Abstract
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.
Keywords: biomarkers, lower extremity, peripheral artery disease
1. INTRODUCTION
Lower‐extremity peripheral artery disease (LEAD) is associated with significant cardiovascular mortality and morbidity. 1 The true prevalence of LEAD in the general population is unknown, likely because of the asymptomatic nature of the disease and the insufficiency of screening methods. However, the reported prevalence of LEAD in people between 55 and 70 years of age is 4% to 25% and as high as 30% in people over 70 years old. 2 The trans‐atlantic inter‐society consensus II (TASC II) classification is an internationally derived consensus definition that is used for the classification of LEAD according to the anatomical distribution and nature of lesions. 3 Therapy modalities are based on this classification.
The main cause of LEAD is atherosclerosis. Previous reports determined that inflammation and thrombosis play major roles in the pathogenesis of atherosclerosis. 4 , 5 The neutrophil‐to‐lymphocyte ratio (NLR), plasma high‐sensitivity C reactive protein (hs‐CRP) levels, and monocyte‐to‐high‐density lipoprotein‐cholesterol (HDL‐C) ratio (MHR) represent markers of inflammation, whereas the platelet‐to‐lymphocyte ratio (PLR), mean platelet volume (MPV), whole blood viscosity (WBV) at high shear rate (HSR) and low shear rate (LSR), and fibrinogen‐to‐albumin ratio (FAR) have been associated with both inflammation and thrombosis. 6 , 7 , 8 , 9 , 10 In addition, data showed that elevated inflammatory marker levels are associated with poor outcomes in LEAD patients. 11 However, data about the associations of inflammatory and thrombotic markers with the severity of LEAD are scarce. In this cross‐sectional study, we evaluated the relationships between LEAD severity and inflammatory and thrombotic biomarkers.
2. METHODS
2.1. Patients
From March 2014 to December 2018, 168 patients who underwent peripheral angiography at our clinics because of suspected LEAD after physical examination, history, and non‐invasive tests were screened, and 152 patients were enrolled in our cross‐sectional retrospective study. The control group consisted of 128 patients without LEAD on peripheral angiography. Patients with a recent history of myocardial infarction and/or decompensated heart failure, a history of previous peripheral artery revascularisation, acute or chronic infection, malignant disease, autoimmune disease, advanced renal disease (estimated glomerular filtration rate <30 mL/min/1.73 m2), or use of anti‐inflammatory or immunosuppressive drugs were excluded. Sixteen patients were excluded according to these exclusion criteria.
The study protocol was approved by the local ethics committee, and written informed consent was obtained from all patients.
Demographic information was collected, and a physical examination was performed on each patient. Baseline two‐dimensional (2D) and Doppler echocardiographic (GE Vivid 7 Dimension ultrasound system, General Electric Company, Fairfield, Connecticut) examination was performed before the angiography procedure. The left ventricular ejection fraction, left ventricular diameters, right ventricular function, and valvular pathologies were evaluated.
Patients were considered to have hypertension if they had an elevated systolic blood pressure >140 mm Hg and/or a diastolic blood pressure >90 mm Hg on several occasions during their hospital stay, if they were diagnosed with hypertension, or if they were prescribed antihypertensive medications by a treating physician. Diabetes mellitus (DM) was defined according to the standard criteria of the American Diabetes Association as follows: a fasting serum glucose level >126 mg/dL, 2‐hour glucose level >200 mg/dL, or glycosylated haemoglobin value >6.5%. DM was also diagnosed in patients with a prior diagnosis of DM or those who were prescribed antidiabetic medications by a treating physician. Hyperlipidaemia (HL) was defined as total cholesterol ≥200 mg/dL or drug treatment for lipid abnormality. Coronary artery disease (CAD) was defined as a history of previous myocardial revascularisation and/or ≥50% stenosis in one or more major epicardial coronary arteries detected by a coronary angiogram. Patients who were cigarette smokers at admission or who were past smokers were considered smokers.
2.2. Peripheral angiography and TASC II classification
Peripheral angiography was performed via the right or left femoral or radial artery. Iodine‐containing radiopaque medium was administered via the distal abdominal aorta using a pigtail catheter or via the right or left common iliac artery, selectively using the right coronary artery catheter to examine the right‐left common iliac, iliac externa, iliac interna, main femoral, superficial femoral, deep femoral, popliteal, tibioperoneal trunks, anterior tibial, and posterior tibial arteries up to the distal peroneal artery and from the aortoiliac bifurcation to the distal genicular arteries with only a single radiopaque injection. After the procedure, the patients with LEAD were classified according to TASC II classification. Subsequently, the 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. TASC II classification was performed on the basis of a previously published report. 3
2.3. Blood samples and laboratory analyses
Fasting blood samples for laboratory assessment were obtained before the peripheral angiography procedure using EDTA‐containing tubes.
In all patients, blood samples were drawn upon admission before starting any medication via atraumatic puncture of the antecubital vein. Dry tubes for biochemical tests and tubes with EDTA for the haematological test were used. The erythrocyte count, haemoglobin level, haematocrit, and white blood cell count were measured using an automated Coulter Counter LH Series haematology analyser (Beckman Coulter Inc., Hialeah, Florida). The biochemical measurements were determined using an automated chemistry analyser (Abbott Aeroset, Abbott Laboratories, Abbott Park, Illinois).
Absolute cell counts were used to perform the subsequent analyses. The NLR was obtained by dividing the neutrophil count by the absolute lymphocyte count. Fibrinogen levels were measured by the Clauss method using the BCS Analyzer (Multifibren U; Siemens Healthcare, Erlangen, Germany). The FAR was calculated at admission as the ratio of the fibrinogen level to the albumin level.
The eGFR was calculated using the Modification of Diet in Renal Disease formula.
WBV was calculated from the haematocrit (HTC) (%) and plasma protein concentration (TP; g/L) at a LSR (0.5 seconds−1) and a HSR (208 seconds−1) using the validated formula 12 , 13 —HSR: WBV (208 seconds−1) = (0.12 × HCT) + 0.17 × (TP − 2.07); LSR: WBV (0.5 seconds−1) = (1.89 × HCT) + 3.76 × (TP − 78.42).
The hs‐CRP was measured using a latex‐enhanced immunonephelometer (Dade Behring; Netwark, DE).
2.4. Statistics
Statistical analyses were performed using IBM SPSS Statistics 22.0 statistical software (IBM Corporation, Armonk, New York). The continuous variables were described as the mean ± SD, whereas the discrete variables were reported as the frequency and percentage. The Kolmogorov‐Smirnov test was used to test the normality of a distribution. The χ 2 test or Fisher's exact test was used to compare categorical variables between two groups. For the continuous parameters, the Mann‐Whitney test or Student's t‐test was used to compare the differences between two independent groups. Analysis of variance was used to compare multiple variables with normal distributions, and Tukey's test was used for the post hoc analysis. Spearman's correlation analysis was used to analyse the correlations of the TASC II classes. Multiple binary logistic regression analysis was performed to find the independent predictors of the TASC II classes. Univariate logistic regression models were first used to evaluate the crude associations between the TASC II classes and possible confounding factors. The factors that exhibited a significant association with a P value <.1 were tested in multivariate logistic regression analysis. A P value <.05 was accepted as statistically significant.
3. RESULTS
The study population included 280 patients who underwent peripheral angiography. Figure 1 demonstrates the distribution of the LEAD patients according to the TASC II classification. Afterward, these LEAD patients were stratified into two groups according to their TASC II scores; TASC A to B patients were categorised as mild to moderate LEAD patients (n = 89), and TASC B to C patients were categorised as advanced LEAD patients (n = 63).
FIGURE 1.
The distribution of the lower‐extremity peripheral artery disease patients according to the trans‐atlantic inter‐society consensus II classification
The clinical and demographic characteristics of the study population are given in Table 1. The patients with LEAD were older than the patients without LEAD (69.01 ± 11.13 vs 58.13 ± 12.78, respectively, P = .038). There was also a significant difference between the LEAD (+) and (−) patients in terms of smoking status and DM and HL incidences.
TABLE 1.
Demographic and basal characteristics of study population
| Variable | LEAD (+) n = 152 | LEAD (−) n = 128 | P value |
|---|---|---|---|
| Age, y | 69.01 ± 11.13 | 58.13 ± 12.78 | .038 |
| Male, n% | 126 (82.90) | 86 (67.18) | .653 |
| BMI, kg/m2 | 22.35 ± 3.51 | 22.18 ± 2.74 | .892 |
| Smoking, n% | 112 (73.70) | 41 (32.03) | <.001 |
| CAD, n% | 81 (53.28) | 36 (28.12) | <.001 |
| HT, n% | 78 (51.31) | 65 (50.78) | .642 |
| HL, n% | 58 (38.15) | 36 (28.12) | .040 |
| DM, n% | 59 (38.81) | 32 (25.00) | .008 |
| Medication, n% | |||
| Antidiabetic | 48 (31.57) | 22 (17.18) | .580 |
| Statin | 42 (27.63) | 15 (11.71) | .060 |
| ASA | 98 (64.4) | 68 (53.12) | .388 |
| ACEi/ARB | 62 (40.78) | 46 (35.93) | .120 |
| Cilastozol | 18 (11.84) | 9 (7.03) | .152 |
| Pentoxifylin | 5 (3,28) | 3 (2.34) | .610 |
| LVEF,% | 58.42 ± 12.36 | 59.32 ± 8.3 | .963 |
| eGFR, mL/min/1.73m2 | 76.38 ± 14.17 | 83.14 ± 19.87 | .759 |
| Neutrophil x103/μL | 4.86 ± 0.69 | 3.82 ± 0.32 | .040 |
| Lymphocyte x103/μL | 1.30 ± 0.19 | 1.12 ± 0.02 | .066 |
| NLR | 4.38 ± 0.97 | 3.19 ± 0.21 | .027 |
| LDL, mg/dL | 146.78 ± 58.42 | 138.91 ± 43.87 | .080 |
| Monocyte x103/μL | 0.42 ± 0.88 | 0.26 ± 0.19 | .030 |
| HDL, mg/dL | 42.31 ± 1.74 | 41.89 ± 0.75 | .565 |
| MHR | 11.15 ± 2.97 | 8.56 ± 1.95 | .021 |
| Fibrinogen, mg/dL | 359.80 ± 72.30 | 289.26 ± 36.89 | .018 |
| Albumin, mg/dL | 3.23 ± 0.62 | 4.56 ± 1.29 | .001 |
| FAR | 66.38 ± 9.16 | 32.16 ± 7.32 | .003 |
| Hs‐CRP, mg/L | 2.47 ± 1.32 | 1.61 ± 0.91 | .685 |
| Platelet x103/μL | 284.11 ± 32.16 | 286.65 ± 12.87 | .386 |
| MPV | 9.21 ± 0.80 | 8.98 ± 1.24 | .045 |
| WBV at LSR | 77.36 ± 18.11 | 57.49 ± 9.37 | .001 |
| WBV at HSR | 26.35 ± 5.18 | 16.12 ± 3.10 | .001 |
| Hb, g/dL | 13.9 ± 1.10 | 14.30 ± 1.12 | .248 |
| Htc, % | 41.18 ± 4.17 | 42.26 ± 3.65 | .651 |
| TP, g/L | 69.16 ± 4.52 | 72.18 ± 4.46 | .072 |
| ABI | 0.82 ± 0.11 | 1.05 ± 0.27 | .001 |
Abbreviations: ABI, ankle brachial index; ACE i/ARB, angiotensin‐converting enzyme inhibitors/angiotensin receptor blockers; ASA, acetylsalicylic acid; BMI, body mass index; CAD, coronary artery disease; DM, diabetes mellitus; eGFR, estimated glomerular filtration rate; FAR, fibrinogen‐to‐albumin ratio; Hb, haemoglobin; HDL, high‐density lipoprotein; HL, hyperlipidaemia; Hs‐CRP, high sensitive C reactive protein; HSR, high shear rate; HT, hypertension; Htc, haematocrit; LDL, low‐density lipoprotein; LEAD, lower‐extremity peripheral artery disease; LSR, low shear rate; LVEF, left ventricular ejection fraction; MHR, monocyte‐to‐high‐density lipoprotein cholesterol ratio; MPV, mean platelet volume; NLR, neutrophil‐to‐lymphocyte ratio; TP, serum total protein; WBV, whole‐blood viscosity.
The NLR, MHR, FAR, WBVs at LSR and HSR, and MPV were higher in the patients with LEAD than the patients without LEAD (4.38 ± 0.97 vs 3.19 ± 0.21, P = .027; 11.15 ± 2.97 vs 8.56 ± 1.95, P = .021; 66.38 ± 9.16 vs 32.16 ± 7.32, P = .003; 77.36 ± 18.11 vs 57.49 ± 9.37, P = .001; 26.35 ± 5.18 vs 16.12 ± 3.10, P = .001; and 9.21 ± 0.80 vs 8.98 ± 1.24, P = .045, respectively.). The percentages of patients with hyperlipidaemia and smokers were significantly higher in patients with LEAD compared with those without LEAD.
When we compared the patients with LEAD according to the TASC classification, we determined that, compared with the TASC A to B patients, the patients with TASC C‐D disease were older and had a significantly higher incidence of DM (Table 2). There were no differences between the TASC A to B and TASC C to D groups with respect to HL and smoking status (31.46% vs 47.61%, P = .221, and 71.91% vs 76.19%, P = .128, respectively). Inflammatory and thrombotic parameters such as the NLR, MHR, FAR, WBVs at LSR and HSR, and MPV were significantly higher in the patients with TASC C to D disease than in the patients with TASC A to B disease. There was no difference in the hs‐CRP level between the groups (1.97 ± 1.43 vs 2.65 ± 0.38, respectively, P = .367).
TABLE 2.
Demographic and basal characteristics of patients according to trans‐atlantic inter‐society consensus (TASC) II class
| Variable | TASC A‐B n = 89 | TASC C‐D n = 63 | P value |
|---|---|---|---|
| Age, y | 58.32 ± 12.39 | 68.87 ± 10.96 | .006 |
| Male, n% | 68 (76.40) | 58(92.06) | .025 |
| BMI, kg/m2 | 22.16 ± 3.32 | 21.18 ± 5.49 | .248 |
| Smoking, n% | 64 (71.91) | 48 (76.19) | .128 |
| CAD, n% | 42 (47.19) | 39 (61.90) | .045 |
| HT, n% | 42 (47.19) | 36 (57.14) | .658 |
| HL, n% | 28 (31.46) | 30 (47.61) | .221 |
| DM, n% | 23 (25.84) | 36 (57.14) | .008 |
| Medication, n% | |||
| Antidiabetic | 26 (29.21) | 22 (34.92) | .245 |
| Statin | 23 (25.84) | 19 (30.15) | .125 |
| ASA | 50 (56.17) | 48 (76.19) | .141 |
| ACEi/ARB | 40(44.94) | 22 (34.92) | .958 |
| Cilastozol | 6 (6.74) | 12 (19.04) | .169 |
| Pentoxifylin | 1(1.12) | 4 (6.34) | .097 |
| LVEF, % | 59.38 ± 9.71 | 58.12 ± 7.61 | .483 |
| eGFR, mL/min/1.73m2 | 77.16 ± 10.95 | 76.11 ± 26.12 | .349 |
| Neutrophil x103/μL | 3.87 ± 0.26 | 4.93 ± 1.29 | .083 |
| Lymphocyte x103/μL | 1.11 ± 0.67 | 1.52 ± 1.09 | .190 |
| NLR | 3.36 ± 1.07 | 6.28 ± 0.59 | .002 |
| LDL, mg/dL | 128.39 ± 39.58 | 166.18 ± 41.11 | .059 |
| Monocyte x103/μL | 0.34 ± 0.31 | 0.56 ± 0.12 | .003 |
| HDL, mg/dL | 43.23 ± 2.38 | 42.53 ± 1.04 | .650 |
| MHR | 10.16 ± 2.7 | 14.46 ± 3.27 | .007 |
| Fibrinogen, mg/dL | 321.63 ± 56.39 | 452.19 ± 23.30 | .235 |
| Albumin, mg/dL | 3.86 ± 0.84 | 2.16 ± 0.54 | .054 |
| FAR | 58.42 ± 10.71 | 86.18 ± 9.08 | <.001 |
| Hs‐CRP, mg/L | 1.97 ± 1.43 | 2.65 ± 0.38 | .367 |
| Platelet x103/μL | 264.68 ± 28.37 | 289.78 ± 88.32 | .637 |
| MPV | 9.10 ± 1.34 | 9.21 ± 0.80 | .009 |
| WBV at LSR | 64.21 ± 12.16 | 87.46 ± 22.94 | .001 |
| WBV at HSR | 17.16 ± 8.23 | 26.35 ± 5.18 | .007 |
| Hb, g/dL | 14.28 ± 1.33 | 13.9 ± 1.10 | .549 |
| Htc, % | 42.80 ± 3.16 | 41.18 ± 4.17 | .117 |
| T.prt, g/L | 68.21 ± 5.87 | 69.16 ± 4.52 | .476 |
| ABI | 0.79 ± 0.18 | 0.85 ± 0.12 | .082 |
Abbreviations: ABI, ankle brachial index; ACE i/ARB, angiotensin‐converting enzyme inhibitors/angiotensin receptor blockers; ASA, acetylsalicylic acid; BMI, body mass index; CAD, coronary artery disease; DM, diabetes mellitus; eGFR, estimated glomerular filtration rate; FAR, fibrinogen‐to‐albumin ratio; Hb, haemoglobin; HDL, high‐density lipoprotein; HL, hyperlipidaemia; HSR, high shear rate; HT, hypertension; Htc, haematocrit; LDL, low‐density lipoprotein; LSR, low shear rate; LVEF, left ventricular ejection fraction; MHR, monocyte‐to‐high‐density lipoprotein cholesterol ratio; MPV, mean platelet volume; NLR, neutrophil‐to‐lymphocyte ratio; T.prt, total protein; WBV, whole‐blood viscosity.
We also determined that NLR, MHR, FAR, and WBVs at LSR and HSR increased significantly with increasing TASC II class (Figure 2).
FIGURE 2.
A, A box pilot showing the neutrophil‐to‐lymphocyte ratio according to trans‐atlantic inter‐society consensus (TASC) II class. B, A box pilot showing the monocyte‐to‐high‐density lipoprotein‐cholesterol ratio according to TASC II class. C, A box pilot showing the fibrinogen‐to‐albumin ratio according to TASC II class. D, A box pilot showing the whole‐blood viscosity at high shear rate according to TASC II class. E, A box pilot showing the whole‐blood viscosity at low shear rate according to TASC II class
Correlation analysis showed that the TASC II class was significantly and positively correlated with the NLR, MHR, FAR, and WBVs at LSR and HSR (Table 3).
TABLE 3.
Results of correlation analysis
| Variable | r | Odds ratio (95% confidence interval) | P value |
|---|---|---|---|
| NLR | 0.719 | 0.836 (0.659–1.236) | .004 |
| MHR | 0.257 | 0.637 (0.350–0.749) | .008 |
| FAR | 0.691 | 0.945 (0.724–1.168) | .002 |
| WBV at LSR | 0.546 | 0.721 (0.369–1.192) | <.001 |
| WBV at HSR | 0.448 | 0.643 (0.589–1694) | .001 |
Abbreviations: FAR, fibrinogen‐to‐albumin ratio; HSR, high shear rate; LSR, low shear rate; MHR, monocyte‐to‐high‐density lipoprotein cholesterol ratio; NLR, neutrophil‐to‐lymphocyte ratio; WBV, whole‐blood viscosity.
Multivariate regression analysis was used to determine the independent predictors of advanced LEAD using the parameters that were found to be associated with advanced LEAD in the univariate analyses (DM, smoking status, HL, NLR, MPV, MHR, FAR, WBV at LSR, and WBV at HSR). The NLR, DM, MHR, FAR, and WBV at LSR and at HSR were found to be independent predictors of advanced LEAD (Table 4).
TABLE 4.
Predictors of advanced LEAD
| Variables | Univariate odds ratio (95% confidence interval) | P value | Multivariate odds ratio (95% confidence interval) | P value |
|---|---|---|---|---|
| Age, y | 1.487 (1.125–1.988) | .960 | ||
| Gender (male) | 1.617 (0.917–2.346) | 1.160 | ||
| CAD | 1.281 (0.349–1.447) | .180 | ||
| DM | 0.852 (0.128–1.590) | .023 | 1.056 (0.376–1.359) | .004 |
| Smoking | 1.892 (0.849–2.217) | .035 | 0.739 (0,561–1.012) | .971 |
| HL | 0.123 (0.689–1.158) | .024 | 0.418 (0.342–1.118) | .864 |
| Platelet | 2.128 (1.239–2.480) | .139 | ||
| MPV | 1.524 (1.048–3.161) | .092 | 1.187 (0.946–1.327) | .568 |
| Neutrophil | 0.846 (0.542–1.274) | .179 | ||
| NLR | 2.079 (0.935–4.625) | .073 | 0.896 (0.845–0.950) | <.001 |
| LDL‐C | 0.184 (0.061–2.469) | .619 | ||
| MHR | 0.999 (0.473–2.109) | .998 | 1.043 (1.012–1.074) | .006 |
| FAR | 1.259 (0.126–2.743) | .089 | 1.196 (0.589–1.492) | .001 |
| Fibrinogen | 1.138 (0.942–2.117) | .170 | ||
| WBV at LSR | 1.002 (0.845–2.214) | .023 | 1.283 (0.746–1.940) | .008 |
| WBV at HSR | 0.896(0.289–1.547) | .009 | 1.089 (0.837–2.117) | .002 |
Abbreviations: DM, diabetes mellitus; FAR, fibrinogen‐to‐albumin ratio; HL, hyperlipidaemia; HSR, high shear rate; LEAD, lower‐extremity peripheral artery disease; LSR, low shear rate; MHR, monocyte‐to‐high‐density lipoprotein cholesterol ratio; MPV, mean platelet volume; NLR, neutrophil‐to‐lymphocyte ratio; WBV, whole‐blood viscosity.
Receiver operating characteristic (ROC) curve analysis showed that the cut‐off value of the NLR for the prediction of advanced LEAD was 4.25, with a sensitivity of 73.0% and a specificity of 78% (area under the curve = 0.811; 95% confidence interval [CI]: 0.732‐0.890; P < .001); the cut‐off value of the MHR for the prediction of advanced LEAD was 12.16, with a sensitivity of 74.6% and a specificity of 82.1% (area under the curve = 0.842; 95% CI: 0.618‐0.842; P < .001); the cut‐off value of the FAR for the prediction of advanced LEAD was 69.76, with a sensitivity of 72.4% and a specificity of 82.1% (area under the curve = 0.864%; 95% CI: 0.716‐0.839; P < .001); the cut‐off value of the WBV at LSR for the prediction of advanced LEAD was 71.84, with a sensitivity of 73.6% and a specificity of 68.8% (area under the curve = 0.896%; 95% CI: 0.419‐0.762; P < .001); and the cut‐off value of the WBV at HSR for the prediction of advanced LEAD was 20.76, with a sensitivity of 75.2% and a specificity of 70.9% (area under the curve = 0.814%; 95% CI: 0.642‐0.827; P < .001) (Figure 3).
FIGURE 3.
The receiver operating characteristic curves of neutrophil‐to‐lymphocyte ratio (NLR), monocyte‐to‐high‐density lipoprotein‐cholesterol ratio (MHR), fibrinogen‐to‐albumin ratio (FAR), and whole‐blood viscosity at high shear rate (WBVHSR) and low shear rate (WBVLSR) for predicting advanced peripheral artery disease
4. DISCUSSION
In this study, we found that markers of inflammation and thrombosis predict both the severity and the presence of LEAD. As expected and in consensus with those of similar studies, the data showed that patients with LEAD are older and have a higher prevalence of DM and HL than patients without LEAD. The patients with LEAD had a significantly higher NLR, MHR, FAR, and WBVs at LSR and HSR compared with the patients without LEAD. Moreover, the NLR, MHR, FAR, and WBVs at LSR and HSR were significantly correlated with the severity of LEAD. We determined that all these markers are independent predictors of advanced LEAD. Our study is the first to evaluate both inflammatory and thrombotic markers in LEAD.
LEAD affects approximately 10% to 25% of the general population, and its prevalence increases with increasing age. 14 , 15 LEAD is usually asymptomatic in the early and middle stages of the disease, and by the time symptoms are apparent, patients have advanced disease and/or critical limb ischaemia.
Previous studies have shown that there is a close relationship between the NLR and atherosclerosis. 16 , 17 , 18 It is clear that inflammation plays a pivotal role in the initiation and progression of atherosclerosis. As the main cause of LEAD is atherosclerosis, studies have also evaluated the association between the inflammation and LEAD. It was determined that critical limb ischaemia is more frequent in patients with a higher NLR (>3.95) compared with those with a lower NLR (≤ 3.95) (P < .001) (10). Tasoglu et al showed that an NLR ≥5.2 is an independent predictor of early and midterm amputation in patients with acute limb ischaemia. 19
In a prospective, observational follow up of 149 patients with chronic limb ischaemia or intermittent claudication, an elevated NLR was independently associated with a high probability of mortality. 20
Aykan et al demonstrated that the NLR is an independent predictor of TASC II‐classified LEAD. 21 They found that the NLR (OR: 1.91; 95% CI: 1.51‐2.41; P < .001) predicts higher TASC II class lesions. Our study results are consistent with their findings.
The MHR is a novel biomarker that has recently emerged as an indicator of inflammation. Studies have shown that MHR predicts the severity and prognosis of CAD. 7 , 22 Monocytes play an important role in atherosclerotic plaque accumulation. Circulating monocytes are components of innate immunity. They promote atherosclerotic plaque growth by producing inflammatory cytokines, MMPs, and reactive oxidative species. In contrast, HDL‐C has anti‐inflammatory and antioxidant effects. Thus, a higher MHR is a good predictor of cardiovascular events. Our study is the first in the literature to evaluate the role of the MHR in LEAD. We determined that the MHR is significantly higher in patients with LEAD than in those without LEAD. In addition, a higher MHR predicts the severity of LEAD.
The roles of serum albumin and fibrinogen in atherosclerosis are clear. Serum albumin has antioxidant and anti‐inflammatory properties, and fibrinogen has a pivotal role in thrombogenesis. 23 Higher serum fibrinogen levels are associated with vulnerable atherosclerotic plaque formation. Hypoalbuminaemia may cause aggravated ischaemia and reperfusion injuries. 24 Furthermore, it has been shown that hypoalbuminaemia is associated with a poor prognosis after infra‐inguinal lower‐extremity bypass for critical limb ischaemia. 25 However, there are less few data about the effectiveness of FAR to predict atherosclerotic endpoints. To the best of our knowledge, no previous study has evaluated the relationship between the FAR and LEAD. In our study, we determined that the FAR is associated with LEAD and that a cut‐off value of 69.76 predicts advanced LEAD.
WBV indicates the intrinsic resistance of whole blood to flow. It has an important influence on tissue perfusion and microcirculation. A high blood viscosity increases thromboembolic risk and is correlated with the presence of systemic inflammation. 26 Moreover, it has been shown that high blood viscosity is significantly associated with adverse cardiovascular outcomes. 27 Previous studies showed that there is a clear association between blood viscosity and LEAD. 28 , 29 Dormandy et al reported that mean high shear blood viscosity of LEAD patients (4.74 ± 0.54) was higher than controls (4.29 ± 0.49) (P < .001). 30 Lowe et al showed that blood viscosity was significantly associated with ankle brachial index after adjusting for other cardiovascular risk factors. 31 Similarly, in our study, we found that the WBV, both at LSR and at HSR, is significantly correlated with LEAD severity.
In our study, we did not find any relationship between serum hs‐CRP and LEAD. The patients with and without LEAD had similar hs‐CRP levels. Serum hs‐CRP is an important marker of inflammation, and previous studies have shown a relationship between serum hs‐CRP and atherosclerosis. 32 However, in our study, we did not identify an association between hs‐CRP and LEAD. We do not have a clear explanation for these results. However, the atherosclerotic process of LEAD may be different from that of CAD. Further studies are needed to confirm this hypothesis.
Our study may have important clinical implications. These simple, cheap, and readily detectable inflammatory and thrombotic markers could help identify individuals at risk of advanced LEAD. A new classification of LEAD severity using these markers may improve the clinical course of LEAD. Further studies are needed to evaluate the effect of the addition of these markers to conventional classification systems based on the LEAD disease course.
4.1. Limitations
Our study has several limitations. First, this is a retrospective study; second, the number of the study populations is limited; and third, we used only the TASC II classification. Unlike the Fontaine classification, which uses clinical symptoms, the TASC II classification is based on angiograms. However, the TASC II classification is widely used in clinical decision‐making for the management of LEAD. This is associated with the retrospective nature of our study.
Celebi S, Berkalp B, Amasyali B. The association between thrombotic and inflammatory biomarkers and lower‐extremity peripheral artery disease. Int Wound J. 2020;17:1346–1355. 10.1111/iwj.13407
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