
The study aimed to externally validate an echocardiographic algorithm derived by machine learning (e′VM) and explore whether it can identify subgroups of individuals who may benefit from spironolactone. The results showed that the e′VM algorithm identified distinct echocardiographic phenotypes with different responses to spironolactone, as evidenced by changes in E/e' and BNP levels. The interactions were not observed when considering guideline-recommended echocardiographic abnormalities. The study suggests that the e′VM algorithm may help identify individuals who are more likely to benefit from spironolactone treatment.
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