High prevalence of sarcopenia in Asian female patients awaiting primary total knee arthroplasty: Application of updated diagnostic tools from the Asian working group for sarcopenia

Abstract

Introduction

Sarcopenia, a loss of muscle mass and strength with aging, is associated with various TKA-related complications. In 2020, the AWGS published an undated guideline (AWGS 2019) based on studies from East and Southeast Asia. The purpose of this study was to determine the prevalence of sarcopenia in Asian female patients awaiting primary total knee arthroplasty due to advanced knee osteoarthritis using the updated AWGS criteria.

Materials and Methods

The present study included 138 female patients who scheduled for primary TKA with severe osteoarthritis. The included patients were assessed with use of an AWGS 2019 diagnostic criteria based on muscle strength, physical performance, and appendicular skeletal muscle mass. Clinical parameters related to sarcopenia were collected and knee status assessed using the Knee Society scoring system. To better define the association with age, patients were stratified into following four groups: <60, 60–69, 70–79, ≥80. The prevalence of sarcopenia was identified, and the association between sarcopenia and clinical variables was analyzed.

Results

The prevalence of sarcopenia and severe sarcopenia in this cohort according to the updated AWGS criteria was 35.5% and 21.7%. Prevalence of sarcopenia and severe sarcopenia significantly increased with advancing age (p = .003, p = .040, respectively). Although not statistically significant, the proportion of severe sarcopenia among sarcopenia also increased with age. Multivariate logistic regression analysis revealed that lower BMI and lower 25-OH-vitamin D3 level were independent risk factors associated with sarcopenia in women awaiting TKA.

Conclusions

In conclusion, our study confirmed that sarcopenia is more prominent amongst female patients awaiting primary TKA than the general population. Therefore, orthopedic surgeons should consider sarcopenia prevention and intervention in this group. Further studies are needed to investigate the effect of TKA on sarcopenia, and the difference of TKA outcomes between groups with or without underlying sarcopenia.

Keywords

Total knee arthroplasty sarcopenia prevalence osteoarthritis female patients Asian

Introduction

Total knee arthroplasty (TKA) is one of the most widely used surgical methods in the orthopedic field, and the demand is steadily increasing due to population aging.^1–3 However, as the amount of surgery volume gradually increases, TKA related complications also increase, which is a major challenge for orthopedic surgeons. Several studies have reported that sarcopenia, a highly discussed phenomenon in the medical community, can independently predict postoperative complications.^4–13 Since sarcopenia is known to be an independent risk factor for falls, lower extremity fracture and periprosthetic joint infection, it should be emphasized more in patients undergoing TKA.^4,14–18

The diagnostic criteria of sarcopenia have been proposed by several groups. Among them, the diagnostic criteria proposed by the Asian Working Group for Sarcopenia (AWGS) in 2014 was based on Asian data that reflects differences in the anthropology, culture, and lifestyle of Asians compared to Western populations.¹⁹ This was because special consideration was required for Asians' relatively smaller body sizes, higher adiposity, and active lifestyle due to delayed industrialization. In 2020, the AWGS published an updated guideline (AWGS 2019) based on studies from East and Southeast Asia.²⁰ Updated AWGS criteria evaluate low muscle mass, low muscle strength, and low physical performance to diagnose sarcopenia.

Sarcopenia, a loss of muscle mass and strength with aging, is associated with various TKA-related complications.^4,14–18 Elderly women make up about 70–90% of TKA candidates,^21,22 and the number is gradually increasing due to population aging.^1–3 However, a few research has been conducted on the prevalence and risk factors of sarcopenia in these patients.

The purpose of this study was to determine the prevalence of sarcopenia in Asian population awaiting primary TKA due to advanced knee osteoarthritis using the updated AWGS criteria. The study also examined the relationship between sarcopenia and other clinical parameters. This study finds that sarcopenia is prevalent amongst TKA candidates; therefore, orthopedic surgeons should understand sarcopenia to be a risk factor and educate potential TKA candidates of its effect on TKA.

Materials and methods

Study sample

The study samples were retrospectively collected from consecutive patients scheduled for primary TKA due to osteoarthritis at a single secondary hospital in Korea from January 2017 and August 2018. We included independently walking female patients who were diagnosed with primary osteoarthritis. Osteoarthritis was diagnosed by physical and radiological examination, and Kellgren/Lawrence grades ≥3 were used as the inclusion criteria. The exclusion criteria were male, any diagnosis other than primary osteoarthritis, non-independent ambulation due to comorbid medical conditions, and patients with metal implants in appendicular body regions, which potentially could affect the accuracy of calculating appendicular skeletal muscle mass (ASM).²³ A total of 170 patients participated in the study. The final analysis included 138 participants after excluding 20 male patients, nine patients diagnosed with non-primary osteoarthritis and three patients with metal implants in appendicular body regions identified on DXA (dual‐energy X‐ray absorptiometry) images.

All investigations were approved by the Institutional Review Board of our institution and the procedures used in this study adhered to the tenets of the Declaration of Helsinki. Written consent was not required due to the retrospective nature of this study.

Diagnosis of sarcopenia

Muscle strength measurement

Muscle strength was evaluated by the handgrip strength test. The dominant handgrip strength was measured with a handgrip dynamometer (Jamar, Bolingbrook, IL, USA) by applying the Southampton protocol (sitting with 90° elbow flexion as the standard position).²⁴ The participants, with verbal encouragement, squeezed the dynamometer with the utmost effort possible. Participants were given three trials with 30 second resting intervals. The maximum handgrip strength was expressed in kilograms by selecting the highest measurement of the three trials. Low muscle strength was defined as a hand strength of less than 18 kg for women.²⁰

Physical performance measurement

Physical performance was evaluated by 4-m walking speed. The patient was asked to walk down a hallway through a 2-m acceleration zone, a central 4-m testing zone, and a 2-m deceleration zone. A stopwatch was used to record the gait speed. The gait speed was measured twice in order to find the average speed. Patients who took longer than 4 s to walk 4 m (<1.0 m/s) suggested low physical performance.²⁰ To reduce knee pain that may affect physical performance, all patients were given 200 mg of Celecoxib and an additional 500 mg of acetaminophen as needed.

Measurement of appendicular skeletal muscle mass

Appendicular skeletal muscle mass (ASM) was measured using a whole-body DXA scanner in accordance with the manufacturer’s protocol (Lunar Prodigy Advance, GE Healthcare, Madison, WI, USA). ASM was defined as the sum of the lean mass of both the upper and lower extremities and was assumed to be almost equal to the skeletal muscle mass. As height increases, the muscle mass of the limbs will increase. Therefore, we obtained the skeletal muscle index (SMI) by correcting the muscle mass with height (ASM (kg)/height (m²)). The cutoff values for the ASM index for low muscle mass were <5.4 kg/m² in women, respectively.²⁰

Definition of sarcopenia

The updated AWGS criteria defined sarcopenia as low muscle mass and low muscle strength or low physical performance, and severe sarcopenia as low muscle mass, low muscle strength, and low physical performance.

Assessment of clinical parameter

The following clinical parameters were collected based on the literature: age, body weight, height, body mass index (BMI), and the Charlson comorbidity index. The commercial kit, Architect 25-OH Vitamin D3 Reagent kit (Abbott Diagnostics, Lake Forest, IL, USA) was used to measure serum concentration of 25-OH vitamin D3. Knee status was assessed using the Knee Society (KS) scoring system (including knee score and function score), which was designed to provide a simple and objective scoring system to rate the knee and patient’s functional abilities in TKA. All assessments were performed the day before surgery.

The prevalence of sarcopenia in female patients with severe osteoarthritis awaiting primary TKA was determined. The prevalence of sarcopenia in this cohort was compared to that reported by the Korean Frailty and Aging Cohort Study for community-dwelling adults aged 70 years and older.²⁵ That study also used the updated AWGS diagnostic criteria to conduct an evaluation. The association of sarcopenia with the clinical parameters was investigated.

Statistical analyses

All variables are presented as the mean ± standard deviation or number (percentage). To better define the association with age, patients were stratified into following four groups: <60, 60–69, 70–79, ≥80. Statistical comparisons of the continuous variables were performed using Student’s t-test, the Mann-Whitney U test or Jonckheere-Terpstra trend test, whereas the categorical variables were analyzed using the χ2 test, Fisher’s exact test, or a linear by linear association, as appropriate. Multiple logistic regression analysis was performed to evaluate the independent risk factors of sarcopenia. p-values of less than .05 were considered statistically significant in all analyses. The statistical analyses were conducted using Microsoft Excel 2013 (Microsoft, Redmond, WA, USA) and SPSS software (version 20 SPSS, Chicago, IL, USA).

Results

After selection, a total of 138 female patients were included to the study. The mean age and BMI of all participants were 72.7 ± 6.5 years (range 56–87 years) and 26.7 ± 3.5 kg/m² (range, 17.2–39.0 kg/m²), respectively. All participants had at least K-L grade III knee OA, and 52.2% of all patients were K-L grade IV. The baseline characteristics of each age group and the parameters for diagnosing sarcopenia according to the updated AWGS criteria are summarized in Table 1. The age stratification was implemented to identify age-related characteristics. Height, body weight and BMI significantly decreased with increasing age, and the Charlson comorbidity index significantly increased with advancing age. There were no statistically significant differences in the 25-OH-vitamin D3 level, K-L grade, KS score among age groups. As sarcopenic parameters for each age group, diagnosis of low skeletal muscle mass and low muscle strength significantly increased with the age. However, there was no significant differences in the proportion of low physical performance (gait speed) among age groups.

Table 1.

Characteristics of patients from the total sample and according to age group.

Variable	Overall (n = 138)	<60 (n = 14)	60–69 (n = 42)	70–79 (n = 60)	≥80 (n = 22)	P-value^a
Age, y	72.7 ± 6.5	58.8 ± 1.6	67.9 ± 3.0	75.7 ± 1.8	83.7 ± 2.2	< .001
Height, m	1.5 ± 0.1	1.56 ± 0.1	1.54 ± 0.1	1.5 ± 0.1	1.48 ± 0.0	< .001
Weight, kg	61.9 ± 9.5	65.1 ± 5.2	65.3 ± 9.5	61.1 ± 9.2	55.4 ± 9.5	< .001
BMI, kg/m²	26.7 ± 3.5	27.2 ± 3.1	27.6 ± 3.2	26.5 ± 3.6	25.3 ± 3.8	.001
Charlson comorbidity index	0.4 ± 0.7	0.1 ± 0.4	0.4 ± 0.7	0.4 ± 0.6	1.0 ± 0.8	.001
25-OH-vitamin D3	22.5 ± 10.8	25.0 ± 11.0	20.6 ± 11.0	24.2 ± 10.2	20.0 ± 11.6	.770
K-L grade IV	72 (52.2)	10 (71.4)	18 (42.9)	28 (46.7)	16 (72.7)	.550
KS score
Knee	45.4 ± 17.1	41.3 ± 13.8	50.7 ± 21.0	43.7 ± 14.4	42.6 ± 16.2	.295
Function	39.4 ± 15.4	36.8 ± 11.2	44.6 ± 15.6	35.6 ± 15.6	41.7 ± 14.3	.494
Diagnostic assessment for sarcopenia
Skeletal muscle mass
ASM by DEXA, kg	13.6 ± 2.1	14.3 ± 1.6	14.3 ± 2.1	13.5 ± 2.1	12.1 ± 1.4	< .001
ASM/height²	5.6 ± 0.7	5.7 ± 0.4	5.8 ± 0.7	5.6 ± 0.7	5.4 ± 0.6	.019
ASM/height² (<5.4 in women), %	49 (35.5)	4 (28.6)	11 (26.2)	22 (36.7)	12 (54.5)	.040
Muscle strength
Grip strength, kg	16.8 ± 4.4	18.5 ± 3.2	17.8 ± 3.9	16.5 ± 4.5	14.7 ± 4.8	.003
Grip strength (<18 kg in women), %	79 (57.2)	5 (35.7)	20 (47.6)	36 (60.0)	18 (81.8)	.002
Physical performance
4-m usual gait speed, m/s	0.6 ± 0.2	0.6 ± 0.1	0.6 ± 0.2	0.6 ± 0.2	0.4 ± 0.2	.001
Gait speed (<1.0 m/s in women), %	124 (89.9)	14 (100.0)	36 (85.7)	54 (90.0)	20 (90.9)	.778

P-value in bold are statistically significant (p < 0.05).

Data are presented by mean ± standard deviation or number (%).

Abbreviations: BMI (Body mass, index); K-L (Kellgren Lawrence); KS (knee society); ASM (appendicular skeletal muscle mass); DEXA (dual-energy X-ray absorptiometry).

^aJockheere-Terpstra test for continouous variables and linear-by-linear association for categorical variables.

The prevalence of sarcopenia and severe sarcopenia in this cohort according to the updated AWGS criteria was 35.5% (49/138) and 21.7% (30/138) (Table 2). The Jonckheere–Terpstra test showed that prevalence of sarcopenia and severe sarcopenia significantly increased with advancing age (p = .003, p = .040, respectively). Although not statistically significant, the proportion of severe sarcopenia among sarcopenia also increased with age. (Figure 1)

Table 2.

Prevalence rates of sarcopenia and severe sarcopenia from the total sample and according to age group.

Variable	Overall (n = 138)	<60 (n = 14)	60–69 (n = 42)	70–79 (n = 60)	≥80 (n = 22)	p-value^a
Sarcopenia, %
ASM/height² + grip strength	33 (23.9)	0 (0.0)	8 (19.0)	15 (25.0)	11 (50.0)	.001
ASM/height² + gait speed	46 (33.3)	4 (28.6)	10 (23.8)	22 (36.7)	10 (45.5)	.096
ASM/height² + grip strength and/or gait speed	49 (35.5)	4 (28.6)	11 (26.2)	22 (36.7)	12 (54.5)	.040
Severe sarcopenia, %
ASM/height² + grip strength + gait speed	30 (21.7)	0 (0.0)	7 (16.7)	15 (25.0)	9 (40.9)	.003
Proportion of patients with severe sarcopenia among sarcopenia patients, %	30/49 (61.2)	0/4 (0.0)	7/11 (63.6)	15/22 (68.2)	9/12 (75.0)	.056

P-value in bold are statistically significant (p < 0.05).

Data are presented by number (%).

Abbreviation: ASM (appendicular skeletal muscle mass).

^alinear-by-linear association for categorical variables.

Figure 1.

Distribution of sarcopenia and severe sarcopenia for overall sample and different age groups.

Compared to the general Korean elderly female population,²⁵ the prevalence of sarcopenia and severe sarcopenia in severe knee osteoarthritis female patients were significantly higher (35.5% vs. 18.8%, p < .001 and 21.7% vs. 3.2%, p < .001 respectively).

According to the updated AWGS criteria, the participants were classified into groups with sarcopenia and without sarcopenia, and then, the anthropometric measurements and sarcopenic parameters were compared between the two groups (Table 3). Sarcopenic patients weighed significantly less and had lower BMI and lower 25-OH-vitamin D3 level than non-sarcopenic patients. From the perspective of sarcopenic parameters, the prevalence of low skeletal muscle mass was significantly higher in the sarcopenic group, while there were no significant differences between the two groups in terms of muscle strength and physical performance.

Table 3.

Characteristics of patients from the total sample and according to the presence or absence of sarcopenia.

Variable	Overall (n = 138)	No sarcopenia (n = 89)	Sarcopenia (n = 49)	p-value^a
Age, y	72.7 ± 6.5	71.7 ± 6.1	74.6 ± 6.8	.060
Height, m	1.5 ± 0.1	1.5 ± 0.1	1.5 ± 0.1	.097
Weight, kg	61.9 ± 9.5	65.1 ± 9.3	55.9 ± 6.8	< .001
BMI, kg/m²	26.7 ± 3.5	27.9 ± 3.5	24.4 ± 2.3	< .001
Charlson comorbidity index	0.4 ± 0.7	0.5 ± 0.7	0.4 ± 0.6	.868
25-OH-vitamin D3	22.5 ± 10.8	24.6 ± 11.4	18.6 ± 8.6	.031
K-L grade IV	72 (52.2)	46 (51.7)	26 (53.1)	.877
KS score
Knee	45.4 ± 17.1	45.3 ± 15.7	45.6 ± 19.6	.696
Function	39.4 ± 15.4	40.2 ± 14.3	38.0 ± 17.2	.506
Diagnostic assessment for sarcopenia
Skeletal muscle mass
ASM by DEXA, kg	13.6 ± 2.1	14.7 ± 1.6	11.7 ± 1.3	< .001
ASM/height²	5.6 ± 0.7	6.0 ± 0.5	4.9± 0.3	< .001
ASM/height² (<5.4 in women), %	49 (35.5)	0 (0)	49 (100.0)	< .001
Muscle strength
Grip strength, kg	16.8 ± 4.4	17.3 ± 4.5	15.9 ± 4.0	.267
Grip strength (<18 kg in women), %	79 (57.2)	46 (51.7)	33 (67.3)	.075
Physical performance
4-m usual gait speed, m/s	0.6 ± 0.2	0.6 ± 0.2	0.5 ± 0.2	.084
Gait speed (<1.0 m/s in women), %	124 (89.9)	78 (87.6)	46 (93.9)	.246

P-value in bold are statistically significant (p < 0.05).

Data are presented by mean ± standard deviation or number (%).

Abbreviations: BMI (body mass, index); K-L (Kellgren Lawrence); KS (knee society); ASM (appendicular skeletal muscle mass); DEXA (dual-energy X-ray absorptiometry).

^ap-values are based on the chi-square, Fisher exact, or independent t-test.

Subsequently, parameters defined as significant correlates of sarcopenia were included in multivariate logistic regression analysis. To better investigate the effects of risk factors on sarcopenia, we excluded the sarcopenic parameters of diagnostic criteria from regression analysis. The results of the multivariate regression analysis are shown in Table 4. This analysis revealed that lower BMI and lower 25-OH-vitamin D3 level were independent risk factors associated with sarcopenia in women awaiting TKA.

Table 4.

Multivariate logistic regression analysis of variables associated with sarcopenia.

Variable	Crude OR					Adjusted OR
Variable	OR	95% CI			p-value	OR	95% CI			p-value
Age	1.08	1.02	––	1.14	.013	0.99	0.92	––	1.08	.894
Height	0.01	0.00	––	2.34	.095	0.00	0.00	––	1451.85	.266
Weight	0.85	0.80	––	0.91	< .001	1.06	0.84	––	1.34	.612
BMI	0.64	0.50	––	0.79	< .001	0.58	0.47	––	0.71	< .001
Charlson comorbidity index	0.93	0.56	––	1.57	.791	0.70	0.33	––	1.47	.343
25-OH-vitamin D3	0.95	0.91	––	0.98	.002	0.91	0.87	––	0.96	< .001
K-L grade IV	1.06	0.53	––	2.12	.877	1.00	0.96	––	1.03	.771
KS Score
Knee	1.00	0.98	––	1.02	.916	0.99	0.96	––	1.03	.735
Function	0.99	0.97	––	1.01	.411	0.99	0.38	––	2.61	.983

P-value in bold are statistically significant (p < 0.05).

Abbreviations: OR (odds ratio calculated with logistic regression); BMI (body mass, index); K-L (Kellgren Lawrence); KS (knee society).

Discussion

Aging causes undesirable changes in body composition, such as the loss of skeletal muscle, which is sarcopenia.²⁶ Sarcopenia is defined as skeletal muscle disorders involving an accelerated loss of muscle mass, strength, and function associated with age.²⁷ In elderly people, this condition is associated with various chronic diseases and a decrease in the quality of life, as well as an increased risk of physical limitations.²⁸

The prevalence of sarcopenia in Asia is reported to be 0.1% to 23.6% in community‐dwelling older women,²⁹ and elderly female OA patients make up about 70–90% of TKA candidates.³⁰ Although the number of older women with TKA is increasing due to an aging population, little is known about the prevalence and risk factors of sarcopenia in this group. More information on sarcopenia in this group may help surgeons select and educate patients more appropriately. To the best of our knowledge, this is the first study to apply the recently updated AWGS criteria to female patients awaiting TKA due to primary knee osteoarthritis.

Using three diagnostic assessments including low appendicular skeletal muscle mass and low muscle strength (grip strength) or low physical performance (gait speed), this study cohort yielded a 35.5% prevalence of sarcopenia according to the updated AWGS criteria. The prevalence in this severe osteoarthritis cohort was significantly higher compared to the general Korean female population (35.5% vs. 18.8%, p < .001). The prevalence of sarcopenia and severe sarcopenia increased statistically significantly with advanced cohort age. Although not statistically significant, the proportion of severe sarcopenic patients increased among total sarcopenic patients with advanced cohort age.

Previous studies showed that age, low exercise rate, and inflammatory reactions accounted for the progression of osteoarthritis associated with sarcopenia.^31,32 Severe pain and poor physical function due to advanced osteoarthritis of the knee joint might limit patient activities, which may increase the risk of developing sarcopenia. Our research results supported this by revealing that the prevalence of sarcopenia in female patients prior to TKA was significantly higher than that in the general population. In addition, more than half of the sarcopenia cases diagnosed in our cohort were severe sarcopenia. These results suggest that more attention to sarcopenia is needed in this population.

In the present study, the presence of sarcopenia was associated with some baseline characteristics, such as age, lower weight, and lower BMI and lower 25-OH-vitamin D3 levels. Among them, lower BMI and 25-OH-vitamin D3 levels remained associated in the multivariate analysis.

Low BMI was a risk factor for sarcopenia in female patients with severe knee osteoarthritis, as in previous studies in the general population.^33,34 SMI is positively correlated with BMI, and low SMI is uncommon when BMI is greater than 25.³⁵ The strong relationship between BMI and sarcopenia deserves further consideration.

Vitamin D deficiency is common in both geriatric patients (30–90%) and community-dwelling older persons (2–60%).^36,37 Correlation between low vitamin D concentration and poor muscle function has been suggested in some studies^38–42 while there are still some contrary findings.^43,44 Our study also found that low 25-OH-vitamin D3 is an independent risk factor for sarcopenia. Decreased Vit D3 synthesis among the elderly patient’s skin compounded with reduced UV exposure due to arthritic sedentariness may explain this relationship.

Our results suggest that female patients with advanced knee osteoarthritis may be more likely to develop sarcopenia with aging. According to the Lancet’s latest review on sarcopenia, physical activity is considered as the primary treatment for sarcopenia, because there are currently no specific drugs approved for sarcopenia.²⁷ Through arthritic pain relief, TKA helps sarcopenic patients engage in therapeutic physical activity. In this respect, physicians need to pay attention to sarcopenic status in patients with osteoarthritis and provide appropriate intervention. It is also recommended that the preoperative assessments of TKA include screening assessments for sarcopenia. The AWGS recommends case-finding to identify the early signs of sarcopenia, screening by measuring calf circumference, administering the SARC-F questionnaire (a simplified screening tool for assessing sarcopenia in older adults), and the SARC-F administration combined with calf circumference (SARC-CalF).²⁰

In previous studies amongst patients with knee osteoarthritis, physical performance was inadequately tested due to the severe pain or mobility limitations. The strength of this study was that all diagnostic assessments were well-performed. However, this study had some limitations. First, its retrospective design could lead to selection bias. Although subjects were continuously enrolled, the number of patients in each age group were not equal. Second, these results are not representative of all patients. The cohort of this study consisted of patients with severe knee osteoarthritis who were scheduled for TKA due to their intractable pain, but not all knee osteoarthritis patients are willing or eligible to receive TKA. Nevertheless, considering the assessment and management of sarcopenia before and after TKA in severe knee osteoarthritis patients, the results of this study would provide meaningful information. Third, we used the 4-m test to evaluate physical performance, whereas the AWGS standard uses the 6-m test. However, several studies have used 4-m to assess physical performance,^45–47 which would not significantly affect our study results. Fourth, there was no data collection on physical activity or nutritional status that could be related to the differences in muscle mass. In addition, not all information was collected on the therapeutic interventions that could affect physical performance. Furthermore, some patients may have had hand OA, which could affect grip strength.

Conclusion

Footnotes

Authors’ contributions

All authors contributed to the study conception and design. Material preparation, data collection and analysis were performed by Dojoon Park, Chan Jin Park, Min-gee Jung, Youn Ho Choi, Kwang-Sun Park, Hae Seok Koh. The first draft of the manuscript was written by Dojoon Park and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript.

Declaration of conflicting interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) received no financial support for the research, authorship, and/or publication of this article.

Ethical approval

All investigations were approved by the Institutional Review Board of our institution and the procedures used in this study adhere to the tenets of the Declaration of Helsinki.

Data availability statement

The datasets used and/or analyzed in this study are available from the corresponding author upon reasonable request.

ORCID iD

Dojoon Park

References

Culliford

Maskell

Judge

, et al. Future projections of total hip and knee arthroplasty in the UK: Results from the UK clinical practice research datalink. Osteoarthr Cartil 2015; 23: 594–600. DOI: 10.1016/j.joca.2014.12.022.

Inacio

MCS

Graves

Pratt

, et al. Increase in total joint arthroplasty projected from 2014 to 2046 in Australia: A conservative local model with international implications. Clin Orthop Relat Res 2017; 475: 2130–2137. DOI: 10.1007/s11999-017-5377-7.

Kurtz

Ong

Lau

, et al. Projections of primary and revision hip and knee arthroplasty in the United States from 2005 to 2030. J Bone Jt Surg Am 2007; 89: 780–785. DOI: 10.2106/jbjs.f.00222.

Bokshan

Han

DePasse

, et al. Effect of sarcopenia on postoperative morbidity and mortality after thoracolumbar spine surgery. Orthopedics 2016; 39: e1159–e1164. DOI: 10.3928/01477447-20160811-02.

Cosquéric

Sebag

Ducolombier

, et al. Sarcopenia is predictive of nosocomial infection in care of the elderly. Br J Nutr 2006; 96: 895–901. DOI: 10.1017/bjn20061943.

Ebbeling

Grabo

Shashaty

, et al. Psoas: Lumbar vertebra index: Central sarcopenia independently predicts morbidity in elderly trauma patients. Eur J Trauma Emerg Surg Official Publ Eur Trauma Soc 2014; 40: 57–65. DOI: 10.1007/s00068-013-0313-3.

Englesbe

Patel

, et al. Sarcopenia and mortality after liver transplantation. J Am Coll Surgeons 2010; 211: 271–278. DOI: 10.1016/j.jamcollsurg.2010.03.039.

Janssen

. Influence of Sarcopenia on the development of physical disability: The cardiovascular health study. J Am Geriatr Soc 2006; 54: 56–62. DOI: 10.1111/j.1532-5415.2005.00540.x.

Kim

Lim

Choi

, et al. Sarcopenia: An independent predictor of mortality in community-dwelling older Korean men. J Gerontol Ser A Biol Sci Med Sci 2014; 69: 1244–1252. DOI: 10.1093/gerona/glu050.

10.

Deren

Babu

Cohen

, et al. Increased mortality in elderly patients with Sarcopenia and Acetabular fractures. J Bone Jt Surg Am 2017; 99: 200–206. DOI: 10.2106/jbjs.16.00734.

11.

Landi

Cruz-Jentoft

Liperoti

, et al. Sarcopenia and mortality risk in frail older persons aged 80 years and older: results from ilSIRENTE study. Age Ageing 2013; 42: 203–209. DOI: 10.1093/ageing/afs194.

12.

Landi

Liperoti

Fusco

, et al. Sarcopenia and mortality among older nursing home residents. J Am Med Directors Assoc 2012; 13: 121–126. DOI: 10.1016/j.jamda.2011.07.004.

13.

Wallace

Calvo

Lewis

, et al. Sarcopenia as a predictor of mortality in elderly blunt trauma patients: Comparing the masseter to the psoas using computed tomography. J Trauma Acute Care Surg 2017; 82: 65–72. DOI: 10.1097/ta.0000000000001297.

14.

Jochum

Kistner

Wood

, et al. Is sarcopenia a better predictor of complications than body mass index? Sarcopenia and surgical outcomes in patients with rectal cancer. Colorec Dis Official J Assoc Coloproctol Great Br Ireland 2019; 21: 1372–1378. DOI: 10.1111/codi.14751.

15.

Zhang

Huang

Dou

, et al. Falls among older adults with sarcopenia dwelling in nursing home or community: A meta-analysis. Clin Nutr 2020; 39: 33–39. DOI: 10.1016/j.clnu.2019.01.002.

16.

Mayhew

Amog

Phillips

, et al. The prevalence of sarcopenia in community-dwelling older adults, an exploration of differences between studies and within definitions: A systematic review and meta-analyses. Age Ageing 2019; 48: 48–56. DOI: 10.1093/ageing/afy106.

17.

Landi

Liperoti

Russo

, et al. Sarcopenia as a risk factor for falls in elderly individuals: Results from the ilSIRENTE study. Clin Nutr 2012; 31: 652–658. DOI: 10.1016/j.clnu.2012.02.007.

18.

Goates

Arensberg

, et al. Economic impact of hospitalizations in US adults with Sarcopenia. J Frailty Aging 2019; 8: 93–99. DOI: 10.14283/jfa.2019.10.

19.

Chen

Liu

Woo

, et al. Sarcopenia in Asia: Consensus report of the Asian working group for Sarcopenia. J Am Med Directors Assoc 2014; 15: 95–101. DOI: 10.1016/j.jamda.2013.11.025.

20.

Chen

Woo

Assantachai

, et al. Asian working group for Sarcopenia: 2019 consensus update on Sarcopenia diagnosis and treatment. J Am Med Directors Assoc 2020; 21: 300–307.e302. DOI: 10.1016/j.jamda.2019.12.012.

21.

Waddell

Johnson

Hein

, et al. Orthopaedic practice in total hip arthroplasty and total knee arthroplasty: Results from the Global Orthopaedic Registry (GLORY). Am J Orthopedics 2010; 39: 5–13.

22.

Yang

Gong

, et al. Sex, age, and annual incidence of primary total knee arthroplasty: A university affiliated hospital survey of 3118 Chinese patients. Chin Med J 2012; 125: 3952–3955.

23.

Giangregorio

Webber

. Effects of metal implants on whole-body dual-energy x-ray absorptiometry measurements of bone mineral content and body composition. Can Assoc Radiolog J 2003; 54: 305–309. quiz 270-301.

24.

Roberts

Denison

Martin

, et al. A review of the measurement of grip strength in clinical and epidemiological studies: Towards a standardised approach. Age and Ageing 2011; 40: 423–429. DOI: 10.1093/ageing/afr051.

25.

Kim

Won

. Sarcopenia in Korean community-dwelling adults aged 70 years and older: application of screening and diagnostic tools from the Asian working group for Sarcopenia 2019 update. J Am Med Directors Assoc 2020; 21: 752–758. DOI: 10.1016/j.jamda.2020.03.018.

26.

Hunter

Singh

Carter

, et al. Sarcopenia and its implications for metabolic health. J Obes 2019; 2019: 1–10. DOI: 10.1155/2019/8031705.

27.

Cruz-Jentoft

Sayer

. Sarcopenia. Lancet 2019; 393: 2636–2646. DOI: 10.1016/s0140-6736(19)31138-9.

28.

Tsekoura

Kastrinis

Katsoulaki

, et al. Sarcopenia and its impact on quality of life. Adv Exp Med Biol 2017; 987: 213–218. DOI: 10.1007/978-3-319-57379-3_19.

29.

Lau

Chau

, et al. End-stage knee osteoarthritis with and without sarcopenia and the effect of knee arthroplasty - a prospective cohort study. BMC Geriatr 2021; 21: 2. DOI: 10.1186/s12877-020-01929-6.

30.

Tao

Tang

Huang

, et al. Prevalence and risk factors of osteoporosis in Chinese postmenopausal women awaiting total knee arthroplasty. Clin Interven Aging 2021; 16: 379–387. DOI: 10.2147/cia.s297947.

31.

Misra

Fielding

Felson

, et al. Risk of knee osteoarthritis with obesity, Sarcopenic obesity, and Sarcopenia. Arthritis Rheumatol 2019; 71: 232–237. DOI: 10.1002/art.40692.

32.

Papalia

Zampogna

Torre

, et al.

Sarcopenia and its relationship with osteoarthritis: Risk factor or direct consequence?

Musculoskelet Surg 2014; 98: 9–14. DOI: 10.1007/s12306-014-0311-6.

33.

Landi

Liperoti

Fusco

, et al. Prevalence and risk factors of sarcopenia among nursing home older residents. J Gerontol Ser A Biol Sci Med Sci 2012; 67: 48–55. DOI: 10.1093/gerona/glr035.

34.

Wong

Leung

, et al. Incidence, reversibility, risk factors and the protective effect of high body mass index against sarcopenia in community-dwelling older Chinese adults. Geriatr Gerontol Int 2014; 14(Suppl 1): 15–28. DOI: 10.1111/ggi.12220.

35.

Dodds

Granic

Davies

, et al. Prevalence and incidence of sarcopenia in the very old: findings from the Newcastle 85+ Study. J Cache Sarcop Muscle 2017; 8: 229–237. DOI: 10.1002/jcsm.12157.

36.

Lips

. Vitamin D deficiency and secondary hyperparathyroidism in the elderly: Consequences for bone loss and fractures and therapeutic implications. Endocr Rev 2001; 22: 477–501. DOI: 10.1210/edrv.22.4.0437.

37.

Souberbielle

Cormier

Kindermans

, et al. Vitamin D status and redefining serum parathyroid hormone reference range in the elderly. J Clin Endocrinol Metab 2001; 86: 3086–3090. DOI: 10.1210/jcem.86.7.7689.

38.

Pfeifer

Begerow

Minne

, et al. Vitamin D status, trunk muscle strength, body sway, falls, and fractures among 237 postmenopausal women with osteoporosis. Exp Clin Endocrinol Diab Official J German Soc Endocrinol [and] Ger Diab Assoc 2001; 109: 87–92. DOI: 10.1055/s-2001-14831.

39.

Dhesi

Bearne

Moniz

, et al. Neuromuscular and psychomotor function in elderly subjects who fall and the relationship with vitamin D status. J Bone Mineral Res Official J Am Soc Bone Mineral Res 2002; 17: 891–897. DOI: 10.1359/jbmr.2002.17.5.891.

40.

Mets

Torgerson

CaMpbellM . Calcium, vitamin D, and hip fractures. Incidence of falls may have decreased. BMJ Clin Res Educ 1994; 309: 193. DOI: 10.1136/bmj.309.6948.193.

41.

Mowé

Haug

Bøhmer

. Low serum calcidiol concentration in older adults with reduced muscular function. J Am Geriatr Soc 1999; 47: 220–226. DOI: 10.1111/j.1532-5415.1999.tb04581.x.

42.

Bischoff

Borchers

Gudat

, et al. In situ detection of 1, 25-dihydroxyvitamin D3 receptor in human skeletal muscle tissue. Histochem J 2001; 33: 19–24. DOI: 10.1023/a:1017535728844.

43.

Iannuzzi-Sucich

Prestwood

Kenny

. Prevalence of sarcopenia and predictors of skeletal muscle mass in healthy, older men and women. J Gerontol Ser A Biol Sci Med Sci 2002; 57: M772–M777. DOI: 10.1093/gerona/57.12.m772.

44.

Boonen

Lysens

Verbeke

, et al. Relationship between age-associated endocrine deficiencies and muscle function in elderly women: a cross-sectional study. Age Ageing 1998; 27: 449–454. DOI: 10.1093/ageing/27.4.449.

45.

Rossi

Fantin

Micciolo

, et al. Identifying sarcopenia in acute care setting patients. J Am Med Directors Assoc 2014; 15: 303.e7–303.e12. DOI: 10.1016/j.jamda.2013.11.018.

46.

Yang

Liu

Zuo

, et al. Sarcopenia for predicting falls and hospitalization in community-dwelling older adults: EWGSOP versus EWGSOP2. Sci Rep 2019; 9: 17636. DOI: 10.1038/s41598-019-53522-6.

47.

Bruyère

Beaudart

Ethgen

, et al. The health economics burden of sarcopenia: a systematic review. Maturitas 2019; 119: 61–69. DOI: 10.1016/j.maturitas.2018.11.003.