A systematic review and meta-analysis of the association between sarcopenia and myocardial infarction

A sarcopenia prediction model based on the calf maximum muscle circumference measured by ultrasound

BACKGROUND

The correlation between calf circumference（CC）and sarcopenia has been demonstrated, but the correlation between calf maximum muscle circumference (CMMC) measured by ultrasound and sarcopenia has not been reported. We aims to construct a predictive model for sarcopenia based on CMMC in hospitalized older patients.

METHODS

This was a retrospective controlled study of patients > 60 years of age hospitalized in the geriatric department of Hunan Provincial People's Hospital. The patients were thoroughly evaluated by questionnaires, laboratory, and ultrasound examinations, including measuring muscle thickness and calf muscle maximum circumference using ultrasound. Patients were categorized into sarcopenia and non-sarcopenia groups according to the consensus for diagnosis of sarcopenia recommended by the Asian Working Group on Sarcopenia 2019 (AWGS2). Independent predictors of sarcopenia were identified by univariate and multivariate logistic regression analyses, and a predictive model was developed and simplified. The prediction performance of the models was assessed using sensitivity, specificity, and area under the curve (AUC) and compared with independent predictors.

RESULTS

We found that patient age, albumin level (ALB), brachioradialis muscle thickness (BRMT), gastrocnemius lateral head muscle thickness (Glh MT), and calf maximum muscle circumference (CMMC) were independent predictors of sarcopenia in hospitalized older patients. The prediction model was established and simplified to Logistic P = -4.5 + 1.4 × age + 1.3 × ALB + 1.6 × BR MT + 3.7 × CMMC + 1.8 × Glh MT, and the best cut-off value of the model was 0.485. The sensitivity, specificity, and AUC of the model were 0.884 (0.807-0.962), 0.837 (0.762-0.911), and 0.927 (0.890-0.963), respectively. The kappa coefficient between this model and the diagnostic criteria recommended by AWGS2 was 0.709.

CONCLUSION

We constructed a sarcopenia prediction model with five variables: age, ALB level, BR MT, Glh MT, and CMMC. The model could quickly predict sarcopenia in older hospitalized patients.

Sarcopenia and Cardiogeriatrics: The Links Between Skeletal Muscle Decline and Cardiovascular Aging

Sarcopenia, an age-related decline in skeletal muscle mass, strength, and function, is increasingly recognized as a significant condition in the aging population, particularly among those with cardiovascular diseases (CVD). This review provides a comprehensive synthesis of the interplay between sarcopenia and cardiogeriatrics, emphasizing shared mechanisms such as chronic low-grade inflammation (inflammaging), hormonal dysregulation, oxidative stress, and physical inactivity. Despite advancements in diagnostic frameworks, such as the EWGSOP2 and AWGS definitions, variability in criteria and assessment methods continues to challenge standardization. Key diagnostic tools include dual-energy X-ray absorptiometry (DXA) and bioimpedance analysis (BIA) for muscle mass, alongside functional measures such as grip strength and gait speed. The review highlights the bidirectional relationship between sarcopenia and cardiovascular conditions such as heart failure, aortic stenosis, and atherosclerotic cardiovascular disease, which exacerbate each other through complex pathophysiological mechanisms. Emerging therapeutic strategies targeting the mTOR pathway, NAD+ metabolism, and senescence-related processes offer promise in mitigating sarcopenia's progression. Additionally, integrated interventions combining resistance training, nutritional optimization, and novel anti-aging therapies hold significant potential for improving outcomes. This paper underscores critical gaps in the evidence, including the need for longitudinal studies to establish causality and the validation of advanced therapeutic approaches in clinical settings. Future research should leverage multi-omics technologies and machine learning to identify biomarkers and personalize interventions. Addressing these challenges is essential to reducing sarcopenia's burden and enhancing the quality of life for elderly individuals with comorbid cardiovascular conditions. This synthesis aims to guide future research and promote effective, individualized management strategies.

Disparities in the Prevalence of Hospitalizations and In-Hospital Mortality Due to Acute Myocardial Infarction Among Patients with Non-Alcoholic Fatty Liver Disease: A Nationwide Retrospective Study

Background: Non-alcoholic liver disease (NAFLD) may be associated with cardiovascular diseases; however, only a few studies have analyzed this relationship. We aimed to assess the epidemiologic data and the association between NAFLD and acute myocardial infarction (AMI) in the United States. Methods: The National Inpatient Sample (NIS) database 2016-2019 was queried using ICD10-CM diagnostic codes to identify hospitalizations of AMI + NAFLD. Essential demographic variables were analyzed to determine the disparities in the prevalence of AMI hospitalizations and deaths among NAFLD patients. Univariate and multivariate logistic regression models determined the association between NAFLD and AMI hospitalizations and death. Results: Among the total 5450 NAFLD patients hospitalized with AMI, 5.11% (279) died. Females were less likely to be admitted and die due to AMI than males. Younger patients (<50) were less likely to be hospitalized and die than those ≥50. Compared to the white population, black patients were less likely; however, Hispanics, Asians, and Pacific Islanders were more likely to be hospitalized. Race was not found to affect hospital mortality. On multivariate analysis, NAFLD was associated with higher odds of AMI hospitalization [OR 1.55, 95% CI 1.51-1.60, p < 0.01] and death [OR 1.96, 95% CI 1.74-2.21, p < 0.01]. Conclusions: Older white males with NAFLD had a higher prevalence of AMI hospitalizations and mortality.

Prognostic role of sarcopenia on major adverse cardiac events among patients who underwent successful percutaneous coronary intervention: a retrospective cohort study

AIMS

We investigated the prevalence of sarcopenia and its influence on 1-year major adverse cardiac events (MACEs) in patients after successful percutaneous coronary intervention (PCI).

METHODS AND RESULTS

This retrospective medical record review using purposive sampling was conducted at a tertiary care university hospital in Korea. Medical records of a total of 303 patients (≥40 years) who underwent successful PCI between January 2014 and December 2020 were analysed. We retrospectively assessed sarcopenia at initial admission. Sarcopenia was assessed by a sarcopenia index based on a ratio of serum creatinine to serum cystatin C. MACE rates were evaluated within l year after PCI. A Kaplan-Meier analysis with a log-rank test was performed to compare the time with 1-year MACE event-free survival between groups with and without sarcopenia. Cox proportional hazards regression was conducted to assess sarcopenia's influence on MACE. The prevalence of sarcopenia and 1-year MACE after PCI were 24.8 and 8.6%, respectively. We found that sarcopenia at admission (hazard ratio, 3.01; 95% confidence interval, 1.22-7.38, P = 0.017) was significantly associated with 1-year MACE among patients after PCI.

CONCLUSION

Expanding knowledge of sarcopenia among cardiovascular nurses may aid in early recognition of patients at risk of sarcopenia. Our finding implies that the sarcopenia index based on serum creatinine and cystatin C may be available as a prognostic factor for MACE in patients undergoing PCI. Future studies should be conducted to prospectively validate the sarcopenia index with a multi-centre, large sample.