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Table of Contents
ORIGINAL ARTICLE
Year : 2020  |  Volume : 11  |  Issue : 4  |  Page : 212-216

Study of microalbuminuria in acute ischemic stroke and its correlation with severity


1 Department of Internal Medicine, VMMC and Safdarjang Hospital, New Delhi, India
2 Department of Biochemistry, VMMC and Safdarjang Hospital, New Delhi, India

Date of Submission04-Sep-2020
Date of Decision01-Oct-2020
Date of Acceptance03-Oct-2020
Date of Web Publication02-Dec-2020

Correspondence Address:
Dr. Rupali Malik
Department of Internal Medicine, VMMC and Safdarjang Hospital, New Delhi - 110 029
India
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Source of Support: None, Conflict of Interest: None


DOI: 10.4103/injms.injms_108_20

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  Abstract 


Introduction: With the rising incidence of noncommunicable diseases such as stroke in low- and medium-income countries like India, it has become imperative to identify the potentially modifiable risk factors and focus on prevention. Microalbuminuria (MA) is now gaining recognition as an independent risk factor for ischemic stroke. It has also been studied as a prognostic marker for acute ischemic stroke. Thus, it was intended to study MA in acute ischemic stroke and its correlation with stroke severity. Methods: A single-center case–control study was done after enrolling seventy cases of ischemic stroke with age between 40 and 65 years, satisfying inclusion and exclusion criteria during a span of 2 years. Fifty patients in the age group of 40–65 years with no history of stroke and transient ischemic attack and fulfilling the exclusion criteria were taken as control. All cases were subjected to detailed history, systemic clinical examination, and biochemical and radiological investigations with assessment of National Institutes of Health Stroke Scale (NIHSS) for grading of severity of ischemic stroke with semi-quantitative measurement of MA (urinary albumin: creatinine ratio). Results: Hypertension (62.86%), diabetes mellitus (34.29%), and smoking (27.14%) were found to be the major risk factors for acute ischemic stroke. MA was present in 48.57% of cases, whereas in the control group, MA was present only in 18% of patients. Our study showed MA as an independent risk factor for acute ischemic stroke. On multivariate logistic regression analysis of risk factors of acute ischemic stroke, odd ratio for MA was 4.312 with P = 0.005. In our study, cases with mean NIHSS 17.71 and median NIHSS 18 were positive for MA, while cases with mean NIHSS 13.03 and median NIHSS 12 were negative for MA, that is, cases with higher mean and median NIHSS were positive for MA. This association of MA with NIHSS was statistically significant (P = 0.036). Conclusion: MA was found in approximately half of the patients studied with acute ischemic stroke, and there was a significant association between MA and higher NIHSS.

Keywords: Acute ischemic stroke, microalbuminuria, noncommunicable diseases


How to cite this article:
Gaurav DK, Malik R, Rani A, Dua A. Study of microalbuminuria in acute ischemic stroke and its correlation with severity. Indian J Med Spec 2020;11:212-6

How to cite this URL:
Gaurav DK, Malik R, Rani A, Dua A. Study of microalbuminuria in acute ischemic stroke and its correlation with severity. Indian J Med Spec [serial online] 2020 [cited 2023 May 29];11:212-6. Available from: http://www.ijms.in/text.asp?2020/11/4/212/302077




  Introduction Top


Stroke is one of the leading causes of death and serious disability in adult individuals worldwide. The age-adjusted prevalence of stroke in rural India is 244–262/100,000 and in urban India is 334–545/100,000, while the incidence is 105–262/100,000.[1]

Ischemic stroke is the most common type of stroke. In India, a pooled data incorporating multiple studies reveal that ischemic stroke occurs in 68%–80% and hemorrhagic stroke in 20%–32%. Ischemic stroke comprise large vessel (41%), lacunar (18%), cardioembolic (10%), other determined (10%), and undetermined (20%) subtypes.[1]

Ischemic stroke is associated with a number of risk factors which can be modifiable or nonmodifiable. Nonmodifiable risk factors include older age, male gender, ethnicity, family history, and prior history of stroke. Modifiable risk factors include arterial hypertension (HTN), cigarette smoking, diabetes mellitus (DM), obesity, oral contraceptive use, dyslipidemia, alcohol consumption, low socioeconomic status, heart disease, asymptomatic carotid artery disease, increased fibrinogen, elevated homocysteine, elevated anticardiolipin antibodies, and sickle cell disease.[2]

The significance of albuminuria as a possible risk factor for cerebrovascular disease in the general population has been suggested.[3-6] Microalbuminuria (MA) is now gaining recognition as an independent risk factor for ischemic stroke.[5] It has also been studied as a prognostic marker for acute ischemic stroke.[7]

MA is excretion of 30–300 mg albumin per day in urine or spot urinary albumin: creatinine ratio (UACR) 30–300 mg/g. Although often seen as a sign of early kidney disease, that is, impairment in glomerular filtration barrier, MA interacts with several conventional vascular risk factors and is an independent marker of endothelial dysfunction.[8] In the Insulin Resistance and Atherosclerosis Study, USA, MA was independently associated with carotid artery intima-media thickness.[6] Carotid intima-media thickness is itself a risk factor for stroke.[9] It has been suggested that a pathophysiological link between MA and atherosclerosis may be mediated through an increased generalized transvascular leakage of albumin, and that this systemic transvascular leakiness may also include lipoproteins, thus allowing for an increased lipid penetration into the vessel walls.[10]

Few studies have been done in India which also show a similar correlation of MA in ischemic stroke. [11,12] Overall, in India, there is a paucity of literature pertaining to MA in acute ischemic stroke and its correlation with severity of stroke. Hence, the present study was undertaken to determine the frequency of MA in acute ischemic stroke and its correlation with the severity of stroke.


  Methods Top


This was a single-center case–control study. Patients were enrolled after taking informed consent from the patients or family member. Seventy cases of ischemic stroke with age between 40 and 65 years were recruited into the study after satisfying the inclusion and exclusion criteria during a span of 2 years (January 2015–December 2016). Fifty patients of age group 40–65 years with no history of stroke and transient ischemic attack and fulfilling exclusion criteria were taken as control.

Inclusion criteria

Patients of either sex in the age group of 40–65 years, presenting with acute ischemic stroke, were included in the study.

Exclusion criteria

Patients with:

  • Renal disease
  • Eclampsia and preeclampsia
  • Malignancy
  • Urinary infection
  • Rheumatic heart disease
  • Cardiomyopathy.


The study samples were recruited from those patients attending a tertiary care hospital to determine the frequency of MA in acute ischemic stroke and to assess the severity of acute ischemic stroke with MA.

The cases were subjected to detailed history and physical examination, laboratory investigation, and noncontrast computed tomography head. The severity of stroke was assessed by National Institutes of Health Stroke Scale (NIHSS)[Table 1]. The NIHSS is a 15-item neurologic examination stroke scale used to evaluate the effect of acute ischemic stroke on the levels of consciousness, language, neglect, visual-field loss, extraocular movement, motor strength, ataxia, dysarthria, and sensory loss that provide a quantitative measure of stroke-related neurologic deficit. Ratings for each item are scored with 3–5 grades, with 0 as normal.[13]
Table 1: National Institutes of Health Stroke Scale (NIHSS)

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MA was detected by using? AU680 urine auto-analyzer (Beckman Coulter, CA, USA) which gives the outcome value of spot UACR as follows:

UACR

  • <30 mg/g – normal
  • 30–300 mg/g – abnormal
  • >300 mg/g – high abnormal.


Because UACR between 30 and 300 mg/g is MA, “abnormal” value of urine analyzer was considered MA.

All the patients were subjected to the following investigations: complete blood count, urine examination, liver/kidney function test, serum electrolytes, fasting and postprandial blood sugar, glycated hemoglobin, where ever indicated, lipid profile, and UACR (albumin in mg % and creatinine in g %). Use of UACR as a measure of MA has been validated against gold standard urinary albumin excretion rate (UAER) measured on timed urine collection with correction coefficients ranging from 0.8 to 0.99, sensitivity 77%to 100%, and specificity 80% to 100% of UACR for UAER in various studies.[14-16]

Electrocardiography and two-dimensional–echocardiography were done in all patients. Chest X-ray and color Doppler were done where ever indicated. All the cases were subjected to noncontrast computerized tomographic scan of head.

Statistical analysis

Categorical variables were presented in number and percentage (%) and continuous variables were presented as mean ± standard deviation and median. Normality of data was tested by Kolmogorov–Smirnov test. If the normality was rejected, then nonparametric test was used. Quantitative variables were compared using unpaired t-test/Mann–Whitney test (when the data sets were not normally distributed) between the two groups. Qualitative variables were correlated using Chi-square test/Fisher’s exact test. Univariate and multivariate logistic regression analysis was used to find out the risk factors of ischemic stroke and MA in ischemic stroke. P < 0.05 was considered statistically significant. The data were entered in MS EXCEL spreadsheet, and analysis was done using Statistical Package for Social Sciences (SPSS) version 21.0 (IBM SPSS Statistics, IBM Corporation, Armonk, NY).


  Results Top


There was no significant difference in age distribution among cases and controls. In the case group, majority of the patients were between the age of 50 and 59 years (comprises 38.57%). In the control group, majority of the patients were in age group of 60 years and above (comprises 40%) [Figure 1].
Figure 1: Distribution of age group

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HTN (62.86%), DM (34.29%), and smoking (27.14%) were the major risk factors for acute ischemic stroke. Among cases, 62.86% were hypertensive, whereas among control group, 26% were hypertensive. There was a significant difference of HTN distribution among cases and controls (P < 0.0005). Among cases, 34.29% were diabetic, while among control group, 16% were diabetic, which was statistically significant different (P = 0.026). Among cases, 27.14% were smoker, whereas among the control group, 8% were smoker, which was again statistically significant (P = 0.01). Among cases, 24.29% were dyslipidemic, whereas among the control group, 10% were dyslipidemic, which was statistically significant different (P = 0.046). Obesity was seen in 30% of the cases and 14% of the controls, with a statistically significant difference (P = 0.041).

Univariate logistic regression analysis showed that HTN, DM, smoking, and obesity were significant risk factors for acute ischemic stroke [Table 2]. Multivariate logistic regression analysis showed that HTN, DM, and smoking were significantly associated with acute ischemic stroke [Table 3].
Table 2: Univariate logistic regression for risk factors of acute ischemic stroke

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Table 3: Multivariate logistic regression for risk factors of acute ischemic stroke

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MA was present in 48.57% cases, whereas in the control group, MA was present only in 18% of patients. Statistical analysis showed a significant difference of MA distribution among case and control groups (P = 0.001). MA was more prevalent in older age group (P = 0.003). The correlation between risk factors of ischemic stroke such as HTN, diabetes, smoking, and obesity with MA was insignificant.

In our study, multivariate logistic regression analysis showed that MA was an independent risk factor for acute ischemic stroke (P = 0.005). Univariate logistic regression for risk factors of MA in acute ischemic stroke showed that only age was statistically significantly associated with MA (P = 0.006) [Table 4] and [Figure 2].
Figure 2: Distribution of microalbuminuria in relation to age group

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Table 4: Univariate logistic regression for risk factors of microalbuminuria in acute ischemic stroke

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MA was present in 3 out of 8 patients belonging to minor stroke severity (on NIHSS), 8 out of 24 (33.3%) of moderate severity, 14 out of 22 (63.6%) of severe, and 9 out of 16 (56.2%) of very severe category. The average NIHSS score in stroke patients with MA was 17.71 ± 9.43 compared to 13.03 ± 8.84 in stroke patients without microalbuminuria (P = 0.036).


  Discussion Top


This study was conducted to study MA in acute ischemic stroke and its correlation with severity. We found HTN (present in 62.86% cases) to be the major risk factor for acute ischemic stroke, similar to previous literature.[17-20] These studies have also shown the frequency of HTN in stroke in India to vary between 48% and 83.2%. Arterial HTN predisposes to ischemic stroke by aggravating atherosclerosis and accelerating heart disease, increasing the relative risk for stroke to an estimated three- to fourfolds.[2]

Two other major risk factors are diabetes (34.29%) and smoking (27.14%).

Previous studies [17, 19, 20] have also shown that DM and tobacco intake increase the risk of ischemic cerebrovascular disease. These studies have shown that the frequency of diabetes and tobacco intake in stroke in India varies between 25.42% and 50% and between 26.8% and 33.15%, respectively. The mechanisms of stroke secondary to diabetes may be caused by cerebrovascular atherosclerosis and cardiac embolism.[2]

The risk for stroke in smokers is two to three times greater than that in nonsmokers possibly through enhanced atherosclerosis, arterial spasm, and increased coagulability.[2]

There was a significant difference of dyslipidemia distribution and obesity as well among cases and controls (P = 0.046).

In our study, in the case group MA was present in 48.57% of patients, whereas in the control group, MA was present only in 18% of patients. Statistical analysis showed a statistically significant difference of MA distribution among case and control groups (P = 0.001). This is similar to the results of several previous studies.[21-26] Turaj et al.[25] reported that MA was found in 46.1% of acute stroke patients and 13.5% in controls. Słowik et al.[26] reported that MA was found in 46.7% of patients with acute stroke and 16.7% of controls.

In our study, multivariate logistic regression analysis showed that MA was an independent risk factor for acute ischemic stroke (P = 0.005). Thus, our finding has similar association as described by several previous literature.[24-30]

Cases with a mean age of 57.94 years and a median age of 59.5 years were positive for MA. Cases with a mean age of 52.97 years and a median age of 54.5 years were negative for MA. Nearly 65.38% of cases with age 60 years and above were positive for MA, whereas only 23.53% cases in the age group of 40–49 years were positive for MA. This difference of MA distribution among different age groups was statistically significant (P = 0.003).

In our study, univariate logistic regression for risk factors of MA in acute ischemic stroke showed that only age was statistically significantly associated with MA (P = 0.006). Previous studies have also showed correlation of MA with age. [7,11] Gumbinger et al.[7] found a significant association of MA with higher age (mean age of MA positive group was 72.4 ± 10.4 years and MA negative group was 66.1 ± 11.1 years) (P = 0.003). Mathur et al.[11] found that MA was present more often in patients aged more than 60 years than in patients aged 60 years or less; 80.76% versus 54.16% (P < 0.05).

Among cases, 60.71% of females were positive for MA, whereas 40.48% of male were positive for MA. This difference was not statistically significant (P = 0.097). Previous study done by Mathur et al.[11] did not find any difference between patients with and without MA according to gender.

Overall, MA was present in 48.57% of cases. Nearly 37.50% of minor stroke cases, 33.33% of moderate stroke cases, 56.25% of severe stroke cases, and 56.25% of very severe stroke cases were positive for MA. In our study, cases with mean NIHSS 17.71 and median NIHSS 18 were positive for MA, whereas cases with mean NIHSS 13.03 and median NIHSS 12 were negative for MA, that is, cases with higher mean and median NIHSS were positive for MA. This association of MA with NIHSS was significant (P = 0.036). Thus, our finding has similar association as described by previous studies. [7,21-23, 26, 31-33] Gumbinger et al. found that MA was associated with NIHSS upon admission (eight in MA-positive group and four in MA-negative group) (P < 0.0001) and NIHSS upon discharge (five in MA-positive group and one in MA-negative group) (P < 0.0001).[7] Das et al. had reported mean NIHSS score 29.12 versus 18.88 between two groups of strokes, that is, with and without MA.[32] Chowdhury et al. had reported significantly higher mortality in patients with MA than that of patients without MA.[31]

Our study showed a correlation of MA with age, but no correlation with other risk factors of stroke, probably due to small sample size.

Our study showed correlation between the presence of MA and clinical severity of acute ischemic stroke. The pathophysiological mechanism is still unclear. A plausible explanation for our findings is that MA is a marker of endothelial dysfunction and plays an important role in the inflammatory response in the acute phase of a vascular event. [7, 24, 34]

Our study has some limitations. First, there is lack of follow-up. Second, MA was measured by a semi-quantitative method; for better correlation, MA should be measured quantitatively. Third, our study did not have consecutive recruitment of patients (as patients with age below 40 years and above 65 years were excluded) and the number of patients included was relatively small.


  Conclusion Top


Our study has found MA as an independent marker of acute ischemic stroke with a prevalence of 48.57%. It also correlates with the clinical severity of stroke. Those with a higher NIHSS score had a higher rate of urine albumin excretion and vice versa. Measurement of MA may thus help to assess those who are at increased risk and to triage those who may need a more aggressive management protocol.

Although the results of our study need to be confirmed in a larger cohort, we believe that further studies should investigate whether MA is only a biomarker of severity of stroke or a potential modifiable risk factor for stroke.

Financial support and sponsorship

None.

Conflicts of interest

There are no conflicts of interest.



 
  References Top

1.
Banerjee TK, Das SK. Fifty years of stroke researches in India. Ann Indian Acad Neurol 2016;19:1-8.  Back to cited text no. 1
[PUBMED]  [Full text]  
2.
Daroff RB, Fenichel GM, Jankovic J, Mazziotta JC. Bradley?s Neurology in Clinical Practice. 6th ed.. Philadelphia: Elsevier Saunders; 2012.  Back to cited text no. 2
    
3.
Miettinen H, Haffner SM, Lehto S, Ronnemaa T, Pyorala K, Laakso M. Proteinuria predicts stroke and other atherosclerotic vascular disease events in non-diabetic and non-insulin dependent diabetic subject. Stroke 1996;27:2033-9.  Back to cited text no. 3
    
4.
Nakayama T, Dat C, YokoyamaT, Yoshiike N, Yamaguchi M, Tanaka H. A 15.5-years follow up study of stroke in a Japanese provincial city. The Shibata study. Stroke 1997;28:45-52.  Back to cited text no. 4
    
5.
Woo J, Lau E, Kay R, Lam CW, Cheung CK, Swaminathan R, et al. A case control study of some hematological and biochemical variables in acute stroke and their prognostic value. Neuroepidemiology 1990;9:315-20.  Back to cited text no. 5
    
6.
Mykkanen L, Zaccaro DJ, O’Leary DH, Howard G, Robbins DC, Haffner SM. Microalbuminuria and carotid artery intimamedia thickness in nondiabetic and NIDDM subjects. The Insulin Resistance Atherosclerosis Study (IRAS). Stroke 1997;28:1710-6.  Back to cited text no. 6
    
7.
Gumbinger C, Sykora M, Diedler J, Ringleb P, Rocco A. Microalbuminuria: A potential prognostic marker for acute stroke. Nervenarzt 2012;83:1357-60.  Back to cited text no. 7
    
8.
Ovbiagele B. Microalbuminuria: Risk factor and potential therapeutic target for stroke? J Neurol Sci 2008;271:21-8.  Back to cited text no. 8
    
9.
O’Leary DH, Polak JF, Kronmal RA, Manolio TA, Burke GL, Wolfson SK Jr., Carotid-artery intima and media thickness as a risk factor for myocardial infarction and stroke in older adults. Cardiovascular Health Study Collaborative Research Group. N Engl J Med 1999;340:14-22.  Back to cited text no. 9
    
10.
Jensen JS. Renal and systemic transvascular albumin leakage in severe atherosclerosis. Arterioscler Thromb Vasc Biol 1995;15:1324-9.  Back to cited text no. 10
    
11.
Mathur PC, Punekar P, Muralidharan R. Microalbuminuria in nondiabetic acute ischemic stroke: An Indian perspective. Ann Indian Acad Neurol 2005;8:237-42.  Back to cited text no. 11
  [Full text]  
12.
Kala SN, Abhilash K. Determinants of metabolic syndrome in acute ischemic stroke. Sch J App Med Sci 2013;1:783-5.  Back to cited text no. 12
    
13.
Lyden PD, Lu M, Levine SR, Brott TG, Broderick J, NINDS rtPA Stroke Study Group. A modified National Institutes of Health Stroke Scale for use in stroke clinical trials: Preliminary reliability and validity. Stroke 2001;32:1310-7.  Back to cited text no. 13
    
14.
Ginsberg JM, Chang BS, Matarese RA, Garella S. Use of single voided urine samples to estimate quantitative proteinuria. N Engl J Med 1983;309:1543-6.  Back to cited text no. 14
    
15.
Nathan DM, Rosenbaum C, Protasowicki VD. Single-void urine samples can be used to estimate quantitative microalbuminuria. Diabetes Care 1987;10:414-8.  Back to cited text no. 15
    
16.
Wiegmann TB, Chonko AM, Barnard MJ, MacDougall ML, Folscroft J, Stephenson J, et al. Comparison of albumin excretion rate obtained with different times of collection. Diabetes Care 1990;13:864-71.  Back to cited text no. 16
    
17.
Das SK, Banerjee TK, Biswas A, Roy T, Raut DK, Mukherjee CS, et al. A prospective community-based study of stroke in Kolkata, India. Stroke 2007;38:906-10.  Back to cited text no. 17
    
18.
Dalal PM, Malik S, Bhattacharjee M, Trivedi ND, Vairale J, Bhat P, et al. Population-based stroke survey in Mumbai, India: Incidence and 28-day case fatality. Neuroepidemiology 2008;31:254-61.  Back to cited text no. 18
    
19.
Sridharan SE, Unnikrishnan JP, Sukumaran S, Sylaja PN, Nayak SD, Sarma PS, et al. Incidence, types, risk factors, and outcome of stroke in a developing country: The Trivandrum Stroke Registry. Stroke 2009;40:1212-8.  Back to cited text no. 19
    
20.
Nagaraja D, Gururaj G, Girish N, Panda S, Roy AK, Sarma GR, Srinivasa R. Feasibility study of stroke surveillance: data from Bangalore, India. Indian J Med Res 2009;130:396-403  Back to cited text no. 20
    
21.
Li F, Chen QX, Peng B, Chen Y, Yao T, Wang G. Microalbuminuria in patients with acute ischemic stroke. Neurol Res 2019;41:498-503.  Back to cited text no. 21
    
22.
Singh S, Singh H, Singh TP. Micro-albuminuria in non-diabetic acute ischemic stroke: prevalence and its co-relation with stroke severity. Int J Res Med Sci 2017;5:982-6.  Back to cited text no. 22
    
23.
Elyas S, Shore AC, Kingwell H, Keenan S, Boxall L, Stewart J, et al. Microalbuminuria could improve risk stratification in patients with TIA and minor stroke. Ann Clin Transl Neurol 2016;3:678-83.  Back to cited text no. 23
    
24.
Farooq MA, Anjum MS, Malik FA, Kalsoom N. Frequency of microalbuminuria in patients with ischemic stroke. Rawal Med J 2013;38:97-9.  Back to cited text no. 24
    
25.
Turaj W, Slowik A, Wyrwicz-Petkow U, PankiewiczJ, Iskra T, Rudzinska M, Szczudik A. The prognostic significance of microalbuminuria in non-diabetic acute stroke patients. Med Sci Monit 2001;7:989-94.  Back to cited text no. 25
    
26.
Słowik A, Turaj W, Iskra T, Strojny J, Szczudlik A. Microalbuminuria in nondiabetic patients with acute ischemic stroke: Prevalence, clinical correlates, and prognostic significance. Cerebrovasc Dis 2002;14:15-21.  Back to cited text no. 26
    
27.
Saha SP, Bhattacharya S, Das SK, Maity B, Roy T, Raut DK. Epidemiological study of neurological disorders in a rural population of Eastern India. J Indian Med Assoc 2003;101:299-300, 302-4.  Back to cited text no. 27
    
28.
Banerjee TK, Mukherjee CS, Sarkhel A. Stroke in the urban population of Calcutta An epidemiological study. Neuroepidemiology 2001;20:201-7.  Back to cited text no. 28
    
29.
Yuyun MF, Khaw KT, Luben R, Welch A, Bingham S, Day NE, et al. Microalbuminuria and stroke in a British population: The European Prospective Investigation into Cancer in Norfolk (EPIC-Norfolk) population study. J Intern Med 2004;255:247-56.  Back to cited text no. 29
    
30.
Viazzi F, Leoncini G, Conti N, Tomolillo C, Giachero G, Vercelli M, et al. Microalbuminuria is a predictor of chronic renal insufficiency in patients without diabetes and with hypertension: The MAGIC study. Clin J Am Soc Nephrol 2010;5:1099-106.  Back to cited text no. 30
    
31.
Chowdhury J, Sultana N, Ahmed S, Rahman MM, Akter M, Rafique T. Microalbuminuria as a predictor of short-term mortality in acute ischemic stroke. Bangladesh J Med Biochem 2012;5:16-9.  Back to cited text no. 31
    
32.
Das S, Yadav U, Ghosh KC, Panchadhyayee S, Kundu SS, Ganguly PK. A clinical study of ischaemic strokes with micro-albuminuria for risk stratification, short-term predictive value and outcome. J Indian Med Assoc 2012;110:908-10, 919.  Back to cited text no. 32
    
33.
Ghosh S, Bandyopadhyay SK, Bandyopadhyay R, Ghosh S, Sarkar N, Bandyopadhyay SK. Micro-albuminuria: A predictor of short-term mortality in acute ischaemic stroke. J Indian Med Assoc 2008;106:783-4, 786.  Back to cited text no. 33
    
34.
Pedrinelli R, Dell’Omo G, Penno G, Mariani M. Non-diabetic microalbuminuria, endothelial dysfunction and cardiovascular disease. Vasc Med 2001;6:257-64.  Back to cited text no. 34
    


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  [Table 1], [Table 2], [Table 3], [Table 4]



 

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