Osteoarthritis (OA), the most common degenerative chronic joint disease, is characterized primarily by pain, stiffness, and a progressive decline in joint function, ultimately leading to joint dysfunction and disability1,2. Over 654 million people worldwide have symptomatic osteoarthritis (OA), with knee OA exhibiting the highest prevalence3. Owing to its high prevalence, high disability rate, and substantial treatment costs, knee osteoarthritis (KOA) has become a significant burden on both society and the economy4. Total knee arthroplasty (TKA), the standard treatment for end-stage KOA5,6, was performed on 429 per 100,000 people in the US in 2012 and is projected to increase by 565% by 20507. Despite high success rates and long-term prosthesis survival with TKA, 20–30% of patients remain dissatisfied postoperatively, primarily due to poor joint function8,9. Identifying preoperative factors that influence postoperative functional outcomes is essential for improving clinical efficacy of TKA, as it helps clinicians recognize patients at risk for poor outcomes and develop preventive interventions.

Sarcopenia is a geriatric syndrome characterized by an age-related decline in skeletal muscle mass and strength10. Although sarcopenia has only recently been recognized as a disease, it has already become a common global condition, with an estimated 500 million patients projected by 2050 11,12. In clinical practice, KOA and sarcopenia often coexist. In KOA patients undergoing TKA, the prevalence of sarcopenia can reach 63.7% 13. The impact of sarcopenia on TKA has also garnered increasing attention from researchers in recent years. Although KOA patients with sarcopenia can achieve significant improvements in muscle mass following TKA, they face serious risks, including prolonged hospital stays, increased medical costs, higher transfusion rates, and an increased likelihood of complications such as infections and prosthetic loosening14,15,16.

Currently, an increasing number of researchers are focusing on the impact of sarcopenia on various organ system diseases. In the surgical and oncological fields, sarcopenia is often diagnosed via disease-related or opportunistically obtained computed tomography (CT) imaging, which has been proven to be a risk factor for reduced overall survival and poor postoperative outcomes in patients with multiple organ system diseases17,18,19,20,21,22. Diagnosing sarcopenia via opportunistic CT images offers the distinct advantage of imposing no additional financial burden or radiation exposure on patients. Furthermore, research suggested that CT is likely the best technique for assessing muscle mass and quality, and it is considered the gold standard method for body composition analysis and the diagnosis of abnormal body composition phenotypes23. Owing to comorbidities and preoperative evaluations, elderly patients undergoing TKA are more likely to receive chest CT rather than abdominal CT24. To our knowledge, no studies have yet evaluated the association between sarcopenia determined by chest CT and postoperative functional outcomes after TKA. It remains unclear whether sarcopenia diagnosed through chest CT is associated with poor functional outcomes after TKA. If such an association exists, preoperative opportunistic chest CT imaging could help to identify patients at risk of poor postoperative functional outcomes and may consequently improve patient outcomes. Therefore, this study aimed to explore the association between chest CT-determined sarcopenia and functional outcomes following TKA in KOA patients. We hypothesized that sarcopenia determined through chest CT is associated with poorer functional outcomes after TKA in these patients.

Methods

Population

This retrospective study included all clinical cases of patients who underwent TKA in the Department of Orthopedics at our hospital between January 2021 and June 2022. The study was approved by the Ethics Committee of our institution (Approval No: KY2022325). The inclusion criteria were meeting the diagnostic criteria for KOA, undergoing primary unilateral TKA, having no significant contraindications for surgery, having surgery performed by the same team of experienced surgeons, and having complete case data. The exclusion criteria were the presence of neuromuscular disorders or lower limb neuromuscular dysfunction; subsequent surgery on the same or contralateral lower limb during the follow-up period; cognitive or psychological disorders; speech impairment; severe cardiac, pulmonary, hepatic, or renal insufficiency; malignancy; the absence of preoperative chest CT imaging data; and the absence of postoperative follow-up data. According to the inclusion and exclusion criteria, 158 patients were ultimately enrolled in the cohort.

Treatment

Routine preoperative examinations were conducted to exclude surgical contraindications. Owing to the study period coinciding with the COVID-19 pandemic, patients in the study region were generally required to undergo chest CT scans instead of chest X-rays to better screen for potential infections and reduce the risk of transmission. Smokers were advised to quit smoking at least two weeks before surgery (in the post-epidemic era, preoperative thoracic CT scans are not mandatory for patients undergoing TKA). For patients with hypertension or diabetes, regular monitoring was performed, and blood pressure or blood glucose levels were adjusted to within the normal range. Preoperative rehabilitation training guidance was provided, and patients with a preoperative visual analogue scale (VAS) pain score greater than 4 were prescribed regular oral celecoxib. Thirty minutes before surgery, second-generation cephalosporins were administered via intravenous infusion, and tranexamic acid was given intravenously 10 min before surgery. All surgeries were performed through a midline approach, using posterior-stabilized fixed-bearing prostheses without patellar resurfacing. Postoperatively, all patients received cryotherapy on the knee joint for 72 h and were prescribed regular oral celecoxib for pain management. Tranexamic acid was administered intravenously 4 h after surgery, and a closed suction drain was placed. Low-molecular-weight heparin was initiated 12 h postoperatively for thromboprophylaxis, followed by oral rivaroxaban for up to 3 weeks after discharge. The closed suction drain was removed within 24 h postoperatively. On the first postoperative day, patients were encouraged to begin weight-bearing activities and perform active and passive knee joint function exercises.

Data collection

Sociodemographic data included age, gender, body mass index (BMI), current or preretirement occupation, place of residence, and educational level. Preoperative disease-related clinical data included the affected side, disease duration, history of smoking, history of alcohol consumption, and presence of chronic comorbidities (including hypertension, diabetes, heart disease, and pulmonary disease). The preoperative laboratory data included hemoglobin, white blood cell count, platelet count, albumin, serum potassium concentration, serum sodium concentration, and serum calcium concentration. Perioperative data included the length of hospital stay and postoperative VAS pain score on the first postoperative day. The Hospital for Special Surgery (HSS) scores of all patients 6 months after TKA were recorded. This score was primarily assessed through follow-up visits by the same team members. The HSS scoring system involves six major categories: pain (30 points), function (22 points), range of motion (18 points), muscle strength (10 points), flexion deformity (10 points), and stability (10 points). Deductions are made for walking aids, knee extension lag, and varus or valgus deformities. The maximum score is 100, and knee function is classified on the basis of the score as excellent (≥ 85 points), good (70–84 points), fair (60–69 points), or poor (< 59 points). In this study, scores ≥ 85 points were considered excellent, and scores < 85 points were considered poorer.

Definition of sarcopenia

Preoperative chest CT images obtained at the time of hospital admission were collected to evaluate the skeletal muscle index (SMI) for diagnosing sarcopenia. The evaluation process was as follows: chest CT images at the T12 vertebral level were imported into specialized muscle analysis software (SliceOmatic, version 5.0, Canada). Using the predefined and widely accepted muscle tissue thresholds (-29–150 HU) from previous studies25, the muscle area was semiautomatically identified in the specified cross-sectional image. The images were then visually reviewed and manually adjusted to ensure the exclusion of all nonmuscle areas and the inclusion of all muscle areas. The muscle area obtained was divided by the square of the patient’s height to calculate the SMI. For diagnosing sarcopenia, the cut-off values proposed by Nemec et al.26, which are based on muscle measurements at the T12 vertebral level, were used: SMI < 42.6 cm²/m² for males and < 30.6 cm²/m² for females. These cut-off values have been widely applied in the diagnosis of sarcopenia27,28,29,30,31,32. Two orthopedists, with no knowledge of patient details, independently collected all the data. Both were professionally trained and proficient in the technique. To assess reproducibility, 20 CT images were randomly chosen and re-evaluated by the two observers after a two-week interval. The final analysis was based on the average values from both observers (Fig. 1).

Fig. 1
figure 1

The muscle area was measured using a cross-sectional CT image at the level of the 12th thoracic vertebra. (A) shows the cross-sectional CT image at the level of the 12th thoracic vertebra for a 64-year-old man patient. The calculated SMI was 44.0 cm2/m2, which exceeds the cut-off value for men, and the patient was diagnosed as non-sarcopenic. (B) shows the cross-sectional CT image at the level of the 12th thoracic vertebra for a 71-year-old woman patient. The calculated SMI was 27.3 cm2/m2, which is below the cut-off value for women, and the patient was diagnosed with sarcopenia. CT computed tomography; SMI skeletal muscle index.

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Data analyses

The sample size for this study was estimated via G*Power (version 3.1.9.7). Post-hoc power analysis indicated that, given the sample size and an α level of 0.05, there was over 90% power (1-β) to detect differences in HSS scores between the two groups (effect size = 0.54). Additionally, the sample size for each group was sufficient, reaching 5–10 times the number of independent variables included in the binary multivariate logistic regression analysis, thereby meeting the requirements for logistic regression analysis.

All the statistical analyses were performed via IBM SPSS Statistics software (version 26.0). A two-sided P-value < 0.05 was considered statistically significant. Intraclass correlation coefficients (ICCs) were calculated to assess the intra-rater and inter-rater reliabilities of the measurements. Data normality was assessed using the Shapiro-Wilk test. Categorical variables are expressed as frequencies (%), continuous variables following a normal distribution are expressed as the mean ± standard deviation (x̄ ± s), and continuous variables not following a normal distribution are expressed as the median (interquartile range). Continuous variables with a normal distribution were compared via the independent samples t-test, whereas those without following a normal distribution were compared via the Mann-Whitney U test. Categorical variables were compared via the chi-square test or Fisher’s exact test. Binary multivariate logistic regression analysis was used to explore the risk factors for sarcopenia in KOA patients undergoing TKA and the impact of sarcopenia on postoperative knee function in these patients.

Results

During the research period, our institution carried out primary total knee arthroplasty for 178 patients with KOA. Since the case data of 2 patients were incomplete, 176 patients were included. Three patients who underwent contralateral TKA during the follow-up period, 8 patients lacking available CT data and 7 patients with missing postoperative follow-up were excluded. Therefore, a total of 158 patients were finally included in the study. The interval between patients receiving a chest CT scan and surgery ranged from a minimum of 1 day to a maximum of 30 days. Table 1 presents the intraobserver and interobserver ICCs for skeletal muscle area measurements, all of which demonstrated excellent consistency.

Table 1 ICC values of interobserver A.d intraobserver reliabilities of the measurements a. ICC intraclass correlation coefficient. a 95% confidence interval (CI) is displayed in brackets.
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In this cohort, the patients had a mean age of 67.34 ± 7.48 years and a mean BMI of 25.3 ± 3.8 kg/m2. The group comprised 25 males (15.8%) and 133 females (84.2%). Based on chest CT assessments, the prevalence of sarcopenia was 48.7%. The baseline characteristics of the overall patient population are presented in Table 2. In this study, patients with sarcopenia were significantly older (P < 0.001), had a lower BMI (P < 0.001), and had a longer disease duration (P = 0.039) than those without sarcopenia (Table 2). After incorporating the aforementioned factors into the multivariate analysis, advanced age (P = 0.001), lower BMI (P < 0.001), and a disease duration of ≥ 10 years (P = 0.013) were identified as being significantly associated with sarcopenia in KOA patients undergoing TKA (Table 3).

Table 2 Baseline characteristics of A.l patients A.d comparison of patients with A.d without sarcopenia (n = 158) a. BMI body mass index; SD standard deviation.
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Table 3 Multivariate analysis assessing predictors of sarcopenia in patients undergoing total knee arthroplasty. BMI body mass index; CI confidence interval; OR odds ratio.
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A comparison between the two groups revealed that the poorer functional group was characterized by significantly greater age (P = 0.002), higher BMI (P = 0.030), sarcopenia (P = 0.007), and higher postoperative VAS pain scores (P < 0.001), with all differences reaching statistical significance (Table 4). Incorporating the aforementioned factors into the logistic regression analysis revealed that advanced age (P = 0.025), higher BMI (P = 0.027), sarcopenia (P = 0.020), and higher postoperative VAS pain scores (P = 0.003) were risk factors for poorer joint functional outcomes at 6 months after KOA patients underwent TKA (Table 5).

Table 4 Univariate A.alysis of poorer postoperative functional outcomes in patients undergoing total knee A.throplasty (n = 158) a. BMI body mass index.
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Table 5 Multivariate analysis of poorer postoperative functional outcomes in patients undergoing total knee arthroplasty.
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Discussion

To the best of our knowledge, this is the first study to evaluate the association between chest CT-determined sarcopenia and postoperative functional outcomes following TKA in KOA patients. Sarcopenia is a relatively newly recognized condition. However, its high prevalence and severe negative impact on the health of the elderly population have garnered significant attention from researchers. A recent large-scale meta-analysis revealed that the prevalence of sarcopenia among individuals aged 60 and older ranges from 10 to 27%33. In patients undergoing TKA for KOA, the prevalence of sarcopenia is as high as 19.9–63.7%, which is significantly greater than that reported in community-dwelling populations13,14,34,35,36,37. Although this study did not specifically include an elderly population, which may have led to an underestimation of the prevalence of sarcopenia, the prevalence of sarcopenia in the studied cohort was still remarkably high at 48.7%. Therefore, particular emphasis should be placed on the screening and identification of sarcopenia in this specific patient population. Previous studies have reported that elderly individuals with KOA generally experience a greater decline in muscle mass than do those without KOA38,39. Additionally, KOA patients with coexisting sarcopenia have been shown to exhibit higher KOA grades on knee joint radiographs than their non-sarcopenic counterparts40. These findings highlight the mutual influence and interaction between the two conditions, partially accounting for the high prevalence of sarcopenia among KOA patients. However, one study reported a relatively low prevalence of sarcopenia in KOA patients41, which may be attributed to the relatively small sample sizes used in these investigations.

In this study, we revealed that advanced age, lower BMI, and longer disease duration were independently associated with CT-determined sarcopenia, which could facilitate a more efficient and accurate identification of CT-determined sarcopenia patients in clinical practice.

According to previous research, both sarcopenia and KOA are age-related diseases, with older age serving as a critical risk factor contributing to the increased prevalence of both conditions13,34,37,42. One of the characteristic manifestations of muscle alterations in KOA is its replacement by fat, which is clinically associated with an increase in BMI34. While the majority of studies, including the present study, have identified higher BMI as a protective factor against sarcopenia, this observation is not contradictory. BMI, defined as the ratio of body mass to the square of height, does not accurately reflect body fat composition and incorporates muscle mass. This perspective is further supported by Oosting et al.43, who reported that elevated BMI alone was not associated with prolonged hospitalization after total hip arthroplasty, whereas the coexistence of low muscle strength and higher BMI was significantly associated with extended hospital stays postoperatively. KOA patients with longer disease durations experience more pronounced deceases in muscle mass and strength due to prolonged activity limitations and chronic pain. Moreover, the extended persistence of a low-grade inflammatory environment in the knee joint exacerbates the effects of inflammatory mediators on muscle protein synthesis and degradation, potentially contributing to a decline in both muscle quality and function44,45. Anemia is recognized as a risk factor for sarcopenia46,47, and this study revealed significantly lower hemoglobin levels in the sarcopenia group. However, multivariate analysis revealed no independent associations, possibly due to the inclusion of younger KOA patients with lower nutritional risk, where age adjustment eliminated low hemoglobin as an independent risk factor.

Using existing CT scans from surgical or oncology patients (opportunistic CT) to diagnose sarcopenia and predict outcomes is a well-studied approach that avoids extra exams, costs, and radiation17,18,19,20,21,22. While DXA is currently the most recommended diagnostic method10,11, its accuracy can be compromised by tissue fibrosis, and it involves radiation exposure48. Bioelectrical impedance analysis is another diagnostic tool, but its reliability is often limited by fluctuations in body hydration, electrolytes, and temperature, hindering its widespread use for diagnosing sarcopenia49. A recent study reported that sarcopenia diagnosed via abdominal CT was independently associated with poorer patient-reported outcomes (PROMs), with differences meeting the minimal clinically important difference (MCID)36. However, the study highlighted that abdominal CT is not readily available for KOA patients undergoing TKA, which significantly limits its clinical applicability. Chest CT is the most commonly performed imaging examination for preoperative and comorbidity evaluations in the elderly population24.

In this study, we found that sarcopenia diagnosed via chest CT was independently associated with poor functional outcomes after TKA, providing a practical method for identifying patients at risk of poor functional recovery in clinical practice. Two recent studies revealed that KOA patients with DXA-based sarcopenia had poorer knee function scores after TKA37,41. Although earlier studies on TKA outcomes did not control for confounders such as age and BMI, later research indicated that sarcopenia is an independent risk factor for poorer postoperative function, even after adjusting for these variables. He et al.35 reported that this association persisted after adjusting for BMI, whereas Liao et al.13 confirmed that DXA-diagnosed sarcopenia remained independently linked to poor functional scores after accounting for age, BMI, and comorbidities. Similarly, our findings showed that after adjusting for age, BMI, and postoperative pain scores, sarcopenia was still independently associated with poorer functional outcomes.

Our study duration was limited to 6 months postoperatively, which may not be sufficiently long. However, previous research has shown that postoperative HSS scores are significantly associated with long-term satisfaction following TKA50. Additionally, other studies have reported that the negative impact of sarcopenia on postoperative function can persist for 10 months to 5 years13,35,37. Therefore, identifying patients at rehabilitation risk within 6 months is clinically meaningful, as targeted interventions can be implemented to prevent poor long-term outcomes. Currently, there are numerous studies on interventions for sarcopenia in TKA patients51,52,53. As a modifiable condition, sarcopenia can be addressed preoperatively54. Moreover, sarcopenia has been associated with postoperative complications such as infections, prosthetic loosening and blood transfusions15,55. Therefore, future research on the use of chest CT to predict overall adverse outcomes in TKA patients is warranted. With the advancement of artificial intelligence, muscle measurement and sarcopenia diagnosis have become increasingly feasible55,56. In the future, it could be used to analyse opportunistic chest CT scans to predict the risk of various adverse events after TKA. This would enable early identification and intervention, ultimately improving clinical outcomes.

This study had several limitations. First, although the sample size provides sufficient statistical power, it remains relatively small. Larger multicenter studies are needed in the future. Second, owing to the limitations inherent in a retrospective design, more comprehensive assessment data, such as muscle strength, grip strength, bone density, preoperative HSS scores, and patient-reported outcome measures (PROMs), were not included. Although evaluating the impact of sarcopenia solely on postoperative functional scores is a focal point in similar studies and possesses significant clinical value13,35, the absence of preoperative HSS scores precluded an assessment of the preoperative functional status and the dynamic changes in functional status before and after surgery. Furthermore, while the HSS score is a widely accepted and validated measure of knee joint function, and numerous prior studies have similarly utilized only HSS scores for evaluating post-TKA function57,58,59, PROMs are gaining increasing importance in clinical practice as they better reflect patients’ subjective satisfaction. The lack of these two aforementioned metrics necessitates further elucidation through future prospective studies. Lastly, the diagnosis of sarcopenia via CT is not the gold standard; however, diagnosing sarcopenia via muscle mass measured by CT alone has gained significant attention across multiple disciplines17,18,19,20,21,22. Moreover, in this study, sarcopenia diagnosed via thoracic CT was utilized to predict post-TKA knee joint function, rather than to formally diagnose sarcopenia within this population. This approach was adopted because, although the TKA surgical population does not routinely undergo thoracic CT evaluation, chest CT is the most frequently performed type of CT scan in elderly individuals due to comorbidities and preoperative assessments24. Furthermore, during the study period, patients undergoing TKA at our institution commonly received chest CT scans, which consequently minimized significant heterogeneity.

Conclusions

Chest CT-determined sarcopenia is highly prevalent among KOA patients undergoing TKA and is significantly associated with poorer functional outcomes. The use of opportunistic chest CT imaging for the preoperative diagnosis of sarcopenia allows for the prediction of patients at risk for poorer postoperative functional outcomes. This facilitates the implementation of targeted interventions, which may contribute to optimizing postoperative recovery and improving functional prognoses.