Carotid stenosis as a risk factor for ischemic stroke

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INTRODUCTION

Cerebrovascular diseases are leading in the statistics of reasons for mortality and disablement of adult employable population [1] and bringing a marked economic loss [2]. Among cerebrovascular diseases, cerebrovascular accidents (CVA) are to be seen as the major medico-social problem of international scale [3]. The modern status of the problem justifies the high importance of studying the risk factors of stroke development, development of new and improvement of existing methods of diagnostics [4], treatment and prevention of this condition [5]. According to the WHO data, diseases of the circulation organs due to atherosclerosis become the reason of death of more than 16 million people every year; and the prevalence of ischemic stroke associated with atherosclerosis among patients aged 50–55 increases by 1.8–2.0 times in every successive decade of life. Within 12 months from the old CVA, 40-45% patients die [6], every fifth patient develops a second stroke in the successive years [7]. Among survivors, up to 90% of patients become disabled [1], and 20% of them would require nursing care [8]. Less than 10% of patients would be able to return to labor and regular life after a stroke [9]. Modern clinical practice of management of stroke patients sees its primary and secondary prevention as priorities. A complex study of factors relevant to the risk of stroke development will enable a more efficient approach to prevention of this disease [10].

The pathogenic mechanism of ischemic stroke (IS) is the hypoxia of the brain that can be aggravated with various comorbidities [11], including carotid stenosis [12]. Underlying diseases may acts as isolated or complex risk factors for the development of stroke, and their therapy is the basis for the primary and secondary prevention of the stroke [13]. One of the most significant reasons for the development of chronic hypoperfusion of the brain is the lesion of the great vessels [14], including constrictive lesions of the major arteries of the head and neck [15].

The carotid arteries play a major role in the formation of the total volume of cerebral circulation [16], providing for approx. 75% of cerebral blood flow [17]. Since the stenosis of the carotid artery due to atherosclerosis disrupts the normal cerebral blood flow, it surely increases the risk of CVA. In 80% of the cases, the atherosclerotic process affects the area of bifurcation of the arteria carotis communis, and multiple atherosclerotic lesions are seen much more often that isolated ones. Therefore, the stricture formation of the extracranial sections of the carotid arteries by an atherosclerotic plaque is the most frequent reason of defects of perfusion of the brain tissue, which might be accompanies with chronic [18] and acute cerebrovascular circulation deficiencies [19].

Atherosclerotic carotid plaques are often found in elderly patients and individuals with a high risk of other cardiovascular diseases. The stenosis of the carotid artery, as a rule, us the consequence of systemic atherosclerosis, and its prevalence demonstrates an age-associated dynamic and is seen in approx. 7.5% men and 5% women aged over 80 [20]. There are many risk factors contributing to atherosclerosis, namely, smoking, hyperlipidemia, male sex, age that may increase the risks of stenosis of the carotid artery. A plaque occupying over 50% of the carotid arterial lumen is considered to cause substantial constriction of the vessel known as hemodynamically significant stenosis of the carotid artery [21], which may be accompanied with clinically relevant decrease of brain tissue perfusion with blood [22]. Patients with severe stenosis of the carotid artery demonstrate higher degrees of cardiac accidents and mortality; with asymptomatic carotid stenosis of over 75% of the lumen, the risk of the stroke is 5.5% per year; with asymptomatic stenosis of 60% of the vessel lumen, 11% over 5 years. The lesions of carotid arteries are related to a third of all strokes. This data shows the importance of early diagnosis and treatment of carotid stenosis to prevent complications such as CVA [23].

Despite the numerous studies of various aspects of epidemiology, pathogenic mechanisms, diagnostics and prevention of IS, there are some problems the solution of which would allow a more efficient prognosis of the outcome [24] and improve prevention of CVA in these patients [25]. One of the aspects that is still needs more research are the specifics of risks of development of first and second ischemic stroke associated with carotid stenosis of different degrees or associated with other risk factors.

MATERIAL AND METHODS

An open retrospective study was conducted to assess risk factors for primary and recurrent stroke in patients with carotid stenosis of varying severity. The subjects of the study were 606 patients who were treated in neurological departments, as well as patients who sought outpatient care. The study included 292 women (48.2%) and 314 men (51.8%) aged from 39 to 89, the median age of patients being 67.4 (84.25; 50.56) years. The study was conducted in accordance with the standards of good clinical practice and the principles of the Declaration of Helsinki. The study protocol was approved by the ethics committee of the Federal State Budgetary Educational Institution of Higher Education SSMU of the Ministry of Health of Russia, written informed consent was obtained from all patients before participating in the study.

Depending on the degree of stenosis of the major vessels of the head and the neck (based on the stenosis degree evaluation method NASCET – North American Symptomatic Carotid Endarterectomy Trial), the patients were divided into three groups (Table 1). In 446 patients (73.6% of the total number of patients within the study), stenosis was identified without hemodynamically significant damage to the major vessels of the head and the neck (stenosis of 0–49%), in 85 patients (14.0%) stenosis was between 50–69%, and the group of patients with stenosis damage of 70% and above included 75 people (12.4%).

 

Age	0–49%		50–69%		≥ 70%		Total
	Abs.	%	Abs.	%	Abs.	%	Abs.	%
below 50	37	8,3	1	1,2	1	1,3	39	6,4
50–59 y.o.	86	19,3	17	20,0	15	20,0	118	19,5
60–69 y.o.	142	31,8	19	22,4	35	46,7	196	32,4
70–79 y.o.	123	27,6	28	32,9	14	18,7	165	27,2
80 and above	58	13,0	20	23,5	10	13,3	88	14,5
TOTAL	446	100,0	85	100,0	75	100,0	606	100,0

Table 1. Distribution of patients depending on the carotid stenosis severity

Таблица 1. Распределение пациентов в зависимости от степени выраженности каротидного стеноза

 

The pathogenic subtype of the ischemic stroke was identified using the TOAST criteria, Trial of ORG 10172 in Acute Stroke Treatment (1993): atherothrombotic, cardioembolic, lacunar, or of other identified ethiology.

At the same time, the patients were divided into three comparative groups: no history of stroke; one stroke; two cases of IS and more (Table 2).

 

Patient group	Carotid stenosis of 0– 49% (n, %)	Carotid stenosis of 50–69% (n, %)	Carotid stenosis of ≥ 70% (n, %)
No stroke history	223 (36,8%)	10 (1,6%)	3 (0,5%)
First stroke	134 (22,1%)	47 (7,8%)	20 (3,3%)
Second stroke	89 (14,7%)	28 (4,6%)	52 (8,6%)
TOTAL	446 (73,6%)	85 (14,0%)	75 (12,4%)

Note: n – total number; % – relative number from the total number of patients within the study.

Table 2. Distribution of patients into study groups

Таблица 2. Распределение пациентов по группам сравнения

 

The comparison of study groups was performed against the fact of history of first or second IS. In post-stroke patients, the size of the ischemic site was assessed using computed tomography (CT) scans of the brain, manifestation of the neurologic impairment using the NIHSS scale (National Institutes of Health Stroke Scale) and the degree of its restoration, functional outcome of IS (Rankin scale, Rivermead index). The study did not include patients with hemorrhagic stroke and patients with adverse outcome of disease.

All patients were examined by a neurologist and underwent computed tomography (CT) of the brain with contrast enhancement or CT angiography as indicated. Other examinations included ultrasonic dopplerography of the brachiocephalic arteries (BCA USDG), duplex ultrasonic scanning (DUSS) of the vessels of the head and the neck combined with color flow mapping (CFM). If necessary, other studies, analyzes and consultations with relevant specialists were carried out. Patients with stroke received therapy in accordance with the standards of medical care for this disease, and a set of rehabilitation measures was also carried out as part of the first stage of rehabilitation.

The statistical analysis was performed using the SPSS Statistics software suite, Ver. 27. Both parametric and nonparametric statistical methods were used to analyze the data in the study. The parametric methods included a t-тест and regression analysis. Nonparametric methods were used to analyze data that did not meet the requirements of normality of distribution or homogeneity of variances and included the Mann-Whitney test and Wilcoxon’s test. The assessment of the distribution type was performed using the Shapiro-Wilt test and Kolmogorov-Smirnov test.

The study used logistic regression analysis to assess the relationship between the dependent variable (presence of primary or recurrent stroke) and a set of predictors, which were a set of clinical and instrumental data. Logistic regression was used to estimate the probability of the occurrence of primary or recurrent IS when changing the values of the predictors. The critical level of significance when testing statistical hypotheses was taken equal to 0.05.

RESULTS

Analysis of individual risk factors is not a sufficiently objective method for analyzing the risk of CVA in a patient, since a combination of them is observed, as a rule. From a practical point of view, the most promising thing is to study a set of clinical and instrumental indicators that correspond to the risk of developing a primary or recurrent stroke, which is a reflection of the effectiveness of primary / secondary prevention and requires special attention. The use of models considering a complex of clinical and instrumental parameters allows for a personalized approach towards assessment of their dynamics in the course of primary and secondary prevention.

Regression analysis of a complex of clinical and instrumental parameters of a group of patients without a history of stroke and with a history of stroke demonstrated the participation of a small number of regressors in the formation of the regression model (Table 3).

 

Variable	Coefficient (β)	Standard error	р-value	Odds ratio
Constant term	-0,537	0,079	-	-
Third-degree CHF	21,740	0,301	0,049	1,876
Stenosis on opposite side 50–69%	0,624	0,306	0,041	1,867

Table 3. Predictor values in the equation of clinical and instrumental indicators of groups of patients without a history of ischemic stroke and having a history of ischemic stroke in the carotid territory

Таблица 3. Показатели предикторов уравнения клинических и инструментальных показателей групп пациентов без ишемического инсульта в анамнезе и с перенесенным ишемическим инсультом в каротидном бассейне

 

The equation describing the probability of classification of clinical and instrumental indicators as matching the risk of development of the first stroke is as follows:

y= - 0,537+ 21,740*(3-degree CHF)+0,624*

(Stenosis on opposite side 50-69%)

The presence of significant concomitant diseases is a separate risk factor for the development of IS, but their presence aggravates the risks of stroke in patients with stenosis of 50–69%. Thus, the presence of hemodynamically significant carotid stenosis in the presence of a pronounced comorbid condition in the form of grade 3 CHF can be considered as an indication for its surgical treatment, since the risks of developing IS increase by 1.8 times. It is known that asymptomatic stenosis of 60% is accompanied by a probability of stroke within 5 years in only 11% of cases [23].

The quality of the proposed model can be characterized by the following indicators: -2Log-likelihood, Cox and Snell R Square and Nigelkerk R Square, the values of which were 966.893; 0.016 and 0.022, respectively.

Despite the completeness of the model, one cannot assert its high quality with respect to its specificity (Table 4). According to the general summary, the percentage of correctly identified states is only 62.6%.

 

Studied group	Without history of IS	With history of IS	Correct indications
Without history of ischemic stroke	433	22	95,2
With history of ischemic stroke	253	28	10,0

Table 4. Сlassification of clinical and instrumental parameters of patients without a history of ischemic stroke and having a history of ischemic stroke in the carotid territory

Таблица 4. Таблица классификации показателей клинических и инструментальных показателей пациентов из групп без ишемического инсульта в анамнезе и с перенесенным ишемическим инсультом в каротидном бассейне

 

Table 5 shows the parameters of the ROC-curve of the formed model (Fig. 1). It is to be noted that the model is not sufficiently reliable for use in clinical practice. Not all risk factors of stroke development are considered when building the module. This is indeed supported by the volume of data that was involved in the analysis. Thus, clinical and instrumental data were limited to the results of vascular ultrasound, CT scan of the brain, and the presence of concomitant diseases of the cardiovascular system.

 

Area	Standard error	Asymptotic significance	Asymptotic 95% confidence interval
			Lower threshold	Upper threshold
0,526	0,022	0,236	0,483	0,569

Table 5. The ROC curve area values when comparing clinical and instrumental indicators of patients without a history of ischemic stroke and having a history of ischemic stroke in the carotid territory

Таблица 5. Показатели площади под ROC-кривой при сравнении клинических и инструментальных показателей пациентов без ишемического инсульта в анамнезе и с перенесенным ишемическим инсультом в каротидном бассейне

 

Figure 1. The ROC curve for the differences between the group of patients without a history of ischemic stroke and having a history of ischemic stroke in the carotid territory.

Рисунок 1. ROC-кривая, отражающая различия между группой пациентов без ишемического инсульта в анамнезе и с перенесенным ишемическим инсультом в каротидном бассейне.

 

The next stage of the analysis was the study of factors influencing the occurrence of recurrent stroke, which can be interpreted as insufficient effectiveness of secondary prevention of ischemic stroke.

The major predictors involved in the increase of the risk of development of second stroke are shown in Table 6.

 

Variable	Coefficient (β)	Standard error	р-value	Odds ratio
Constant term	-20,000	1478,916	-	-
Rankin2	-0,366	0,196	0,042	0,693
HT above 181 mmHg	-3,564	1,685	0,034	0,028
Stenosis on the side of the site over 70%	-6,306	1,514	0,000	0,002
Stenosis on the opposite side over 70%	-5,700	1,661	0,001	0,003

Table 6. Predictors values in the equation of clinical and instrumental parameters of patients with primary and recurrent ischemic stroke in the carotid territory

Таблица 6. Показатели предикторов уравнения клинических и инструментальных показателей пациентов с первичным и повторным ишемическим инсультом в каротидном бассейне

 

The equation describing the probability of development of second stroke based on the analyzed complex of clinical and instrumental data is as follows:

y= - 20,0 - 0,366*(Rankin2) - 3,564* (Ht higher than 181 mmHg) - 6,306 (Stenosis on the focal side over 70%)- 5,700* (Stenosis on the opposite side over 70%)

The quality of the proposed model may be characterized with the following indicators: -2Log-likelihood, Cox and Snell R Square and Nigelkerk R Square, the values of which were 28.037; 0.595 and 0.975, respectively.

The performance indicators of the model are shown in Table 7. The model is characterized with a rather good sensitivity and specificity of classification of a complex of parameters. The total percentage of correctly classified conditions was 99.3%.

 

Study group	First stroke	Second stroke	Correct indications
First stroke	602	257	99,7
Second stroke	365	129	97,7

Table 7. Classification of clinical and instrumental parameters of patients with primary and recurrent ischemic stroke in the carotid territory

Таблица 7. Таблица классификации показателей клинических и инструментальных показателей пациентов c первичным и повторным ишемическим инсультом в каротидном бассейне

 

Table 8 shows the indicators of the ROC-curve of the formed model, and its graphical representation is shown on the graph (Fig. 2).

 

Area	Standard error	Asymptotic significance	Asymptotic 95% confidence interval
			Lower threshold	Upper threshold
1,000	0,000	0,000	0,999	1,000

Table 8. The ROC curve area values when comparing clinical and instrumental indicators of patients with primary and recurrent ischemic stroke in the carotid territory

Таблица 8. Показатели площади под ROC-кривой при сравнении показателей клинических и инструментальных показателей пациентов с первичным и повторным ишемическим инсультом в каротидном бассейне

 

Figure 2. The ROC curve showing the differences between the group of patients with primary and recurrent ischemic stroke in the carotid territory.

Рисунок 2. ROC-кривая, отражающая различия между группой пациентов с первичным и повторным ишемическим инсультом в каротидном бассейне.

 

It was revealed that patients with carotid stenosis of more than 70% after stroke have a high risk of developing a recurrent stroke. Thus, correction of changes in the vessels of the carotid territory should be considered as an important aspect of secondary prevention of IS.

Taking into account the critical role of the preventive approach in the management of neurological patients and the global medical and social significance of acute vascular pathology of the brain, continuous improvement of existing diagnostic and rehabilitation approaches is necessary [26, 27], as well as complex stratification of risks [28] in the development of the stroke [29, 30]. The introduction of methods for modeling the pathological process, including the use of regression analysis, provides prediction of the risk of stroke, and makes it possible to develop new approaches to effective prevention of patients with a combination of comorbidities [31, 32].

DISCUSSION

Carotid artery stenosis of varying severity as a comorbid condition and a serious medical problem is characterized by positive correlations with the age of patients and high cardiovascular risk and depends on a number of other factors, including, for example, smoking status, hyperlipidemia, and male gender. Therapy of carotid artery stenosis may include conservative medical and surgical methods, the most accessible of which are carotid endarterectomy [33] and carotid artery stenting [34]. Despite the fact that any of the therapeutic approaches is aimed at reducing the risk of cerebral ischemia and is an important aspect of primary and/or secondary prevention of IS, the decision on the tactics of surgical / endovascular intervention or the optimal choice in favor of conservative medical treatment remains controversial and difficult in many cases. Moreover, the level of restoration of neurological deficiency in the early post-stroke period, and, respectively, the rehabilitation potential directly depends on the severity of atherosclerotic changes of the major vessels of the neck and the head [35]. Therefore, a personalized approach to the evaluation of exceptional features of the clinical and demographical status of the patient, determination of the main and dependent risk factors and, in particular, the degree of influence of carotid stenosis on the course and prognosis of IS [36] will definitely improve the treatment outcomes, optimize care [37] and, in the future, reduce the probability of onset of cerebrovascular accidents [38].

CONCLUSIONS

The study found that hemodynamically significant stenotic lesions of the great vessels of the head and neck, with carotid stenosis values of 50-69%, significantly increase the risk of developing ischemic stroke (IS) when combined with cardiovascular system pathology. As a secondary prevention measure, it is crucial to focus on the degree of carotid stenosis. Mathematical models indicate that a stenotic lesion exceeding 70% significantly increases the likelihood of recurrent ischemic stroke (IS). Additionally, poor recovery from an initial stroke, as measured by the Rankin Scale, is a significant predictor of recurrent stroke.

Thus, carotid stenosis independently serves as a risk factor for the development of acute cerebrovascular accidents (CVA), a finding corroborated by several clinical studies. Studying the impact of a combination of factors on the likelihood of primary and recurrent ischemic stroke, manifesting against the backdrop of carotid stenosis, allows for a reduction in the risk of subsequent vascular events. It also facilitates a personalized approach to treatment strategy selection and helps determine the optimal timing for preparing patients for surgical interventions.

 

ADDITIONAL INFORMATION	ДОПОЛНИТЕЛЬНАЯ ИНФОРМАЦИЯ
Ethical expertise. Protocol No. 202 of the SamSMU Bioethics Committee meeting dated 09.10.2019.	Этическая экспертиза. Протокол №202 заседания комитета по биоэтике при СамГМУ от 09.10.2019.
Study funding. The study was the authors' initiative without external funding.	Источник финансирования. Работа выполнена по инициативе авторов без привлечения финансирования.
Conflict of Interest. The authors declare that there are no obvious or potential conflicts of interest associated with the content of this article.	Конфликт интересов. Авторы декларируют отсутствие явных и потенциальных конфликтов интересов, связанных с содержанием настоящей статьи.
Contribution of individual authors. I.E. Poverenova – developed the study idea. A.S. Tkachenko – developed the study idea, wrote the first draft of the manuscript. A.V. Zakharov – provided data analysis. I.V. Shirolapov, T.V. Romanova – wrote the first draft of the manuscript. S.A. Ananyeva, M.S. Sergeeva – provided detailed manuscript editing and revision. N.P. Romanchuk – wrote the first draft of the manuscript, provided data analysis. A. Khan – visualized the study results and conclusions. All authors gave their final approval of the manuscript for submission, and agreed to be accountable for all aspects of the work, implying proper study and resolution of issues related to the accuracy or integrity of any part of the work.	Участие авторов. И.Е. Повереннова – идея статьи. А.С. Ткаченко – идея статьи, написание текста. А.В. Захаров – анализ данных. И.В. Широлапов, Т.В. Романова – написание текста статьи. С.А. Ананьева, М.С. Сергеева – редактирование и корректировка ошибок. Н.П. Романчук – написание текста статьи, анализ данных. А. Хан – презентация результатов и выводов. Все авторы одобрили финальную версию статьи перед публикацией, выразили согласие нести ответственность за все аспекты работы, подразумевающую надлежащее изучение и решение вопросов, связанных с точностью или добросовестностью любой части работы.

About the authors

Irina E. Poverennova

Samara State Medical University

Email: i.e.poverennova@samsmu.ru
ORCID iD: 0000-0002-2594-461X

PhD, Professor, Head of the Department of Neurology and Neurosurgery

Russian Federation, Samara

Anastasiya S. Tkachenko

Samara State Medical University

Email: edition@innoscience.ru
ORCID iD: 0000-0002-1081-7140

a postgraduate student of the Department of Neurology and Neurosurgery

Russian Federation, Samara

Aleksandr V. Zakharov

Samara State Medical University

Author for correspondence.
Email: a.v.zaharov@samsmu.ru
ORCID iD: 0000-0003-1709-6195

PhD, Associate professor, Head of the Neurosciences Research Institute

Russian Federation, Samara

Igor V. Shirolapov

Samara State Medical University

Email: i.v.shirolapov@samsmu.ru
ORCID iD: 0000-0002-7670-6566

Associate professor, Head of the Laboratory of Translational Research and Personalized Medicine

Russian Federation, Samara

Tatyana V. Romanova

Samara State Medical University

Email: t.v.romanova@samsmu.ru
ORCID iD: 0000-0003-2851-8672

PhD, Professor, Department of Neurology and Neurosurgery

Russian Federation, Samara

Svetlana A. Ananeva

Samara State Medical University

Email: s.a.ananeva@samsmu.ru
ORCID iD: 0000-0002-2226-546X

PhD, Associate professor of the Department of Neurology and Neurosurgery

Russian Federation, Samara

Mariya S. Sergeeva

Samara State Medical University

Email: m.s.sergeeva@samsmu.ru
ORCID iD: 0000-0002-0926-8551

PhD, Associate professor, Leading specialist in the Neurosciences Research Institute

Russian Federation, Samara

Natalya P. Romanchuk

Samara State Medical University

Email: n.p.romanchuk@samsmu.ru
ORCID iD: 0000-0003-3522-6803

PhD, Associate professor, Leading specialist in the Neurosciences Research Institute

Russian Federation, Samara

Azizuddin Khan

Indian Institute of Technology Bombay

Email: khanaziz@iitb.ac.in
ORCID iD: 0000-0001-5113-4760

PhD, Professor of the Psychophysiology Laboratory Department of Humanities and Social Sciences

India, Mumbai

References

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