Impact of simple equation for estimating appendicular skeletal muscle mass in patients with stable coronary artery disease undergoing percutaneous coronary intervention

Background Sarcopenia, which is evaluated based on appendicular skeletal muscle mass (ASM) using dual-energy X-ray absorptiometry and bioelectrical impedance analysis, is a prognostic predictor for adverse outcomes in patients with coronary artery disease (CAD). However, a simple equation for estimating ASM is yet to be validated in clinical practice. Methods We enrolled 2211 patients with CAD who underwent percutaneous coronary intervention at our hospital between 2010 and 2017. The mean age was 68 years and 81.5 % were men. Patients were divided into 2 groups based on each ASM index (ASMI): low; male < 7.3 and female < 5.0 and high; male ≥ 7.3 and female ≥ 5.0. ASM was calculated using the following equation: 0.193 × bodyweight + 0.107 × height − 4.157 × gender − 0.037 × age − 2.631. Primary endpoints were major adverse cardiac events (MACE, which includes cardiovascular death, non-fatal myocardial infarction, non-fatal stroke, and hospitalization for heart failure), and all-cause mortality. Results During the median follow-up period of 4.8 years, cumulative incidence of events were significantly higher in the low ASMI group. Cox proportional hazards model revealed that the low ASMI group had a significantly higher risk of primary endpoints than the high ASMI group (all-cause mortality; hazard ratio (HR): 2.13, 95 % confidence interval [CI]: 1.40–3.22, p < 0.001 and 4-point MACE; HR: 1.72, 95 % CI: 1.12–2.62, p = 0.01). Similar trends were observed after stratification by age of 65 years. Conclusion Low ASMI, evaluated using the aforementioned equation, is an independent predictor of MACE and all-cause mortality in patients with CAD.


Introduction
Globally, coronary artery disease (CAD) is a leading cause of mortality and cardiovascular deaths (CVD) are increasing due to an aging population [1][2][3]. Aging is associated with changes in muscle quantity and quality. The European Working Group on Sarcopenia in Older People and the Asian Working Group for Sarcopenia (AWGS) recommends diagnosis of sarcopenia based on the presence of low muscle strength, low physical performance, and low appendicular skeletal muscle mass (ASM) [4,5]. Sarcopenia has negative consequences, Abbreviations: ASM, appendicular skeletal muscle mass; ASMI, appendicular skeletal muscle mass index; AWGS, Asian Working Group for Sarcopenia; BIA, bioelectrical impedance analysis; CAD, coronary artery disease; CKD, chronic kidney disease; CI, confidence interval; CVD, cardiovascular deaths; DXA, dual-energy X-ray absorptiometry; HR, hazard ratio; LVEF, left ventricular ejection fraction; MACE, major adverse cardiac events; PCI, percutaneous coronary intervention. ☆ All authors take responsibility for all aspects of the reliability and freedom from bias of the data presented and their discussed interpretation.
including motor and physical disabilities, reduced quality of life, and mortality [6,7]. In addition, it is a prognostic factor in patients with heart failure and cardiovascular disease [8][9][10][11] and is a factor that exacerbates the metabolic syndrome [12]. Skeletal muscle mass, a diagnostic parameter of sarcopenia, accounts for almost half of body weight and is vital in various metabolic pathways (i.e., insulin resistance, arterial stiffness, and oxidative stress) [13][14][15]. In Asia, dual-energy Xray absorptiometry (DXA) and bioelectrical impedance analysis (BIA) are frequently used to measure skeletal muscle mass. The AWGS has established cutoff values for DXA and BIA and recommended the use of either modality to measure muscle mass to diagnose sarcopenia [4]. Recently, equations for estimating ASM using height, weight, sex, and age have been proposed for the Asian population. The estimation equation was developed based on skeletal muscle mass measured via DXA in Chinese adults aged 18-69 years [16,17]. However, whether ASM calculated from the estimation equation is a prognostic factor in patients with CAD has not yet been assessed. This study investigated whether the ASM equation can predict the prognosis of patients with CAD undergoing percutaneous coronary intervention (PCI).

Methods
In this single-center observational retrospective cohort study, 2,211 consecutive patients with CAD who underwent PCI (first-time) from 2010 to 2017 were enrolled. The data of patients with measurements of the appendicular skeletal muscle mass (ASM) and ASM index (ASMI) on day of admission for PCI were analyzed. The ASM was estimated using an equation previously validated for the Asian population [4,17].
(Weight in kg; height in m; age in years; gender: 1, for men and 2, for women). ASMI = ASM / height 2 (height in m).
Low ASMI was defined as the lowest 20th percentile of the study population [16]. The cut-off values were < 7.3 kg/m 2 and < 5.0 kg/m 2 in men and women, respectively. Patients were divided into 2 groups based on the ASMI: low ASMI; male < 7.3 and female < 5.0 and high ASMI; male ≥ 7.3 and female ≥ 5.0 ( Fig. 1). Demographic data and information on coronary risk factors, medications, revascularization procedure-related factors, and comorbidities were collected to create a database.
Blood samples were collected early morning on the day of PCI after overnight fasting. Blood pressure (BP) was measured on admission. Patients with BP of > 140/90 mmHg and/or those on antihypertensive medications were considered hypertensive (HT). Dyslipidemia (DL) was defined based on the values of low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C), and triglycerides (TG), (≥140, ≤40, and ≥ 150 mg/dL, respectively) or undergoing treatment with statins and/or lipid-lowering agents [18]. Diabetes mellitus (DM) was defined as either hemoglobin A1c (HbA1c) level of ≥ 6.5 % or medication with insulin or oral hypoglycemic drugs. Chronic kidney disease (CKD) was defined as an estimated glomerular filtration rate of < 60 mL/min/1.73 m 2 , calculated using the Modification of Diet in Renal Disease equation modified with a Japanese coefficient using the follow-up serum creatinine level [19]. A "current smoker" was defined as a person who was a smoker at the time of PCI or had quit smoking ≤ 1 year before PCI [20].
The primary endpoints of this study were major adverse cardiac events (MACE) and all-cause mortality. MACE was defined as a composite of CVD, non-fatal myocardial infarction (MI), non-fatal stroke, and hospitalization for heart failure. CVD was defined as death caused by MI or heart failure, or sudden death. Survival data and information about MACE was obtained by contacting the patients and accessed from their medical records. Mortality data were collected from the patients' families, and details of events associated with the cause of death, from hospitals where the patient had been admitted. All data were collected by blinded investigators. Time to event was measured from the date of the first PCI.
Categorical data were presented as numbers and percentages and compared using the chi-square test. Continuous variables were expressed as mean ± standard deviation or as median and interquartile range and compared using one-way analysis of variance (Kruskal-Wallis test), which was applied to the 4 groups. Unadjusted cumulative event rates were estimated using Kaplan-Meier curves and compared between the 2 groups. Additionally, patients were stratified by age using 65 years as the cutoff level in the Kaplan-Meier analysis. Associations between ASMI and the primary endpoint were determined using multivariate Cox proportional hazard regression analysis. Model 1 was adjusted for the variables in HT, DL, DM, and CKD; model 2 was adjusted for the variables in model 1 plus left ventricular ejection fraction (LVEF), and multivessel disease. Furthermore, patients were stratified by age using 65 years as the cutoff level in the Cox proportional hazard regression analysis. Hazard ratios (HRs) and 95 % confidence intervals (CIs) were calculated; p-values < 0.05 were considered statistically significant. All statistical analyses were performed using JMP version 14.0 (SAS Fig. 1. Study flow chart. A total of 2211 consecutive patients with stable CAD who underwent PCI (first) from 2010 to 2017 at the Juntendo University Hospital. All patients were divided into 2 groups based on the ASMI. CAD, coronary artery disease; PCI, percutaneous coronary intervention; ASMI, appendicular skeletal muscle mass index.

Results
All patients who underwent the first PCI from 2010 to 2017 were enrolled and classified into 2 groups: low ASMI included 523 patients (23.7 %) and ASMI, 1688 patients (76.3 %). Table 1 presents the clinical characteristics of the patients. The mean ASMI values were 7.0 (6.8-7.2) and 4.6 (4.4-4.9) in males and females, respectively, in the low ASMI group and 8.0 (7.7-8.4) and 5.7 (5.4-6.2) in males and females, respectively, in the high ASMI group. The mean age of the patients was 67.5 ± 11.0 years. No significant differences were noted in gender, hypertension, diabetes, and acute coronary syndrome between the 2 groups. Low ASMI groups had a higher prevalence of CKD, multivessel disease, and higher value of brain natriuretic peptide (p < 0.01 for all). The high ASMI group exhibited a higher prevalence of dyslipidemia, family history of CAD, and higher value of LVEF, albumin, and HbA1c (p < 0.01 for all).
The association between ASMI and clinical parameters were examined. ASMI had a significant correlation with age (r = 0.46, p < 0.001) and BMI (r = 0.73, p < 0.001). Correlation between ASMI and albumin (r = 0.23, p < 0.001) was statistically significant, although relatively weak. The median follow-up period was 4.8 (interquartile range, 2.9-7.1) years. The median follow-up period for the low ASMI group was 4 (interquartile range, 2.1-6.2) years and for the high ASMI group was 5 (interquartile range, 3.1-7.3) years. In total, 266 (12.0 %) cases of MACE and 279 (12.6 %) cases of all-cause mortality were identified during the follow-up, including 77 (3.4 %), 49 (2.2 %), 60 (2.7 %), and 80 (3.6 %) cases of CVD, non-fatal MI, non-fatal stroke, and hospitalization for heart failure, respectively. In the low ASMI group, 88 (16.8 %) cases of MACE and 121 (23.1 %) cases of all-cause mortality were identified, and in the high ASMI group, 178 (10.5 %) cases of MACE and 158 (9.3 %) cases of all-cause mortality were observed. Fig. 2a and 2b illustrate the Kaplan-Meier curves for MACE and all-cause mortality. The cumulative incidences of MACE were significantly higher in the low ASMI group (26.0 % versus 19.6 %; log-rank p < 0.001). Furthermore, Kaplan-Meier curves for MACE revealed significant differences in the incidence of events between the 2 groups, even when stratified by the age of 65 years (<65 age group: log-rank p = 0.003; ≥65 age group: logrank p = 0.003) ( Fig. 3a and 3b). In addition, the cumulative incidences of all-cause mortality were significant higher in the low ASMI group (39.9 % versus 19.9 %; log-rank p < 0.001). Despite stratification by the age of 65 years, Kaplan-Meier curves for all-cause mortality revealed significant differences in the incidence of events between the 2 groups (<65 age group: log-rank p < 0.001; ≥65 age group: log-rank p < 0.001) ( Fig. 3c and 3d). Supplemental Table 1 shows the baseline clinical characteristics of patients stratified into two age groups (65 years was set as the cut-off age). There were no significant differences in LVEF, multivessel disease, statin use, and albumin between low ASMI group and high ASMI group in < 65 years age group. In ≥ 65 years age group, high ASMI group had significantly higher rates of HT and higher rates of angiotensin-converting enzyme inhibitors and angiotensin receptor blockers medications than low ASMI group. The Kaplan-Meier curve was stratified by age tertiles: Tertile 1: <64 years age group, Tertile 2: 64-73 years age group, and Tertile 3: ≥74 years age group. MACE and all-cause mortality were significantly higher in the low ASMI group for Tertile 1 and Tertile 3. In Tertile 2, all-cause mortality was higher in the low ASMI group, whereas, there was no significant difference in MACE. Table 2 summarizes the results of the Cox proportional hazard regression analysis for MACE and all-cause mortality. The low ASMI group was significantly associated with MACE than the high ASMI group (HR 1.65; 95 % CI 1.20-2.24; p = 0.01), even after adjustment for other risk factors (HT, DL, DM, CKD, LVEF, and multivessel disease). Furthermore, the risk of all-cause mortality was significantly higher in patients in the low ASMI group after adjustment for vital covariates (HR 2.79; 95 % CI 2.09-3.70; p < 0.001). Even after adjusting the significant differences in patient backgrounds between the two groups, the low ASMI group was significantly associated with MACE (HR 1.76; 95 % CI 1.15-2.68; p = 0.009) and all-cause death (HR 2.20; 95 % CI 1.45-3.33; p = 0.002). In Cox regression analysis, there was no significant interaction between ASMI and gender (MACE: p for interaction = 0.51, allcause death: p for interaction = 0.31).

Discussion
We investigated the relationship between long-term prognosis (median 4.8 years) and estimated ASMI in patients undergoing PCI for CAD. The major findings of the present study are as follows: (1) the rates of MACE in the low ASMI group were significantly higher than those in high ASMI group. Even after adjusting for vital covariates, low ASMI was associated with a higher incidence of MACE; (2) all-cause mortality was higher in the low ASMI group, and low ASMI was an independent predictor of all-cause mortality; (3) in the < 65 years group, low ASMI was a significant predictor of MACE and all-cause mortality. In addition, the HR for MACE in ≥ 65 years group was lower than that in the < 65 years group. Low skeletal muscle mass has been reported as a potential prognostic predictor for CAD because of its association with decreased cardiopulmonary function, reduced exercise capacity, and arteriosclerosis [21][22][23][24]. These studies have used CT and DXA to measure skeletal muscle mass. Although these methods provide a more accurate measurement, additional radiation exposure to patients who have undergone coronary angiography or PCI may be a critical issue. Therefore, measurement of skeletal muscle mass is not routinely performed in realworld clinical practice. In this study, we examined the prognosis of CAD patients using a simple equation for estimating ASMI. This estimated ASMI is a potential prognostic predictor of MACE and all-cause mortality in patients with CAD; it can help identify high-risk populations and may contribute to improved clinical outcomes.
Exercise therapy for sarcopenia has been reported to improve skeletal muscle mass and strength and gait speed [25] Several guidelines recommend cardiovascular rehabilitation especially for patients with CAD undergoing PCI [26,27]. Increased daily activity in patients with CAD, including acute coronary syndrome, was closely associated with lower all-cause and cardiovascular mortalities, and has been reported to improve the quality of life and reduce mortality [28,29]. However, the effect of cardiac rehabilitation on improving prognosis in patients with stable angina is unclear [30,31]. Our study included approximately 70 % of patients with stable angina. This was considered necessary because these patients, particularly those with low ASMI, would benefit more from cardiac rehabilitation. Although in this study, we were only able to assess low ASMI, as one of the indicators of sarcopenia, our results indicate that low ASMI may be a potential therapeutic target to reduce adverse clinical outcomes in patients with CAD. In addition, cardiac rehabilitation has been reported to be safe when performed early after PCI [32,33]. Thus, early exercise initiation as a non-pharmacologic Kaplan-Meier curves demonstrate significant differences in allcause mortality between the groups (both log-rank test, p < 0.001). ASMI, appendicular skeletal muscle mass index; MACE, major adverse cardiac events. therapy may prevent further progression of sarcopenia and lead to better clinical outcomes in patients with CAD. In our study, accurately determining the changes in skeletal muscle mass over time was challenging due to the nature of the estimation equation. Hence, further studies are needed to determine the prognostic value of improved skeletal muscle mass.
Sarcopenia has been reported as a poor prognostic factor in elderly patients [6,34,35]. Our study indicates that low ASMI may be a poor prognostic factor even in patients < 65 years. However, HR for MACE in ≥ 65 years group was lower than that in the < 65 years group. These results suggest that not only low skeletal muscle mass but also other indicators of sarcopenia, such as low muscle strength and low physical activity level, may play a role in prognosis in ≥ 65 years patients. In our study, we did not measure 6-minute walk or grip strength, and these factors need to be evaluated and analyzed additionally in the future, in order to evaluate the improvement of the prognosis for ≥ 65 years patients with CAD. Exercise therapy for elderly patients with CAD was reported to improve exercise tolerance and coronary risk factors as much  Kaplan-Meier curves for MACE demonstrate significant differences in event rates between the groups, even when stratified by the age of 65 years (log-rank test, all p = 0.003). Kaplan-Meier curves for all-cause mortality demonstrate significant differences in event rates between the groups, even when stratified by the age of 65 years (log-rank test, all p < 0.001). ASMI, appendicular skeletal muscle mass index; MACE, major adverse cardiac events.  as that of non-elderly patients [36,37]. In addition to exercise therapy, there were also reports that suggested supplementation with essential amino acids and protein as nutritional therapy improves skeletal muscle mass [25]. In ≥ 65 years patients, past exercise habits (20 to 50 years old), usual number of steps, and physical activity level of 3 metabolic equivalents of task (METs) were associated with skeletal muscle mass and the development of sarcopenia. Exercise, nutrition, and lifestyle interventions may be effective in improving outcomes for ≥ 65 years patients with low ASMI. Patients under 65 years of age were more strongly affected by low ASMI than patients over 65 years of age were affected. Regarding the association between sarcopenia and lifestyle-related diseases, skeletal muscle mass is reported to be lower in patients with type 2 diabetes [38,39]. A report from the United States indicates that sarcopenia is related to glucose metabolism independent of obesity and this tendency is stronger in those aged < 60 years; moreover, reduced skeletal muscle mass may be a predictor of diabetes mellitus [40]. In addition to glucose metabolism, a relationship between sarcopenia and metabolic syndrome has been reported [41,42], possibly because skeletal muscles secrete myokines, which increase insulin sensitivity, affect muscle physiology, and regulate the metabolism [43][44][45]. Nutritional therapy is an important part of treatment in patients with diabetes. Japanese guidelines do not set energy-producing nutrient ratios (carbohydrate, protein, and fat) for prevention and management of diabetes. Total energy intake is determined based on each patient's weight and BMI for weight loss [46]. However, it was reported that low energy intake in patients with diabetes decreases skeletal muscle mass [47]. Excessive energy restriction may induce sarcopenia in patients with low ASMI. In our study, low ASMI in patients aged < 65 years was a poor prognostic factor in multivariate analysis adjusting for cardiovascular risk at the time of PCI. In addition to perioperative complications, correction of metabolic syndrome and follow-up of abnormal metabolism was considered important after PCI in patients with low ASMI. Therefore, introducing nutritional and exercise guidance to increase skeletal muscle mass may be effective even in younger patients.
This study has a few limitations. First, the ASM estimation equation used in this study was not specific to the Japanese population and there is no consensus in the interpretation of skeletal muscle assessment. Hence, further knowledge is needed, and this can easily be obtained without additional radiation burden. Second, sarcopenia is defined based on the presence of low muscle strength, low physical performance, and low ASM. However, low muscle strength and low physical performance could not be evaluated in this study. In the future, it is necessary to examine the significance of estimated skeletal muscle mass considering the diagnostic criteria for sarcopenia. Third, unknown confounders might have affected outcomes regardless of analytical adjustments because this was a single-center observational study of a small-sized patient cohort. Therefore, further multicenter studies with a larger population should be conducted to provide greater statistical power and confirm the reproducibility of the results.

Conclusion
Low ASMI evaluated by a simple equation is an independent predictor of MACE and all-cause mortality in patients with CAD. Exercise therapy, nutritional therapy, and lifestyle modifications are considered important for patients with low ASMI.

Declarations
Funding: Not applicable. Ethics approval: The ethics committee of Juntendo Clinical Research and Trial Center approved this study (IRB number 17-0206).
Consent to participate and for publication: Written informed consent to participate was obtained from all patients.
Availability of data and material: The datasets during and/or analyzed during the current study are available from the corresponding author with reasonable request.
Code availability: The relevant SAS codes for the statistical analysis are available from the corresponding author with reasonable request.
Financial support: This research received no external funding.

Declaration of Competing Interest
The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.