Artikel
Acute coronary syndrome after aneurysmal subarachnoid haemorrhage – incidence, risk factors and impact on the outcome
Akutes Koronarsyndrom nach aneurismatischer Subarachnoidalblutung: Inzidenz, Risikofaktoren und Einfluss auf das Outcome
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Veröffentlicht: | 25. Mai 2022 |
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Gliederung
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Objective: Development of acute coronary syndrome (ACS) after aneurysmal subarachnoid hemorrhage (SAH) strongly impacts the neuro-intensive care management of the affected individuals. We aimed at analyzing the incidence, risk factors and clinical impact of ACS in SAH patients.
Methods: All consecutive SAH cases treated between 01/2003 and 06/2016 were retrospectively analyzed. Occurrence of ACS during 3 weeks of SAH was documented. Patients’ demographic, clinical, radiographic and laboratory characteristics at admission were collected as potential ACS predictors. The association between ACS and SAH outcome was analyzed upon the occurrence of cerebral infarcts in the computed tomography scans, and unfavorable outcome (modified Rankin scale>3) at 6 months after SAH. Univariable and multivariable analyses were performed.
Results: ACS was documented in 3.3 % (28/855) of cases in the final cohort (mean age: 54.9 years; 67.8% females). In the multivariable analysis, there was a significant association between ACS with unfavorable outcome (aOR=3.43, p=0.027) and borderline significance with cerebral infarcts (p=0.066, aOR=2.5). The final prediction model for ACS occurrence included five independent predictors (age>55 years [1 point], serum sodium170 mg/dl [2 points], serum creatine kinase>254 U/l [3 points] and gamma-glutamyl transferase>35 U/l [1 point]) and showed a high diagnostic accuracy for ACS prediction (AUC=0.879). Depending on the cumulative points value, the risk of ACS in the cohort varied between 0% (0 points) and 66.7% (10 points).
Conclusion: ACS is a rare, but clinically very relevant complication of SAH. Development of ACS can reliably be predicted by the presented prediction model which enables proper and early identification of SAH individuals at high risk for ACS. External validation of the prediction model is mandatory.