Journal of Neurological Research And Therapy

Journal of Neurological Research and Therapy

Journal of Neurological Research and Therapy

Current Issue Volume No: 1 Issue No: 1

Research Article Open Access Available online freely Peer Reviewed Citation

Endothelial Function in Stroke Subtypes Using Endopat Technology

1Department of Neurology, San Pedro de Alcántara Hospital, Avenida de Pablo Naranjo nº 2, 10003. Cáceres. Spain.

Abstract

Background. Endothelial function is characterized by the vasodilator capacity of blood vessel smooth muscle cells mediated by nitric oxide. Some studies have shown an inverse association between the endothelial function and the carotid intima-media thickness (IMT). The relationship between endothelial dysfunction and stroke based on several studies has shown that is altered in all stroke subtypes especially lacunar strokes. Methods. We aimed to investigate endothelial function by EndoPAT device in relation to stroke subtypes. We investigate too the correlations between endothelial function and IMT and we study possible interactions with age, sex, traditional risk factors and severity of stroke. Subsequent patients with acute ischemic stroke were enrolled. They were divided according with the etiological mechanism of stroke (TOAST classification). Endothelial function was assessed with finger plethysmography by the EndoPAT device that gave Reactive Hyperemia Index (RHI) and Augmentation Index (AI). Results. Patients with a cardioembolic stroke had a RHI higher than atherotrombotic or lacunar stroke. There was a negative correlation between RHI and IMT and positive between AI and age. Conclusions. The endothelial function is different between stroke subtypes with higher values of RHI in the cardioembolic respect to lacunar or atherotrombotic. The RHI is correlated with the atherosclerosis by the negative relationship with the IMT. The AI that shows the rigidity in the arteries increased with the age.

Author Contributions
Received 03 Aug 2014; Accepted 24 Jan 2015; Published 19 May 2015;

Academic Editor: Zheng Jiang, Department of Neuroscience, The Johns Hopkins University School of Medicine

Checked for plagiarism: Yes

Review by: Single-blind

Copyright ©  2015 Pedro Enrique Jiménez Caballero, et al

License
Creative Commons License     This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Competing interests

The authors have declared that no competing interests exist.

Citation:

Pedro Enrique Jiménez Caballero, Fidel López Espuela, Juan Carlos Portilla Cuenca, José Antonio Fermin Marrero, Ignacio Casado Naranjo (2015) Endothelial Function in Stroke Subtypes Using Endopat Technology. Journal of Neurological Research and Therapy - 1(1):1-10. https://doi.org/10.14302/issn.2470-5020.jnrt-14-558

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DOI 10.14302/issn.2470-5020.jnrt-14-558

Introduction

Endothelial function is characterized by the vasodilator capacity of blood vessel smooth muscle cells mediated by nitric oxide 1. In recent years, a number of experimental and clinical studies have established the role of endothelial dysfunction (ED) in the development of cerebrovascular diseases 2. ED is an early event of atherosclerosis that precedes structural atherosclerotic changes in the vascular wall. As the major regulator of vascular homeostasis the endothelium maintains the balance between vasodilatation and vasoconstriction. Damage of the endothelium upsets this balance and initiates a number of events that promote or exacerbate atherosclerosis; these include increased endothelial permeability, platelet aggregation, leukocyte adhesion and generation of cytokines. Some studies have shown an inverse association between the endothelial function and the carotid intima-media thickness (IMT) 3, 4.

There are different non-invasive methods for assess the endothelial function. Respect to brachial flow mediated dilatation (FMD), the peripheral arterial tonometry (PAT) has several unique qualities that improve its accuracy in assessing endothelial-mediated changes in vascular tone: The PAT signal is simultaneously recorded from both arms and the EndoPAT device enables assessment of occlusion and provocation quality. Comparing EndoPAT scores to intra-coronary assessment of endothelial function (considered as gold standard) yielded a sensitivity of 82% and a specificity of 77% 5.

The relationship between endothelial dysfunction and stroke based on several studies has shown that is altered in all stroke subtypes especially lacunar strokes. Chen et al. showed that overall stroke patients had impaired FMD, but only lacunar infarction had significantly impaired FMD versus controls 6. Other studies have shown ED in large artery atheromatous stroke 7, cerebral atherosclerosis 8 and cardioembolic infarcts 1. Chlumsky et al. showed that patients with atrial fibrillation had significantly better FMD results than patients without it 9.

We aimed to investigate endothelial function by EndoPAT device in relation to stroke subtypes according to the TOAST (Trial of ORG 10172 in Acute Stroke Treatment) classification. We studied the correlations between endothelial function and IMT and study possible interactions with age, sex, traditional risk factors and severity of stroke.

Methods

We studied patients consecutively admitted to our stroke unit between May 2012 and January 2013 with a clinical diagnosis of acute ischemic stroke (IS). The patients were enrolled within 48 hours and the examinations were completed within 4 days after the event. Stroke severity was assessed with the NIHSS score 10. During the acute phase after stroke, all patients were on standard medical cardiovascular therapy in individual adjusted doses. . The patients only received sporadically Labetalol or Urapidil as treatment for release the arterial tension. Patients within the therapeutic window on admission for thrombolysis were treated with alteplase.

Acute IS was classified according to the TOAST classification: cardioembolic infarcts, large-artery atherosclerotic infarcts and lacunar infarcts. We obtained information about vascular risk factors: arterial hypertension (HTN), diabetes mellitus, hyperlipidemia and smoking.

Exclusion criteria were stroke of undetermined aetiology, poor participation with testing, amputation of one arm, hand or fingers, intercurrent acute illness, renal failure (glomerular filtration rate < 30), hemodynamic instability or use of vasoactive drugs.

Colour-coded duplex ultrasonography of the carotid arteries was performed in all patients. Carotid IMT was measured according to the Mannheim IMT consensus 11. Local ethics committee approved the study, and all subjects gave their written informed consent.

Assessment of Endothelial Function

Quantitative determination of endothelial function was assessed using a finger plethysmograph (EndoPAT 2000; Itamar Medical, Caesarea, Israel). Endothelial function was based on PAT measurement of the index finger during reactive hyperemia of the forearm vascular bed. The post-occlusion reading is adjusted for the pre-occlusion baseline measurement PAT signal. To control for potential confounding stimuli during the recording, the signal is further adjusted for the spontaneous variations of the pulse pressure amplitude by simultaneous PAT assessment of the contralateral (nonocluded) arm. Pressure curves were recorded electronically and the reactive hyperemia index (RHI) as dimensionless ratio and the augmentation index (AI) as percentages were calculated using a computerized algorithm of the EndoPAT 2000 software system 12. As this value changes with the heart rate, the device gives the normalized value at 75 bpm, the AI@75 13.

All EndoPAT assessments were performed under standardized conditions with the patient in the supine position, in a quiet, air-conditioned and well-tempered room (23ºC). Pneumatic probes were placed on both index fingers. Baseline measurement was carried out for 10 minutes. Complete arterial occlusion for 5 minutes was induced by external compression with 50 mmHg above systolic blood pressure. In all subjects, the dominant arm was used for the occlusion protocol but in patients with arm paresis, the nonparetic arm was used.

Statistical Analysis

Continuous variables were expressed as mean ± SD or median and interquartile ranges, depending on whether they were normally distributed, and groups were compared using the Student t test or the Mann-Whitney test, as appropriate. Categorical variables were reported as percentage or absolute numbers. Proportions between groups were compared using the chi-squared test, and Fisher exact test as appropriate.

One-way analysis of variance test followed by Bonferroni multiple comparison tests was used to compare the differences among different stroke subtypes. The relationship between variables was analyzed by linear regression analysis. Statistical analysis was performed with SPSS-13.0 program for Windows. p < 0,05 was considered statistically significant.

Results

The study included 74 patients with a mean age of 68.1 ± 12.2 years, 39.2% were women. Stroke aetiology was: cardioembolic in 28.4%, large-artery atherosclerosis in 33.8% and small-vessel occlusion in 37.8% of patients. Mean RHI was 1.83 ± 0.65, median AI was 19% IQR= and AI@75 was 16% 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26. The main clinical characteristics are summarized in Table 1.

Table 1. Clinical and demographic characteristics of patients with acute ischemic stroke (subgroups according to TOAST classification) enrolled in the study, n=74.
Variable n Percentage or Mean ± SD or Median ± IQR
Age 74 68.1 ± 12.2
Men 45 60.8%
Hypertension arterial 41 55.4%
Diabetes mellitus 20 27.0%
Hypercholesterolemia 30 40.5%
Current smoking 19 35.6%
Right Carotid IMT 74 0.84 ± 0.25
Left Carotid IMT 74 0.86 ± 0.25
RHI 74 1.83 ± 0.65
AI 74 19 (8 – 30)
AI@75 74 16 (7 – 26)
NIHSS score 74 4.55 ± 5.41
Cardioembolic 21 28.4%
Large-artery atherosclerosis 25 33.8%
Small-vessel occlusion 28 37.8%

The differences in the RHI, AI and AI@75 between demographic, clinical, risk factors and stroke subtypes are shown in Table 2. There were differences in the RHI between subtype strokes (p=0.036) as shows the Figure 1, but not in the AI (p=0.163) or AI@75 (p=0.258). The Bonferroni multiple comparison showed that RHI was lower in lacunar and large-artery atherosclerosis infarcts compared with cardioembolic strokes (p=0.003). Differences continued spite of stratification by risk factors.

Table 2. Studies comparing the variables RHI, AI and AI@75 between patients with or without risk factors and stroke subtypes.
EndoPAT values Variable Mean SD p
RHI Sex Male 1.86 0.73 0.676
Female 1.93 0.46
Hypertension arterial Yes 1.76 0.50 0.065
No 2.04 0.76
Diabetes Mellitus Yes 1.97 0.95 0.623
No 1.86 0.45
Hypercholesterolemia Yes 1.92 0.80 0.766
No 1.87 0.51
Current Smoking Yes 1.71 0.63 0.158
No 1.95 0.63
Stroke Subtypes Lacunar 1.87 0.76 0.036
Cardioembolic 2.16 0.47
Atherotrombotic 1.68 0.54
AI Sex Male 15.16 21.53 0.124
Female 23.76 24.10
Hypertension arterial Yes 23.15 25.47 0.043
No 12.79 17.71
Diabetes Mellitus Yes 18.15 28.87 0.941
No 18.67 20.62
Hypercholesterolemia Yes 23.90 22.62 0.094
No 14.86 22.62
Current Smoking Yes 13.84 16.70 0.219
No 20.15 24.49
Stroke Subtypes Lacunar 19.5 15.9 0.102
Cardioembolic 11.0 29.8
Atherothrombotic 23.7 21.8
AI@75 Sex Male 12.76 15.90 0.042
Female 22.17 20.68
Hypertension arterial Yes 21.41 20.12 0.006
No 10.27 13.92
Diabetes Mellitus Yes 17.75 21.92 0.744
No 15.96 17.09
Hypercholesterolemia Yes 20.50 18.81 0.123
No 13.68 17.76
Current Smoking Yes 11.32 10.39 0.061
No 18.22 20.20
Stroke Subtypes Lacunar 15.18 13.91 0.258
Cardioembolic 12.52 24.65
Atherothrombotic 21.16 16.29

Figure 1.Blox plot showing differences in the RHI between stroke subtypes: Cardioembolic infarcts have a RHI value higher than lacunar and atherotrombotic infarcts (p:0,003).
 Blox plot showing differences in the RHI between stroke subtypes: Cardioembolic infarcts have a RHI value higher than lacunar and atherotrombotic infarcts (p:0,003).

Patients with HTN have an AI and AI@75 higher than not hypertensive patients (p=0.043 and p=0.006, respectively). There were differences in the AI@75 between males and females, so the last had higher values (p=0.042)

Linear regression analysis between continuous variables is summarized in Table 3. There is a negative correlation between RHI and carotid IMT. There was a negative correlation between AI and AI@75 with NIHSS scores but positively between AI and AI@75 with age. There was not a correlation between RHI and AI or AI@75.

Table 3. Lineal regression analysis between continuous variables.
Variables R P
RHI – Age +0.153 0.194
RHI – carotid IMT - 0.411 0.000
RHI – AI -0.071 0.549
RHI – AI@75 -0.017 0.885
RHI – NIHSS score -0.061 0.605
AI – Age +0.243 0.037
AI – carotid IMT +0.085 0.437
AI – NIHSS score -0.270 0.020
AI@75 – Age +0.309 0.007
AI@75 – carotid IMT +0.029 0.808
AI@75 – NIHSS score -0.238 0.041

Discussion

The main results of this study are that the patients with cardioembolic strokes had higher values in the endothelial function assesses by RHI than the lacunar and large-artery atherosclerotic strokes. Patients with history of HTN had an AI and AI@75 higher than non hypertensive patients.

Despite widespread use in clinical research, the methods used for the assessment of endothelial function are not adequately standardized. The non-invasive EndoPAT technology was used for evaluating peripheral ED. This method was applied previously in other clinical studies 14, 15. The third-generation Framingham Heart Study tested an association between peripheral vascular function determined by fingertip peripheral tonometry device and cardiovascular risk factors 16. Notably, the RHI signal recorded by Endo-PAT is not limited to endothelium-dependent vasodilation but also includes endothelium-independent signals induced by ischemia.

ED is an important link between risk factors and atherosclerosis. It is considered to be an integral component of atherosclerotic vascular disease and its presence is a risk factor for the development of clinical event. Decreased endothelial function may reduce vascular compliance, which is related to increased arterial stiffness and correlates with cardiovascular events 17. Thus, increased arterial stiffness may be a mechanism by which ED predisposes to complications of atherosclerosis 18.

A systematic review of endothelial function in stroke have shown than ED is present in patients with lacunar stroke but may simply reflect exposure to vascular risk factors and having a stroke, because a similar degree of dysfunction is found in large-artery atherosclerotic strokes 7. Large-artery atherosclerotic infarcts are also associated with ED 19.

Chlumsky et al. 9 measured carotid IMT and FMD in patients with ischemic strokes and evaluated if there was a relationship between these measurements and the presence of atrial fibrillation. Patients with atrial fibrillation had lower IMT values compared with patients without atrial fibrillation and better FMD results. Compliance increased in patients with atrial fibrillation compared with patients without atrial fibrillation. They concluded that measuring IMT, compliance and FMD might be helpful in the differentiation between stroke of embolic and thrombotic aetiology. Our data show than endothelial function too is different between aterothrombotic and cardioembolic aetiologies, but the arterial stiffness is similar. A systematic review of ED in lacunar strokes revealed that ED might be involved in the pathogenesis of lacunar stroke, especially in those patients with concomitant silent lacunar infarcts and ischemic white matter lesions 20.

ED assessed by FMD has been proposed as an independent predictor for a new-onset vascular event after first-ever ischemic stroke 21. Another study measured with FMD showed that ED is similar in patients with recent acute and stable cerebrovascular disease 22. Rundek et al. 4 found a significant association between endothelial dysfunction and presence of carotid plaque in a population-based cohort.

Noon et al. 23 showed by applanation tonometry that women had a higher degree of arterial stiffness than men of a similar age. The majority of women were over 40 years, providing the possibility of postmenopausal effects on arterial compliance. These data are congruent with us results. Mitchell et al. 24 studied in a healthy sample with no evidence of cardiovascular disease and low burden of risk factors, an age-related increase in arterial stiffness. We have found similar results with an increase of arterial stiffness with age.

Treatment with Atorvastatin has shown an improvement of FMD values in patients with lacunar infarcts and patients with risk factors but without stroke 25. One study showed than endothelial nitric oxide synthase gene is a modifier of the cerebral response to ischemia 26 and in obese patients the endothelial function is related with thrombolysis 27. There are no physiopatological reasons for think that the administration of Alteplase could change the results in endothelial reactivity.

Our study has some limitations: Firstly, the small sample size and the fact that our study was not a control group mean that our conclusions must be treated with caution. Secondly, we were unable to withdraw some medications for more than five half-lives before the stroke. The beneficial effects on vasoreactivity of these medications might be confounding. And finally, we did not study the underlying mechanisms of endothelial dysfunction as analysis of endothelin or other substances as circulating endothelial cells 28.

In conclusion, this study demonstrates that in the acute phase of ischemic cerebrovascular diseases the endothelial function assessed by EndoPAT technology is different between the stroke subtypes with higher values in cardioembolic infarcts and patients with arterial hypertension had higher values of arterial stiffness than non hypertensive patients.

Funding:

This study was supported by grants from the Aid for Basic and Applied Research in the area of Neuroscience from the Extremeña Neurological Society.

References

  1. 1.Scherbakov N, Sandek A, Martens-Lobenhoffer J. (2012) Endothelial dysfunction of the peripheral vascular bed in the acute phase after ischemic stroke. , Cerebrovasc Dis 33, 37-46.
  1. 2.Davignon J, Ganz P. (2004) Role of endothelial dysfunction in atherosclerosis. , Circulation 109, 27-32.
  1. 3.Juonala M, JSA Viikari, Laitinen T. (2004) Interrelations between brachial endothelial function and carotid Intima-Media thickness in young adults. The cardiovascular risk in young Finns study. , Circulation 110, 2918-2923.
  1. 4.Rundek T, Hundle R, Ratchford E. (2006) Endothelial dysfunction is associated with carotid plaque. A cross-sectional study from the population based Northen Manhattan Study. , BMC Cardiovasc Disord 6, 35.
  1. 5.Bonetti P O, Pumper G M, Higano S T. (2004) Noninvasive identification of patients with early coronary atherosclerosis by assessment of digital reactive hyperemia. , J Am Coll Cardiol 44, 2137-2141.
  1. 6.Chen P L, Wang P Y, Sheu W H. (2006) Changes of brachial flow-mediated vasodilatation in different ischemic stroke subtypes. , Neurology 67, 1056-1058.
  1. 7.Stevenson S F, Doubal F N, Shuler K. (2010) A systematic review of dynamic cerebral and peripheral endothelial function in lacunar stroke versus controls. Stroke 41:e434-e442.
  1. 8.Kim J S, Lee H S, Park H Y. (2009) Endothelial function in lacunar infarction. A comparison of lacunar infarction, cerebral atherosclerosis and control group. , Cerebrovasc Dis 28, 166-170.
  1. 9.Chlumsky J, Charvat J. (2005) Endothelial dysfunction distensibility and intima-media thickness and aetiology of stroke. , Inter Med Res 33, 555-561.
  1. 10.Kasner S E. (2006) Clinical interpretation and use of stroke scales. , Lancet Neurol 5, 603-612.
  1. 11.Touboul P J, Hennerici M G, Meairs S. (2004) . Advisory Board of the 3rd Watching the Risk Symposium 2004, 13th European Stroke Conference. Cerebrovasc Dis 18, 346-349.
  1. 12.Kuvin J T, Mammen A, Mooney P. (2007) Assessment of peripheral vascular endothelial function in the ambulatory setting. , Vasc Med 12, 13-16.
  1. 13.Gatzka C D, Cameron J D, Dart A M. (2001) Correction of carotid augmentation index for heart rate in elderly essential hypertensives. ANBP2 Investigators. Australian Corporative Trial of Angiotensin-Converting Enzyme Inhibitor and Diuretic-based Treatment of hypertension in the elderly. , Am J Hypertens 14, 573-577.
  1. 14.Peled N, Bendayan D, Shitrit D. (2008) Peripheral endothelial dysfunction in patients with pulmonary arterial hypertension. , Respir Med 102, 1791-1796.
  1. 15.Rubinshtein R, Kuvin J T, Soffler M. (2010) Assessment of endothelial function by non-invasive peripheral arterial tonometry predicts late cardiovascular adverse events. , Eur Heart J 31, 1142-1148.
  1. 16.Hamburg N M, Keyes M J, Larson M G. (2008) Cross-sectional relations of digital vascular function to cardiovascular risk factors in the Framingham Heart Study. , Circulation 117, 2467-2474.
  1. 17.Wang Y X. (2007) Do measures of vascular compliance correlate wit endothelial function?. , Curr Diab Rep 7, 265-268.
  1. 18.Correia M L, Haynes W G. (2007) Arterial compliance and endothelial function. , Curr Diab Rep 7, 269-275.
  1. 19.Newby D E, McLeod A L, Uren N G. (2001) Impaired coronary tissue plasminogen activator release is associated with coronary atherosclerosis and cigarette smoking. Direct link between endothelial dysfunction and atherotrombosis. , Circulation 103, 1936-1941.
  1. 20.ILH Knottnerus, Cate H T, Lodder J. (2009) Endothelial dysfunction in lacunar stroke: A systematic review. , Cerebrovasc Dis 27, 519-526.
  1. 21.Santos-García D, Blanco M, Serena J. (2011) Impaired braquial flow-mediated dilation is a predictor of a new-onset vascular event after stroke. , Cerebrovasc Dis 32, 155-162.
  1. 22.Beer C D, Potter K, Blacker D. (2010) Systematic vascular function, measured with forearm flow mediated dilatation, in acute and stable cerebrovascular disease. A case-control study. , Cardiovasc Ultrasound 8, 46.
  1. 23.Noon P, Trischuk T C, Gaucher S A. (2008) The effect of age and gender on arterial stiffness in healthy Caucasian Canadians. , J Clin Nurs 17, 2311-2317.
  1. 24.Mitchell G F, Parise H, Benjamin E J. (2004) Changes in arterial stiffness and wave reflection with advancing age in healthy men and women. The Framingham Heart Study. , Hypertension 43, 1239-1245.
  1. 25.Pretnar-Oblak J, Sabonic M, Sebestjen M. (2006) Influence of Atorvastatin treatment on L-Arginine cerebrovascular reactivity and Flow-mediated dilatation in patients with lacunar infarcts. , Stroke 37, 2540-2545.
  1. 26.Dutra A V, Lin H F, Juo S H. (2006) Analysis of the endothelial nitric oxide synthase gene as a modifier of the cerebral response to ischemia. , J Stroke Cerebrovasc Dis 15, 128-131.
  1. 27.Abe K. (2012) An emerging topic on obesity, arterial endothelial function and thrombolysis. , J Stroke Cerebrovasc Dis 21, 159-160.
  1. 28.Woywodt A, Gerdes S, Ahl B. (2012) Circulating endothelial cells and stroke: influence of stroke subtypes and changes during the course of disease. , J Stroke Cerebrovasc Dis 21, 452-458.

Cited by (2)

  1. 1.Hansen Aina S., Butt Jawad H., Holm-Yildiz Sonja, Karlsson William, Kruuse Christina, 2017, Validation of Repeated Endothelial Function Measurements Using EndoPAT in Stroke, Frontiers in Neurology, 8(), 10.3389/fneur.2017.00178
  1. 2.Cooper Leroy L., Wang Na, Beiser Alexa S., Romero José Rafael, Aparicio Hugo J., et al, 2021, Digital Peripheral Arterial Tonometry and Cardiovascular Disease Events: The Framingham Heart Study, Stroke, 52(9), 2866, 10.1161/STROKEAHA.120.031102