Научная статья на тему 'Neurological and neuroimaging factors associated with post-stroke fatigue over the second half year after acute cerebrovascular events'

Neurological and neuroimaging factors associated with post-stroke fatigue over the second half year after acute cerebrovascular events Текст научной статьи по специальности «Клиническая медицина»

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Ключевые слова
POST-STROKE FATIGUE / ACUTE CEREBROVASCULAR EVENTS / UNIVARIATE LOGISTIC REGRESSION ANALYSIS

Аннотация научной статьи по клинической медицине, автор научной работы — Delva I.I.

Post-stroke fatigue (PSF) is a common syndrome for stroke survivors. The study was aimed to identify clinical and neuroimaging factors associated with different PSF domains over the second half year after acute cerebrovascular events (ACE). There were examined 194 patients at 6, 9 and 12 months after ACE. Global PSF and PSF domains were measured by multidimensional fatigue inventory-20 scale. It had been identified the significant prevalence of global PSF and physical PSF in stroke patients in comparison with TIA. In univariate logistic regression analysis, in stroke patients it had been found reliable associations between MRS score and risk of global PSF as well as risk of PSF domains related to physical activity. Infratentorial infarcts were significantly associated with increased risk of global PSF and white matter lesion extension, according to Fazekas scale score, was directly associated with significant higher risk of mental and motivational PSF. Decreased post-stroke functional ability, infratentorial ischemic stroke location and leukoaraiosis grade could be prognostic factors for certain PSF domains over the second half year after ACE.

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Текст научной работы на тему «Neurological and neuroimaging factors associated with post-stroke fatigue over the second half year after acute cerebrovascular events»

14. Xu M, Xu M, Han L, Yuan C, Mei Y, Zhang H, Chen S, Sun K, Zhu B. Role for Functional SOD2 Polymorphism in Pulmonary Arterial Hypertension in a Chinese Population. Int J Environ Res Public Health. 2017; 14(3). pii: E266. doi: 10.3390/ijerph14030266.

РОЛЬ ГЕНЕТИЧЕСКОЙ ДЕТЕРМИНАНТЫ В РАЗВИТИИ СЕРДЕЧНО-СОСУДИСТЫХ РАССТРОЙСТВ У ПРЕЖДЕВРЕМЕННО РОДИВШИХСЯ ДЕТЕЙ Гончарь М.А., Бойченко А.Д. С целью исследования связи между полиморфными вариантами С786Т в гене эндотелиальной синтазы оксида азота (еNOS), T58C в гене митохондриальной супероксиддисмутазы (MnSOD2) и Ser49Gly в гене Р1-адренорецепторов (ADRB1) с риском развития кардиоваскулярных событий, обследовано 120 недоношенных детей в неонатальный период. Обнаружены ассоциативные связи по ряду значимых полиморфизмов генов еNOS (С786Т), MnSOD2 (Т58С) и ADRB1 @ет49О1у) с ранним развитием миокардиальной дисфункции у недоношенных детей в неонатальный период. Наличие генотипа GG полиморфизма гена ADRB1 можно считать предиктором развития гипокинетического режима центральной гемодинамики, а генотип СС полиморфизма гена MnSOD2 фактором риска формирования легочной гипертензии. Установлено наличие ассоциации между генотипом СС полиморфизма гена еNOS и сократительной способностью миокарда, интегральной функцией левого желудочка по индексу Тег Риск развития систоло-диастолической дисфункции правого желудочка выше у новорожденных с генотипом ОО полиморфизма гена ADRB1.

Ключевые слова: новорожденные, сердечнососудистые расстройства, полиморфизм гена эндотелиальной синтазы оксида азота, митохондриальная супероксиддисмутаза, ген р1-адренорецепторов.

Стаття надшшла: 29.12.17 р.

THE GENETIC DETERMINANT ROLE IN THE DEVELOPMENT OF CARDIOVASCULAR DISORDERS IN PRETERM

CHILDREN Gonchar M.O., Boichenko A.D.

In order to study the correlation between C786T polymorphic variants in the endothelial nitric oxide synthase (eNOS) gene, T58C in the mitochondrial superoxide dismutase (MnSOD2) gene and Ser49Gly in the pi-adrenergic receptor gene (ADRB1) with a risk of cardiovascular events, 120 preterm infants in the neonatal period were examined. Associated connections in a number of significant eNOS (C786T), MnSOD2 (T58C) and ADRB1 (Ser49Gly) genes polymorphisms with early development of myocardial dysfunction in preterm infants during the neonatal period have been identified. The presence of the GG genotype polymorphism of the ADRB1 gene can be considered as a predictor of the central hemodynamics hypokinetic regimen development, and the CC genotype polymorphism of the MnSOD2 gene as a risk factor causing pulmonary hypertension. The association between the CC genotype polymorphism of the eNOS gene and the contractile capacity of the myocardium is established, as well as the integral function of the left ventricle according to the Tei index. The risk of the right ventricle systolic and diastolic dysfunction is higher in newborns with the GG genotype polymorphism of the ADRB1 gene.

Key words: newborn, cardiovascular disorders, polymorphism of endothelial nitric oxide synthase genes, mitochondrial superoxide dismutase, p1-adrenergic receptor gene.

Рецензент: Похилько B.I.

DOI 10.26724/2079-8334-2018-4-66-51-56 UDC 616.831-005.1-036.86

NEUROLOGICAL AND NEUROIMAGING FACTORS ASSOCIATED WITH POST-STROKE FATIGUE OVER THE SECOND HALF YEAR AFTER ACUTE CEREBROVASCULAR EVENTS

E-mail: iryna.delva@gmail.com

Post-stroke fatigue (PSF) is a common syndrome for stroke survivors. The study was aimed to identify clinical and neuroimaging factors associated with different PSF domains over the second half year after acute cerebrovascular events (ACE). There were examined 194 patients at 6, 9 and 12 months after ACE. Global PSF and PSF domains were measured by multidimensional fatigue inventory-20 scale. It had been identified the significant prevalence of global PSF and physical PSF in stroke patients in comparison with TIA. In univariate logistic regression analysis, in stroke patients it had been found reliable associations between MRS score and risk of global PSF as well as risk of PSF domains related to physical activity. Infratentorial infarcts were significantly associated with increased risk of global PSF and white matter lesion extension, according to Fazekas scale score, was directly associated with significant higher risk of mental and motivational PSF. Decreased post-stroke functional ability, infratentorial ischemic stroke location and leukoaraiosis grade could be prognostic factors for certain PSF domains over the second half year after ACE.

Keywords: post-stroke fatigue, acute cerebrovascular events, univariate logistic regression analysis.

The present study was performed within the framework of the research project "Clinical and pathogenetic optimization of diagnosis, prognosis, treatment and prevention of complicated central nervous system's disorders and neurological impairments due to therapeutic pathologies" (state registration number 0116U004190).

Post-stroke fatigue (PSF) is a common syndrome for stroke survivors [1]. PSF exerts a negative impact on participation in physical activities and rehabilitation. Patients with PSF have difficulty in resuming social, familial, and professional activities. Evidences indicate that PSF is evolving multi-domain

© I.I. Delva, 2018

entity [1]. PSF has multidimensional causes varying depending on timing after stroke occurrence [12]. Understanding triggering factors for PSF development over different post-stroke periods has crucial importance for early prevention and effective PSF management. In our previous works we revealed that some neurological and neuroimaging factors have significant associations with certain PSF components within the first 3 months after stroke occurrence [2]. Moreover, to the best of our knowledge, up to now there has been no research on the clinical and neuroimaging determinants of certain PSF domains over the later periods after acute cerebrovascular events (ACE).

The purpose of this study was to identify clinical and neuroimaging factors associated with different PSF domains over the second half year after ACE occurrence.

Materials and methods. Initially we enrolled in the study 194 patients: 137 with ischemic strokes, 19 with hemorrhagic strokes and 38 with TIA. Patients were included in the study if they agreed to participate and were able to provide informed consent. Exclusion criteria were major medical illness that could cause secondary fatigue (oncological, hematological diseases, cardiac, liver, kidney and respiratory insufficiency, progressive angina pectoris, acute myocardial infarction), alcohol abuse, consciousness impairments, insufficient cognitive ability (Mini-Mental State Examination scores less than 24), depressive and anxious disorders (Hospital Anxiety and Depression Scale scores more than 10 for both pathologies), impaired speech function to participate (severe dysphasia or dysarthria), impaired language or written ability to complete the study questionnaire, severe functional disabilities (modified Rankin scale (MRS) scores >4).

Patients' characteristics had been evaluated consequently in definite time points: at 6, 9 and 12 months after ACE occurrence. During the third quarter of post-stroke year 21 patients (12 with ischemic stroke, 5 with hemorrhagic stroke, and 4 with TIA) and during the last quarter of post-stroke year 14 more patients (9 with ischemic stroke, 2 with hemorrhagic stroke and 3 with TIA) were dropped out due to different reasons. So, at 9 and 12 months after ACE we have examined 173 and 159 patients, respectively.

PSF was measured by self-report multidimensional fatigue inventory-20 (MFI-20) questionnaire which covers global, physical, mental, activity-related and motivational fatigue dimensions. A cut-off of 12 out of 20 for every sub-scale has been suggested for use with people with stroke.

For all stroke patients we recorded such clinical variables as affected cerebral hemisphere (right -left) and post-stroke functional disability (according to MRS score). Additionally, for ischemic stroke patients we recorded some specific variables - stroke subtype (non-lacunar - lacunar, according to TOAST criteria) and affected cerebral arterial region (carotid - vertebrobasilar).

Among enrolled patients 141 subjects underwent head magnetic resonance imaging (MRI) - 107 with ischemic strokes, 5 with hemorrhagic strokes and 29 with TIA. MRI studies were performed with a 1,5-T system (Siemens MAGNETOM Avanto 1.5T) and 0,2-T system (Signa Profile HD GE 0.2T).

For measurement of brain atrophy we used planimetrical indexes: bifrontal index (BFI), bicaudate index (BCI), maximum diameter of the third ventricle and cortical atrophy index (CAI) on T1 MRI sequence. BFI - maximum width of the anterior horns of the lateral ventricles in relation to the inner skull width at the same level. BCI - minimum width of the lateral ventricles in relation to the inner skull at the same level. CAI - sum of the width of the four widest sulci at the two highest scanning levels divided into maximum inner scull diameter.

White matter lesions derived from fluid-attenuated inversion recovery (FLAIR) imaging was graded from 0 to 3 on Fazekas scale on the basis of visual assessment both periventricular (0=absent, 1=caps or pencil lining, 2=smooth halo, and 3=irregular periventricular hyperintensities extending into deep white matter) and subcortical areas (0=absent, 1=punctuate foci, 2=beginning confluence of foci, and 3=large confluent areas). The total Fazekas scale score was calculated by adding the periventricular and subcortical scores [4]. Leukoaraiosis severity was graded according to the Fazekas scale as mild (1-2), moderate (3-4), and severe (5-6).

Continuous variables with parametric distribution (according to Shapiro-Wilk test) were represented as mean±standard deviation. Categorical data were represented by number (n) and percentage. Differences in categorical variables were compared using chi-square test. Univariate logistic regression analysis was performed to analyze the odds ratio (OR) with 95% confidence intervals (CI) of clinical and neuroimaging variables associated with PSF domains. P-value less 0,05 was taken to indicate statistical significance. Statistical analyses were performed using SPSS 14.0 statistics software.

Results of the study and their discussion. Patients' age ranged from 41 to 79 years (63,1±8,7 years). There were 93 (47,9%) males and 101 (52,1%) females.

As it can be seen from table 1, over the second half year after ACE occurrence it had been observed a significant increase of the risk of global PSF (probably, due to reliable increasing of the risk of physical PSF domain) in stroke patients in comparison with TIA patients. So, patients with strokes, in relation to TIA, had more common global PSF and physical PSF in all time points within the observation period: at 6 months - OR 4,37 (95% CI, 1,47-12,98; p=0,01) and OR, 3,91 (95% CI, 1,44-10,57; p=0,01), at 9 months - OR 3,59 (95% CI, 1,19-10,81; p=0,02) and OR 3,47 (95% CI, 1,15-10,46; p=0,03), at 12 months - OR, 4,08 (95% CI, 1,17-14,26; p=0,03) and OR 4,24 (95% CI, 1,22-14,78; p=0,02), respectively. Moreover, at 9 months after stroke mental PSF component was significant more frequently than after TIA (OR, 2, 87; 95% CI, 1,04-7,90; p=0,04).

Table 1

Frequencies of certain PSF domains over the second half year after ACE occurrence

PSF domain Time point after ACE occurrence

6 months 9 months 12 months

global

TIA, n (%) 4 (10,5%)* 4 (11,8%)* 3 (9,7%)*

stroke, n (%) 53 (34,0%) 45 (32,4%) 39 (30,5%)

physical

TIA, n (%) 5 (13,2%)* 4 (11,8%)* 3 (9,7%)*

stroke, n (%) 58 (37,2%) 44 (31,7%) 40 (31,3%)

mental

TIA, n (%) 6 (15,8%) 5 (14,7%)* 5 (16,1%)

stroke, n (%) 49 (31,4%) 46 (33,1%) 40 (31,3%)

motivational

TIA, n (%) 5 (13,2%) 4 (11,8%) 4 (12,9%)

stroke, n (%) 34 (21,8%) 30 (21,6%) 26 (20,3%)

activity-related

TIA, n (%) 5 (13,2%) 5 (14,7%) 3 (9,7%)

stroke, n (%) 41 (26,3%) 35 (25,2%) 29 (22,7%)

- significant difference (p<0,05) by chi-square test in comparison with stroke patients.

Table 2 shows patients' distribution according to their clinical characteristics. In patients with stroke univariate logistic regression analysis did not reveal any association between any PSF domain in all time points within the second half year after disease onset and all analyzed stroke characteristics (affected cerebral hemisphere, ischemic stroke subtype and affected cerebral arterial region for ischemic stroke).

Table 2

Clinical characteristics of stroke patients at the baseline

Affected cerebral hemisphere right 84 (53,8%)

left 72 (46,2%)

Ischemic stroke characteristics subtype non-lacunar 98 (71,5%)

lacunar 39 (28,5%)

affected cerebral arterial region carotid 90 (65,7%)

vertebrobasilar 47 (34,3%)

Table 3 demonstrates patients' distribution on the basis of functional limitation degree. Over the second half year after stroke occurrence there were some reliable associations between MRS score values and risk of global PSF as well as risk of such PSF domains that are just related to physical activity (physical PSF and activity-related PSF). Univariate logistic regression analysis showed that at 6 months after stroke the MRS score increment of 1 point was significantly associated with higher risk of global PSF (OR, 1,81; CI, 1,27-2,59; p=0,001), physical PSF (OR, 1,83; CI, 1,29-2,60; p=0,001) and activity-related PSF (OR, 1,53; CI, 1,06-2,22; p=0,02). In the same way, at 9 and 12 months after stroke occurrence identical values were - OR 1,91 (CI, 1,30-2,80; p=0,001), OR 1,95 (CI, 1,33-2,88; p=0,001), OR 1,57 (CI, 1,06-2,32;

p=0,03) and - OR 1,65 (CI, 1,11-2,47; p=0,01), OR 1,77 (CI, 1,18-2,65; p=0,01), OR 1,63 (CI, 1,06-2,51; p=0,03), respectively.

Table 3

Rates of MRS scores over the second half year after stroke occurrence

MRS score Time point after stroke occurrence

6 months 9 months 12 months

0 24 (15,4%) 31 (22,2%) 31 (24,2%)

1 54 (34,6%) 52 (37,4%) 45 (35,2%)

2 43 (27,6%) 32 (23,8%) 39 (30,5%)

3 35 (22,4%) 24 (16,6%) 13 (10,1%)

First of all, univariate logistic regression analysis did not reveal any reliable statistical regularities between frequencies of any PSF domain and any brain atrophy indexes (BFI, BCI, third ventricle diameter, CAI) over the second half year after ACE occurrence. On the other hand, it had been shown that cerebral infarcts of infratentorial locations were significantly associated with increased risk of global PSF at 6 months (OR, 3,19; CI, 1,34-7,58; p=0,01) and at 12 months (OR, 3,10; CI, 1,25-7,65; p=0,01) after disease occurrence. Moreover, univariate logistic regression analysis showed that the Fazekas scale score increment of 1 point was significantly associated with higher risk of mental PSF (OR, 1,49; CI, 1,11-2,00; p=0,01) at 6 months after ACE occurrence as well as with higher risk of mental PSF and motivational PSF in later observation time points - OR 1,56 (CI, 1,13-2,16; p=0,01) and OR 1,61 (CI, 1,11-2,34; p=0,01) at 9 months, OR 1,78 (CI, 1,24-2,55; p=0,002) and OR 1,64 (CI, 1,10-2,46; p=0,02) at 12 months, respectively.

Table 4

Neuroimaging characteristics of stroke patients at the baseline

Ischemic lesion location, n (%)

cortical-subcortical 33 (30,8%)

subcortical 38 (35,5%)

infratentorial 36 (33,7%)

Brain atrophy indexes

BFI 0,33±0,04

BCI 0,23±0,06

third ventricle diameter, mm 8,3±2,0

CAI 0,04±0,02

Fazekas scale score, n (%)

1 18 (12,8%)

2 38 (26,9%)

3 35 (24,8%)

4 33 (23,4%)

5 17 (12,1%)

The first finding is that in comparison with TIA, we can see the significant prevalence of global and physical PSF over the second half year after ACE occurrence. The same peculiarity we previously revealed within the first 3 months after ACE occurrence [6]. Possibly this phenomenon may be determined in some degree by post-stroke functional limitations (whereas TIA don't have any functional deficit) and by extended and permanent ischemic brain lesion due to stroke (PSF, at least partially, may be of central origin [11]).

In our study all neurological characteristics of stroke were not predictive of any PSF domain in any time point within the second half year after disease onset. In literature there are controversial data regarding connections between stroke features and PSF as whole entity. According to systematic review by Ponchel A. et al. in 11 studies it had not been discovered any connection between stroke site and PSF [7]. On the other hand, it should be noted studies that had shown relationships between PSF and vertebrobasilar stroke [4] and this phenomenon was explained by the lesion of ascending activating reticular formation in brainstem.

The second finding is the direct significant associations between decreased functional ability according to MRS score and risk of global PSF as well as risk of PSF domains that are related to physical activity (physical PSF and activity-related PSF). Whereas, to the above mentioned associations, our previous study showed also significant negative connections between MRS score and risk of mental PSF at 1 month as well as at 3 months after stroke [1]. Generally, literature data about post-stroke functional

status and PSF are quite contradictory - systematic review of factors that contribute to PSF identified 25 studies in which PSF was associated with greater disability and dependency, though this association was not detected in other 15 studies [7]. In any case, PSF is an independent contributor to post-stroke disability (maybe through the various behavioral impacts), so the effective early management of PSF might be an important step in post-stroke rehabilitation [5].

The third finding is some significant regularities between neuroimaging characteristics (ischemic stroke location, extent of white matter lesion) and increased risk of definite PSF domains over the second half year after ACE occurrence. Infratentorial infarcts were associated with increased risk of global PSF. In the same way, cerebral infarcts of infratentorial locations were significantly associated with increased risk of global PSF at 3 months after stroke. Our results support others who found an association between PSF and brainstem strokes and this phenomenon may be explained, according to authors, by the interruption of brainstem reticular activating system which is involved in attention [8]. Additionally, leukoaraiosis extension was directly associated with risk of mental PSF and motivational PSF over the second half year after ACE. Our results are supported by other work where the presence of leucoareosis on CT was independently associated with PSF at 6 months and later after ischemic and hemorrhagic strokes occurrence [6]. Generally, it's known the importance of white matter lesions in the pathophysiology of fatigue at all, for example in chronic fatigue syndrome was observed reduced white matter volume. It's well known that white matter lesions are directly connected with cognitive decline. Associations between leukoaraiosis severity and risk of mental PSF can be explained, at least partially, by the fact that persons with cognitive impairments try to compensate the cognitive deficits by making extra effort with subsequent faster tiredness. According to MFI-20, the essence of fatigue motivational component has close overlap with depressive signs. As known, white matter hyperintensities may contribute to the development of post-stroke depressive signs (and thus to risk of motivational PSF) as directly as well as indirectly through different mechanisms [3, 9].

1. Over the second half year after strokes, in comparison with TIA, it had been identified significant higher rates of global and physical PSF domains.

2. The MRS score was directly associated with significant higher risk of global PSF and of PSF domains related to physical activity (physical and activity-related PSF).

3. Infratentorial infarcts were associated with significantly increased risk of global PSF. 4. White matter lesion extension according to Fazekas scale score was directly associated with significant higher risk of mental and motivational PSF.

Future investigations in this field should be directed toward identification of clinical and neurological factors associated with general PSF as well as with certain PSF domains during later post-stroke periods.

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2. Delva I, Lytvynenko N, Delva M. Post-stroke fatigue and its dimensions within first 3 months after stroke. Wiadomosci Lekarskie. 2017; 1: 43-7.

3. Hommel M, Carey L, Jaillard A. Depression: Cognition relations after stroke. International Journal of Stroke. 2015; 10(6): 893-6.

4. Kutlubaev M, Shenkin S, Farrall A. CT and clinical predictors of fatigue at one month after stroke. Cerebrovascular Diseases. 2013; 3(1): 26-34.

5. Mandliya A, Das A, Unnikrishnan J. Post-stroke fatigue is an independent predictor of post-stroke disability and burden of care: a path analysis study. Topics in Stroke Rehabilitation. 2016; 23(1): 1-7.

6. Naess H, Lunde L, Brogger J. Fatigue among stroke patients on long-term follow-up. The Bergen Stroke Study. Journal of the Neurological Sciences. 2012; 312(1): 138-41.

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7. Ponchel A, Bombois S, Bordet R. Factors associated with post-stroke fatigue: a systematic review. Stroke Research and Treatment. 2015. Available from: Http://dx.doi.org/10.1155/2015/347920.

8. Snaphaan L, van der Werf S, de Leeuw F. Time course and risk factors of post-stroke fatigue: a prospective cohort study. European Journal of Neurology. 2011; 18: 611-7.

9. Tang W, Chen Y, Lu J. White matter hyperintensities in post-stroke depression: a case control study. Journal of Neurology, Neurosurgery and Psychiatry. 2010; 81(12): 1312-5.

10. Valdes Hernandez Model C, Morris Z, Dickie D. Close correlation between quantitative and qualitative assessments of white matter lesions. Neuroepidemiology. 2013; 40: 13-22.

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КЛ1ШКО-НЕВРОЛОГ1ЧШ ТА НЕЙРОВ1ЗУАЛ1ЗАЦШН1 ФАКТОРИ, АСОЦ1ЙОВАН1 З ПОСТШСУЛЬТНОЮ ВТОМОЮ НА ПРОТЯЗ1 ДРУГОГО П1ВР1ЧЧЯ П1СЛЯ РОЗВИТКУ ГОСТРИХ ПОРУШЕНЬ МОЗКОВОГО КРОВООБ1ГУ Дельва 1.1.

Постшсультна втома (П1В) - розповсюджене ускладнення гострих порушень мозкового кровообiгу (ГПМК). Метою роботи було iдентифiкувати клшчш та нейровiзуалiзацiйнi фактори, асоцiйованi з рiзними компонентами П1В на протязi другого пiврiччя пiсля розвитку ГПМК. Обстежено 194 пащенти через 6, 9 та 12 мюящв тсля ГПМК. Глобальну П1В та окремi 11 компоненти вимiрювали за допомогою багатомiрно!' шкали оцiнки втоми (МТР-20). Виявлена достовiрно вища розповсюдженiсть глобально! та фiзично!' П1В при шсультах, порiвняно з транзиторними iшемiчними атаками. В одновимiрному логiстичному регресiйному аналiзi знайдено достовiрнi асощацп мiж ступенем функцюнально! неспроможностi, згiдно модифковано! шкали Ренина, та ризиком наявност глобально! i фiзично! П1В. Наявнiсть iнфартенторiальних iнфарктiв асоцiювалася з пiдвищеним ризиком глобально! ШВ, а ступiнь лейкоареозу, зпдно шкали Фазекас, прямо асощювалася з пiдвищеним ризиком психiчно!' та мотивацшно! П1В. Рiвень функцiонально!' неспроможностЦ iнфратенторiальна локалiзацiя iнфарктiв та стутнь лейкоареозу можуть розглядатися як прогностичш фактори наявностi П1В протягом другого пiврiччя пiсля розвитку ГПМК.

Ключовi слова: постiнсультна втома, гострi порушення мозкового кровообiгу, одновимiрний логiстичний регресшний аналiз.

Стаття надiйшла 21.11.17 р.

КЛИНИКО-НЕВРОЛОГИЧЕСКИЕ И НЕЙРОВИЗУАЛИЗАЦИОННЫЕ ФАКТОРЫ, АССОЦИИРОВАННЫЕ С ПОСТИНСУЛЬТНОЙ УСТАЛОСТЬЮ НА ПРОТЯЖЕНИИ ВТОРОГО ПОЛУГОДИЯ ПОСЛЕ РАЗВИТИЯ ОСТРЫХ НАРУШЕНИЙ МОЗГОВОГО КРОВООБРАЩЕНИЯ Дельва И.И.

Постинсультная усталость (ПИУ) - распространенное осложнение острых нарушений мозгового кровообращения (ОНМК). Целью работы было идентифицировать клинические и нейровизуализационные факторы, ассоциированные с разными компонентами ПИУ на протяжении второго полугодия после развития ОНМК. Обследовано 194 пациента через 6, 9 и 12 месяцев после ОНМК. Глобальную ПИУ и отдельные ее компоненты измеряли с помощью многомерной шкалы оценки усталости (М1Б-20). Выявлена достоверно большая

распространенность глобальной и физической ПИУ при инсультах, в сравнении с транзиторными ишемическими атаками. В одномерном логистическом регрессионном анализе найдены достоверные ассоциации между степенью функциональной несостоятельности, согласно

модифицированной шкале Рэнкина, и риском глобальной и физической ПИУ. Инфартенториальные инфаркты прямо ассоциировались с повышенным риском глобальной ПИУ, а степень лейкоареоза, по шкале Фазекас, - с повышенным риском психической и мотивационной ПИУ. Уровень функциональной несостоятельности, инфратенториальная локализация инфарктов и степень лейкоареоза могут рассматриваться в качестве прогностических факторов наличия ПИУ на протяжении второго полугодия после развития ОНМК.

Ключевые слова: постинсультная усталость, острые нарушения мозгового кровообращения, одномерный логистический регрессионный анализ.

Рецензент Литвиненко Н. В.

DOI 10.26724/2079-8334-2018-4-66-56-62 УДК 616-022.854-092.19-085.218.373(477.4)(477.8)

ANALYSIS OF SENSITIZATION FEATURES TO WEED POLLEN AND EFFICACY OF ALLERGEN IMMUNOTHERAPY IN PATIENTS OF THE CENTRAL AND WESTERN REGIONS IN UKRAINE

E-mail: svitlana_zu@meta.ua

Incidence of sensitization is changing geographically based on multiple environmental factors. About 1.5 thousand different types of weeds are common in Ukraine. Climatic and geographical conditions such as air temperature, humidity and plant diversity in the region is of great importance in the prevalence of allergic diseases. Allergy to weeds is a global problem due to development of respiratory allergy - seasonal allergic rhino-conjunctivitis (hay fever) with/without bronchial asthma in patients living in Ukraine. Allergen immunotherapy is a disease-modifying treatment for patients with seasonal hay fever with/without bronchial asthma. However, in Ukraine there are little data on the efficacy of sublingual form of allergen immunotherapy. The use of standardized sublingual immunotherapy is efficient in treating patients with seasonal hay fever with/without bronchial asthma.

Keywords: Ambrosia. Artemisia. molecular allergodiagnosis, VAS, SLIT efficacy.

The present study is a fragment of the research project "Peculiarities of allergic genesis diseases formation in children of all ages and the possibilities of their prevention and treatment" (State Registration No. 0111U002801)

There are over 1.5 thousand types of weeds on the territory of Ukraine. They not only significantly pollute agricultural land - some of them possess strong allergenic activities [5]. Allergy to weed pollen is considered the late wave of hay fever, which usually begins in the second half of summer (end of July to August) and lasts until the first frosts [9]. However, today these data are relative due to global warming

© S.O. Zubchenko, O. Sharikadze, 2018

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