The Aga Khan University Hospital is a JCIA (Joint Commission International Accreditation) accredited tertiary care hospital in Karachi, Pakistan. Stroke care is delivered through a 24-hour on-call neurology team with a stroke service on call for hyperacute stroke with a 5 bed specialized stroke unit and a full range of ancillary services. As a standard of care, all admitted stroke patients are evaluated by a consultant neurologist and undergo stroke workup that includes neuroimaging via MRI and MRA, electrocardiogram (ECG), transthoracic echocardiography (TTE), Carotid Doppler Sonography and Biochemical workup such as serum glucose, lipid profile, blood urea nitrogen and serum creatinine. These are standardized investigations that are conducted on every admission and ensure homogeneity of evaluation. All these scans and echocardiograms are accessible via the hospital online database that details all investigations for these patients. In addition, all admissions are encoded for stroke diagnosis through a hospital wide ICD-9 coding system allowing identification of all admissions.
This set up enabled a comprehensive review of all adult stroke patients admitted to this service from July 2005 to December 2010. There were 633 patients admitted, identified as suffering from ischemic stroke through the ICD-9 code with the assistance of medical records. Patients with evidence of hemorrhagic stroke, subarachnoid hemorrhage, and those with hematologic, neoplastic, infectious, iatrogenic or inflammatory conditions associated with stroke were excluded because the pathophysiology and natural course of these causes differ from atherosclerotic ischemic stroke. Patients with stroke due to any other subtype e.g. Cryptogenic stroke, stroke due to known hypercoagulable state, dissection were excluded from this review. Additionally, patients with more than one competing diagnosis were excluded.
Data was reviewed for demographic characteristics and electrocardiographic and echocardiographic data was also recorded on a predesigned structured questionnaire. This was developed in conjunction with cardiological input.
Demographic variables included age and gender, medical variables including height, weight, history or evidence of diabetes mellitus, hypertension, dyslipidemia, history of ischemic heart disease, prior stroke, and history of atrial fibrillation, congestive cardiac failure and tobacco use were recorded. ECGs were analyzed for evidence of atrial fibrillation. Echocardiographic evidence was documented for the presence of left atrial thrombus, left ventricular thrombus, presence of any vegetation, global segmental hypokinesia, left ventricular ejection fraction less than 30%, measurements were recorded for left atrial diameter (LAD) which was measured in antero posterior (AP) linear dimension obtained from the parasternal long axis view, at Left Ventricular end systole (when left atrium is at the maximum volume), left atrial volume index (LAVi), left ventricular diameter in diastole (LVD), posterior left ventricular wall thickness (PWT), and interventricular septal thickness(IVST). Left Ventricular mass (LVM) was calculated using the guidelines from American Society of Echocardiography (ASE) and indexed for body surface area (LVMi) as recommended for reference in population. Reference values for LAD, LAVi and LVMi in males and females were derived from Guidelines from the American Society of Echocardiography [8].
Furthermore for left atrial measures, since single axis measurement is unreliable when atrial dilation is non-uniform, in our laboratory we actually measure both. i.e. the LA diameter in AP length and also the atrial volume which is measured by using area-length (L) method using Apical 4 chamber view (A1) and apical 2 chamber view (A2) at ventricular end systole. The information is put in the formula 0.85 (A1 × A2) divided by L for the atrial volume and indexed to Body Surface Area (BSA) giving us the left atrial volume index (LAVi).
Strokes were classified using the Causative Classification of Stroke by neurologists who were trained in stroke diagnosis and ran a stroke clinic [9]. In addition, magnetic resonance imaging and carotid doppler scans read by trained neuroradiologists were utilized for this classification. The stroke classifying personnel were trained and certified in this technique before undertaking this review. This classification team did not have access to the exact advanced echocardiographic measures that are reported in this study during the time of stroke classification. The CCS system is an online system where data is entered into a computerized system and it assists in the correct mechanistic diagnosis, with a level of confidence assigned to the mechanism as probable, possible or evident, we included patients in the cardioembolic and atherosclerotic stroke category when any of these levels were assigned, and there were no competing mechanisms.
After entering the data for stroke classification, demographic variables and echocardiographic data, simple frequencies were run and comparisons were performed. Data was entered centrally with the echocardiography team and classification team both unaware of any emerging trends till the data entry was complete.
For the purpose of this comparative analysis those with evident, possible and probable Cardioembolic Strokes were compared with patients with stroke due to atherosclerotic mechanisms (Large artery, ICAD -IntraCranial Atherosclerotic Disease, ECAD-ExtraCranial Atherosclerotic Disease and Small vessel strokes).
The study was approved by the Ethical Review Committee of the Aga Khan University through approval number 1660-Neu-ERC-2010 under exemption category as it is a detailed review.
Statistical analysis
Data were analyzed through SPSS 19, and reported as mean ± SD for continuous variables and proportions and percentages for categorical data. Comparisons between groups were done by the unpaired Student’s t-test and Chi- square test respectively. P value less than 0.05 was considered significant. Normality of the data was assessed by Kolmogorov-Smirnov statistic.