Development and validation of a clinical factor-based nomogram for predicting imaging-defined cardiopulmonary abnormality risk in an asymptomatic screening population.
A new nomogram accurately predicts cardiopulmonary abnormalities in asymptomatic individuals.
Development and validation of a clinical factor-based nomogram for predicting imaging-defined cardiopulmonary abnormality risk in an asymptomatic screening population.
Chronic cardiopulmonary diseases, including chronic obstructive pulmonary disease, interstitial lung disease, and coronary artery disease, represent a major global health burden.
To evaluate early risk factors for cardiopulmonary imaging abnormalities in asymptomatic middle-aged and elderly population using single-inspiratory phase low-dose computed tomography combined with artificial intelligence-based whole-lung quantitative analysis.
A retrospective collection was conducted on 1035 asymptomatic individuals aged ≥ 40 years who underwent routine single-inspiratory-phase low-dose computed tomography screening at Zhuzhou 331 Hospital in 2025.
how accurately the model predicted heart and lung problems in people without symptoms
Univariate analysis showed that smoking history, abnormal metabolic status, body mass index (BMI), age, and gender were significantly associated with cardiopulmonary imaging-defined high-risk status ( P < 0.05), while work style showed a marginal association in univariate analysis ( P = 0.043) but did not retain statistical significance in the multivariate model ( P = 0.851).
The Hosmer-Lemeshow goodness-of-fit test confirmed satisfactory calibration (training set: χ 2 = 10.40, P = 0.238; validation set: χ 2 = 6.50, P = 0.591).
Calibration curves and decision curve analysis demonstrated good agreement and positive clinical net benefit.
The low-dose computed tomography-based nomogram model combined with artificial intelligence quantitative imaging analysis may assist in identifying individuals with cardiopulmonary imaging abnormalities in asymptomatic screening populations, potentially guiding further diagnostic evaluation.
Prospective studies are warranted to establish its role in improving clinical outcomes.