Patients and methods: This case-control study was conducted with 162 individuals (107 males, 55 females; mean age: 52.5±13.7 years; range, 24 to 87) between January 2023 to January 2024. Eighty-seven of these participants were diagnosed with PAD by lower extremity color Doppler ultrasonography and computed tomography angiography, and the remaining 75 were healthy individuals. Biochemical results of patients and control groups were examined.

Results: Comparing the groups, statistical significance (p<0.05) was found according to sex, age, hypertension, diabetes mellitus, smoking, blood glucose levels, blood creatinine levels, estimated glomerular filtration rate, high-density lipoprotein, triglyceride, fibrinogen, white blood cell count, and C-reactive protein levels. In the group of PAD patients, male sex, hypertension, diabetes mellitus, and smoking were more prevalent, along with higher levels of glucose, creatinine, triglyceride, fibrinogen, white blood cell count, and C-reactive protein.

Conclusion: Inflammation biomarkers, such as fibrinogen and C-reactive protein, were found to be significantly higher in the PAD group, indicating that the low-grade inflammation hypothesis may play a role in PAD. Large-scale, prospective, randomized controlled studies on this subject are needed.

Statistical analysis
A power analysis was calculated according to creatinine levels using G*Power version 3.1.9.7 (Heinrich-Heine-Universität Düsseldorf, Düsseldorf, Germany). A power of 87% was found according to n1=75 (0.82±0.34), n2=87 (1.16±0.83), alpha=0.05, and effect size (d)=0.49.

Data were analyzed using IBM SPSS version 27.0 (IBM Corp., Armonk, NY, USA) and MedCalc version 15.8 (MedCalc Software, Ostend, Belgium). While evaluating the data, in addition to descriptive statistical methods (frequency, percentage, mean, standard deviation, median, minimum-maximum, and interquartile range), the chi-square test was used to compare qualitative data. The suitability of the data for normal distribution was evaluated with the Kolmogorov-Smirnov test, skewness-kurtosis, and graphical methods (histograms, Q-Q plots, stem-and-leaf plots, and boxplots). In this study, for the evaluation of normally distributed quantitative data, the independent samples t-test was used. For the evaluation of data that did not show normal distribution, the Mann-Whitney U test was used. Receiver operating characteristic curves were used to determine the distinctiveness of the variables, and binary logistic regression was used to determine risk ratios. The level of statistical significance was set at p<0.05.

Table 1: Demographic characteristics of the study participants

In the PAD group, it was found that the male sex, HT, DM, and smoking rates were higher, along with older age and higher levels of fasting blood glucose, creatinine, triglyceride, fibrinogen, WBCs, and CRP (Table 2). There was no statistically significant difference between the groups in terms of other variables (p>0.05). Variables that were considered to be more clinically significant and did not have a high correlation between the variables that showed differences in pairwise comparisons between groups (sex, age, HT, DM, smoking, glucose, creatinine, eGFR, HDL, triglyceride, fibrinogen, WBCs, monocytes, lymphocytes, platelets, and CRP) were included in the model. The backward stepwise method was used in the analysis, and the model was terminated at the ninth step. In this model, approximately 87% of the dependent variable (PAD group) could be explained (Nagelkerke R2=0.866). According to this model, there was a statistically significant relationship between PAD status and sex, age, glucose, creatinine, fibrinogen, monocytes, platelets, and CRP (p<0.05; Table 3).

Table 2: Comparisons between groups

Table 3: Analysis with logistic regression

Peripheral Artery Disease (PAD) is approximately 21.52 times more prevalent in men. It is 1.07 times more common in individuals with higher age, 1.03 times more common in those with elevated glucose levels, and 0.34 times more frequent in those with increased creatinine levels. PAD is also 1.02 times more likely in individuals with higher fibrinogen levels, 1764.11 times more prevalent in those with elevated monocyte counts, 1.01 times more common in those with higher platelet counts, and 1.28 times more frequent in individuals with elevated CRP levels (Table 3). A prediction table was created according to the model. Eighty-two of 87 patients (94.3%) with PAD were predicted correctly, and 71 of 75 patients (94.7%) without PAD were predicted correctly. The overall accuracy rate was found to be 94.4% (Table 4). Variables that were considered to be more clinically significant and did not have a high correlation between the variables that showed differences in pairwise comparisons between groups (fibrinogen, WBC count, and CRP) were included in the model. The backward stepwise method was used in the analysis, and the model was finalized at the second step. Approximately 67% of the dependent variable (PAD group) could be explained in this model (Nagelkerke R2=0.665). According to this model, there was a statistically significant relationship between PAD status and fibrinogen and CRP values (p<0.05; Figures 1-5). Those with high fibrinogen values were approximately 1.02 times more likely to have PAD than those without, and those with high CRP values were approximately 1.18 times more likely to have PAD than those without (Table 5). A prediction table was created according to the created model. Eighty of 87 patients (92.0%) with PAD were predicted correctly, while 69 of 75 patients (92.0%) without PAD were predicted correctly. The overall accuracy rate was found to be 92.0% (Table 6).

Table 4: Real and predicted values according to the created model

Table 5: Evaluations with logistic regression

Table 6: Real and predicted values according to the created model

Figure 1: The range of distribution of fibrinogen values in the control and patient groups.

Figure 2: The range of distribution of CRP values in the study groups.

Figure 3: Fibrinogen blood levels in the patient and control groups.

Figure 4: C-reactive protein blood levels in the patient and control groups.
CRP: C-reactive protein.

Figure 5: White blood cell count blood levels in the patient and control groups.
WBC: White blood cell count.

As a result of the evaluations conducted using ROC analysis on the variables found to be different in pairwise comparisons. The cutoff points of different variables were as follows: fasting blood glucose, >110 mg/dL (area under the curve [AUC]=0.741, 95% confidence interval [CI]: 0.667-0.807, p<0.001); creatinine, >0.94 (AUC=0.731, 95% CI: 0.656-0.798, p<0.001); eGFR, ≤83 (AUC=0.803, 95% CI: 0.733-0.861, p<0.001); HDL, ≤43.8 (AUC=0.620, 95% CI: 0.540-0.695, p=0.007); triglycerides, >154.4 (AUC=0.661, 95% CI: 0.583-0.734, p<0.001); fibrinogen, >373 (AUC=0.923, 95% CI: 0.871- 0.959, p<0.001); monocytes, >0.51 (AUC=0.740, 95% CI: 0.665-0.805, p<0.001); and CRP, >4.76 (AUC=0.781, 95% CI: 0.709-0.842, p<0.001) (Table 7).

Table 7: Receiver operating characteristic analysis

One study demonstrated that HT is associated with lower-grade systemic inflammation indices in hypertrophic cardiomyopathy patients and that the adverse effect of HT in hypertrophic cardiomyopathy patients is a result of systemic effects rather than changes in cardiac function since left ventricular systolic and diastolic dysfunction measurements did not differ between hypertensive and normotensive patients.[16] In a review, it was stated that low-grade inflammation plays an important role in the relationship between the immune system and angiotensin II-induced HT.[17] It has been emphasized that monocyte/macrophage cells play an important role in vascular inflammation and interaction with the arterial wall throughout the progression of HT.[17] In our study, hypertension is statistically absent in 36% of patients with PAD (p<0.001; Table 2). One of the risk factors for PAH is dyslipidemia.[1] The risk of early atherosclerotic cardiovascular disease dramatically increases in patients with lipid disorders.[8] Recent studies have shown a definite link between systemic low-grade inflammation and obesity and dyslipidemia, with both disorders being associated with endothelial dysfunction/activation, a proinflammatory and prothrombotic state of the endothelium leading to the infiltration of leukocytes into the arterial wall.[18-20] In our study, the average triglyceride value in the PAD group was 161.60 mg/dL (98.70-243.40 mg/dL), with statistical significance (p<0.001; Table 2). Smoking, one of the other risk factors of PAD, is one of the most important preventable factors causing this disease.[1] Cigarette smoke extracts activate the NLRP3 inflammasome via reactive oxygen species, resulting in the downstream release of interleukin (IL)-1 beta, IL-18, and other inflammatory factors, leading to functional changes such as autophagy, pyrolysis, and apoptosis in endothelial cells.[19-21] According to our findings, the rate of smokers in the PAD group was 23% and this results was compatible with the literature (Table 2). In their study investigating the effect of physical activity on inflammation in PAD patients, Christofaro et al.[22] found that high hsCRP values were associated with inflammation and that hsCRP values significantly decreased in patients who engaged in regular physical activity. Jacobs et al.,[23] in their study on patients with metabolic syndrome, investigated CRP, IL-6, sVCAM-1 (soluble vascular cell adhesion molecule-1), sICAM-1 (soluble intercellular adhesion molecule-1), and serum amyloid A levels. They found a partial association between metabolic syndrome and the prevalence of coronary artery disease and PAD severity, suggesting that this relationship was mediated by low-grade inflammation. In our study, the mean fibrinogen 462.58±88.09 mg/dL and mean CRP 7.21±9.7 (3.74-9.43) mg/L values were high and were statistically significant (p<0.001). We observed other noteworthy findings in this study. For example, the mean monocyte and lymphocyte values were higher in the PAD group (0.55±0.21 and 2.82±1.57, respectively), with statistical significance (p<0.001). Barhoumi et al.[17] demonstrated that monocyte activation plays a role in vascular inflammation and low-grade inflammation.

This study had several limitations, including a small sample size and a retrospective design. Additionally, it would have been more valuable if other inflammatory biomarkers, such as tumor necrosis factor-alpha and IL-6, had been analyzed in this study.

In conclusion, inflammatory biomarkers such as fibrinogen, CRP, and WBC count were found to be statistically significant in the PAD group, indicating that the low-grade inflammation hypothesis may play a role in PAD. If the role of low-grade inflammation in PAD is proven in future large-scale, prospective, randomized controlled trials, anti-inflammatory treatment modalities may be incorporated into PAD treatment.

Data Sharing Statement: The data that support the findings of this study are available from the corresponding author upon reasonable request.

Author Contributions: Study design, overwiew: A.D.K.; Writing and references: E.N.M.K.; Statistics: İ.A.

Conflict of Interest: The authors declared no conflicts of interest with respect to the authorship and/or publication of this article.

Funding: The authors received no financial support for the research and/or authorship of this article.

1) Wang W, Zhao T, Geng K, Yuan G, Chen Y, Xu Y. Smoking and the pathophysiology of peripheral artery disease. Front Cardiovasc Med 2021;8:704106. doi: 10.3389/ fcvm.2021.704106.

2) Gimbrone MA Jr, García-Cardeña G. Endothelial cell dysfunction and the pathobiology of atherosclerosis. Circ Res 2016;118:620-36. doi: 10.1161/CIRCRESAHA.115.306301.

3) Donato AJ, Morgan RG, Walker AE, Lesniewski LA. Cellular and molecular biology of aging endothelial cells. J Mol Cell Cardiol 2015;89:122-35. doi: 10.1016/j.yjmcc.2015.01.021.

4) Alur İ. Low-grade inflammation: A familiar factor in cardiovascular diseases. JACC Basic Transl Sci 2023;8:1475. doi: 10.1016/j.jacbts.2023.09.010.

5) Tristan Asensi M, Napoletano A, Sofi F, Dinu M. Low-grade inflammation and ultra-processed foods consumption: A review. Nutrients 2023;15:1546. doi: 10.3390/nu15061546.

6) Cecoro G, Annunziata M, Iuorio MT, Nastri L, Guida L. Periodontitis, low-grade inflammation and systemic health: A scoping review. Medicina (Kaunas) 2020;56:272. doi: 10.3390/medicina56060272.

7) Yener AU, Cicek OF, Cicek MC, Ozkan T, Korkmaz K, Yener O, et al. Does a basic blood test tell the location of peripheral arterial lesions? Acta Medica Mediterranea 2015;31:377.

8) Handelsman Y, Bloomgarden ZT, Grunberger G, Umpierrez G, Zimmerman RS, Bailey TS, et al. American Association of Clinical Endocrinologists and American College of Endocrinology--Clinical practice guidelines for developing a diabetes mellitus comprehensive care plan--2015. Endocr Pract 2015;21:413-37.

9) Mancia G, Fagard R, Narkiewicz K, Redon J, Zanchetti A, Böhm M, et al. 2013 ESH/ESC guidelines for the management of arterial hypertension: The task force for the management of arterial hypertension of the European Society of Hypertension (ESH) and of the European Society of Cardiology (ESC). Eur Heart J 2013;34:2159-219. doi: 10.1093/eurheartj/eht151.

10) National Cholesterol Education Program (NCEP) expert panel on detection, evaluation, and treatment of high blood cholesterol in adults (Adult Treatment Panel III). Third report of the National Cholesterol Education Program (NCEP) expert panel on detection, evaluation, and treatment of high blood cholesterol in adults (Adult Treatment Panel III) final report. Circulation 2002;106:3143-421.

11) Torzewski M, Rist C, Mortensen RF, Zwaka TP, Bienek M, Waltenberger J, et al. C-reactive protein in the arterial intima: Role of C-reactive protein receptor-dependent monocyte recruitment in atherogenesis. Arterioscler Thromb Vasc Biol 2000;20:2094-9. doi: 10.1161/01.atv.20.9.2094.

12) Zwaka TP, Hombach V, Torzewski J. C-reactive proteinmediated low density lipoprotein uptake by macrophages: implications for atherosclerosis. Circulation 2001;103:1194- 7. doi: 10.1161/01.cir.103.9.1194.

13) Sharif S, Van der Graaf Y, Cramer MJ, Kapelle LJ, de Borst GJ, Visseren FLJ, et al. Low-grade inflammation as a risk factor for cardiovascular events and all-cause mortality in patients with type 2 diabetes. Cardiovasc Diabetol 2021;20:220. doi: 10.1186/s12933-021-01409-0.

14) Lucci C, Cosentino N, Genovese S, Campodonico J, Milazzo V, De Metrio M, et al. Prognostic impact of admission highsensitivity C-reactive protein in acute myocardial infarction patients with and without diabetes mellitus. Cardiovasc Diabetol 2020;19:183. doi: 10.1186/s12933-020-01157-7.

15) Sima C, Glogauer M. Diabetes mellitus and periodontal diseases. Curr Diab Rep 2013;13:445-52. doi: 10.1007/ s11892-013-0367-y.

16) Zach DK, Schwegel N, Santner V, Winkelbauer L, Hoeller V, Kolesnik E, et al. Low-grade systemic inflammation and left ventricular dysfunction in hypertensive compared to nonhypertensive hypertrophic cardiomyopathy. Int J Cardiol 2024;399:131661. doi: 10.1016/j.ijcard.2023.131661.

17) Barhoumi T, Todryk S. Role of monocytes/macrophages in renin-angiotensin system-induced hypertension and end organ damage. Front Physiol 2023;14:1199934. doi: 10.3389/ fphys.2023.1199934.

18) Domingo E, Marques P, Francisco V, Piqueras L, Sanz MJ. Targeting systemic inflammation in metabolic disorders. A therapeutic candidate for the prevention of cardiovascular diseases? Pharmacol Res 2024;200:107058. doi: 10.1016/j. phrs.2024.107058.

19) Ismaeel A, Brumberg RS, Kirk JS, Papoutsi E, Farmer PJ, Bohannon WT, et al. Oxidative stress and arterial dysfunction in peripheral artery disease. Antioxidants (Basel) 2018;7:145. doi: 10.3390/antiox7100145.

20) Wu X, Zhang H, Qi W, Zhang Y, Li J, Li Z, et al. Nicotine promotes atherosclerosis via ROS-NLRP3-mediated endothelial cell pyroptosis. Cell Death Dis 2018;9:171. doi: 10.1038/s41419-017-0257-3.

21) Wang X, Bian Y, Zhang R, Liu X, Ni L, Ma B, et al. Melatonin alleviates cigarette smoke-induced endothelial cell pyroptosis through inhibiting ROS/NLRP3 axis. Biochem Biophys Res Commun 2019;519:402-8. doi: 10.1016/j.bbrc.2019.09.005.

22) Christofaro DGD, Ritti-Dias RM, Tebar WR, Werneck AO, Bittencourt MS, Cucato GG, et al. Are C-reactive protein concentrations affected by smoking status and physical activity levels? A longitudinal study. PLoS One 2023;18:e0293453. doi: 10.1371/journal.pone.0293453.

23) Jacobs M, van Greevenbroek MM, van der Kallen CJ, Ferreira I, Blaak EE, Feskens EJ, et al. Low-grade inflammation can partly explain the association between the metabolic syndrome and either coronary artery disease or severity of peripheral arterial disease: The CODAM study. Eur J Clin Invest 2009;39:437-44. doi: 10.1111/j.1365- 2362.2009.02129.x.