Hypertrophic cardiomyopathy (HCM), a genetic heart condition affecting approximately one in 500 individuals, is characterized by a thickening of the heart’s muscular wall, impeding its ability to efficiently pump blood. This condition can be life-threatening if left untreated, potentially leading to abnormal heart rhythms, cardiac arrest, and sudden death. Despite affecting both men and women equally, current diagnostic guidelines have led to a significant underdiagnosis in women, with two-thirds of diagnosed cases being men. This disparity stems from outdated testing methods that fail to account for natural variations in sex and body size.
Traditionally, HCM diagnosis has relied on measuring the thickness of the left ventricle wall, the heart’s primary pumping chamber, with a threshold of 15mm. Any measurement exceeding this threshold has typically indicated a likely HCM diagnosis. However, this one-size-fits-all approach, based on studies from the 1970s, has proven inadequate in accurately diagnosing HCM across diverse populations. The fixed threshold disregards the influence of age, sex, and body size on heart wall thickness, leading to misdiagnoses and overlooking cases, particularly in women.
A recent study funded by the British Heart Foundation has challenged this outdated method, proposing a new, personalized approach to HCM diagnosis. This innovative method utilizes artificial intelligence to analyze thousands of heart scans, incorporating factors like age, sex, and body size to establish individualized thresholds for heart wall thickness. This personalized approach has demonstrated a significant improvement in diagnostic accuracy, particularly for women, with a 20 percentage point increase in HCM identification.
The study, published in the Journal of the American College of Cardiology, involved 1,600 HCM patients whose conditions were reassessed using the new personalized method. Further validation was conducted on data from over 43,000 individuals in the UK Biobank. The results revealed a lower overall number of HCM diagnoses when applying the personalized thresholds, suggesting a reduction in misdiagnoses and a more accurate representation of the condition’s prevalence. Significantly, the gender distribution among diagnosed individuals shifted to a more balanced 44% for women, supporting the hypothesis that women have been systematically underdiagnosed.
The implications of this research are profound, emphasizing the urgent need to revise existing HCM diagnostic guidelines. The outdated, one-size-fits-all approach not only fails to accurately diagnose the condition but also disproportionately affects women, potentially delaying or denying them access to life-saving treatments. The personalized method offers a more precise and equitable approach, ensuring that individuals of all sexes and sizes receive appropriate and timely diagnosis.
Dr. Hunain Shiwani, the lead researcher, stresses the importance of adopting personalized thresholds, highlighting the influence of age, sex, and body size on heart wall thickness. With the emergence of effective HCM treatments, accurate diagnosis becomes even more critical to ensure that those in need receive appropriate care. Dr. Sonya Babu-Narayan, clinical director at the British Heart Foundation, echoes this sentiment, emphasizing the severe and potentially life-threatening nature of HCM and the importance of preventing misdiagnoses and missed diagnoses. The new personalized approach offers a significant step towards improving the accuracy of HCM diagnosis, ensuring that both men and women receive the appropriate medical attention they require. This improved diagnostic accuracy has the potential to significantly impact the lives of those affected by HCM, facilitating earlier intervention and improving long-term outcomes.
