Background/Objectives: The Metabolic Score for Insulin Resistance (METS-IR), a non-insulin-based index of insulin resistance (IR), and subclinical myocardial injury (SCMI), identified by electrocardiogram (ECG), are each associated with cardiovascular disease (CVD). However, their joint impact on mortality remains unclear. We examined the association of the METS-IR with SCMI and evaluated the individual and combined associations of SCMI and IR with cardiovascular mortality. Methods: We analyzed adults without baseline CVD from the Third National Health and Nutrition Examination Survey (1988–1994) with mortality follow-up through 31 December 2019. The METS-IR was calculated from fasting glucose, triglycerides, high-density lipoprotein cholesterol, and body mass index and categorized as low (<75th percentile) or high (≥75th percentile). SCMI was defined as a cardiac infarction injury score ≥ 10 on ECG. Multivariable logistic regression assessed associations between the METS-IR and SCMI, and Cox regression estimated cardiovascular mortality risk across SCMI-IR combinations. Results: Among 6079 participants, 14.1% had SCMI. Higher METS-IR values were associated with greater SCMI odds (OR (95% CI): 1.58 (1.31–1.90)). Over a median of 18.8 years, 563 (9.1%) cardiovascular deaths occurred. Both SCMI and high IR were individually associated with increased cardiovascular mortality ((HR (95% CI): 1.41 (1.19–1.69) and 1.32 (1.09–1.59), respectively). Participants with both SCMI and high IR had the highest risk (HR 1.92; 95% CI 1.49–2.50) compared with those with neither condition. Conclusions: In adults without prior CVD, the METS-IR was positively associated with SCMI. The coexistence of SCMI and high IR identified a subgroup at nearly twofold higher risk of cardiovascular mortality, supporting the combined use of ECG-based injury markers and metabolic indices for cardiovascular risk stratification.

Background/Objectives: The Metabolic Score for Insulin Resistance (METS-IR), a non-insulin-based index of insulin resistance (IR), and subclinical myocardial injury (SCMI), identified by electrocardiogram (ECG), are each associated with cardiovascular disease (CVD). However, their joint impact on mortality remains unclear. We examined the association of METS-IR with SCMI and evaluated the individual and combined associations of SCMI and IR with cardiovascular mortality. Methods: We analyzed adults without baseline CVD from the Third National Health and Nutrition Examination Survey. METS-IR was calculated from fasting glucose, triglycerides, high-density lipoprotein cholesterol, and body mass index and categorized as low (<75th percentile) or high (≥75th percentile). SCMI was defined as a cardiac infarction injury score ≥10 on ECG. Multivariable logistic regression assessed associations between METS-IR and SCMI, and Cox regression estimated cardiovascular mortality risk across SCMI-IR combinations. Results: Among 6,079 participants, 14.1% had SCMI. Higher METS-IR was associated with greater SCMI odds (OR(95%CI): 1.58(1.31-1.90)). Over a median of 18.8 years, 563 (9.1%) cardiovascular deaths occurred. Both SCMI and high IR were individually associated with increased cardiovascular mortality ((HR(95% CI): 1.41(1.19–1.69) and 1.32(1.09–1.59), respectively). Participants with both SCMI and high IR had the highest risk (HR 1.92; 95% CI 1.49–2.50) compared with those with neither condition. Conclusions: In adults without prior CVD, METS-IR was positively associated with SCMI. The coexistence of SCMI and high IR identified a subgroup at nearly twofold higher risk of cardiovascular mortality, supporting combined use of ECG-based injury markers and metabolic indices for cardiovascular risk stratification.

Background: Elevated resting heart rate is associated with increased mortality, but the underlying mechanisms remain incompletely understood. Subclinical myocardial injury (SCMI), defined by a Cardiac Infarction/Injury Score (CIIS) ≥10, represents silent cardiac damage that predicts poor cardiovascular (CV) outcomes and may partially explain this association. Methods: We analyzed 7,152 participants from NHANES III who underwent ECG recording and were free of cardiovascular disease. Heart rate was categorized as bradycardia (≤50 bpm), normal (>50–<100 bpm), or tachycardia (≥100 bpm). Mortality was assessed through National Death Index linkage. Logistic and Cox regression models evaluated associations with SCMI and mortality, respectively, and attenuation was assessed by change in hazard ratios after adjusting for SCMI. Results: SCMI was present in 1,744 (24.3%) participants. Tachycardia was associated with increased odds of SCMI (adjusted OR 2.34, 95% CI 1.42–3.88). Over 13.9 years median follow-up, 2,311 (32.3%) died from all causes and 933 (13.1%) from CV causes. Tachycardia was associated with increased all-cause mortality (HR 3.58, 95% CI 2.63–4.88) and CV mortality (HR 2.05, 95% CI 1.06–3.79). Adjustment for SCMI attenuated the tachycardia–CV mortality association by 8.6% and all-cause mortality by 5%. Bradycardia was not associated with SCMI or mortality. Conclusion: These findings suggest that SCMI partially mediates the heart rate–mortality relationship and that ECG-based assessment of SCMI may enhance risk stratification in individuals with elevated resting heart rate.

Objective: Although an elevated resting heart rate is linked to higher mortality, the pathways underlying this relationship are not fully defined. One candidate mechanism is subclinical myocardial injury (SCMI), an asymptomatic form of cardiac damage indexed by a Cardiac Infarction/Injury Score (CIIS) of at least 10, which has prognostic value for adverse cardiovascular (CV) outcomes. Methods: We analyzed 7152 participants from NHANES III who underwent electrocardiogram (ECG) recording and were free of CV disease. Heart rate was categorized as bradycardia (≤50 bpm), normal (>50–<100 bpm), or tachycardia (≥100 bpm). Mortality was assessed through National Death Index linkage. Logistic and Cox regression models evaluated associations with SCMI and mortality, respectively, and attenuation was assessed by change in hazard ratios after adjusting for SCMI. Results: SCMI was present in 1744 (24.3%) participants. Tachycardia was associated with increased odds of SCMI (adjusted OR 2.34, 95% CI 1.42–3.88). Over 13.9 years median follow-up, 2311 (32.3%) died from all causes and 933 (13.1%) from CV causes. Tachycardia was associated with increased all-cause mortality (HR 3.58, 95% CI 2.63–4.88) and CV mortality (HR 2.05, 95% CI 1.06–3.79). Adjustment for SCMI attenuated the tachycardia–CV mortality association by 8.6% and all-cause mortality by 5%. Bradycardia was not associated with SCMI or mortality. Conclusions: These findings suggest that SCMI modestly attenuates the heart rate–mortality association, suggesting that silent myocardial damage may represent one potential intermediary pathway.

Objective: To examine whether the association between smoking status and cardiovascular (CV) mortality differs by arterial stiffness, assessed by pulse pressure index (PPI), among U.S. adults without baseline cardiovascular disease (CVD). Methods: Using data from the National Health and Nutrition Examination Survey (NHANES) 2005–2016, we analyzed 16,605 adults aged 40–79 years without baseline CVD, with mortality follow-up through December 31, 2019. PPI was calculated as (systolic blood pressure [SBP] − diastolic blood pressure [DBP])/SBP and split at the cohort median (0.415) as low versus high. Smoking status was classified as never, former, or current, yielding six joint PPI–smoking groups. Cox models estimated hazard ratios (HRs) and 95% confidence intervals (CIs) for CV mortality, adjusting for demographics and cardiometabolic risk factors. Results: Over a median follow-up of 8.4 years, 518 CV deaths (3.1%) occurred. Among individuals with low PPI, former smokers had CV mortality comparable to never smokers (HR 0.86, 95% CI 0.56–1.33), whereas current smokers remained at elevated risk (HR 2.51, 95% CI 1.65–3.81). This pattern was not observed in the high PPI stratum, where both former and current smokers had significantly higher CV mortality than never smokers. Conclusion: Former smokers with low PPI had CV mortality similar to never smokers, whereas former smokers with high PPI remained at elevated risk. These findings suggest that the CV benefit of smoking cessation may be greatest when arterial stiffness is minimal, supporting early cessation before substantial vascular aging occurs.

Background: Electrocardiographic markers of atrial cardiomyopathy (AtCM) are associated with adverse cardiovascular outcomes. Whether AtCM further refines cardiovascular disease (CVD) mortality risk across increasing cardiometabolic risk factor (CMRF) burden is unclear. Methods: We analyzed 7,083 adults free of baseline CVD. AtCM was defined by the presence of ≥1 ECG marker: prolonged P-wave duration ≥120 ms in lead II, abnormal P-wave axis outside 0-75, or deep terminal negativity of the P wave in V1 <-100 μV. CMRF burden was defined as the presence of 0, 1, or ≥2 of hypertension, diabetes, and obesity. CVD mortality was ascertained through December 31, 2006. Results: Among 7,083 participants (mean age 58 years and 48% men), CVD mortality rates increased progressively across the six combined exposure groups. In a multivariable adjusted Cox proportional hazard analysis, AtCM identified higher-risk subgroups within each CMRF burden category, with risk increasing progressively across combined exposure groups and highest among participants with ≥2 risk factors and AtCM (HR 2.25, 95% CI 1.75-2.87). In secondary analyses, a similar pattern was observed for individual CMRFs, with the combination of AtCM and hypertension, diabetes, or obesity conferring the highest risk compared with participants with neither condition (HR (95% CI): 1.58 (1.31-1.89); 2.08 (1.62-2.68); and 1.47 (1.19-1.82), respectively). Conclusions: ECG-defined AtCM refined CVD mortality risk across increasing CMRF burden. Individuals with both AtCM and multiple CMRFs had the highest risk. These findings support the potential role of ECG-based AtCM assessment as a scalable approach to improve cardiovascular risk stratification among individuals with CMRFs.