A prospective two-step screening strategy using a self-report questionnaire accurately identified 59–60-year-olds most likely to harbor significant coronary artery calcium (CAC ≥100). Among 563 individuals who completed CT imaging after model-based pre-selection, the mean predicted probability of CAC ≥100 was 28.3% versus an observed prevalence of 28.4%—an expected/observed ratio of 0.99, indicating near-perfect calibration. Critically, 64% of those with CAC ≥100 were not receiving lipid-lowering therapy, and 11% had LDL-C ≥1.8 mmol/L, signaling a substantial prevention gap.
CAC scoring has long been recognized as one of cardiovascular medicine's sharpest tools for reclassifying intermediate-risk individuals, yet its population-wide deployment is constrained by cost and radiation exposure. A validated self-report pre-filter that achieves this calibration precision could dramatically improve the efficiency of screening programs without requiring biomarkers or clinic visits upfront. The treatment gap finding is particularly striking: nearly two-thirds of high-calcium individuals were unprotected by statins, suggesting that targeted screening translates directly into actionable clinical opportunities.
Limitations deserve emphasis. Only 32% of invited individuals completed the questionnaire, introducing potential selection bias toward health-conscious participants—likely inflating model performance. The cohort is narrow (ages 59–60, Swedish population), limiting generalizability. Causal benefit of the screening strategy on hard cardiovascular outcomes remains undemonstrated. As a preprint posted to medRxiv and not yet peer-reviewed, these promising calibration results should be interpreted cautiously until independent validation and formal peer scrutiny are complete. Confirmatory, but meaningfully so.
