Development and external validation of an explainable machine learning model for identifying depressive symptoms in middle-aged and older adults with low haemoglobin: a prediction-model study

Background

Early screening for depressive symptoms in middle-aged and older adults is important for timely risk identification. Low haemoglobin may identify a clinically accessible vulnerable subgroup in which chronic disease burden, fatigue, functional impairment, and reduced physiological reserve often coexist. However, it should be understood as a high-risk phenotype rather than a direct measure of nutritional deficiency or frailty. Evidence in this population remains limited.