Prevention guidelines might be failing younger patients, after a new JACC Advances analysis of first-MI patients under 65 revealed that over half would not have qualified for statins just two days before their cardiac event based on their ASCVD Risk Estimator Plus and PREVENT equations scores.
- Traditional cardiovascular risk assessment relies on population-level calculators that use biomarkers like LDL-C and BP to estimate 10-year ASCVD risk and statin therapy needs.
- Current ACC/AHA guidelines recommend intensive treatment only for patients classified as intermediate or high risk, leaving low-risk patients without preventive interventions.
Assessing these equations’ applicability to younger people, researchers examined 465 patients (81% male) aged ≤65 presenting with first MI at two large hospitals and simulated how current guideline-directed tools would have classified them just 48 hours before their cardiac event…
- Using ASCVD Risk Estimator Plus, 45% of MI patients would not have been recommended statins or imaging based on low 10-year risk scores, with one-third classified as low risk.
- The newer PREVENT equations performed even worse, missing 61% of MI patients who would have been classified as too low-risk for preventive interventions.
Beyond the equations, symptom-based screening also failed…
- 60% of patients had no chest pain or dyspnea until within 48 hours of MI presentation, with 54% experiencing chest pain for the first time only 24 hours before their event.
- None of these low-to-intermediate risk patients would have received statin recommendations under 2018’s ACC/AHA cholesterol management guidelines.
Despite guideline-directed risk assessment tools working well on the population level, they’re not the most capable at gauging a patient’s individual risk.
- Clinical events still occur in patients deemed low risk by current calculators, so we know risk-score approaches are limited.
- Low LDL-C also doesn’t provide any guarantees that a patient is free from ASCVD, since it’s not a form of direct disease detection.
The Takeaway
While we’ve seen many studies validate population-level risk equations in the past, this study is a reminder that patients are individuals, and more importantly, looking for disease using only biomarkers is like judging how good something tastes just by how it smells – it’s never the full picture.
