Accurate prediction of mortality is central to modern clinical decision-making. Prognostic insights guide targeted delivery of screening and therapeutic interventions, support timely advance care planning, optimize resource allocation, and shape care quality metrics that reflect practical benefit rather than theoretical need. [[1], [2], [3], [4]] In recent years, interest has grown in leveraging routine diagnostic tools, such as electrocardiography (ECG), to identify low-cost, noninvasive markers of morbidity and mortality. For example, Raghunath et al. employed machine learning to predict 1-year all-cause mortality from 12‑lead ECG data. [5]

The frontal QRS axis is a critical and easily determined component of ECGs. Deviation from the normal axis can occur in a variety of physiologic and pathologic conditions, including aging, conduction abnormalities, ventricular hypertrophy, structural heart disease, myocardial infarction, and congenital heart defects. [[6], [7], [8], [9], [10], [11], [12], [13]] Deviation from the normal QRS axis has previously been associated with adverse outcomes, such as increased all-cause mortality and major cardiovascular events. [[14], [15], [16], [17], [18], [19]] However, these findings are often limited to narrowly defined cohorts (e.g. hospitalized Japanese patients; patients with systemic sclerosis-related pulmonary hypertension, acute coronary syndrome, or heart failure undergoing cardiac resynchronization therapy). Other studies have altogether questioned the prognostic utility of axis deviation. [20] Thus, there remains uncertainty about whether axis deviation remains a risk marker for mortality in general and unselected populations.

In this retrospective cohort study, we analyzed over 1200 randomly selected adult ECGs to evaluate the extent to which left axis deviation (LAD) and right axis deviation (RAD) were associated with 10-year all-cause mortality. Our aim was to determine whether this simple, widely available ECG parameter could serve as a practical tool for long-term mortality risk stratification in the general adult population.