Skip to main content
Advertisement
Browse Subject Areas
?

Click through the PLOS taxonomy to find articles in your field.

For more information about PLOS Subject Areas, click here.

  • Loading metrics

Toe-brachial index is beyond a peripheral issue in patients with type 2 diabetes

Abstract

Background

Atherosclerosis is the leading cause of death in patients with diabetes. We aimed to evaluate the association between ankle-brachial index (ABI) and toe-brachial index (TBI) with carotid intima-media thickness (CIMT) in patients with type 2 diabetes (T2DM).

Methods

This cross sectional study included 296 patients with T2DM who met the American Diabetes Association criteria for the assessment of peripheral arterial atherosclerosis. The ABI ≤ 0.9 and TBI ≤ 0.7 were considered as abnormal values. Linear and logistic regression analyses were performed to evaluate the association between TBI/ABI and CIMT.

Results

Right CIMT was significantly greater in the low TBI group (p = 0.03) while, left CIMT did not show a significant difference. Each 0.1-unit decrease in TBI value was independently associated with 0.017 mm increase in the right CIMT (β ± SE; -0.017 ± 0.005, p = 0.002) and with odds of the presence of increased CIMT [odds ratio and 95% confidence interval: 1.21 (1.02, 1.44)] after adjustment with all traditional risk factors. There was not any significant association between ABI and increased CIMT.

Conclusions

Beyond a suitable tool for the diagnosis of peripheral artery disease in patients with T2DM, TBI can be applied for prediction of subclinical carotid atherosclerosis.

Introduction

With the improvement in the life expectancy of human beings, early identification and timely treatment of chronic disease is of a significant importance. In the recent decades, atherosclerosis leading to the heart attack and stroke is the most common cause of death and morbidity worldwide [1]. Peripheral arterial disease (PAD) is atherosclerotic narrowing of arteries that supply organs other than heart and brain. It most commonly affects the lower extremity arteries. The growing body of knowledge suggesting the association between PAD and carotid artery atherosclerosis emphasizes the fact that atherosclerosis is a systemic disease, so that the presence of atherosclerosis in some area is a warning sign for that in the other regions [2]. Considering the growing number of patients with diabetes and the attributed double risk of developing cardiovascular and cerebrovascular events due to the atherosclerosis among these patients, screening tests for diagnosis of subclinical vascular problems in patients with type 2 diabetes (T2DM) seems to be essential [35].

Ankle-brachial index (ABI) is an inexpensive, easy-to-use, and widely available method for evaluating PAD and is correlated to the cardiovascular disease [6] Toe-brachial index (TBI) seems to provide a more accurate risk evaluation in patients with diabetes because medial calcification of the arteries frequently present in these patients and may lead to detection of a falsely normal ABI value underestimating the PAD [7, 8]. TBI is not affected by this phenomenon and may not only be a precise indicator of PAD but may also be a predictor of general arterial atherosclerosis in patients with diabetes.

Carotid intima-media thickness (CIMT) is an established marker for the diagnosis of subclinical atherosclerosis and a predictor for future cardiovascular events [911]. Vascular screening with ABI, TBI and CIMT in patients with T2DM gives invaluable information about the further need for medical or non-medical prophylactic interventions. Previous studies have shown the decreased ABI and increased CIMT are related to more severe coronary artery disease and increase the global atheroma burden and cardiovascular events [12, 13]. However, there is little research regarding the relation between TBI and CIMT. The aim of this study was to evaluate the association between ABI/ TBI and CIMT and also survey the ability of ABI/TBI to predict the increased CIMT in patients with T2DM.

Materials and methods

Participants

This is a cross-sectional study on the patients with T2DM referred to the foot clinic for routine checkups at Institute of Endocrinology and Metabolism, Iran University of Medical Sciences (IUMS) during 2018_2019. Ethical approval was obtained from the local ethics committee. All participants provided written informed consent before participation.

We included all patients with a history of decreased walking speed, claudication, or abnormal pedal pulse. Moreover, all asymptomatic patients aged more than 50 years or less than 50 years who have other PAD risk factors (e.g., smoking, hypertension, dyslipidemia, or duration of diabetes > 10 years) were also included in the study [14]. Patients with a history of severe congestive heart failure, lymphedema, bilateral mastectomy, cellulitis, vasospastic disorders (Raynaud’s phenomenon, Raynaud’s disease, livedo reticularis, and, acrocyanosis) thrombophlebitis, deep vein thrombosis (DVT) within the past 6 months, or presence of a wound preventing Doppler probe or ankle cuff placement, were excluded from the study. Patients with major amputation, morbid obesity, severe osteoarthritis, and those unable to walk were also excluded from the study.

Clinical and laboratory data

Participants were asked to complete a brief questionnaire including demographic data, duration of diabetes, smoking status, medical history (hypertension (HTN), coronary artery disease (CAD), or stroke). In the same session measurement of blood pressure (BP), weight, and height as well as assessment for the presence of neuropathy were performed by an experienced nurse. Neurological exam was designed to identify loss of protective sensation (LOPS) [15]. The 10-g monofilament at four points (1st, 3rd, and 5th metatarsal heads and plantar surface of distal hallux) was tested on each foot. The 128 Hz tuning fork was applied over the tip of the great toe bilaterally to assess vibration perception. Ankle reflexes was tested while the patient is resting on the couch. Pinprick test was performed using a disposable pin which was applied just proximal to the toenail on the dorsal surface of the hallux. The presence of any abnormal test was considered as having LOPS.

Moreover, blood sample was obtained for the measurement of glycated hemoglobin (HbA1C), triglyceride (TG), total cholesterol (chol), low density lipoprotein (LDL), high density lipoprotein (HDL). All laboratory tests were performed at the institute’s laboratory.

Vascular measures

The patients were asked to abstain from caffeine, cigarettes, and exercise at least two hours before the examination. After a 15-minute rest in the supine position, in a room with a constant temperature of 23_25°C, each participant underwent ABI and TBI measurement with Doppler ultrasound (DUS) (LifeDop 150; Summit Doppler, Wallach Surgical Devices, Turn-bull, Conn). All measurements were performed by an experienced nurse to avoid the interobserver discrepancies [16].

The toe pressure and the higher pressure between the arteries of posterior tibial (PT) and dorsalis pedis (DP) for each leg is divided into the higher blood pressure recorded from either arm to calculate the TBI and ABI for each lower extremity, respectively. For each patient the lower values of ABI and TBI of either side were used for the analysis. The ABI ≤ 0.9 and TBI ≤ 0.7 were considered abnormal [17]. The participants were categorized into two groups based on normal vs. abnormal ABI as well as TBI.

DUS of both common carotid arteries was performed by an experienced sonographer blinded to the other results with the MylabClassC color Doppler ultrasound diagnostic system (Esaote, Guangdong, China), using a 5–13 MHz vascular probe. In the supine position with a head rotated towards the opposite side, the CIMT was measured at the end of the diastole. The distance between the echogenic lines of intima-blood interface and outer adventitia-media junction in a plaque free area of the far wall considered as CIMT. All measurements was done in a longitudinal plane [18]. The CIMT greater than 0.82 and 0.85 mm for the right and left side were considered to be increased, respectively [19].

Statistical analysis

All statistical analyses were conducted using IBM SPSS Statistics for Windows (Version 22.0 IBM Corp. Released 2013. Armonk, NY). Skewness and kurtosis of the continuous variables tested for the assumption of normality. Continuous variables were reported as mean ± standard deviation (SD) or median with interquartile range and the categorical variables were presented as a percentage. Between-group differences were examined using the χ2 test, independent sample t-test, or Mann-Whitney U test, as appropriate. TBI coefficient of correlation with age, gender, diabetes duration, Body Mass Index (BMI), CIMT, and laboratory measures were assessed. Linear and logistic regression analyzes were performed to evaluate the association between CIMT and TBI or ABI in the following 3 different models: the first unadjusted, the second adjusted for age and gender, and the third adjusted for age, gender, BMI, duration of diabetes, smoking status, HDL, LDL, and HbA1c. Models were checked for multi-collinearity and variance inflation factors (VIF) were below 2 for all variables.

Sample size with type 1 error of 0.05 and 95% confidence interval was calculated as 120 patients using the following equation. SD for CIMT in patients with T2DM assumed 0.2. (S1 File) [20].

Results

Two hundred and ninety-six participants with T2DM met inclusion criteria. There were more women (n = 176) than men (n = 120). The mean age of the participants was 60.1±8.4 years and most of them (90%) were below 70 years old. The mean duration of diabetes was 13.4±8.4 years and only 20.6% had duration of fewer than 5 years. The mean BMI of the patients was 28.9±4.5 kg/m2. The percentage of current smokers was 6.4%. Most patients were asymptomatic and do not need any interventions. Only 13 participants needed endovascular intervention or revascularization. Asymptomatic patients had normal distribution for age and mean ± SD for this group was 59.6±8.1. Individuals were categorized by TBI and ABI status. About 41% of participants had low TBI (TBI≤0.7) while only 6% had low ABI (ABI≤0.9). Patients with lower ABI were more likely to be male, had a higher prevalence of neuropathy, CVD, smoking, and higher TG but lower HDL levels. There was no significant difference in age, duration of diabetes, BMI, systolic and diastolic blood pressure, HbA1c, total cholesterol, and LDL between the two ABI categories. The group with lower TBI had higher age, longer duration of diabetes, higher prevalence of CVD and neuropathy, and higher LDL level. There was no difference in gender, BMI, history of smoking, systolic and diastolic blood pressure, HbA1c, TG, total cholesterol, and HDL between the two categories of TBI. Right CIMT was significantly greater in the low TBI group compared to the high TBI counterparts (0.77± 0.16 vs 0.73±0.14, p = 0.03) and also in the low ABI group compared to high ABI counterparts (0.91± 0.19 vs 0.74±0.14, p = 0.001). However, there was no significant difference between left CIMT in different TBI/ABI categories. (Table 1).

TBI was correlated negatively with right CIMT (r = -0.21, p<0.001) but there was no significant correlation between TBI and left CIMT (r = -0.09, p = 0.08). Besides, ABI did not show any significant correlation with right CIMT (r = -0.10, p = 0.08) or left CIMT (r = 0.04, p = 0.49). (Fig 1).

thumbnail
Fig 1. Graph illustrating correlation between right CIMT and TBI (A) and ABI (B).

CIMT: carotid intima media thickness. TBI: toe brachial index. ABI: ankle brachial index.

https://doi.org/10.1371/journal.pone.0253138.g001

The association between ABI/TBI and right CIMT as a continuous variable was studied applying linear regression analyzes. Each 0.1-unit decrease in TBI was associated with 0.017 mm increase in the right CIMT. This association was significant even after adjustment for age, gender, BMI, smoking status, HDL, LDL, and HbA1C (p = 0.002). On the contrary, there was no significant association between ABI and right CIMT in any of the models. (Table 2).

thumbnail
Table 2. Linear regression analysis of relation between TBI/ABI (0.1 unit) and CIMT (1mm).

https://doi.org/10.1371/journal.pone.0253138.t002

Logistic regression analyzes showed that each 0.1-unit decrease in TBI value was significantly associated with odds of increased right CIMT [odds ratio (OR) and 95% confidence interval (CI): 1.27 (1.08, 1.49) in model 1; 1.25 (1.06, 1.47) in model 2; and 1.21 (1.02, 1.44) in model 3]. There was not any significant association between ABI and increased right CIMT. (Table 3).

thumbnail
Table 3. Logistic regression analysis on relationship between ABI/TBI (0.1 unit) and high CIMT.

https://doi.org/10.1371/journal.pone.0253138.t003

Discussion

In the current study, the relevance of ABI/TBI and ultrasound marker of carotid artery atherosclerosis, CIMT, was surveyed in the middle-aged patients with T2DM. There was a significant negative association between TBI and CIMT considering all potential risk factors. However, no relationship was observed between ABI and CIMT. Although decreased ABI is a well-known predictor of increased cardiovascular and all-cause mortality [21, 22], incompressible leg vessel due to the medial calcification in patients with diabetes makes ABI less sensitive in this population [23, 24]. Some previous studies have shown the superiority of TBI in predicting cardiovascular outcomes compared to ABI in the special populations [25]. Wang et al. [26] described a U-shaped relationship between ABI and CIMT obtained from the common carotid, internal carotid, and carotid bifurcation. Brasileiro et al. [27] observed a negative correlation between ABI and CIMT in their investigation but Wyman et al. [28], and Mitu et al. [29] found no association as ours. This discrepancy in the results might be due to the fact that the former study was done in the general population that lower proportion has diabetes. Arterial wall calcification in patients with diabetes interferes with the utility of the ABI [8]. Moreover, differences in age and ethnicity of the study populations as well as the methods and confounders are other explanations for these diverse results.

We found a significant negative correlation between TBI and CIMT both as a continuous and binary outcome. This result is consistent with the results of previous studies that had been conducted in a similar population of different ethnicities [20, 30, 31]. In our study, the right CIMT correlated better with TBI than did the left CIMT. Various studies have mentioned a significant difference between the right and left CIMT [32, 33]. A research conducted by Luo et al. indicated that risk factors affecting CIMT differed in the right and left sides. Right CIMT was more correlated with hemodynamic parameters while left CIMT was better correlated with biochemical and body composition changes including BMI, hip circumference, total cholesterol, LDL, and blood glucose [32]. Various effects of different risk factors on each CIMT seem to be the cause of the observed issue.

Strength and limitations

To the best of our knowledge, this study is the first one that evaluated the association of TBI and CIMT in a population of Iranian people with T2DM. Moreover, all potential confounders have been taken into account. However, this is a single-center, cross-sectional study, and no casualty between TBI and CIMT could be concluded from it.

We found that the changes in CIMT values with decreasing TBI is too small to be measured with current methods. It highlights the need for further and more accurate techniques for CIMT evaluation.

Conclusion

In summary, the present study demonstrated a significant negative association between TBI and right CIMT in patients with T2DM. The association was independent of all conventional risk factors. Thus, beyond a suitable tool for diagnosis of PAD in patients with diabetes, TBI can provide us with information on subclinical carotid atherosclerosis. This emphasized the necessity for more frequent use of TBI measurement, as a non-invasive, easily available, and low-cost tool, in diabetes clinics than previously recognized.

Supporting information

S2 File. Contribution of each element in linear regression analysis.

https://doi.org/10.1371/journal.pone.0253138.s002

(DOCX)

S3 File. Contribution of each element in logistic regression.

https://doi.org/10.1371/journal.pone.0253138.s003

(DOCX)

Acknowledgments

We do appreciate the staff of the Endocrine Research Center at Iran University of Medical Sciences (IUMS).

References

  1. 1. Lopez-Cancio E, Dorado L, Millan M, Reverte S, Sunol A, Massuet A, et al. The population-based Barcelona-Asymptomatic Intracranial Atherosclerosis Study (ASIA): rationale and design. BMC neurology. 2011;11:22. pmid:21329527
  2. 2. Morillas P, Quiles J, Cordero A, Guindo J, Soria F, Mazon P, et al. Impact of clinical and subclinical peripheral arterial disease in mid-term prognosis of patients with acute coronary syndrome. The American journal of cardiology. 2009;104(11):1494–8. pmid:19932781
  3. 3. Nicolucci A, De Berardis G, Sacco M, Tognoni G. Primary prevention of cardiovascular diseases in people with diabetes mellitus: a scientific statement from the American Heart Association and the American Diabetes Association: response to Buse et al. Diabetes care. 2007;30(6):e57; author reply e8. pmid:17526819
  4. 4. Whiting DR, Guariguata L, Weil C, Shaw J. IDF diabetes atlas: global estimates of the prevalence of diabetes for 2011 and 2030. Diabetes research and clinical practice. 2011;94(3):311–21. pmid:22079683
  5. 5. Norgren L, Hiatt WR, Dormandy JA, Nehler MR, Harris KA, Fowkes FG, et al. Inter-Society Consensus for the Management of Peripheral Arterial Disease (TASC II). European journal of vascular and endovascular surgery: the official journal of the European Society for Vascular Surgery. 2007;33 Suppl 1:S1–75.
  6. 6. Creager MA, White CJ, Hiatt WR, Criqui MH, Josephs SC, Alberts MJ, et al. Atherosclerotic Peripheral Vascular Disease Symposium II: executive summary. Circulation. 2008;118(25):2811–25. pmid:19106402
  7. 7. Cao P, Eckstein HH, De Rango P, Setacci C, Ricco JB, de Donato G, et al. Chapter II: Diagnostic methods. European journal of vascular and endovascular surgery: the official journal of the European Society for Vascular Surgery. 2011;42 Suppl 2:S13–32. pmid:22172470
  8. 8. Álvaro-Afonso FJ, Lázaro-Martínez JL, Aragón-Sánchez J, García-Morales E, García-Álvarez Y, Molines-Barroso RJ. What Is the Clinical Utility of the Ankle-Brachial Index in Patients With Diabetic Foot Ulcers and Radiographic Arterial Calcification? The international journal of lower extremity wounds. 2015;14(4):372–6. pmid:26216917
  9. 9. Lorenz MW, Markus HS, Bots ML, Rosvall M, Sitzer M. Prediction of clinical cardiovascular events with carotid intima-media thickness: a systematic review and meta-analysis. Circulation. 2007;115(4):459–67. pmid:17242284
  10. 10. Gepner AD, Young R, Delaney JA, Tattersall MC, Blaha MJ, Post WS, et al. Comparison of coronary artery calcium presence, carotid plaque presence, and carotid intima-media thickness for cardiovascular disease prediction in the Multi-Ethnic Study of Atherosclerosis. Circulation Cardiovascular imaging. 2015;8(1).
  11. 11. Polak JF, O’Leary DH. Carotid Intima-Media Thickness as Surrogate for and Predictor of CVD. Global heart. 2016;11(3):295–312.e3. pmid:27741977
  12. 12. Kassem A, Kamal Y, Abdelwahab M, Elrashedy M. A3005 Carotid Intima-Media Thickness and Ankle-Brachial Index as Predictors of the Severity of Coronary Artery Disease. 2018;36:e142–e3.
  13. 13. Weir-McCall JR, Khan F, Lambert MA, Adamson CL, Gardner M, Gandy SJ, et al. Common carotid intima media thickness and ankle-brachial pressure index correlate with local but not global atheroma burden: a cross sectional study using whole body magnetic resonance angiography. PLoS One. 2014;9(6):e99190. pmid:24933122
  14. 14. 9. Microvascular Complications and Foot Care. Diabetes care. 2016;39 Suppl 1:S72–80. pmid:26696685
  15. 15. 10. Microvascular Complications and Foot Care. 2017;40(Supplement 1):S88–S98.
  16. 16. Álvaro-Afonso FJ, García-Morales E, Molines-Barroso RJ, García-Álvarez Y, Sanz-Corbalán I, Lázaro-Martínez JL. Interobserver reliability of the ankle-brachial index, toe-brachial index and distal pulse palpation in patients with diabetes. Diabetes & vascular disease research. 2018;15(4):344–7.
  17. 17. Correction to: 2016 AHA/ACC Guideline on the Management of Patients With Lower Extremity Peripheral Artery Disease: A Report of the American College of Cardiology/American Heart Association Task Force on Clinical Practice Guidelines. Circulation. 2017;135(12):e791–e2. pmid:28320816
  18. 18. Heiss G, Sharrett AR, Barnes R, Chambless LE, Szklo M, Alzola C. Carotid atherosclerosis measured by B-mode ultrasound in populations: associations with cardiovascular risk factors in the ARIC study. American journal of epidemiology. 1991;134(3):250–6. pmid:1877584
  19. 19. Azarkish K, Mahmoudi K, Mohammadifar M, Ghajarzadeh M. Mean right and left carotid intima-media thickness measures in cases with/without coronary artery disease. Acta Med Iran. 2014;52(12):884–8. pmid:25530049
  20. 20. Spangeus A, Wijkman M, Lindstrom T, Engvall JE, Ostgren CJ, Nystrom FH, et al. Toe brachial index in middle aged patients with diabetes mellitus type 2: not just a peripheral issue. Diabetes research and clinical practice. 2013;100(2):195–202. pmid:23522916
  21. 21. Criqui MH, Langer RD, Fronek A, Feigelson HS, Klauber MR, McCann TJ, et al. Mortality over a period of 10 years in patients with peripheral arterial disease. N Engl J Med. 1992;326(6):381–6. pmid:1729621
  22. 22. Fowkes FG, Murray GD, Butcher I, Heald CL, Lee RJ, Chambless LE, et al. Ankle brachial index combined with Framingham Risk Score to predict cardiovascular events and mortality: a meta-analysis. Jama. 2008;300(2):197–208. pmid:18612117
  23. 23. Hyun S, Forbang NI, Allison MA, Denenberg JO, Criqui MH, Ix JH. Ankle-brachial index, toe-brachial index, and cardiovascular mortality in persons with and without diabetes mellitus. J Vasc Surg. 2014;60(2):390–5. pmid:24657294
  24. 24. Babaei MR, Malek M, Rostami FT, Emami Z, Madani NH, Khamseh ME. Non-invasive vascular assessment in people with type 2 diabetes: Diagnostic performance of Plethysmographic-and-Doppler derived ankle brachial index, toe brachial index, and pulse volume wave analysis for detection of peripheral arterial disease. Primary care diabetes. 2019.
  25. 25. Wickström JE, Laivuori M, Aro E, Sund RT, Hautero O, Venermo M, et al. Toe Pressure and Toe Brachial Index are Predictive of Cardiovascular Mortality, Overall Mortality, and Amputation Free Survival in Patients with Peripheral Artery Disease. European journal of vascular and endovascular surgery: the official journal of the European Society for Vascular Surgery. 2017;53(5):696–703.
  26. 26. Wang Y, Li J, Guo X, Zhao D, Hu D, Wei Y, et al. A U-shaped relationship between ankle-brachial index and carotid intima-media thickness in a Chinese population of Inner Mongolia. International angiology: a journal of the International Union of Angiology. 2011;30(5):451–7.
  27. 27. Brasileiro AC, Oliveira DC, Victor EG, Oliveira DA, Batista LL. Association between ankle-brachial index and carotid atherosclerotic disease. Arq Bras Cardiol. 2013;100(5):422–8. pmid:23568096
  28. 28. Wyman RA, Keevil JG, Busse KL, Aeschlimann SE, Korcarz CE, Stein JH. Is the ankle-brachial index a useful screening test for subclinical atherosclerosis in asymptomatic, middle-aged adults? Wmj. 2006;105(6):50–4. pmid:17042421
  29. 29. Mitu F, Mitu O, Dimitriu C, Dimitriu G, Mitu M. Significance of arterial stiffness and relationship with other noninvasive methods for the assessment of subclinical atherosclerosis inpatients with metabolic syndrome. Rev Med Chir Soc Med Nat Iasi. 2013;117(1):59–64. pmid:24505893
  30. 30. Zhang Y, Peng K, Liu J, Chen X, Wang T, Li M, et al. Carotid intima-media thickness and plagues are associated with indicators of peripheral artery diseases in patients with diabetes. Diabetes research and clinical practice. 2018;144:245–51. pmid:30194009
  31. 31. Martin-Fuentes M, Herranz L, Saez-de-Ibarra L, Sanchez LFP. Toe Brachial Pressure Index as Alternative Method to Correlate Arteriosclerotic Disease in Type 2 Diabetes. The Journal of the Association of Physicians of India. 2018;66(10):36–9. pmid:31317706
  32. 32. Luo X, Yang Y, Cao T, Li Z. Differences in left and right carotid intima-media thickness and the associated risk factors. Clin Radiol. 2011;66(5):393–8. pmid:21324442
  33. 33. Liu D, Du C, Shao W, Ma G. Diagnostic Role of Carotid Intima-Media Thickness for Coronary Artery Disease: A Meta-Analysis. Biomed Res Int. 2020;2020:9879463. pmid:32185231