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ORIGINAL ARTICLE
Year : 2017  |  Volume : 20  |  Issue : 3  |  Page : 289-293
 

Clinical features, risk factors, and short-term outcome of ischemic stroke, in patients with atrial fibrillation: Data from a population-based study


1 Department of Neurology, Christian Medical College, Ludhiana, India
2 Statistician, Department of Anesthesiology, Pharmacology & Therapeutics, University of British Columbia, Canada
3 Department of Neurology, Dayanand Medical College, Ludhiana, India
4 Department of Community Medicine, Christian Medical College, Ludhiana, Punjab, India
5 Division of Non-Communicable Diseases, n Council of Medical Research, Ansari Nagar, New Delhi, India

Date of Web Publication10-Aug-2017

Correspondence Address:
D Pandian Jeyaraj
Department of Neurology, Christian Medical College, Ludhiana - 141 008, Punjab
India
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Source of Support: None, Conflict of Interest: None


DOI: 10.4103/aian.AIAN_16_17

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   Abstract 

Objectives: Atrial fibrillation (AF) is the most common sustained cardiac rhythm disorder associated with stroke. This study was done to describe risk factors, clinical features, and short-term outcomes of stroke patients with AF. Materials and Methods: This study was a part of the Indian Council of Medical Research funded “Ludhiana urban population based Stroke Registry.” Data were collected using WHO STEPS stroke method. All patients ≥18 years of age, who developed ischemic stroke between March 26, 2011, and March 25, 2013, were included in this study. Data about demographic details, clinical features, and risk factors were collected. The outcome was assessed at 28 days using modified Rankin scale (mRs) (good outcome: mRS ≤2; poor outcome >2). The statistical measures calculated were descriptive statistics, Chi-square test, Fischer's exact test, and independent t-test. Results: Of the total 7199 patients enrolled in the registry, data of 1942 patients who fulfilled inclusion criteria were analyzed, and AF was seen in 203 (10%) patients. AF patients were older (AF 62 ± 14 vs. non-AF 60 ± 15 years, P= 0.01), had more hypertension (AF 176 [87%] vs. non-AF 1396 [80%], P= 0.03), hyperlipidemia (AF 60 [32%] vs. non-AF 345 [21%], P= 0.001), coronary artery disease (AF 60 [30%] vs. non-AF 195 [11%], P< 0.0001), and carotid stenosis (AF 14 [7%] vs. non-AF 57 (3%), P= 0.02). They had worse outcome (mRS >2; AF 90 [50%] vs. non-AF 555 [37%], P= 0.001). Conclusions: Ten percent of stroke patients had AF. They were older, had multiple risk factors and worse outcome. There was no gender difference in this large cohort.


Keywords: Atrial fibrillation, ischemic stroke, population-based stroke registry


How to cite this article:
Akanksha G W, Paramdeep K, Gagandeep S, Rajinder B, Birinder S P, Monika S, Shavinder S, Clarence J S, Shweta J V, Sharma M, Jeyaraj D P. Clinical features, risk factors, and short-term outcome of ischemic stroke, in patients with atrial fibrillation: Data from a population-based study. Ann Indian Acad Neurol 2017;20:289-93

How to cite this URL:
Akanksha G W, Paramdeep K, Gagandeep S, Rajinder B, Birinder S P, Monika S, Shavinder S, Clarence J S, Shweta J V, Sharma M, Jeyaraj D P. Clinical features, risk factors, and short-term outcome of ischemic stroke, in patients with atrial fibrillation: Data from a population-based study. Ann Indian Acad Neurol [serial online] 2017 [cited 2019 Sep 20];20:289-93. Available from: http://www.annalsofian.org/text.asp?2017/20/3/289/212707



   Introduction Top


Atrial fibrillation (AF) is the most common sustained cardiac rhythm disorder known to increase morbidity, mortality, and socioeconomic burden in patients with stroke.[1],[2],[3] The prevalence of AF increases steadily with age, with only 2% of patients ≤65 years, while affecting nearly 9% of people ≥65 years.[1] AF causes disability and cognitive dysfunction (vascular dementia) even in the absence of overt stroke.[4] Use of oral anticoagulants reduces stroke risk substantially.[5]

The prevalence of AF in general population is well documented in developed countries, such as in Rotterdam 5.5%, Auckland 0.4% and Northern Manhattan after stratification according to ethnic groups.[4],[6],[7] Global prevalence and incidence of AF are low in developing countries compared to developed countries.[8] In India, the reported burden of AF is largely from few studies.[9],[10],[11] About 8% of stroke patients had AF in Trivandrum population-based registry. However, they did not collect information on valvular heart disease.[12] In central India, in a community-based sample of 4077, 8 (0.19%) were found to have AF. Rheumatic heart disease (RHD) was the most common cause.[13] Since these studies are either hospital-based and/or do not focus on AF, they may not give the exact burden of AF in stroke patients. Hence, this study was done to evaluate the risk factors, clinical features, and short-term outcomes of stroke in patients with AF.


   Materials and Methods Top


This study was a part of the Indian Council of Medical Research (ICMR) funded research project which was conducted from March 25, 2010, to March 25, 2013. The registry was established in two phases. Phase I was feasibility study (1st year of the registry) and Phase II was epidemiological data collection (from March 26, 2011, to March 25, 2013). Data were collected using WHO-STEPS stroke approach from public hospitals, private hospitals (neurologists and neuro-surgeons), general practitioners (GP), physiotherapy centers, scan/imaging centers, and Municipal Corporation (MC).[14],[15] All stroke patients ≥18 years with first-ever stroke between March 25, 2010, and March 25, 2013, were enrolled in this registry. There was the possibility of duplication of cases. To remove duplicate cases, age, gender, address, and contact were matched. A case was considered duplicate if three or more variables were identical. Duplication could occur at any of the four levels given below:

  1. If the patient's data were collected from the same center more than once
  2. Duplication with hospital and the scan center of the same site
  3. Duplication with hospital and the scan center, GP
  4. Duplication with hospital and MC.


If a patient's data were duplicated at any level mentioned above, then the complete hospital form was collected and included in the data analysis.

The study was approved by the Institutional Ethics Committee, and a written informed consent was taken from all the participants. Data about demographic details, diagnosis modalities, and stroke characteristics were collected at the time of admission. For data collection, WHO STEPS stroke approach was followed. Patients were contacted telephonically and by face-to-face interview 28 days after discharge to assess their outcome. The outcome was measured using modified Rankin scale (MRS 0–2: good outcome; 3–6: poor outcome).

Data selected for this study

For this particular study, ischemic stroke patient's data collected in the stroke registry in Phase-II (from March 26, 2011, to March 25, 2013) from hospitals, general practitioners, and physiotherapy centers were included in the analysis. Due to lack of AF data collected from scan centers and MC centers were excluded from the analysis. The patient is reported to have AF if an electrocardiograph (ECG) done before stroke (old records) or AF documented during hospitalization. In addition, echocardiogram (ECHO) was done where it was indicated by the centers. The research staff verified the information from the patient records.

AF was broadly classified into two categories valvular versus nonvalvular AF:

  • Valvular atrial fibrillation: AF due to RHD
  • Nonvalvular AF: Absence of rheumatic mitral valve disease, a prosthetic heart valve, or mitral valve repair.[16]


Statistical analysis

The statistical measures calculated were descriptive statistics, Chi-square test, Fischer's exact test, and independent t-test. For the comparison of categorical variables, Chi-square test and Fischer exact test were used. For the comparison of continuous variable, independent t-test was used. P< 0.05 was considered as statistical significant. Statistical analysis was performed with SPSS version 21 (IBM Corp., Armonk, NY, USA).


   Results Top


Demography

Total number of patients recruited in the registry during 3-year study period was 7199, after excluding duplicate cases and incomplete entries, 6437 remained. Of these, 5629 were recruited within the study period (from March 26, 2011, to March 25, 2013). After excluding patients from scan centers and MC centers (for the lack of details on AF), 1942 patients' data were analyzed. Among them, AF was seen in 203 (10%) [Figure 1]. Out of 203, 3% had RHD and rest was related to nonvalvular AF. The patients in AF group were older (AF: 62 ± 14 vs. non-AF: 60 ± 15 years, P= 0.01) [Table 1].
Figure 1: Patients' recruitment in the study

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Table 1: Comparison of demographic details of stroke patients in atrial fibrillation versus nonatrial fibrillation patients

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Clinical features and risk factors

AF patients were more likely have aphasia (AF 137 [67%] vs. non-AF 756 [44%], P< 0.0001), less likely to have limb weakness (AF 139 [69%] vs. non-AF 1330 [77%], P= 0.02), unsteady gait (AF 63 [31%] vs. non-AF 894 [52%], P< 0.0001), headache (AF 52 [26%] vs. non-AF 623 [36%], P= 0.005), and facial weakness (AF 57 [28%] vs. non-AF 717 [41%], P< 0.001) [Table 2].
Table 2: Comparison of symptoms of stroke patients in atrial fibrillation versus nonatrial fibrillation patients

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The higher percentage of AF patients had hypertension (AF 176 [87%] vs. non-AF 1396 [80%], P= 0.03), coronary artery disease (AF 60 [30%] vs. non-AF 195 [11%], P< 0.0001), carotid stenosis (AF 14 [7%] vs. non-AF 57 [3%], P= 0.02), and hyperlipidemia (AF 60 [32%] vs. non-AF 345 [21%], P= 0.001) but fewer consumed alcohol (AF 15 [7%] vs. non-AF 248 [14%], P= 0.005) [Table 3].
Table 3: Comparison of risk factors of stroke in patients with atrial fibrillation versus nonatrial fibrillation

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Outcome

At 28 days, it was possible to contact patients telephonically. In AF group, 182 (89.7%) patients were contacted and 1504 (86.5%) patients in non-AF group. Patients in AF group had worse outcome (mRs >2: AF 90 [50%] vs. non-AF 555 [37%], P= 0.001) [Figure 2].
Figure 2: Outcome of patients in stroke patients in atrial fibrillation and nonatrial fibrillation at 28 days using modified Rankin scale

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   Discussion Top


Ten percent of stroke patients had AF. They were older, were more likely to present with aphasia, had multiple risk factors, and worse short-term outcome.

AF as a risk factor of stroke was comparable with other hospital-based studies from Pakistan (7% and 12%)[17],[18] and Nepal (13.8%).[19] Indian Heart Rhythm Society (IHRS-AF) conducted India's first AF registry. In this study, the average age was 54 years, but in the current study, AF patients were older. In IHRS-AF, RHD was the most common cause (732/1537 or 47.6%) followed by hypertension 482 (31.4%), heart failure 288 (18.7%), diabetes mellitus 248 (16.1%), and hyperlipidemia 131 (8.53%).[20] These risk factors were similar to the current study except for fewer RHD patients. Stroke patients with AF have multiple risk factors, and stroke mechanism (s) could be undetermined in these patients. However, certain imaging characteristics such as large artery occlusion or multiple infarcts in different territories may indicate AF as a mechanism in this group. It is important to recognize all risk factors in stroke patients with AF because stroke is multifactorial and other factors (apart from AF) will continue to be active. Hence, each factor needs to be recognized and addressed individually. These risk factors are also reported as common by other series from Pakistan and Nepal.[19],[21],[22],[23],[24],[25],[26]

Patients in AF group had worse outcome when compared to patients in non-AF group. These findings are similar to reported studies that establish stroke in AF patients to be more severe and have worse outcome compared to stroke patients without AF.[1],[27],[28],[29],[30],[31] AF patients usually have large clot burden or occlusion of major vessels. However, in the current study, we did not collect information regarding the volume of infarct and vessel status.

The strength of this study is that it had population-based cohort which provides a more precise burden of AF in stroke patients.

There are a few limitations of this study. First, in this study, the general population was not screened to find out the burden of AF in the community. Second, we did not collect information about single or serial ECGs and also about Holter monitoring. Since ECHO and repeat ECGs were not done in all the patients, AF may be underestimated.


   Conclusions Top


Ten percent of stroke patients had AF. AF patients in this cohort were older with multiple risk factors for stroke and had worse outcome. There was no gender difference seen in this large cohort.

Acknowledgment

The authors would like to thank Madhu Bala for managing the database; Premjeeth Moodbidri, Gagandeep Mehmi, Amber Sharma, Rohit, and Manpreet Kaur for helping with data collection; the following general practitioners for sharing data: Nitin Sood, Bhushan Bansal, B. L. Malhotra, R. S. Bhatia, Punit Midha, Rahul Jain, and Subhash Sachdeva; and members of The ICMR task force group - M. Gourie Devi: Chairperson, ICMR task force group, Emeritus Professor of Neurology, Department of Neurology, Institute of Human Behaviour and Allied Sciences, New Delhi, Former Director-Vice Chancellor, Professor of Neurology, National Institute of Mental Health and Neurosciences, Bengaluru; Senior Consultant, Sir Ganga Ram Hospital, New Delhi; A. Nanda Kumar: National Center for Disease Informatics and Research, Bengaluru; Kameshwar Prasad: Professor and Head, Department of Neurology, Neurosciences Center, All India Institute of Medical Sciences, New Delhi; P. Satish Chandra: Vice-Chancellor and Director, National Institute of Mental Health and Neurosciences, Bengaluru; K. Radhakrishnan: Professor and Head, Department of Neurology, Kasturba Hospital, Manipal, Karnataka, Former Director, Sree Chitra Tirunal Institute for Medical Sciences and Technology, Thiruvananthapuram, Kerala; K. R. Thankappan: Professor and Head, Achutha Menon Center for Health Sciences Studies, Sree Chitra Tirunal Institute for Medical Sciences and Technology, Thiruvananthapuram, Kerala. Sharing of data: Arora Om P., Dhanuka Arun K.

Financial support and sponsorship

This study was supported by ICMR, Task Force Project, New Delhi (SWG/22/Neuro/2008-NCD-I).

Conflicts of interest

There are no conflicts of interest.

 
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[PUBMED]  [Full text]  
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