{'fraction_non_alphanumeric': 0.027235050325636473, 'fraction_numerical': 0.023682652457075192, 'mean_word_length': 5.1454545454545455, 'pattern_counts': {'":': 0, '<': 2, '<?xml version=': 0, '>': 1, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
Role of S100β Glial Protein as a Serological Marker for Analysis of Acute Ischemic Stroke

Background: Stroke is a major cause of neurological disability, which can be often predicted with serological markers. Glial-derived S100β protein is a potential biomarker for cerebral ischemia and may be helpful in predicting the severity, outcome, and recovery of stroke. Aim: This study aimed to study the role of S100β glial protein as a serological marker in predicting the severity of acute ischemic stroke (AIS), outcome, and functional recovery after 1 month. Methods: A hospital-based prospective case control study included 43 consecutive patients, >18 years old, who were admitted with acute middle cerebral artery (MCA) territory infarcts within 72 h of onset of neurological deficits. Control group comprised of 43 age-matched asymptomatic volunteers. Independent t-test and chi square test were used to compare the means and evaluate the association between protein level and various parameters. P ≤ .05 was statistically significant. Results: S100β protein level in AIS patients was significantly higher compared to controls (P < .05). Elevated serum S100β protein level was found to be associated with larger infarct volumes, higher National Institute Health Stroke Scale scores, and higher modified Rankin Scale scores at admission (P < .05). Patients with higher S100β protein levels at admission had poor recovery at 1 month compared to patients having normal S100β protein levels. Conclusion: S100β protein levels at admission after an acute MCA territory infarct may be used as a reliable serological tool in predicting the severity, outcome, and functional recovery in stroke.