Abstract:
Stroke remains a significant public health concern, necessitating accurate and timely classification for optimal management and improved patient outcomes. This thesis investigates the correlation between Emergency Room (ER) stroke classifications using the Bamford criteria and neuroimaging, subsequently exploring the impact of these classifications on early and
long-term patient outcomes in an urban tertiary hospital.
The study employed a prospective analysis of stroke cases presented to the ER over a specified period, focusing on the application of the Bamford classification system and its integration with neuroimaging findings. Bamford criteria, including total anterior circulation infarct (TACI), partial anterior circulation infarct (PACI), lacunar infarct (LACI), and posterior circulation infarct (POCI), were utilized to categorize strokes.
Aims:
Evaluate the Efficacy of Bamford Criteria: Assess the accuracy of stroke subtyping in the Emergency Room (ER) using the Bamford classification system, with a focus on total anterior circulation infarct (TACI), partial anterior circulation infarct (PACI), lacunar infarct (LACI), and posterior circulation infarct (POCI).
Correlate Clinical Presentation with Neuroimaging: Investigate the concordance between clinical presentation and neuroimaging findings in stroke cases, aiming to enhance the precision of stroke subtyping and classification.
Examine Early Outcomes: Explore the predictive value of the Bamford classification system and neuroimaging in determining early outcomes, including the severity of neurological deficits and the necessity for acute interventions, in stroke patients admitted to an urban tertiary hospital.
Assess Long-Term Functional and Clinical Consequences: Investigate the long-term consequences of stroke subtypes on patient outcomes, including functional recovery, recurrence rates, and mortality, to provide insights into the extended impact of accurate stroke classification.
Objectives:
Analyze ER data systematically and determine Concordance between Clinical and Imaging Data: Assess the degree of agreement between clinical symptoms and neuroimaging findings, seeking to establish a correlation that enhances the accuracy of stroke subtyping.
Investigate Early Outcomes: Evaluate the association between Bamford classifications, neuroimaging results, and early outcomes, such as the severity of neurological deficits and the necessity for acute interventions, during the initial phase of stroke care.
Explore Long-Term Patient Follow-Up: Conduct a comprehensive follow-up study to investigate the long-term functional and clinical outcomes of stroke patients, with an emphasis on recurrence rates, mortality, and the impact of accurate stroke classification on sustained recovery.
Provide Recommendations for ER Stroke Protocols: Based on the findings, offer recommendations for refining ER stroke protocols, aiming to improve the accuracy of stroke classification and enhance patient outcomes in both the acute and long-term phases of stroke care.
Materials & Methods:
Study Design:
This research will adopt a prospective cohort study design to investigate the correlation between ER stroke classification utilizing the Bamford criteria and neuroimaging, followed by an examination of early and long-term outcomes using modified Rankin scale in an urban tertiary hospital setting.
Study Setting:
The study will be conducted in the Department of Emergency Medicine, Kauvery Hospital, Chennai, a well-established medical facility with a high volume of stroke admissions over a period of one year.
Study Population:
The study will include all adult patients (age 18 years and above) who presented with acute stroke symptoms to the ER of Kauvery hospital within a specified time period. Cases will be identified using electronic health records.
Inclusion Criteria:
Any patients >18 years with signs & symptoms of acute ischemic stroke.
Exclusion Criteria:
Patients excluded from this study if permission for CT was refused by patient or attending physician, if there was severe previous disability (i.e. Rankin 5, e.g. the patient was bedridden following a previous severe stroke or other severe debilitating illness), if the patient was discharged or died soon after admission or if a primary intracerebral haematoma or tumor was seen on their brain scan and judged likely to be responsible for their symptoms. Patients whose symptoms resolved rapidly, i.e. who suffered a transient ischaemic attack (TIA), will also be excluded.
This study aims at correlating between clinical classification and radiological diagnosis and the sensitivity, specificity, positive predictive value, and negative predictive value of the clinical diagnoses, using CT/MRI as the gold standard will be calculated .
Stroke subtype, demographic, functional status (pre- stroke, within 48 hours, at 2 months, and 6 months) as well as neurological complications will be analysed.
Hence, the integration of Bamford classification and imaging correlation may provide a nuanced understanding of stroke subtypes, aiding in tailored treatment strategies. The observed variations in early outcomes and ongoing analysis of long-term outcomes will further elucidate the impact on patient prognosis and guide post-stroke management.
By merging clinical criteria with advanced imaging, we aim to elevate diagnostic accuracy and prognostic precision. Thereby, optimizing stroke care, tailoring interventions, and ultimately improving patient outcomes in the demanding urban tertiary hospital environment.
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Dr. Kalai Muhilan
Emergency Medicine Resident
Kauvery Hospital, Chennai
Dr. Sivarajan Thandeswaran
Consultant – Stroke & Neuro-vascular Medicine
Kauvery Hospital, Chennai
Dr. Aslesha Vijaay Sheth
Consultant & Clinical Lead,
Department of Emergency Medicine
Kauvery Hospital, Chennai