ISSN: 0970-938X (Print) | 0976-1683 (Electronic)

Biomedical Research

An International Journal of Medical Sciences

Abstract

Acute cerebral infarction in non-diabetes patients: clinical pattern, stroke subtypes, and predictors of in-hospital mortality

Purpose: Cerebral infarction is the most common type of ischemic stroke that is associated with early mortality and decrease functional capacity. Current study aims to compare prognostic characteristics and outcomes of acute cerebral infarction in diabetic and non-diabetic patients.

Methods: A total of 1283 with confirmed diagnosis of cerebral infarction were enrolled in the current study. The patients were followed-up up to 10 y to ascertain the clinical pattern, stroke subtypes and predictors of in-hospital mortality.

Results: The mean age of participants was 66.9 ± 5.3 y and majority 695 (54.1%) were male. Diabetes was diagnosed in one third of study population i.e. 403 (31.4%). Compared to diabetic patients, nondiabetic patients mostly presented with cardioembolic infarcts (28% vs. 17%) and infarcts of unknown cause (16.5% vs. 5.4%) while atherothrombotic (43% vs. 26%) and lacunar infarcts (36% vs. 22%) were more common among diabetics. A total of 210 (16%) cases of in hospital mortality were observed. There was no significant difference in mortality rates of both diabetic and non-diabetics (17.6% vs. 13.6%). Cardioembolic strokes, strokes of unknown cause and unusual etiology and Rankin score<3 were independently associated while age was inversely associated with cerebral infarction in non-diabetic patients. The predictors of mortality included female gender, atrial fibrillation, decreased consciousness, respiratory and cardiac complications.

Conclusion: Compared to diabetic patients, non-diabetic patients with cerebral infarction present with different disease pattern and prognosis. Clinical factors that indicate severity of stroke and predict early mortality might help physicians to assess prognosis of patients more effectively and provide adequate treatment.

Author(s): Junwu Zhang, Peiyu Li
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