Abstract Background Non-invasive left ventricular (LV) pressure-strain loop analysis is a novel technique for the evaluation of global myocardial work (GMW) that provides additional insights on LV contractility and energetics beyond traditional metrics, such as ejection fraction (EF) and global longitudinal strain (GLS). Despite its established value in numerous cardiac diseases, there remains limited data on its predictive power in a low-risk population. Purpose Our objective was to determine the long-term prognostic value of GMW in a population-based screening sample comprising low-risk adult individuals. Methods We retrospectively identified 1562 volunteers from a population-based screening program (mean age 54±15 years, 59% female), with a median follow-up time of 11 years. All subjects underwent 2D echocardiography to measure LV EF, GLS, peak atrial longitudinal strain (PALS), GMW index (GMWI), global wasted work (GWW), and GMW efficiency (GMWE). The primary endpoint was all-cause mortality. Results 191 subjects (12,2%) met the primary endpoint. Subjects who experienced adverse outcomes exhibited significantly lower LV EF (dead vs. alive; 49.7±8.3 vs. 52.7 ±6.4 %, p<0.001), GLS (-18.7±4.1 vs. -20.4±3.6 %, p<0.001), PALS (33.6±15.7 vs. 44.2±15.2 %, p<0.001), and GMWI (2181.7±591.3 vs. 2286.8±482.5 mmHg%, p=0.008). Furthermore, subjects with adverse outcomes had significantly higher GWW (132.6±249.4 vs 95.1±113.4 mmHg%, p<0.001) and, consequently, lower GMWE (0.95±0.05 vs. 0.96±0.03, p<0.001). Univariate Cox regression analysis revealed GMWI to be a significant predictor of mortality (hazard ratio for 100 units 0.957 [95% CI: 0.929-0.986], p=0.004), alongside GMWE (hazard ratio for 1 percent 0.940 [95% CI: 0.912-0.968], p<0.001), and GWW (hazard ratio for 100 units 1.124 [95% CI: 1.063-1.188], p<0.001). By multivariable Cox regression encompassing age, sex, GMWI, LVEF, GLS, PALS, and systolic blood pressure, GMWI remained an independent predictor of all-cause mortality (hazard ratio 0.932 [95% CI: 0.874-0.995], p=0.035), while GLS was not an independent predictor. Moreover, integrating the Atherosclerosis Risk in Communities (ARIC)-HF risk factors (age, sex, race, coronary artery disease, antihypertensive medication, blood pressure, diabetes mellitus, body mass index, heart rate, and smoking status), we constructed a multivariate model with GMWI. GMWI was still an independent predictor of mortality (hazard ratio for 100 units 0.941 [95% CI: 0.903-0.980], p=0.004). Using the GMWI cut-off value of 1576 mm Hg% (based on a large-scale healthy population study), the population was divided into 2 groups. Using Kaplan-Meier curves (Figure), the outcomes of the groups differed significantly (log-rank p<0.001). Conclusions GMW provides added value in clinical outcome prediction, even in low-risk individuals. Myocardial work analysis is a promising approach for a comprehensive evaluation of cardiac function and for cardiovascular risk stratification.