This analysis evaluates treatment strategies and risk prediction for cardiovascular outcomes in patients with hormone deficiency, suggesting improvements in individualized care.
Despite advances in hormone replacement, many patients retain excess CV risk that is not captured by conventional prediction models. Endocrine-adapted risk stratification, individualized replacement strategies considering dose and chronobiology, and integration of emerging tools such as artificial intelligence - based models may improve risk prediction. Dedicated cardiovascular outcome trials in endocrine populations remain a major unmet need.
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Pedro Iglesias (2026) studied this question.
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