| ORIGINAL ARTICLE |
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| Year : 2020 | Volume
: 16
| Issue : 3 | Page : 105-109 |
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Prediction of outcomes in stroke patients from radiological findings – A hospital-based retrospective cohort study from a comprehensive stroke care center in Kerala, India
Remya Sudevan1, Vivek Nambiar2, Padma Priyaa Arumugam Premalatha3, Sridhar Suresh Babu3, Anu Vasudevan4
1 Department of Health Sciences Research, Amrita Institute of Medical Sciences, Kochi, Kerala, India
2 Department of Neurology, Amrita Institute of Medical Sciences, Kochi, Kerala, India
3 Department of Community Medicine, Amrita Institute of Medical Sciences, Kochi, Kerala, India
4 Department of Biostatistics, Amrita Institute of Medical Sciences, Kochi, Kerala, India
Correspondence Address:
Dr. Vivek Nambiar
Division of Stroke, Centre of Neurosciences, Amrita Institute of Medical Sciences, Ponekkara, Kochi - 682 041, Kerala
India
 Source of Support: None, Conflict of Interest: None
DOI: 10.4103/AMJM.AMJM_18_20
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Introduction: Functional outcome after stroke can be improved by early and accurate diagnosis with the help of imaging techniques such as computed tomography (CT) and magnetic resonance imaging. Alberta Stroke Program Early CT Score (ASPECTS) calculated from the CT image infarct areas of middle cerebral artery (MCA) circulation is supposed to be a reliable outcome predictor. Methodology: A retrospective cohort study was conducted in the Comprehensive Stroke Care Center for a period of 6 months. All adult patients (18–90 years) who had visited the hospital from January 2014 to December 2017 were enrolled for the study. Patients with MCA strokes were only included in the study since the ASPECTS is defined for this territory. The data were gathered from the electronic format of the patient information system in the institution and were entered in a structured proforma specifically designed for the study. ASPECTS was calculated from the CT findings of the patient. The modified Rankin Scale (mRS) scores were calculated for every patient at four different time points. The collected data were compiled in a Microsoft Excel sheet and were analyzed using IBM Statistical Package for Social Sciences (SPSS version 21). The summary statistics for categorical variables were reported using frequency and percentage and continuous variables as mean (standard deviation). We reported the association of the ASPECTS with mRS at different time points using the Chi-Square test. Results: A total of 132 adult patients were enrolled in the study. The mean age of the study population was 60.72 (±13.99) years, and among them, 93 (70.45%) were males. Majority of the patients were nonvegetarians (99.92%). The most prevalent risk factor found was hypertension (62.1%). The most common symptom presented by the patients was facial palsy (28%). When the ASPECTS was calculated for 132 patients, 62 patients fell in the high ASPECTS category (8–10), 45 patients had a moderate ASPECTS (5–7), and 25 had low ASPECTS (0–4). mRS scores calculated for four different time points showed a decline in disability in most of the patients. ASPECT and mRS had a negative association signifying, as the ASPECTS increases the number of functional disability decreases. Conclusions: Our study results show that ASPECTS can be a definite outcome predictor in MCA stroke patients.
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