune differences to elucidate LE-PAD pathogenesis. A total of 460 patients with LE-PAD were enrolled and clustered using unsupervised machine learning algorithms (UMLAs). Logistic regression analyses were performed to screen and identify predictive factors for the novel subtype of LE-PAD and a prediction model was built. We performed a comparative analysis regarding neutrophil levels in different subgroups of patients and an immune cell infiltration analysis to explore the associations between neutrophil levels and LE-PAD. Through hematoxylin and eosin (H&E) staining of lower-extremity arteries, neutrophil infiltration in patients with and without LE-PAD was compared. We found that UMLAs can helped in constructing a prediction model for patients with novel LE-PAD subtypes which enabled risk stratification for patients with LE-PAD using routinely available clinical data to assist clinical decision-making and improve personalized management for patients with LE-PAD. Additionally, the results indicated the critical role of neutrophil infiltration in LE-PAD pathogenesis.

The prognostic value of preoperative systemic inflammation-based scoring in patients undergoing endovascular repair of abdominal aortic aneurysm

OBJECTIVE

Abdominal aortic aneurysm (AAA) is a common condition that is predominantly managed in the United Kingdom by endovascular aneurysm repair (EVAR). Activation of the systemic inflammatory response (SIR) appears to offer prognostic value in patients with vascular disease. The present study examines the relationship between the SIR and survival in patients undergoing standard and complex endovascular aneurysm repair (EVAR and fenestrated/branched [F/B]-EVAR).

METHODS

Consecutive patients undergoing elective EVAR and F/B-EVAR were retrospectively identified from three tertiary vascular centers over a 5-year period. Neutrophil:lymphocyte ratio and modified Glasgow Prognostic Score were calculated from preoperative blood results and combined into the systemic inflammatory grade (SIG). The primary outcome was all-cause mortality during the follow-up period, which was compared between subgroups of SIGs.

RESULTS

There were 506 patients included in the final study, with a median follow-up of 68.0 months (interquartile range, 27.3 months), and there were 163 deaths during the follow-up period. Mean survival in the SIG 0 vs SIG 1 vs SIG 2 vs SIG 3 vs SIG 4 subgroups was 80.7 months (95% confidence interval [CI], 76.5-85.0 months) vs 78.7 months (95% CI, 72.7-84.7 months) vs 61.0 months (95% CI, 51.1-70.8 months) vs 65.1 months (95% CI, 45.0-85.2 months) vs 54.9 months (95% CI, 34.4-75.3 months) (P < .05). In the entire cohort, age (P < .001), body mass index (P < .05), high creatinine (P < .05), and SIG (P < .05) were associated with survival on univariate analysis, with retained independent association for age (hazard ratio, 1.72; 95% CI, 1.29-2.31; P < .001) and SIG (hazard ratio, 1.20; 95% CI, 1.02-1.40; P < .05) on multivariate analysis. Increasing SIG (area under the curve, 0.68; 95% CI, 0.58-0.78; P < .01) predicted 1-year mortality.

CONCLUSIONS

Markers of the SIR such the SIG may be used to identify patients at higher risk of adverse outcome in patients undergoing EVAR and F/B-EVAR for abdominal aortic aneurysms. These findings warrant further investigation in large prospective cohort studies.

Application of machine learning algorithms in electronic medical records to predict amputation-free survival after first revascularization in patients with peripheral artery disease

BACKGROUND

This study aimed to apply eight machine learning algorithms to develop the optimal model to predict amputation-free survival (AFS) after first revascularization in patients with peripheral artery disease (PAD).

METHODS

Among 2130 patients from 2011 to 2020, 1260 patients who underwent revascularization were randomly assigned to training set and validation set in an 8:2 ratio. 67 clinical parameters were analyzed by lasso regression analysis. Logistic regression, gradient boosting machine, random forest, decision tree, eXtreme gradient boosting, neural network, Cox regression, and random survival forest (RSF) were applied to develop prediction models. The optimal model was compared with GermanVasc score in testing set comprising patients from 2010.

RESULTS

The postoperative 1/3/5-year AFS were 90%, 79.4%, and 74.1%. Age (HR:1.035, 95%CI: 1.015-1.056), atrial fibrillation (HR:2.257, 95%CI: 1.193-4.271), cardiac ejection fraction (HR:0.064, 95%CI: 0.009-0.413), Rutherford grade ≥ 5 (HR:1.899, 95%CI: 1.296-2.782), creatinine (HR:1.03, 95%CI: 1.02-1.04), surgery duration (HR:1.03, 95%CI: 1.01-1.05), and fibrinogen (HR:1.292, 95%CI: 1.098-1.521) were independent risk factors. The optimal model was developed by RSF algorithm, with 1/3/5-year AUCs in training set of 0.866 (95% CI:0.819-0.912), 0.854 (95% CI:0.811-0.896), 0.844 (95% CI:0.793-0.894), in validation set of 0.741 (95% CI:0.580-0.902), 0.768 (95% CI:0.654-0.882), 0.836 (95% CI:0.719-0.953), and in testing set of 0.821 (95%CI: 0.711-0.931), 0.802 (95%CI: 0.684-0.919), 0.798 (95%CI: 0.657-0.939). The c-index of the model outperformed GermanVasc Score (0.788 vs 0.730). A dynamic nomogram was published on shinyapp (https://wyy2023.shinyapps.io/amputation/).

CONCLUSION

The optimal prediction model for AFS after first revascularization in patients with PAD was developed by RSF algorithm, which exhibited outstanding prediction performance.

The Role of Neutrophils in Lower Limb Peripheral Artery Disease: State of the Art and Future Perspectives

In recent years, increasing attention has been paid to the role of neutrophils in cardiovascular (CV) disease (CVD) with evidence supporting their role in the initiation, progression, and rupture of atherosclerotic plaque. Although these cells have long been considered as terminally differentiated cells with a relatively limited spectrum of action, recent research has revealed intriguing novel cellular functions, including neutrophil extracellular trap (NET) generation and inflammasome activation, which have been linked to several human diseases, including CVD. While most research to date has focused on the role of neutrophils in coronary artery and cerebrovascular diseases, much less information is available on lower limb peripheral artery disease (PAD). PAD is a widespread condition associated with great morbidity and mortality, though physician and patient awareness of the disease remains low. To date, several studies have produced some evidence on the role of certain biomarkers of neutrophil activation in this clinical setting. However, the etiopathogenetic role of neutrophils, and in particular of some of the newly discovered mechanisms, has yet to be fully elucidated. In the future, complementary assessment of neutrophil activity should improve CV risk stratification and provide personalized treatments to patients with PAD. This review aims to summarize the basic principles and recent advances in the understanding of neutrophil biology, current knowledge about the role of neutrophils in atherosclerosis, as well as available evidence on their role of PAD.

Relationship between serum homocysteine, fibrinogen, lipoprotein-a level, and peripheral arterial disease: a dose-response meta-analysis

AIM

At present, the relationship between serum homocysteine (Hcy), fibrinogen (FIB), lipoprotein-a (LPa), and PAD is uncertain, and there has been no meta-analysis to establish the dose-response relationship between their exposure levels and PAD.

METHODS AND RESULTS

Relevant literature published in PubMed, Embase, and Web of Science was retrieved. The robust error meta-regression method was used to assess the linear and non-linear dose-response relationship between exposure level and PAD risk. A total of 68 articles, involving 565,209 participants, were included. Combined with continuous variables, the serum Hcy, FIB, and LPa levels of PAD patients were significantly higher than those of healthy individuals. The odds ratios (ORs) of PAD for individuals with high Hcy, FIB, and LPa levels compared with those with low levels were 1.47, 1.14, and 1.76, respectively. The study also showed that circulating Hcy, FIB, and LPa were significantly elevated in patients with PAD compared with controls. The level of Hcy and the risk of PAD presented a U-shaped distribution. The nonlinear dose-response model showed that each 1 μmol/L increase in serum Hcy increased the risk of PAD by 7%. Similarly, for each 10 mg/dL FIB and 10 mg/dL LPa increases, the risk of PAD increased by 3% and 6%, respectively.

CONCLUSIONS

This meta-analysis provided evidence that elevated Hcy, PIB, and LPa levels may increase the risk of PAD, and the risk of PAD increases with the increase in serum exposure within a certain range. By controlling Hcy level, the incidence of PAD may be reduced to control the PAD growing epidemic.

TRIAL REGISTRATION NUMBER

PROSPERO (CRD42021250501), https://www.crd.york.ac.uk/prospero/.

A Prediction Model Based on Blood Biomarker for Mortality Risk in Patients with Acute Venous Thromboembolism

Background

Most studies to date have focused on predicting the risk of venous thromboembolism (VTE), but prediction models about mortality risk in VTE are rarely reported. We sought to develop and validate a multivariable model to predict the all-cause mortality risk in patients with acute VTE in emergency settings.

Methods

A total of 700 patients were included from Qilu Hospital of Shandong University and were randomly assigned into training set (n=490) and validation set (n=210) in an 7:3 ratio. Multivariate logistics regression analysis was performed to identify independent variables and develop a prediction model, which was validated internally using bootstrap method. The discrimination, calibration and clinical utility were evaluated by receiver operating characteristic curve (ROC) analysis, Hosmer-Lemeshow (HL) test, Kaplan-meier (KM) analysis and decision curve analysis (DCA).

Results

There were 52 patients (10.6%) dying and 437 (89.4%) surviving in training set. Age (odds ratio [OR]: 4.158, 95% confidence interval [CI]: 2.426–7.127), pulmonary embolism (OR: 1.779, 95% CI: 1.124–2.814), platelet count (OR: 0.507, 95% CI: 0.310–0.830), D-dimer (OR: 1.826, 95% CI: 1.133–2.942) and platelet/lymphocyte ratio (OR: 2.166, 95% CI: 1.259–3.727) were independent risk variables associated with all-cause mortality. The model had good predictive capability with an AUC of 0.746 (95% CI: 0.668,0.825), a sensitivity of 0.769 (95% CI: 0.607,0.889), a specificity of 0.672 (95% CI: 0.634,0.707). The validation model had an AUC of 0.739 (95% CI: 0.685,0.793), a sensitivity of 0.690 (95% CI: 0.580,0.787), a specificity of 0.693 (95% CI: 0.655,0.729). The model is well calibrated and the HL test showed a good fit (χ²=5.291, p=0.726, Nagelkerke R²=0.137). KM analysis and DCA showed a good clinical utility of the nomogram.

Conclusion

This study identified independent variables affecting all-cause mortality in patients with acute VTE, and developed a prediction model and provided a nomogram with good prediction capability and clinical utility.

Subunits of C1Q Are Associated With the Progression of Intermittent Claudication to Chronic Limb-Threatening Ischemia

Background

The pathophysiological mechanisms of intermittent claudication (IC) progression to chronic limb-threatening ischemia (CLTI) are still vague and which of patients with IC will become CLTI are unknown. This study aimed to investigate the key molecules and pathways mediating IC progression to CLTI by a quantitative bioinformatic analysis of a public RNA-sequencing database of patients with peripheral artery disease (PAD) to screen biomarkers discriminating IC and CLTI.

Methods

The GSE120642 dataset was downloaded from the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) between IC and CLTI tissues were analyzed using the “edgeR” packages of R. The Gene Ontology and the Kyoto Encyclopedia of Genes and Genomes enrichment analyses were performed to explore the functions of DEGs. Protein–protein interaction (PPI) networks were established by the Search Tool for the Retrieval of Interacting Genes (STRING) database and visualized by Cytoscape software. Hub genes were selected by plugin cytoHubba. Gene set enrichment analysis was performed and the receiver operating characteristic curves were used to evaluate the predictive values of hub genes.

Results

A total of 137 upregulated and 21 downregulated DEGs were identified. Functional enrichment clustering analysis revealed a significant association between DEGs and the complement and coagulation cascade pathways. The PPI network was constructed with 155 nodes and 105 interactions. The most significantly enriched pathway was complement activation. C1QB, C1QA, C1QC, C4A, and C1R were identified and validated as hub genes due to the high degree of connectivity. The area under the curve values for the five hub genes were greater than 0.95, indicating high accuracy for discriminating IC and CLTI.

Conclusion

The complement activation pathway is associated with IC progression to CLTI. C1QB, C1QA, C1QC, C4A, and C1R might serve as potential early biomarkers of CLTI.

The Role of Circulating Biomarkers in Peripheral Arterial Disease

Peripheral arterial disease (PAD) of the lower extremities is a chronic illness predominantly of atherosclerotic aetiology, associated to traditional cardiovascular (CV) risk factors. It is one of the most prevalent CV conditions worldwide in subjects >65 years, estimated to increase greatly with the aging of the population, becoming a severe socioeconomic problem in the future. The narrowing and thrombotic occlusion of the lower limb arteries impairs the walking function as the disease progresses, increasing the risk of CV events (myocardial infarction and stroke), amputation and death. Despite its poor prognosis, PAD patients are scarcely identified until the disease is advanced, highlighting the need for reliable biomarkers for PAD patient stratification, that might also contribute to define more personalized medical treatments. In this review, we will discuss the usefulness of inflammatory molecules, matrix metalloproteinases (MMPs), and cardiac damage markers, as well as novel components of the liquid biopsy, extracellular vesicles (EVs), and non-coding RNAs for lower limb PAD identification, stratification, and outcome assessment. We will also explore the potential of machine learning methods to build prediction models to refine PAD assessment. In this line, the usefulness of multimarker approaches to evaluate this complex multifactorial disease will be also discussed.

The association between thrombotic and inflammatory biomarkers and lower-extremity peripheral artery disease

Lower-extremity peripheral artery disease (LEAD) is associated with increased rates of mortality and morbidity. The aim of this study was to evaluate the associations among inflammatory and thrombotic markers and lower-extremity peripheral disease. A total of 280 patients were enrolled in this study. Of these patients, 152 patients had LEAD on peripheral angiography that was performed because of suspected lower-extremity peripheral disease based on history, physical examination, and non-invasive tests. The control group consisted of 128 patients without LEAD on peripheral angiography. Patients with LEAD were classified according to trans-atlantic inter-society consensus (TASC) II classification. Subsequently, patients in TASC A to B were defined as having mild to moderate peripheral artery disease, and those in TASC C to D were defined as having advanced peripheral artery disease. Thrombotic and inflammatory markers, such as the neutrophil-to-lymphocyte ratio (NLR), the high-sensitivity C (hs-C) reactive protein level, the monocyte-to-high-density lipoprotein-cholesterol ratio, the fibrinogen to albumin ratio (FAR), and whole-blood viscosity at high shear rate (HSR) and low shear rate (LSR), were evaluated in this population. The NLR, the monocyte-to-high-density lipoprotein-cholesterol ratio, the FAR, and whole-blood viscosity, both at a LSR and a HSR, were significantly higher in patients with lower-extremity peripheral disease compared with patients without lower-extremity peripheral disease. We determined that lower-extremity peripheral disease severity was correlated with the NLR, monocyte-to-high-density lipoprotein-cholesterol ratio, FAR, whole-blood viscosity at LSR, and whole-blood viscosity at HSR (r = 0.719, P = .004; r = 0.25, P = .008; r = 0.691, P = .002; r = 0.546, P < .001; and r = 0.448, P = .001, respectively). However hs-C reactive protein levels were similar between patients with or without LEAD (2.47 ± 1.32 1.61 ± 0.91 P = .685). In addition, there was no correlation between the severity of LEAD and hs-C reactive levels. In this study, we determined that the levels of inflammatory and thrombotic biomarkers are elevated in peripheral artery disease, and these levels predict disease severity.