View of Comparison of Erythrocyte Morphological Markers in Patients with the First Ischemic Cerebrovascular Attack

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Comparison of Erythrocyte Morphological Markers in Patients with the First Ischemic Cerebrovascular Attack

Ramin Parvizrad

¹

, Fatemeh Majidi

²

, Alireza Rezaee Ashtyani

³

, Somayeh Nikfar

^4*

1Department of Emergency Medicine, School of Medicine, Arak University of Medical Sciences, Arak, Iran.

2Department of Cardiology, Dr Shariati Hospital, Faculty of Medicine, Tehran University of Medical Sciences, Tehran, Iran.

3Department of Neurology, School of Medicine, Arak University of Medical Sciences, Arak, Iran

4*Department of Gynecology, School of Medicine, Arak University of Medical Sciences, Arak, Iran.

E-mail: [email protected]

ABSTRACT

Background & Objective: Stroke is the third leading cause of death in the world. Preventive and therapeutic approaches in this field are weak and further understanding of molecular mechanisms helps to diagnose and treat more effectively.

Methodology: This case-control study was conducted on 55 patients with ischemic stroke and 55 healthy individuals as a control group. The control group was collected from the staff and patients admitted to Valiasr Hospital in other wards. Demographic variables of the two groups were homogenized and then venous blood samples were taken to measure biochemical levels and complete blood counts.

Results: The mean age of patients was 69.98 years. The mean serum cholesterol level in patients was 157.1 mg/dL and it was 121.5 mg/dL in the control group and there was a statistically significant difference between the two groups (P <0.05). MCV was 88.5 in patients and 83.2 in the control group with a statistically significant difference.

Systolic and diastolic blood pressure were also significantly higher in patients. In addition, serum ferritin and iron levels and hemoglobin were significantly associated with stroke severity (P <0.05).

Conclusion: The results of this study showed the relationship between erythrocyte morphology and stroke and based on this, more prospective studies can be recommended to evaluate the relationship between erythrocyte morphological markers and practical ways to prevent stroke.

KEYWORDS

Ischemic Stroke, Red Blood Cells, Mean Corpuscular Volume.

Introduction

Stroke is the third leading cause of death in the world after heart disease and cancer, and is emerging as the most common and life-threatening neurological problem worldwide (1). On average, every 4 minutes, someone dies of stroke (2). The prevalence of stroke is generally 2.8% and it is 2.7% in Asia (3). The incidence of stroke in Iran, which is a middle-income country, is significantly higher than in Western countries (4).

Worldwide, approximately 70% of strokes and 87% of deaths from stroke and disability occur in low- and middle-income countries (5, 6). Over the past few decades, the incidence of stroke has multiplied in low- income and middle-income countries, while it has fallen by 42% in high-income countries (5).

To prevent stroke, examining the underlying factors of stroke and its treatment can play an important role in reducing mortality (7-9). There is no difference between the prevention of subsequent stroke in a patient with symptomatic or asymptomatic stroke and in a patient with a transient ischemic attack (9).

Findings have shown that preventive and therapeutic approaches in this field are weak and more understanding of molecular mechanisms and prognostic indicators helps to diagnose and treat more effectively (10) and the important issue is to identify prognostic indicators and risk factors (11, 12).

Known risk factors include hypertension, hyperlipidemia and smoking, diabetes, obesity, and a family history of stroke (13-15). In Iran, risk factors such as hypertension and overweight are strong independent predictors of stroke (16). However, cerebrovascular accidents can sometimes occur in people who do not have any of these risk factors, as a result, there are likely to be other risk factors (13, 14).

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Identifying prognostic indicators can help prevent cerebrovascular disease. Pathophysiologies such as atherosclerosis, endothelial dysfunction (17), ferritin, iron and homocysteine levels have been reported in stroke (18-22). Vitamins B9 and B12 are important regulators of homocysteine metabolism. The association of homocysteine with other blood factors in stroke has been proven (23, 24). In addition, it is important to pay attention to micronutrients and factors affecting blood factors because of their role in blood cell morphology (20, 24).

According to the above, the study aimed to identify the rapid and inexpensive predictor of ischemic cerebral attacks and possibly other risk factors by focusing on morphological markers of blood cells.

Materials and Methods

Study Design

This case-control study was conducted on patients with ischemic stroke admitted to the emergency department of Valiasr Hospital with the diagnosis of the first ischemic stroke during March 2016 to March 2017. Eligible patients were included in the study. One hundred and ten patients were divided into two groups of case and control and studies were carried out on them.

Inclusion and Exclusion Criteria

Inclusion criteria were the first ischemic stroke with diagnosis of the emergency medicine attend and confirmation by imaging methods and consent of patients or their companions. Exclusion criteria were individuals with chronic illness, insertion of any invasive device, endarterectomy, stent, thrombectomy or any intravascular treatment of the carotid artery in the last 30 days, general anesthesia or hospitalization equal to or more than 3 days during the last two weeks, receiving lipid-lowering medications, taking medications that affect homocysteine levels in the last 30 days (methotrexate, tamoxifen, levodopa, niacin), any megaloblastic anemia being treated, and a history of taking supplements and vitamins in the last six months.

Patient Selection

Patients were selected by convenience sampling and the sample size was calculated 55 people for each group based on α = 0.05, a generalizable ratio to the population of 84% using the following formula. 55 patients with ischemic stroke and 55 healthy individuals were classified as the control group (110 in total).

Method Description

Patients with a possible diagnosis of stroke based on clinical signs were included in the study and were considered as the case group after following the usual diagnostic and therapeutic measures if the type of cerebrovascular accident was diagnosed as ischemic type, while examining the inclusion criteria if approved by an emergency medicine specialist. The control group was collected from the staff and patients admitted to Valiasr Hospital in other wards. Demographic variables of the two groups were homogenized and then venous blood samples were taken for biochemical measurement and complete blood count.

Data Collection

Basic information of each patient was entered in the questionnaire. and at the same time, MRS questionnaire (Modified Rankin Scale) and MMS questionnaire (Mini Mental State Exam) and nutritional status checklist (Mini Nutritional Assessment) and NIH stroke scale evaluation form of patients with inclusion criteria were completed. The study was continued until the sample size was equal to or greater than 55 and, at the same time, the control group was selected from other patients who were hospitalized for other reasons by homogenizing in terms of age, sex and risk factors, especially diabetes and dyslipidemia.

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Biochemical Study

At the time of admission to the neurology ward, 5 cc of fasting blood samples were taken to measure blood factors and levels of cr, TG, Chol. Level (HDL, total, LDL), complete blood cell count (CBC) and iron profile were obtained and sent to the reference laboratory.

In complete blood cell count (CBC), quantitative values of erythrocyte indices such as RBC count, hemoglobin concentration (Hb), hematocrit percentage (HCT), mean cell volume (MCV), mean cell hemoglobin (MCH), mean cellular hemoglobin concentration (MCHC), red blood cell distribution width (RDW) as well as differential count and number of white blood cells and platelet indices were determined in the same way by cell counter device (Horiba, made in Japan).

Ethical Considerations

Written consent was completed by the patients and the confidentiality of all information obtained from the research units was guaranteed. The cost of iron profile tests was requested with the patients' consent and no additional costs were imposed on the patients.

Data Analysis

After entering the data into SPSS.v22, the data were analyzed by drawing tables and graphs and using Chi- square and t-test and logistic regression test. A P-value of less than 05.0 was considered significant.

Findings

The two groups were similar in terms of primary demographic characteristics. The mean age of the total patients was 69.98 ± 14.28 years (it was 69.92.86 ± 14.61 and 70.07 ± 13.65 in the control and case groups, respectively) (Table 1). Comparison of qualitative indices between the two groups based on the hypothesis of equality in the study showed that the two groups had the same distribution in terms of age, sex, level of education, smoking, history of cardiovascular disease and taking medications and they had no statistically significant difference (p≥ 0.05).

Table 1. Frequency distribution of some demographic characteristics in all samples Percentage Number/Mean

Parameter Variable

69,98±14,28 Total

Age

27,5±4,08 Total

Body mass index

60.9 67

Female Sex

39.1 43

Male

67.3 74

Primary

Education Diploma 7 6.4

24.5 27

Other

1.8 2

Unknown

14.5 16

Blood pressure

Underlying disease

16.4 18

Diabetes

1.8 2

Peripheral vascular disease

.9 1

Carotid artery stenosis

25.5 28

Blood pressure and diabetes

1.8 2

Several diseases

39.1 43

None

90.9 100

Non-smoker

Smoking Occasionally 4 3.6

5.5 6

Continuously

According to Table 2, comparison of laboratory findings showed that the mean systolic and diastolic blood pressures in patients was 151.16 and 86.32, respectively, and was 121.54 and 76.18 in healthy individuals,

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which indicates higher blood pressure in the case group than the control (p <0.001). Cholesterol levels in the control group were 184.24 and were 151.58 mg/dL in the control group, which showed a significant difference between the two groups. Also, the mean level of LDL was 124 and the level of triglyceride was 126 mg/dl and all the three were significantly higher than the control group and HDL with a mean value of 37.6 mg/dl was lower than the control group (p <0.001). The other variables in the two groups were not statistically significant (p ≥0.05).

Table 2. Comparison of laboratory findings in the two groups Index Group Mean Std. Deviation p

sBP Case 151.16 27.70

.000 Control 121.54 18.75

DBP Case 86.32 17.01

.000 Control 76.18 9.32

PR Case 85.91 11.08

Control 85.23 7.57 .71 chol.level Case 184.16 50.24

.000 Control 151.58 34.80

LDL Case 124.30 47.06

.000 Control 85.10 25.75

HDL Case 37.63 11.46

.000 Control 48.19 7.23

TG Case 126.07 69.63

.000 Control 86.70 27.67

BS Case 162.74 60.03370

.000 Control 113.43 30.37

Serum cr Case .85 0.20 Control .81 .130 .19 GFR Case 71.39 31.64

Control 76.24 25.27 .37

Comparison of the two groups in terms of morphology and complete blood count (CBC) indices showed that the level of MCV in the case group was 88.53 and was 83.24 μg/ml in the control group (p <0.001) and serum ferritin levels in the case group were 189.43 and 168.25 μg/ml in the control group (p=0.03). The two groups had a significant difference regarding these variables. But there was no significant difference in terms of other variables (p ≥0.05).

Table 3. Comparison of morphological indices and CBC indices in the two groups Index Group Mean Std. Deviation P-value

RBC Case 4.79 0.77

Control 5.01 0.40 .06

Plt Case 257.27 65.00

Control 273.08 74.15 .23

Hct Case 41.85 4.66

Control 42.03 4.37 .30

Hb Case 13.62 1.80

Control 13.61 0.78 .96

MC Case 88.53 8.32

.000 Control 83.24 2.33

MCH Case 28.48 3.42

Control 28.27 2.96 .72

MCHC Case 32.48 18.89

Control 37.72 39.39 .32 Serum iron Case 95.90 18.31 Control 93.22 21.97 .24

1TIBC Case 279.13 27.75

Control 256.03 32.51 .16 Serum ferritin Case 189.43 38.70 Control 168.25 43.52 .03 Transferin saturation Case 37.72 12.44 Control 33.16 14.91 .34

1Total iron binding capacity

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The effect of erythrocyte morphological indices with ischemic stroke showed that only mean corpuscular volume (MCV) levels were significantly associated with stroke (p=0.001).

Table 4. Logistic regression of erythrocyte morphological indices with ischemic stroke Index β coefficient p odds ratio

RBC 0.245 0.08 1.34

Plt 0.198 0.23 1.03

Hct 0.607 0.09 0.986

Hb 0.451 0.07 1.06

MCV 0.676 0.001 1.89

MCH 0.421 0.08 0.93

MCHC 0.175 0.32 0.83

Serum iron 0.189 0.62 0.103

TIBC 0.296 0.67 0.80

Serumferritin 0.193 0.23 0.89

Transferin saturation 0.288 0.09 1.11

In order to determine the effect of erythrocyte morphology on the severity of ischemic stroke based on MRS index showed that none of the RBC indices were associated with stroke severity (P≥0.05). However, based on the statistical test, serum iron level and ferritin level were associated with the severity of ischemic stroke (p

<0.05) (Table 5).

Table 5. Analysis of variance of ischemic stroke severity based on MRS index and serum iron indices P-value Std. deviation

Mean Number

Stroke severity Index

0.005 .13

4.5 7

no significant disability

Serum iron

.76 4.9

19 slight disability

.46 4.7

4 moderate disability

. 5.1 1

moderatly sever disability

.76 4.6

33 severe disability

0 dead

0.69 47.22

253.5 7

TIBC

44.72 210.9

52.03 248.5

. 290.0 1

82.34 283.8

0 dead

0.01 3.86

42.2 7

Serum ferritin

5.08 42.7

2.73 41.7

. 41.7 1

4.20 40.8

0 dead

0.65 1.08

13.7 7

Transferin saturation

2.11 14.4

1.19 13.1

. 13.3 1

1.81 13.3

0 Dead

According to Table 6, the severity of dependence in patients with stroke based on Barthel Index with erythrocyte morphology by analysis of variance showed that no significant difference was seen in any of the cases (P ≥0.05).

Table 6. Analysis of variance of erythrocyte morphology and severity of dependence based on BI index

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P-value Std. deviation

Mean Number Dependence severity

Index

0.875 .96

4.953 19

total dependent RBC

0.70 4.732 12

severe dep

0.36 4.68 10

mod Dep

0.19 4.678 4

slight dep

0.93 4.71 10

independent

0,112 60.96

263.57 19

total dependent plt

69.02 304.83 12

severe dep

58.06 254.70 10

mod Dep

10.04 235.25 4

slight dep

40.93 269.60 10

independent

0,597 5.64

42.04 19

total dependent HCT

4.58 41.050 12

severe dep

2.58 40.610 10

mod Dep

2.04 44.750 4

slight dep

5.08 42.530 10

independent

0,449 1.98

13.48 19

total dependent HB

1.96 13.24 12

severe dep

1.23 13.26 10

mod Dep

0.12 14.67 4

slight dep

1.99 14.29 10

independent

0,464 7.30

87.71 19

total dependent MCV

10.27 87.20 12

severe dep

3.39 86.63 10

mod Dep

6.56 92.99 4

slight dep

11.20 91.79 10

independent

0,164 2.42

27.78 19

total dependent MCH

4.19 27.67 12

severe dep

2.06 28.39 10

mod Dep

5.36 28.47 4

slight dep

3.82 30.90 10

independent

0,136 2.07

32.08 19

total dependent MCHC

2.01 31.84 12

severe dep

1.47 32.56 10

mod Dep

2.33 33.44 4

slight dep

1.20 33.56 10

independent

There was no significant difference in terms of cognitive changes according to MMSE criteria and using statistical test in erythrocyte morphology (Table 7).

Table 7. Analysis of variance of erythrocyte morphology and cognitive changes based on MMSE criteria

P-value Std. deviation

Mean Number Cognitive changes

Index

0.565 1.02

4.67 9

No cognitive impairment

RBC Mild cognitive impairment 10 4.61 0.54 0.76 4.87 36

Severe cognitive impairment

0,115 56.81

221.66 9

plt Mild cognitive impairment 10 261.10 55.00 63.52 270.11 36

0,945 6.02

41.40 9

HCT Mild cognitive impairment 10 42.11 3.44 4.69 41.89 36

0,777 2.34

13.98 9

1HB Mild cognitive impairment 10 13.70 1.35 1.79 13.51 36

0,375 11.58

90.24 9

MCV Mild cognitive impairment 10 91.10 8.63 7.28 87.40 36

0,113 4.09

30.55 9

MCH Mild cognitive impairment 10 28.69 4.14 2.88 27.91 36

0,054 1.11

33.72 9

MCHC Mild cognitive impairment 10 32.82 1.63 1.99 32.08 36

1hemoglobin

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In terms of stroke severity according to NIHSS criteria and using analysis of variance test according to the table below, a significant difference was seen in erythrocyte morphology only in hemoglobin level (P=003) (Table 8).

Table 8. Analysis of variance of erythrocyte morphology and stroke severity according to NIHSS criteria P-value

Std. deviation Mean

Number Stroke severity

Index

0,131 .18

4.433 7

NO STROK RBC

.71 4.764 18

MINOR STROK

.95 4.693 12

MODERATE STROK

.80 5.373 9

MODERATE TO SEVER STROK

.68 4.684 9

SEVER STROK

0,253 49.06

254.714 7

NO STROK plt

61.00 235.833 18

MINOR STROK

67.97 254.250 12

MODERATE STROK

63.65 267.667 9

74.58 295.778 9

SEVER STROK

0,145 4.05

42.029 7

NO STROK HCT

4.00 42.272 18

MINOR STROK

5.73 39.783 12

MODERATE STROK

4.24 44.822 9

4.29 40.656 9

SEVER STROK

0,003 1.40

13.571 7

NO STROK HB

1.65 14.139 18

MINOR STROK

1.36 12.617 12

MODERATE STROK

1.92 15.078 9

1.58 12.533 9

SEVER STROK

0,285 7.17

93.984 7

NO STROK MCV

7.99 89.139 18

MINOR STROK

8.53 87.163 12

MODERATE STROK

7.27 85.022 9

9.82 88.460 9

SEVER STROK

0,193 2.74

30.4100 7

NO STROK MCH

3.86 29.4039 18

MINOR STROK

3.57 27.6233 12

MODERATE STROK

1.56 27.4644 9

3.55 27.3444 9

SEVER STROK

0,111 1.42

32.2071 7

NO STROK MCHC

1.52 33.4867 18

MINOR STROK

2.19 31.7475 12

MODERATE STROK

1.98 33.0433 9

1.31 31.1456 9

SEVER STROK

The mean severity of malnutrition and nutritional status in the two groups based on the MNA questionnaire showed that the groups were different in terms of nutrition (Table 9). 6 patients (11%) had clinical malnutrition and 22 patients (40%) were exposed to it. In all three cases, the control group was significantly different from the control group (p <0.05).

Table 9. Comparison of nutritional status in the two groups

Index Group Number Percentage P-value

Frequency Case

Malnutrition 6 11

0,000 Exposed to 22 40

Healthy 27 49

Control Malnutrition 0 0,0

Exposed to 0 0,0

Healthy 55 0,0

Number Mean Std. deviation

MNA assessment Case 55 12.54 2.54

0,000

Control 55 15.18 1.18

MNA screening Case 55 10.7 2.94

0,000

Control 55 13 0.86

MNA total assessment Case 55 23.25 4.75

0,000

Control 55 28.2 1.41

Frequency Case Number Percentage 0,000

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Description: Nutritional status checklist is related to anthropometric and nutritional parameters such as albumin, prealbumin, transferrin, cholesterol, retinol, cholecalciferol and zinc. It is also associated with hematologic changes such as hematocrit and hemoglobin

Discussion

Comparison of erythrocyte morphological markers in stroke patients can predict the occurrence of the disease in the individual (11, 20). Our study showed that hyperlipidemia and hypertension were two effective factors in stroke patients and the mean systolic blood pressure was 151 mm Hg and the mean diastolic blood pressure was 86 mm Hg and both were significantly higher than the control group, which is similar to the results of previous studies (7, 25). Similar studies by Aksoy et al. after recording the laboratory findings of patients based on MRSS showed that hypertension has the highest ranking in terms of risk factor (26). In our study, the levels of HDL, LDL and TG in the two groups were significantly different, which was consistent with the studies (13, 14, 16).

Our findings showed that 6 patients (11%) had clinical malnutrition and 22 patients (40%) were exposed to it.

However, all subjects in the control group had normal nutritional status. Similar studies have shown that clinical malnutrition is more common in people with stroke than in healthy individuals (27-29). The status studied in MNA is also associated with micronutrient intake and energy intake of the patient (30). According to the above and the results of this study, it can be claimed that more than 50% of patients with ischemic stroke suffer from some kind of energy or micronutrient eating disorder, or in other words, it can be claimed that ischemic stroke can be associated with energy or micronutrient deficiencies.

Our study showed that among the erythrocyte morphology and indicators, only mean corpuscular volume (MCV) is associated with ischemic stroke (Table 4). Hemoglobin was also an effective and significant factor in increasing the severity of stroke (Table 8).

Studies have shown that iron overload contributes to the development of vascular disease by causing thrombosis after arterial injury. High serum ferritin on admission of acute stroke patients (within 24 to 48 hours after stroke onset) had poor prognosis implicating that increase in body iron stores before stroke onset can aggravate the brain ischemia cytotoxicity. Therefore, it has been suggested that high serum ferritin affects the prognosis of ischemic stroke and also acts as a risk factor for ischemic episodes by enhancing atherogenesis (31, 32).

Studies have shown that folate and iron are directly related. Increasing the intake of high-dose dietary folate as a prophylactic agent in ischemic stroke will be associated with a significant reduction in stroke. (33) Sohini Sengupta et al. have stated that primary treatment measures with vitamins can prevent ischemic stroke attacks due to hyperhomocysteinemia (34).

In our study, mean serum iron and ferritin were significantly associated with stroke severity (Table 5). A consistent study showed that the mean serum iron level was lower in the group of stroke patients and this factor played an important role in stroke (35). In other studies in 2021, the results showed a significant effect of serum iron and ferritin in people with stroke (36, 37). Statistical findings showed that old age, high MCV and low folate levels were associated with stroke prognosis (27).

In the present study, hemoglobin was significantly lower in patients with ischemic stroke attacks with healthy individuals. Recent studies in 2021 show that hemoglobin levels play an important role in stroke (38).

However, in the study of Santos et al., it was shown that the level of hematocrit was significantly lower in patients with ischemic stroke attacks than the control group, but the hemoglobin level was not different in the two groups (39).

In the analysis of variance, none of the indicators and erythrocyte morphology were associated with stroke severity. However, with the increase in iron levels, the stroke severity increased and, conversely, with the decrease in ferritin levels, the stroke severity increased.

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Based on the evidence of the above studies and the association of malnutrition and MCV levels with stroke, it can be concluded that micronutrient malnutrition, especially folic acid and vitamin B12, is associated with ischemic stroke. the role of easy, quick, and low-cost measurement of CBC and observation of high MCV as a risk factor for ischemic stroke and possibly prophylactic measures can be considered in subsequent complementary studies.

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