Stroke-heart syndrome and early mortality in patients with acute ischaemic stroke using hierarchical cluster analysis: An individual patient data pooled analysis from the VISTA database.

BACKGROUND

The patient clinical phenotypes at particularly high risk for early cardiac complications after a recent acute ischaemic stroke (AIS), that is, stroke-heart syndrome (SHS), remain poorly defined. We utilised hierarchical cluster analysis to identify specific phenotypic profiles associated with this risk.

METHODS

We gathered data on patients with AIS from the Virtual International Stroke Trials Archive, a global repository of clinical trial data. We examined cardiac complications within 30 days post-stroke, including acute coronary syndrome, heart failure, arrhythmias and cardiorespiratory arrest. We employed hierarchical cluster analysis to define distinct phenotypic risk profiles. The incidence/risk of SHS and 90-day mortality were compared across these profiles.

RESULTS

We included 12,482 patients (mean age 69 ± 12 years; 55% male), yielding five phenotypes: Profile 1 (''), Profile 2 (''), Profile 3 (''), Profile 4 ('') and Profile 5 (''). Profiles 4 and 1 exhibited the highest risk for SHS (adjusted HR (95% CI): 2.01 (1.70-2.38) and 1.26 (1.05-1.51), respectively, compared to Profile 3), while Profiles 5 and 2 showed moderate risk and Profile 3 had the lowest risk. Although Profiles 1 and 4 were at the highest risk for most SHS presentations, Profile 5 had the highest risk for cardiorespiratory arrest (adjusted HR (95% CI): 2.99 (1.22-7.34)). The 90-day mortality risk was stratified by phenotype, with the highest risk observed in Profiles 5, and 4.

CONCLUSIONS

Hierarchical cluster analysis effectively identified phenotypes with the highest risk of SHS and early mortality in patients with AIS.