Factors affecting daily activities of patients with cerebral infarction

Abstract

BACKGROUND:

Stroke is the leading cause of death and long-term disability. This study was undertaken to investigate the factors influencing daily activities of patients with cerebral infarction so as to take interventional measures earlier to improve their daily activities.

METHODS:

A total of 149 patients with first-episode cerebral infarction were recruited into this prospective study. They were admitted to the Encephalopathy Center, Department of Neurology, the First Affiliated Hospital of Wenzhou Medical College in Zhejiang Province from August 2008 to December 2008. The baseline characteristics of the patients and cerebral infarction risk factors on the first day of admission were recorded. White blood cell (WBC) count, plasma glucose (PG), and many others of laboratory targets were collected in the next morning. Barthel index (BI) was calculated at 2 weeks and 3 months respectively after onset of the disease at the outpatient clinic or by telephone call. Lung infection, urinary tract infection and atrial fibrillation if any were recorded on admission. The National Institute of Health Stroke Scale (NIHSS) scores and the GCS scores were recorded within 24 hours on and after admission, at the second week, and at the third month after the onset of cerebral infarction respectively.

RESULTS:

The factors of BI at 2 weeks and 3 months after onset were the initial PG level, WBC count and initial NIHSS scores. Besides, urinary tract infection on admission was also the factor for BI at 3 months.

CONCLUSION:

Active measures should be taken to control these factors to improve the daily activities of patients with cerebral infarction.

INTRODUCTION

Stroke is the second leading cause of death and the main reason for long-term disability. A high degree of disability makes patients lose the daily activities and the ability to work. Therefore, it is necessary to find out the risk factors affecting the daily activities to improve the prognosis of patients with cerebral infarction.

METHODS

Patients

Altogether 149 consecutive patients with first-episode cerebral infarction were recruited into this prospective study. They were admitted to the Encephalopathy Center of the Department of Neurology, the First Affiliated Hospital of Wenzhou Medical College from August 2008 to December 2008. The patients met the following criteria: first-episode cerebral infarction, one of the National Criteria for Diagnosis of Cerebrovascular Diseases issued in 1995, confirmed by CT or MRI; age≥18 years old; and the time between onset of symptoms to admission≤14 days. Those were excluded according to the following criteria: no symptoms or signs of silent cerebral infarction; non-cerebral vascular diseases; and transient ischemic attack.

Methods

Of the 149 patients aged 30 to 89 years (average 64.67±12.235 years), 89 were male and 60 were female. Their demographic data and factors of ischemic stroke risk were recorded on admission. The National Institute of Health Stroke Scale (NIHSS)[1] scores and GCS scores were taken simultaneously. Red blood cell (RBC) count, white blood cell (WBC) count, platelets, fibrinogens, fasting plasma glucose (PG), low-density lipoprotein, uric acid, calcium, serum magnesium, D-Dmier, neuron-specific enolase (NSE), serum ferritin and other laboratory parameters were measured in the next morning after admission. NIHSS scores and Barthel index (BI) scores were taken on the 14th day after stroke. Lung infection and urinary tract infection were recorded during hospitalization. NIHSS and BI scores were recorded at 2 weeks after onset, and BI scores were recorded again at 3 months after onset by out-patient visit or telephone call. We set the following criteria: WBC≥10×10⁹/L for a higher group, <10×10⁹/L for a normal group; fasting plasma glucose ≥6.1 mmol/L for a higher group, <6.1 mmol/L for a normal group; and NIHSS score>7 score for a higher group, and ≤7 score for a lower group. According to the above criteria, the 149 patients were divided into four groups: 1) group A, none of the three criteria was high; 2) group B, one of the three criteria was high; 3) group C, two of the three criteria were high; 4) group D, all of the three criteria were high.

Statistical analysis

SPSS16.0 was used for statistical analysis in this study. Analysis of variance (ANOVA) was used for the comparison in groups A, B, C, and D. Univariate analysis was used to determine the factors affecting daily activities of the patients. If independent variables were quantitative, we used linear correlation analysis; if not, we used Spearman’s rank-order correlation coefficient analysis. The proability for screening was P<0.10. The multiple linear regression analysis was used for the analysis of screened factors. α=0.15 served as an inclusion criterion, and α=0.10 as an exclusion criterion. P<0.05 was considered statistically significant.

RESULTS

Factors of BI scores at 2 weeks after stroke

Simple linear correlation analysis revealed 7 factors of BI scores at 2 weeks after stroke (Table 1). These factors were further assessed by multiple linear regression analysis, and 3 factors of BI scores were observed at 2 weeks after stroke (Table 2). A multiple linear-regression equation was used as follows:

Table 1.

Single-factor correlation analysis of BI scores at 2 weeks after stroke

Table 2.

Multiple regression analysis of BI scores at 2 weeks after stroke

Y=133.542-2.481×1-3.158×2-3.426×3

Factors of BI scores at 3 months after stroke

Simple linear correlation analysis analysis showed 8 factors of BI scores at 3 months after stroke (Table 3), which were further assessed using multiple linear regression analysis, and 4 factors of BI scores were observed at 3 months after stroke (Table 4). A multiple linear regression equation was used as follows:

Table 3.

Single-factor correlation analysis of BI scores at 3 months after stroke

Table 4.

Multiple regression analysis of BI scores at 3 months after stroke

Y=155.268 -2.677×1-4.611×2-0.913×3-9.633×4

Correlations between daily activities and WBC count, and between PG and NIHSS scores at 3 months after stroke were observed. BI scores decreased in groups A, B, C, and D (P=0.00,Tables 5 and 6). Pairwise comparison showed that there was significant difference in these groups except between groups B and C (Table 7).

Table 5.

BI scores of groups A, B, C, and D

Table 6.

Correlation between daily activities and WBC count, PG, and NIHSS scores at 3 months after stroke.

Table 7.

Pairwise comparison among the four groups

DISCUSSION

Serious neurological deficit on admission, obnubilation, history of diabetes, and atrial fibrillation are factors for poor prognosis and high mortality rate. Routine laboratory indicators such as increased level of hematocrit, high level of blood sugar[2-4] and leukocytosis[3-6] are used as prognostic indicators. In this study, laboratory indicators, baseline demographic data, stroke risk factors and some scores were analyzed. WBC count, fasting blood glucose, NIHSS scores, urinary tract infection were taken as the factors of daily activities in patients at 2 weeks and 3 months after onset of stroke.

Researchers believe that in the acute phase of stroke, blood cells count was correlated with patient’s condition and prognosis.[7] Akopov et al[8] found that most of polymorphonuclear leukocytes were accumulated markedly in the infarct area or big sized infarct. Ernst et al[9] reported the patients with a highWBC count also had a high mortality rate. This study revealed that increased WBC count on admission was independently associated with daily activities at 2 weeks and 3 months after the onset of stroke.

Bruno et al[10] analyzed the relationship between blood glucose and prognosis of stroke in 1259 patients, and found that the higher the blood glucose level on admission, the poorer prognosis of stroke. Bhalla et al[11] investigated the relationship between blood glucose level on admission and prognosis of stroke in 167 patients with acute cerebral infarction, and found that elevated blood glucose in the early period of stroke was an independent risk factor for decreased survival rate and self-sufficiency. Another study on 656 patients showed that hyperglycemia increased the mortality of patients at 30 days, 1 year and 6 years after stroke.[12] This study confirmed that hyperglycemia on admission is independently associated with daily activities at 2 weeks and 3 months after the onset of the disease.

NIHSS scoring system can be used to assess patients’ condition and to predict prognosis in patients with acute cerebral infarction.[13] In this study, NIHSS scores on admission served as a criterion of illness severity, and the scores were independently associated with daily activities at 2 weeks and 3 months after onset of stroke. Some studies showed that the mortality of patients with lung infection was 3 times higher than that of patients without infection within 30 days after the onset. This study showed that urinary tract infection during hospitalization was independently associated with daily activities at 3 months after the onset of the disease. Ishihara et al[14] found that the number of fasting blood glucose combined with WBC count could be used to predict the prognosis of stroke. Kosuge et al[15] found that with the increase of WBC count, fasting blood glucose, and glomerular filtration rate, the odds ratio of hospital mortality increased in patients with myocardial infarction as shown by logistic regression analysis.

In conclusion, NIHSS scores on admission, fasting blood glucose, and WBC count were independent factors of daily activities at 3 months after stroke, and their correlation coefficients increased significantly. Thus, the three variables could be used to predict the prognosis of patients with stroke.