Stroke in acute coronary syndrome: predictors and prognosis. (11th May 2021)

• Record Type: Journal Article
• Authors: Santos, M; Santos, H; Almeida, I; Miranda, H; Sa, C; Chin, J; Almeida, S; Sousa, C; Tavares, J; Santos, L; Almeida, ML
• Is Part Of: European journal of preventive cardiology. Volume 28:Supplement 1(2021)
• Publication Date: 2021-05-11
• Subjects: Cardiovascular system -- Diseases -- Prevention -- Periodicals; Cardiac patients -- Rehabilitation -- Periodicals; 616.12
• DOI: 10.1093/eurjpc/zwab061.055
• Languages: English
• ISSNs: 2047-4873

Abstract

Abstract: Funding Acknowledgements: Type of funding sources: None. OnBehalf: on behalf of the Investigators of " Portuguese Registry of ACS " Introduction: Stroke is a potential complication of acute coronary syndromes (ACS) and it is, therefore, important to access its impact on prognosis and identify patients with higher risk of stroke in the setting of ACS. Objective: To evaluate predictors and prognosis of stroke in the setting of ACS. Methods: Based on a multicenter retrospective study, data collected from admissions between 1/10/2010 and 4/09/2019. Patients (pts) without data on previous cardiovascular history or uncompleted clinical data were excluded. Pts were divided in 2 groups (G): GA – pts without stroke; GB - pts with stroke during hospitalization. Logistic regression was performed to assess predictors of stroke in ACS. Survival analysis was evaluated through Kaplan Meier curve. Results: Population – 25711 pts with ACS, CA occurred in 154 (0.6%). Regarding epidemiological factors and past history, GB was older (72 ± 12 vs 67 ± 14, p < 0.001), had higher rates of females (53.2% vs 27.5%, p < 0.001), diabetes (43.9% vs 31.5%, p < 0.001), previous stroke (13.3% vs 7.2%, p = 0.004), peripheric arterial disease (9.2% vs 5.5%, p = 0.044) and dementia (6.8% vs 1.7%, p < 0.001), and had lower rates of smoking (16.6% vs 26.7%, p = 0.005), dyslipidaemia (53.5% vs 61.6%, p = 0.047) and previous ACS (12.7% vs 20.6%, p = 0.017. GB had longer times from first symptoms to admission (340min vs 240min, p = 0.011). The groups were similar regarding diagnosis, namely non-ST-elevation myocardial infarction (MI) (p = 0.345) and ST-elevation MI (p = 0.541). GB had higher heart rate (HR) (84 ± 24 vs 77 ± 19, p = 0.001), presented more frequently in Killip-Kimball class (KKC) ≥2 (28.0% vs 15.1%, p < 0.001), in atrial fibrillation (AF) (16.4% vs 7.1%, p < 0.001) and with higher brain-natriuretic peptide levels (545 vs 180, p < 0.001). The groups were similar regarding culprit lesion and number of lesions. GB had more left ventricle (<50%) dysfunction (51.4% vs 39.1%, p < 0.001) and needed more frequently mechanical ventilation (10.4% vs 1.9%, p < 0.001) and provisory pacemaker (8.4% vs 1.5%, p < 0.001). Logistic regression confirmed that older age (p = 0.018, OR 1.69, CI 1.10-2.60), female gender (p < 0.001, OR 2.09, CI 1.38-3.15), diabetes (p = 0.002, OR 1.91, CI 1.27-2.86), dementia (p = 0.047, OR 2.13, CI 1.01-4.50), AF (p = 0.024, OR 1.87, CI 1.09-3.21) and lower left ventricle function (p = 0.002, OR 2.01, CI 1.29-3.15) were predictors of stroke in the setting of ACS. Event-free survival was higher in GA than GB (79.9% vs 70.5%, OR 1.58, p < 0.001, CI 1.36-1.83). Conclusion: As expected, stroke in the setting of ACS is associated with poorer prognosis. Several characteristics of the pts may help to predict the occurrence of stroke during hospitalizations, therefore allowing an earlier identification and prompt treatment.