Correlation between symptomatic, radiological and etiological diagnosis in acute ischemic stroke

Understanding stroke subtypes is essential for guiding treatment and predicting outcomes. Prior research has shown that stroke classifications based on symptoms often align with radiological findings. However, the relationship between clinical, imaging, and etiological diagnoses remains unclear in some cases. While established methods like the Oxfordshire Community Stroke Project (OCSP) criteria have been used to classify stroke symptoms, the extent to which these match radiological and etiological diagnoses is not fully resolved. This uncertainty drives the need for studies that clarify these diagnostic correlations. No prior work has fully addressed how well symptomatic classifications predict etiological subtypes. The gap motivated this study to examine the overlap between clinical, imaging, and etiological stroke classifications. This paper's contribution is to provide data on how these classifications align in real-world patient populations.

This study aimed to evaluate the correlation between clinical symptoms, radiological findings, and etiological diagnoses in patients with acute ischemic stroke. The researchers focused on first-ever stroke cases within 24 hours of onset to ensure accurate and timely data collection. By using three diagnostic steps—symptomatic, radiological, and etiological—the study sought to determine how well these classifications align. The motivation for this work stems from the need to improve stroke diagnosis accuracy and treatment planning. The authors wanted to test whether the Oxfordshire Community Stroke Project (OCSP) criteria could predict radiological and etiological outcomes. They also aimed to assess the reliability of these diagnostic methods in different stroke subtypes. This work may help clinicians better understand stroke classifications and their implications. The study’s design allowed for a detailed comparison of symptom-based, imaging-based, and cause-based stroke diagnoses.

The study enrolled 250 patients with first-ever acute ischemic stroke within 24 hours of onset. Each patient underwent three diagnostic assessments: symptomatic diagnosis using the Oxfordshire Community Stroke Project (OCSP) criteria, radiological diagnosis via CT or MRI scans, and etiological diagnosis based on the Lausanne Stroke Registry criteria. The symptomatic classification divided patients into four groups: total anterior circulation infarct (TACI), partial anterior circulation infarct (PACI), posterior circulation infarct (POCI), and lacunar infarct (LACI). Radiological diagnosis confirmed or modified these classifications using brain imaging. The etiological diagnosis categorized strokes into cardioembolism (CE), large-artery atherosclerosis (LAA), or small-artery disease (SAD). Researchers compared the three diagnostic methods to assess their alignment and predictive value. The study used descriptive statistics to analyze the distribution of stroke subtypes and diagnostic correlations. This approach allowed for a detailed comparison of clinical, imaging, and cause-based stroke classifications.

The study found that most patients with TACI, PACI, and POCI symptoms had corresponding radiological findings. However, only 68% of LACI patients had small subcortical infarctions (SSI) on imaging. For TACI cases, over 60% were classified as cardioembolism in the etiological diagnosis. In PACI cases, the etiology was equally split between cardioembolism and large-artery atherosclerosis. In LACI cases, only 58% were classified as small-artery disease, with 29% classified as large-artery atherosclerosis. Of these, 23 patients had lesions other than SSI. The positive predictive value of small-artery disease in LACI and SSI was 0.78. Posterior circulation infarcts showed variable etiologies. The results suggest that symptomatic classifications align well with radiological findings in most stroke types except LACI. The study highlights the difficulty in predicting etiology for POCI and the potential misclassification of some LACI cases.

The authors suggest that symptomatic classifications using the OCSP criteria align well with radiological findings in most stroke subtypes. However, this correlation is less strong in lacunar infarcts (LACI), where only 68% of cases had corresponding small subcortical infarctions on imaging. The study indicates that TACI and PACI classifications may predict etiological diagnoses with reasonable accuracy, but POCI cases show more variability. The findings suggest that LACI cases may be misclassified, with some attributed to large-artery atherosclerosis rather than small-artery disease. The positive predictive value of small-artery disease in LACI and SSI was 0.78. These results may help clinicians better understand the limitations of stroke classification systems. The authors propose that diagnostic accuracy could be improved by combining clinical, imaging, and etiological assessments. This study contributes to the ongoing discussion about stroke diagnosis and classification methods.