ABSTRACT
Background
Lung transplant recipients are at increased risk of sarcopenia and osteoporosis, which may negatively influence respiratory outcomes. Although muscle health is known to affect lung function, little is known about the long‐term interplay between muscle parameters and pulmonary volumes, especially across sexes. The objective of this study is to evaluate the longitudinal relationship between muscle mass and strength and respiratory function in lung transplant patients, with sex‐specific analysis.
Methods
This prospective cohort included three assessments (baseline ≥ 3 months after transplant, ~1 year and 2–3 years). The primary outcome was the longitudinal change in pulmonary function (VC, FVC, FEV1 and TLC) in relation to appendicular skeletal muscle mass index (ASMMI) and handgrip strength (HGS). Associations at baseline were tested with multivariable linear regression. Analyses were performed with linear mixed‐effects models (LMM) including random intercepts for subject, time as a fixed effect and interactions between time and muscle parameters, adjusted for age, ADL, corticosteroid dose, vertebral fractures, osteoporosis, comorbidities and time since transplant.
Results
We studied 155 recipients (43.2% women, age 48.7 ± 13.3 years). Primary indications were cystic fibrosis (30.1%), restrictive (22.2%), obstructive (15.7%), miscellaneous (26.8%) and vascular diseases (5.2%). At baseline, HGS was independently associated with higher VC (R 2: 0.63, β = 0.35, p = 0.001 in women; R 2: 0.58, β = 0.16, p < 0.001 in men) and FEV1 (R 2: 0.51, β = 0.08, p = 0.020 in women; R 2: 0.57, β = 0.19, p = 0.009 in men). ASMMI was independently associated with VC in both sexes (women: R 2: 0.58, β = 0.31, p = 0.003; men: R 2: 0.40, β = 0.16, p = 0.023). Longitudinally, LMMs showed that higher HGS was associated with more favourable trajectories of pulmonary function over follow‐up. Specifically, among women with restrictive disease, lower ASMMI predicted higher FEV1 (β = −4.95, 95% CI −6.93 to −2.97, p = 0.007) and higher TLC (β = −2.22, 95% CI −4.56 to −1.12, p = 0.04) over time. In women with cystic fibrosis, stronger HGS was associated with improved TLC (β = 0.38, p = 0.04). All associations persisted after full adjustment.
Conclusion
Muscle mass and strength are associated with lung function after lung transplantation. These findings underscore the clinical importance of muscle health and support its integration into post‐transplant management.
Keywords: COPD, cystic fibrosis, lung transplant, sarcopenia, vertebral fractures
1. Introduction
Lung transplantation is a worldwide therapeutic option for the treatment of numerous end‐stage lung diseases. The primary indications for this procedure include lung fibrosis, chronic obstructive pulmonary disease (COPD) and cystic fibrosis (CF) [1].
Conditions such as chronic respiratory failure, physical inactivity and corticosteroid therapy in the post‐transplant immunosuppressive regimen can increase the risk of fracture, as a result of the reduction in bone mass and quality [2], disability and mortality [3]. Moreover, inflammatory status and oxidative stress are common in the immediate post‐lung transplantation period [4], and can contribute to the loss of lean mass. For example, in COPD patients, sarcopenia rates (i.e., the loss of muscle strength and mass) range between 10% and 25% [5]. Osteoporosis and sarcopenia could, therefore, be common conditions in transplant recipients and might limit the beneficial effects of the transplant itself; vertebral fractures can lead to thoracic kyphosis, which negatively impacts lung volume [6, S1]. This is particularly important in CF patients, who undergo transplantation at a young age, and whom previous studies have shown to be at risk of bone disease, defined by low bone mineral density (BMD), and at an increased risk of fragility fractures [7, S2].
Pulmonary performance can be influenced by body composition parameters in both healthy individuals and patients with chronic lung disease, although direct comparisons between these groups remain limited [8, 9]. In healthy adults, handgrip strength (HGS) is independently associated with spirometric indices, typically with higher FEV1 and FVC per SD increase in HGS after adjustment for age, sex and body size [10]. For example, Han et al. reported significant positive associations of HGS with FEV1 and FVC in both men and women, independent of confounders, and similar findings have been observed in other cohorts [11]. In COPD cohorts, lower HGS tracks with lower FEV1 and worse clinical status; in interstitial lung disease, disease severity relates to reduced grip strength and poorer functional metrics [12, 13]. However, due to the heterogeneity of diagnostic criteria for sarcopenia, few studies have specifically examined the impact of sarcopenia—European Working Group on Sarcopenia in Older People (EWGSOP) original consensus in 2010 [14] and its revised 2019 version (EWGSOP2) [15]—on respiratory performance in lung transplant recipients. Nonetheless, the shared hypothesis is that both qualitative and quantitative muscle alterations, resulting from chronic disease, medications and lifestyle habits, can negatively affect lung performance. However, there is still a significant lack of research that longitudinally investigates the effects of muscle parameters, such as muscle mass and muscle strength, as well as other muscle‐related variables, on lung function over time.
Given these premises and the gaps in the current literature, this study has two primary objectives. The first aim is to characterize lung transplant recipients in terms of osteo‐muscular parameters, including the presence of osteoporosis, muscle mass and muscle strength, and to evaluate the impact of muscle parameters on respiratory function. The second aim is to determine whether changes in muscle parameters influence lung volumes over time.
2. Materials and Methods
2.1. Study Design
A longitudinal study was conducted on patients who underwent lung transplantation. The patients were enrolled as scheduled post‐transplant admissions by the Thoracic Surgery Unit (UOC) at the Padua University Hospital. Subsequently, they underwent a specialized evaluation at the Geriatric Department within the same hospital.
2.2. Participants
Inclusion criteria were age > 20 years and having undergone a single or double lung transplant. Exclusion criteria were (i) active neoplastic disease or positive screening for previous neoplasms within the last 5 years; (ii) history of heart–lung transplant; (iii) clinically unstable conditions (e.g., fever, worsening respiratory symptoms, recent changes in usual therapy or hospitalization for respiratory issues within 30 days before the evaluation); (iv) inability to perform spirometry or physical performance tests; and (v) lung transplant performed less than 3 months prior to enrolment.
The patients were assessed at three distinct time points: an initial evaluation conducted at least 3 months after the transplant, followed by two subsequent follow‐ups at 1 year and 2–3 years after the initial evaluation.
2.3. Ethical Approval
The study was conducted in strict adherence to the ethics statement of the International Society for Heart and Lung Transplantation (ISHLT). The study protocol received approval from the local ethics committee (Comitato Etico di Padova, number 0014675) and complied with the guidelines outlined in the Declaration of Helsinki. Each participant provided written informed consent to participate in the study.
2.4. Study Variables
Each participant underwent a clinical and functional assessment, both at baseline and during the two follow‐ups, carried out by qualified medical personnel. This assessment included the following.
2.4.1. Medical History
Recent and past pathological, physiological and pharmacological history was recorded, with particular attention to corticosteroid, immunosuppressive and anti‐osteoporosis therapy, as well as previous diagnosis of osteoporosis. Comorbidities and disease severity were evaluated using the Cumulative Illness Rating Scale (CIRS) (please see reference S3).
2.4.2. Functional Assessment
Functional status was evaluated based on independence in Activities of Daily Living (ADL) (please see reference S4).
2.4.3. Anthropometric Measurements
Weight and height were measured to the nearest 0.1 kg and 0.1 cm using a scale and stadiometer (Seca—Germany), without shoes and in light clothing. Body mass index (BMI) was calculated by dividing weight (in kilograms) by height (in metres) squared.
Instrumental methods:
Dual‐energy x‐ray absorptiometry (DEXA): Bone mineral density (BMD) was measured for each patient using dual‐energy x‐ray absorptiometry (DEXA) (Hologic QDR 4500W Inc.), acquiring scans of the proximal femur region (left or right) and lumbar spine (L1–L4) (please see references S5–S7). Body composition was then measured through a whole‐body scan, specifically evaluating fat‐free mass (FFM), fat mass (FM) and appendicular skeletal muscle mass (ASMM). The appendicular skeletal muscle mass index (ASMMI) was obtained by dividing the ASMM by height in metres squared. DEXA is considered the most reliable method for assessing muscle mass (total body FFM or ASMM) due to its simplicity and safety; the required radiation dose is minimal, and the measurements are generally more accurate than those obtained with other techniques.
Spinal x‐rays: Each patient was screened for vertebral fractures using x‐rays taken in anteroposterior and lateral views the day before the evaluation. Vertebral fractures documented radiologically were defined according to the semi‐quantitative Genant method as reductions greater than 20% in anterior, middle or posterior vertebral height and were classified by severity as mild (20%–25%), moderate (26%–40%) or severe (> 40%) (please see reference S8). Vertebral fractures noted in medical history or identified in previous x‐rays and confirmed by radiographic reading were classified as known vertebral fractures, whereas those detected for the first time during outpatient radiographic reading were classified as unknown vertebral fractures.
Spirometry: Spirometry was performed with a spirometer (Jaeger) calibrated according to the manufacturer's technical instructions and administered by the Respiratory Physiopathology Unit Team. The test was performed in the morning, and the best of three spirometric tests performed was considered. The spirometric parameters evaluated were tidal volume (VT), forced vital capacity (FVC), forced expiratory volume in 1 s (FEV1) and total lung capacity (TLC). These values were normalized for age, sex, weight, height and ethnicity according to international spirometric reference values and expressed as a percentage of the predicted value (% pred).
2.4.4. Muscle Strength Tests
Handgrip strength (HGS) was measured on the dominant side using an electronic dynamometer (Akern DynEx). Patients were seated on a standard chair with the dominant arm resting neutrally with the elbow flexed at 90° on the table and the forearm and wrist in a natural position. They were instructed to grip the dynamometer and squeeze to their maximum strength in response to a verbal command, without making any sudden movements. Two measurements were taken on the dominant side with a 1‐min interval between trials, and the highest measurement was used for our analyses (please see reference S9).
2.4.5. Biochemical Parameters
General blood tests were recorded for each patient, and the following phospho‐calcium metabolism tests performed within 3 months of the visit: serum calcium, serum phosphorus, parathyroid hormone (PTH), 25‐hydroxy‐vitamin D, CTX (C‐terminal telopeptide of Type 1 collagen), total and bone alkaline phosphatase, 24‐h urine calcium and phosphate excretion. The analyses were performed following standard procedures at the laboratory unit of the University Hospital of Padua, which has Clinical Pathology Accreditation.
2.5. Assessment of Osteoporosis and Sarcopenia
Osteoporosis was evaluated based on lumbar and femoral T‐score values, as well as the presence of fragility fractures, such as a proximal femur or vertebral fracture. According to the definitions provided by the World Health Organization and the International Osteoporosis Foundation (please see reference S10), four conditions were identified: A T‐score of −1.0 or higher indicated normal bone mineral density, a T‐score between −1.0 and −2.5 indicated osteopenia, and osteoporosis was defined by a T‐score of −2.5 or lower. In accordance with the subsequent refinement proposed by Ferrari et al. (please see reference S11), patients with a T‐score of −2.5 or lower and one or more fragility fractures were classified as having severe osteoporosis.
Sarcopenia was diagnosed based on muscle strength, mass and performance, following the 2019 European Consensus criteria [15]. Values of HGS below 16 kg for women and 27 kg for men or chair stand test scores > 15 s suggested probable sarcopenia and were categorized as low muscle strength. Low muscle mass was defined as ASMMI values below 5.5 kg/m2 for women and 7.0 kg/m2 for men. The contemporaneous presence of low muscle strength and low muscle mass defined confirmed sarcopenia.
2.6. Statistical Analyses
The characteristics of the studied sample were expressed as mean and standard deviation (SD) for normally distributed continuous quantitative variables, as median (interquartile range) for non‐normally distributed variables or counts and percentages for categorical variables. The normality of the distributions for continuous quantitative variables was assessed using the Shapiro–Wilk test. The characteristics of the study participants and the results of the tests were compared based on sex, underlying respiratory condition, presence of osteoporosis and sarcopenia using the Mann–Whitney and Kruskal–Wallis tests for quantitative variables and Pearson's chi‐square test for categorical variables.
To determine whether muscle parameters (mass and strength) were independent predictors of VC, FVC, FEV1 and TLC at baseline, a multivariate linear regression analysis was conducted, stratifying by sex and adjusting for age, functional abilities, steroid dosage, osteoporosis, presence of vertebral fractures, CIRS‐CI and time since transplantation. To evaluate whether pulmonary function changed over time in relation to muscle parameters, we used linear mixed‐effects models (LMMs) with repeated measures. Each participant contributed multiple observations; subject was modelled as a random intercept, whereas time was included as a fixed effect. ASMMI and HGS were modelled as fixed effects, and, when supported by convergence, random slopes for time were also considered. Interaction terms (time × ASMMI and time × HGS) were included to assess whether trajectories differed by muscle status. Models were stratified by sex and additionally by pre‐transplant diagnosis. Covariates included age, ADL, corticosteroid dose, vertebral fractures, osteoporosis, comorbidity burden (CIRS‐CI) and time since transplant.
Statistical tests were deemed significant with a p‐value < 0.05. All analyses were performed using the Statistical Package for the Social Sciences Version 29.0 (SPSS, Armonk, NY: IBM Corp).
3. Results
3.1. Baseline Characteristics
Table 1 summarizes the characteristics of the study population (n = 155; 67 women, 43.2%). The mean age was 48.7 ± 13.3 years (range 21–72), with women being significantly younger than men (p < 0.001). The main indications for lung transplantation were CF (30.1%), restrictive lung diseases (22.2%), obstructive lung diseases (15.7%), miscellaneous conditions (26.8%) and vascular diseases (5.2%). CF was more frequent among women (42.4% vs. 20.7%), whereas obstructive lung diseases were more common in men (21.8% vs. 7.6%; both p = 0.01). On average, participants were assessed 40 months after their transplantation.
TABLE 1.
Descriptive characteristics of the total sample and by gender at baseline.
| Variable | Total (n = 155) | Women (n = 67) | Men (n = 88) | p |
|---|---|---|---|---|
| Age (years), mean ± SD | 48.7 ± 13.3 | 44.6 ± 14.3 | 51.9 ± 11.5 | < 0.001 |
| BMI (kg/m2), mean ± SD | 22.9 ± 4.03 | 21.36 ± 3.46 | 24.2 ± 3.99 | 0.200 |
| ADL, mean ± SD | 5.84 ± 0.62 | 5.88 ± 0.48 | 5.81 ± 0.71 | 0.46 |
| Primary condition, n (%) | 0.01 | |||
| CF | 46 (30.1%) | 28 (42.4%) | 18 (20.7%) | |
| Restrictive lung diseases | 34 (22.2%) | 16 (24.2%) | 18 (20.7%) | |
| Obstructive lung diseases | 24 (15.7%) | 5 (7.6%) | 19 (21.8%) | |
| Miscellaneous | 41 (26.8%) | 13 (19.7%) | 28 (32.2%) | |
| Vascular diseases | 8 (5.2%) | 4 (4.6%) | 4 (6.1%) | |
| Time since transplant (months), mean ± SD | 40.01 ± 80.71 | 40.94 ± 52.76 | 39.31 ± 97.05 | < 0.001 |
| Total medications taken, mean ± SD | 15.05 ± 3.86 | 14.87 ± 3.88 | 15.18 ± 3.87 | 0.007 |
| Duration of corticosteroid therapy (months), mean ± SD | 30.19 ± 47.98 | 38.51 ± 61.60 | 23.84 ± 33.12 | < 0.001 |
| CIRS‐CI, mean ± SD | 4.05 ± 1.67 | 4.00 ± 1.52 | 4.08 ± 1.79 | < 0.001 |
| Pulmonary volumes, mean ± SD | ||||
| VC (% predicted) | 78.5 ± 20.27 | 82.0 ± 20.61 | 73.0 ± 19.49 | 0.094 |
| FVC (% predicted) | 75.94 ± 20.52 | 78.40 ± 20.13 | 73.97 ± 20.74 | 0.013 |
| FEV1 (% predicted) | 78.0 ± 21.64 | 78.0 ± 20.81 | 77.0 ± 22.26 | 0.084 |
| FEV1/FVC ratio (%) | 84.20 ± 9.04 | 85.15 ± 8.57 | 83.41 ± 9.40 | 0.30 |
| TLC (% predicted) | 78.50 ± 17.07 | 83.0 ± 15.48 | 71.0 ± 17.00 | 0.200 |
| Muscle variables | ||||
| Handgrip strength (kg), mean ± SD | 26.49 ± 9.57 | 20.73 ± 5.90 | 30.86 ± 9.52 | 0.016 |
| ASMMI (kg/m2), mean ± SD | 6.51 ± 1.22 | 5.71 ± 0.97 | 7.12 ± 1.02 | < 0.001 |
| Low muscle strength, n (%) | 44 (28.8%) | 13 (8.4%) | 31 (20.1) | 0.03 |
| Low muscle mass, n (%) | 68 (44.4%) | 25 (16.2%) | 43 (27.9%) | 0.16 |
| Sarcopenia prevalence, n (%) | 29 (19.1%) | 10 (15.2%) | 19 (22.1%) | 0.06 |
Note: Descriptive statistics are presented as mean (standard deviation), median (25th–75th percentile) or count (percentages). Pulmonary volumes are % predicted; FEV1/FVC is reported as %.
Abbreviations: ADL, Activities of Daily Living; ASMMI, appendicular skeletal muscle mass index; BMI, body mass index; CIRS‐CI, Cumulative Illness Rating Scale—Comorbidity Index; CF, Cystic Fibrosis; FEV1, forced expiratory volume in 1 s; FEV1/FVC, ratio of FEV1 to FVC; FVC, forced vital capacity; TLC, total lung capacity; VC, vital capacity.
The majority of patients (98.70%) were on immunosuppressive therapy. Of these, 11.7% were on monotherapy, whereas the remaining 87% were receiving a combination of drugs. The most frequently used medications in these combinations included cyclosporine (31.2%), tacrolimus (63.6%), azathioprine (1.3%), everolimus (14.9%) and mycophenolate (79.2%). Additionally, 99.4% of patients were treated with glucocorticoids. The median duration of continuous corticosteroid therapy was significantly longer in patients with CF (p < 0.001).
When examining pulmonary function, there were no significant differences between men and women, except for FVC, which was lower in men [73.97 (20.74) vs. 78.40 (20.13), p = 0.013]. Men tended to have lower levels of muscle strength and muscle mass, although the overall prevalence of sarcopenia did not differ significantly between the sexes. Patients with restrictive lung diseases more often exhibited reduced muscle strength, although there were no significant differences in the rates of reduced muscle mass and sarcopenia across different respiratory conditions (data not shown).
Biochemical analyses revealed that 48% of patients had vitamin D deficiency (with levels below 50 nmol/L). Furthermore, 30 patients presented with hypocalcaemia (serum calcium levels below 2.2 mmol/L), and 55 patients had urinary calcium levels below the normal range (< 2.5 mmol/24 h) (data not shown).
Densitometric values and osteoporosis prevalence (both pre‐ and post‐transplant) are reported in Table 2. Before transplantation, 21.9% of patients were diagnosed with osteoporosis, with a slightly higher prevalence in men than in women (23.9% versus 19.4%, p = 0.01). Additionally, 18.7% of patients were receiving anti‐resorptive therapy, with no significant differences between sexes. Eighteen patients already had known vertebral fractures. Fracture prevalence differed according to some immunosuppressive agents: It was higher among cyclosporine users (35.4% vs. 13.2%; χ2 = 10.14, p = 0.001) and lower among tacrolimus users (13.3% vs. 32.1%; χ2 = 7.90, p = 0.005). No significant differences were observed for everolimus (p = 0.18) or mycophenolate (p = 0.21), whereas azathioprine was used in only two patients, both with events (p = 0.039). After our assessment, it was found that 18.7% of patients had osteopenia and 52.9% had osteoporosis; moreover, men had a higher incidence of vertebral fractures. Overall, 52 patients (33.5%) had at least one vertebral fracture. The percentage of patients treated with anti‐resorptive therapy increased to 71% following the geriatric evaluation, and all patients received calcium and vitamin D supplementation. Considering the underlying lung disease, osteoporosis was more common among patients with CF and restrictive lung disease. However, approximately 46% of patients with obstructive lung disease had at least one vertebral fracture (p = 0.04).
TABLE 2.
Densitometric values and osteoporosis prevalence of the total sample and by sex at baseline.
| Variable | Total (n = 155) | Women (n = 67) | Men (n = 88) | p |
|---|---|---|---|---|
| Pre‐transplant evaluation, n (%) | ||||
| Vitamin D/calcium supplementation | 102 (62.5%) | 48 (72.7%) | 54 (61.4%) | 0.09 |
| Anti‐resorptive therapy | 29 (18.7%) | 9 (13.4%) | 20 (22.7%) | 0.10 |
| Anabolic therapy | 2 (1.3%) | 0 | 2 (2.3%) | 0.45 |
| Osteoporosis diagnosis | 34 (21.9%) | 13 (19.4%) | 21 (23.9%) | 0.01 |
| Post‐transplant evaluation | ||||
| Densitometric values, mean ± SD | ||||
| T‐score lumbar | −1.71 ± 1.41 | −1.73 ± 1.36 | −1.69 ± 1.46 | 0.86 |
| T‐score femur neck | −1.92 ± 1.09 | −2.22 ± 0.94 | −1.70 ± 1.14 | < 0.001 |
| T‐score total hip | −1.53 ± 1.01 | −1.91 ± 0.94 | −1.25 ± 0.98 | < 0.001 |
| BMD lumbar | 0.92 ± 0.49 | 0.94 ± 0.73 | 0.90 ± 0.16 | 0.58 |
| BMD femur neck | 0.92 ± 0.49 | 0.62 ± 0.13 | 0.69 ± 0.15 | < 0.001 |
| BMD total hip | 0.77 ± 0.18 | 0.71 ± 0.14 | 0.83 ± 0.17 | < 0.001 |
| Diagnosis, n (%) | 0.10 | |||
| Osteopenia | 29 (18.7%) | 9 (13.4%) | 20 (22.7%) | |
| Osteoporosis | 82 (52.9%) | 25 (37.3%) | 57 (64.7%) | |
| At least one vertebral fracture, n (%) | 52 (33.5%) | 14 (20.9%) | 38 (43.2%) | 0.005 |
| Anti‐resorptive therapy, n (%) | 109 (70.3%) | 41 (61.2%) | 68 (77.3%) | 0.003 |
| Anabolic therapy, n (%) | 11 (7.1%) | 2 (3.0%) | 9 (10.2%) | 0.003 |
Note: Descriptive statistics are presented as mean (standard deviation), median (25th–75th percentile) or count (percentages).
Abbreviation: BMD, bone mineral density.
3.2. Relationship Between Lung Volumes and Muscle Parameters at Baseline
At baseline, spirometric volumes differed according to muscle status (Figure 1). Patients with low muscle strength, low muscle mass and sarcopenia showed progressively lower values of VC, FVC, FEV1 and TLC compared with those with normal muscle parameters. The lowest spirometric values were consistently observed in patients with sarcopenia.
FIGURE 1.
Spirometric parameters according to muscle variables.
In multivariable linear regression analyses stratified by sex (Table 3), HGS was independently associated with higher VC in both men (β = 0.16, p < 0.001) and women (β = 0.35, p = 0.001). HGS was also associated with higher FVC in men (β = 0.37, p < 0.001) and women (β = 0.33, p = 0.001) and with higher FEV1 in both sexes (men: β = 0.19, p = 0.009; women: β = 0.08, p = 0.020). In men, HGS was additionally associated with higher TLC (β = 0.23, p = 0.005). ASMMI was independently associated with VC in both men (β = 0.16, p = 0.023) and women (β = 0.31, p = 0.003) and with FVC in men (β = 0.16, p = 0.040). All associations remained significant after adjustment for age, functional status, corticosteroid dose, osteoporosis, vertebral fractures, comorbidity burden and time since transplantation.
TABLE 3.
Linear regression analysis for predictors of lung volumes, stratified by gender.
| Men | Women | |||
|---|---|---|---|---|
| Variable | ASMMI | HGS | ASMMI | HGS |
| VC |
R 2: 0.40 β: 0.16, p = 0.023 |
R 2: 0.58 β: 0.16, p < 0.001 |
R2: 0.58 β: 0.31, p = 0.003 |
R 2: 0.63 β: 0.35, p = 0.001 |
| FVC |
R 2: 0.40 β: 0.16, p = 0.040 |
R 2: 0.60 β: 0.37, p < 0.001 |
— |
R 2: 0.60 β: 0.33, p = 0.001 |
| FEV1 | — |
R 2: 0.57 β: 0.19, p = 0.009 |
— |
R 2: 0.51 β: 0.08, p = 0.020 |
| TLC | — |
R 2: 0.54 β: 0.23, p = 0.005 |
— | — |
Note: The table displays the R 2 values, standardized regression coefficients (β), and p‐values for the linear regression models.
Abbreviations: ASMMI, appendicular skeletal muscle mass index; FEV1, forced expiratory volume in 1 s; FVC, forced vital capacity; HGS, handgrip strength test; TLC, total lung capacity; VC, tidal volume.
3.3. Relationship Between Lung Volumes and Muscle Parameters Over Time
The temporal distribution of pulmonary function parameters across follow‐up is illustrated in Figure S1, showing VC, FVC, FEV1 and TLC at 1‐, 2‐ and 3‐year follow‐up. Table 4 presents the results from the longitudinal mixed linear models, which account for repeated measures within subjects, used to assess the association between lung volumes and muscle parameters over time. An inverse relationship was found between ASMMI and FEV1 [β: −4.95, 95% CI (−6.93; 2.97), p = 0.007] as well as TLC [β: −2.22, 95% CI (−4.56; −1.12), p = 0.04] in women with restrictive lung disease. These associations remained significant after adjusting for age, functional abilities, steroid dosage, osteoporosis, presence of vertebral fractures, CIRS‐CI and time since transplantation. In patients with CF, TLC was significantly associated with muscle strength in women [β: 0.38, 95% CI (−0.07; 0.84), p = 0.04] (please see Table S1), also after adjustment for covariates.
TABLE 4.
Linear mixed models for changes in lung volumes over time in patients with restrictive lung disease, stratified by gender.
| Variable | Men | Women | ||||
|---|---|---|---|---|---|---|
| Model 1 | Model 2 | Model 3 | Model 1 | Model 2 | Model 3 | |
| β coefficient (95% CI), p | β coefficient (95% CI), p | β coefficient (95% CI), p | β coefficient (95% CI), p | β coefficient (95% CI), p | β coefficient (95% CI), p | |
| VC | ||||||
| HGS × time | −0.09 (−1.04; 0.84), p = 0.79 | −0.31 (−1.87; 1.24), p = 0.67 | 0.09 (−2.10; 2.29), p = 0.93 | −0.17 (−0.82; 0.48), p = 0.51 | −0.25 (−0.88; 0.39), p = 0.31 | −0.37 (−1.57; 0.83), p = 0.20 |
| ASMMI × time | −0.001 (−3.12; 3.12), p = 0.99 | −0.40 (−4.80; 4.01), p = 0.84 | 1.40 (−4.44; 7.24), p = 0.61 | −1.17 (−4.85; 2.51), p = 0.43 | −0.79 (−5.10; 3.52), p = 0.61 | −1.07 (−7.28; 5.14), p = 0.58 |
| FVC | ||||||
| HGS × time | −0.35 (−1.39; 0.68), p = 0.41 | −0.53 (−2.22; 1.17), p = 0.51 | −0.07 (−2.60; 2.45), p = 0.95 | −0.05 (−0.88; 0.78), p = 0.88 | −0.18 (−0.89; 0.52), p = 0.48 | −0.11 (−1.12; 0.89), p = 0.73 |
| ASMMI × time | −0.57 (−4.16; 3.01), p = 0.68 | −0.98 (−5.80; 3.85), p = 0.66 | 1.01 (−5.66; 7.68), p = 0.74 | −2.78 (−5.90; 0.34), p = 0.07 | −2.17 (−4.96; 0.63), p = 0.09 | −2.37 (−6.52; 1.78), p = 0.14 |
| FEV1 | ||||||
| HGS × time | −0.20 (−1.88; 1.48), p = 0.77 | −0.08 (−2.52; 2.36), p = 0.94 | −0.88 (−3.48; 1.70), p = 0.46 | 0.12 (−1.16; 1.40), p = 0.82 | −0.02 (−1.33; 1.29), p = 0.97 | 0.20 (−1.22; 1.62), p = 0.71 |
| ASMMI × time | 0.78 (−4.80; 6.36), p = 0.73 | 0.27 (−6.71; 7.26), p = 0.93 | −1.81 (−9.38; 5.75), p = 0.60 | −5.63 (−7.89; −3.37), p = 0.002 | −5.12 (−6.75; −3.50), p = 0.002 | −4.95 (−6.93; 2.97), p = 0.007 |
| TLC | ||||||
| HGS × time | 0.16 (−0.45; 0.76), p = 0.52 | −0.18 (−1.28; 0.89), p = 0.70 | 0.07 (−1.63; 1.77), p = 0.93 | −0.21 (−0.72; 0.30), p = 0.32 | −0.22 (−0.88; 0.45), p = 0.38 | −0.06 (−0.73; 0.61), p = 0.80 |
| ASMMI × time | 0.46 (−1.56; 2.48), p = 0.56 | −1.03 (−3.93; 1.87), p = 0.46 | −0.82 (−5.36; 3.63), p = 0.70 | −2.02 (−3.97; −0.09), p = 0.02 | −2.28 (−4.34; −0.21), p = 0.04 | −2.22 (−4.56; −1.12), p = 0.04 |
Note: Model 1 includes age. Model 2 also includes functional capacities and steroid dosage. Model 3 includes the presence of vertebral fractures, CIRS‐CI and time since transplant. Significant results (p < 0.05) are shown in bold.
Abbreviations: ASMMI, appendicular skeletal muscle mass index; FEV1, forced expiratory volume in 1 s; FVC, forced vital capacity; HGS, handgrip strength test; TLC, total lung capacity; VC, tidal volume.
4. Discussion
This is the first study to examine over a period of 3 years the association between muscle parameters and respiratory function. Muscle mass was found to be significantly associated with lung volumes such as TLC and FEV1 in women with restrictive lung disease, whereas muscle strength was associated with TLC in patients with CF. The magnitude of these associations was modest, which is expected given the complex and multifactorial nature of lung function after lung transplantation. Nevertheless, these findings highlight the clinical relevance of muscle assessment in lung transplant recipients, even after accounting for vertebral fractures, time since transplantation and corticosteroid exposure.
In patients undergoing lung transplantation, several conditions can lead to the development of osteoporosis, largely due to the immunosuppressive therapy regimen—which includes glucocorticoids, calcineurin inhibitors, selective mTOR inhibitors, mycophenolate or azathioprine [16]. Glucocorticoids act, for example, through a direct mechanism by promoting the differentiation, activation and survival of osteoclasts [17, S12], as well as through an indirect mechanism by inhibiting the synthesis of gonadal steroids and reducing calcium transport across intestinal, renal tubular, parathyroid cell membranes and hypothalamic membranes of the pituitary–gonadal axis [18, S13]. The percentage of patients with osteoporosis in our study is consistent with previously reported data (please see references S14 and S15), particularly among people with obstructive diseases (please see references S16–S18). It is known that osteoporosis can have significant impacts on respiratory health. The altered conformation of the rib cage associated with vertebral fractures could compromise the amount of air contained in the lungs and the amount that can be forcibly exhaled after taking the deepest breath possible (please see reference S19). For this reason, patients undergoing lung transplantation are often subjected to a comprehensive osteometabolic evaluation to facilitate the early identification of this condition.
In addition to bone metabolism, muscle health is also frequently compromised in these patients. Retrospective studies conducted on lung transplant candidates documented a decrease in lean mass in patients with COPD and interstitial lung diseases and in individuals with CF (please see references S20 and S21). To date, the aetiology of muscle mass and strength loss in these patients is still not fully understood. Factors such as physical inactivity, weight loss, inflammatory cytokines, inadequate caloric/protein intake, oxidative stress and reduced blood flow to the muscles are certainly common characteristics associated with both loss of skeletal muscle and diseases that cause chronic respiratory failure, contributing to the development of so‐called secondary sarcopenia [15, 19]. Moreover, drugs like glucocorticoids, cyclosporine and tacrolimus are known for their catabolic effects on muscles, contributing to reduced protein synthesis and increased muscle degradation [16]. In our study, 29% of participants exhibited a decrease in muscle strength, whereas 44% showed a reduction in muscle mass, results consistent with previous studies [20]. We observed that the reduction in muscle strength was significantly greater in men, whereas there were no significant sex‐differences regarding muscle mass. These findings contrast with those of Nikkuni et al. [21], who reported a higher prevalence of sarcopenia in women post‐transplant. This discrepancy may be explained by the generally older age of the male sample compared to the female sample in our study. The literature agrees that good muscle performance is associated with better spirometric parameters: Feng et al. found that lean mass is positively correlated with FVC and FEV1 in healthy adults [22]. Son et al. documented that FVC and FEV1 increase progressively with improved grip strength in older patients [23], whereas Attaway et al. observed that pectoral muscle cross‐sectional area is positively associated with FEV1, FVC and the FEV1/FVC ratio in COPD patients [24]. These results highlight the negative impact that loss of muscle mass can have on pulmonary function. Indeed, inspiration, a key component of the breathing process, relies on the diaphragm and inspiratory muscles, with lung volumes such as VC, FVC, FEV1 and TLC depending on this mechanism. Our results support this, showing that at baseline, muscle strength is an independent predictor of VC, FVC, FEV1 and TLC in men, whereas appendicular lean mass is an independent predictor of VC in both sexes.
Beyond the muscle–lung physiology, unmeasured factors such as habitual physical activity and participation in structured rehabilitation could favourably influence muscle strength and, indirectly, ventilatory performance. In lung transplant recipients, exercise‐based pulmonary rehabilitation consistently improves exercise capacity (e.g., 6‐min walk distance and peak VO2) and muscle function, with supportive evidence from systematic reviews and meta‐analyses as well as randomized and controlled studies [25, 26]. However, the content, intensity and long‐term maintenance of muscle‐focused components vary substantially across rehabilitation programmes and clinical settings. Moreover, targeted inspiratory muscle training (often integrated within rehabilitation) can augment respiratory muscle performance and further enhance functional outcomes in this population [27]. Notably, observational work shows that many recipients remain insufficiently active months after transplantation, suggesting that effective muscle‐focused rehabilitation may not be uniformly implemented or sustained and underscoring the potential for differential exposure to activity/rehabilitation to confound associations between muscle parameters and lung volumes [28]. Unfortunately, detailed data on physical activity and rehabilitation adherence were not available in our cohort; future studies incorporating these measures are warranted to disentangle their mediating and confounding effects.
A major limitation of the existing literature on these topics is that studies have predominantly focused on the immediate post‐transplant period, without providing evidence on how muscle parameters might affect respiratory volumes over time. Our study is pioneering in evaluating, over a period of 3 years, the association between muscle mass and strength and respiratory volumes. Our results demonstrate a negative relationship between appendicular lean mass and volumes such as TLC and FEV1 in women with restrictive lung diseases, even after adjusting for factors such as the presence of osteoporosis and severe osteoporosis, corticosteroid dosage and time since transplantation. Several explanations might account for these seemingly paradoxical findings. Firstly, it is plausible that pulmonary volumes improve relatively quickly after transplantation, whereas the recovery of muscle mass is a much slower process. This discrepancy could explain why improvements in pulmonary volumes do not immediately correlate with an increase in muscle mass. Another possible explanation involves compensatory mechanisms. As pulmonary function improves, patients may rely less on accessory respiratory muscles, which were previously overused. This reduction in the reliance on these muscles could lead to some degree of atrophy, as they are no longer subjected to the same level of stress. Conversely, we observed a direct association between muscle strength and TLC values in patients with CF over time. This finding has several important implications. First, because exercise performance in CF patients is often limited by pulmonary function, stronger respiratory muscles may enhance exercise tolerance, potentially helping to maintain or even improve pulmonary function over time. This suggests that interventions aimed at improving respiratory muscle strength could have significant benefits for both pulmonary function and exercise capacity [29]. Furthermore, nutritional status is crucial for supporting muscle strength [30], which is necessary for effective breathing and the maintenance of lung volumes such as TLC. Accordingly, adequate nutritional intake is considered a cornerstone of care in lung transplant patients. Current evidence and practical guidelines underline that nutritional support should begin early, particularly when oral intake cannot meet ≥ 60% of estimated energy/protein needs [31, 32]. Indeed, in lung transplantation, the metabolic burden from surgery, immunosuppression, corticosteroids and catabolic stress requires proactive nutritional strategies [33]. In clinical practice, this means formal integration of dietitians into the transplant team, scheduled reassessments of protein–calorie adequacy (especially in the first year) and prompt escalation to supplements or enteral nutrition (or additional strategies) when deficits emerge. Implementing standardized nutrition protocols across centres could help optimize muscle mass recovery, mitigate bone loss and potentially improve long‐term pulmonary–muscle–bone interactions [34]. Although the present study did not intervene nutritionally, our findings underscore that metabolic and musculoskeletal health must remain a therapeutic target alongside immunologic and pulmonary care.
Beyond these mechanistic considerations, the observed sex‐specific patterns may also reflect differences in disease distribution, muscle biology and exposure to risk‐modifying factors. In our cohort, women were more frequently affected by CF, whereas men more often presented with obstructive diseases, a distribution that can shape distinct muscle–lung trajectories and rehabilitation needs. Accordingly, the lower muscle mass observed in men in this cohort should not be interpreted as reflecting sex‐related hormonal mechanisms, as men generally exhibit greater muscle mass than women in the general population. Sex differences in respiratory physiology—including lung and airway size–function relationships and the work of breathing—are well documented and may interact with muscle status to influence spirometric volumes [35]. Importantly, hormonal influences relevant to skeletal muscle are not limited to menopause: Oestrogens modulate satellite cell activity, mitochondrial function and muscle repair, whereas androgens exert anabolic effects on muscle protein synthesis; such pathways can differentially affect muscle quantity and quality in women and men across adulthood [36, 37, 38]. In CF specifically, female sex hormones have been implicated in disease expression (e.g., effects on airway surface liquid, mucociliary clearance, infection and inflammation), potentially contributing to sex‐related differences in functional trajectories after transplant [39]. Moreover, sex differences in inspiratory muscle characteristics (e.g., fatigability profiles) have been reported and could partly modulate the coupling between appendicular muscle status and lung volumes [40].
4.1. Limitations and Strengths
Among the limitations of our study is the heterogeneity of the sample in terms of age, underlying pathology and time since transplantation—factors that may differentially influence both bone and muscle mass. The limited sample size within each diagnostic subgroup also prevented more refined stratified analyses, which might have provided additional insights, and the single‐centre design may limit generalizability to other settings. In addition, data on pre‐transplant body composition as well as on patients' physical activity levels and participation in rehabilitation programs were not available. A major strength of this study is the comprehensive 3‐year follow‐up, which allowed a longitudinal evaluation of the relationship between muscle parameters and lung function in lung transplant recipients. Another strength is the comprehensive clinical characterization of the cohort, including bone health, vertebral fractures, corticosteroid exposure and comorbidity burden, allowing for extensive adjustment of potential confounders.
4.2. Conclusions
In conclusion, our study highlights the importance of muscle mass and strength in the respiratory function of lung transplant patients. Lower appendicular lean mass is associated with high respiratory volumes in women with restrictive lung diseases, suggesting that muscle recovery may be slower compared to improvements in pulmonary function and underscoring the need for greater focus on muscle rehabilitation during the post‐operative period. On the contrary, in patients with CF, increased muscle strength is correlated with better lung volumes over time, indicating that strengthening respiratory muscles could also support pulmonary function. We hope that this study encourages further research, ideally with more homogeneous samples and more comprehensive data collection, to further explore the relationship between muscle mass and respiratory function.
Funding
The authors have nothing to report.
Ethics Statement
The study was conducted in strict adherence to the ethics statement of the International Society for Heart and Lung Transplantation (ISHLT). The study protocol received approval from the local ethics committee (Comitato Etico di Padova, number 0014675) and complied with the guidelines outlined in the Declaration of Helsinki.
Consent
Informed consent was obtained from all subjects involved in the study. Written informed consent has been obtained from the patients to publish this paper.
Conflicts of Interest
The authors declare no conflicts of interest.
Supporting information
Figure S1: Violin plots showing the distribution of pulmonary function parameters over time.
Table S1: Linear mixed models for changes in lung volumes over time in patients with cystic fibrosis, stratified by gender.
Acknowledgements
Open access publishing facilitated by Universita degli Studi di Padova, as part of the Wiley ‐ CRUI‐CARE agreement.
Data Availability Statement
All data generated or analysed during this study are included in this published article (and its Supporting Information).
References
- 1. Bos S., Vos R., Van Raemdonck D. E., and Verleden G. M., “Survival in Adult Lung Transplantation: Where Are We in 2020?,” Current Opinion in Organ Transplantation 25 (2020): 268–273, 10.1097/MOT.0000000000000753. [DOI] [PubMed] [Google Scholar]
- 2. Muschitz C., Zwick R. H., Haschka J., et al., “Osteoporosis in Pneumological Diseases: Joint Guideline of the Austrian Society for Bone and Mineral Research (ÖGKM) and the Austrian Society for Pneumology (ÖGP),” Wiener Klinische Wochenschrift 133, no. Suppl 4 (2021): 155–173, 10.1007/s00508-021-01896-x. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 3. Cairoli E., Eller‐Vainicher C., Morlacchi L. C., et al., “Bone Involvement in Young Adults With Cystic Fibrosis Awaiting Lung Transplantation for End‐Stage Respiratory Failure,” Osteoporosis International 30 (2019): 1255–1263, 10.1007/s00198-019-04893-z. [DOI] [PubMed] [Google Scholar]
- 4. Morley J. E., “Pharmacologic Options for the Treatment of Sarcopenia,” Calcified Tissue International 98 (2016): 319–333, 10.1007/s00223-015-0022-5. [DOI] [PubMed] [Google Scholar]
- 5. Byun M. K., Cho E. N., Chang J., Ahn C. M., and Kim H. J., “Sarcopenia Correlates With Systemic Inflammation in COPD,” International Journal of COPD 12 (2017): 669–675, 10.2147/COPD.S130790. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 6. Harrison R. A., Siminoski K., Vethanayagam D., and Majumdar S. R., “Osteoporosis‐Related Kyphosis and Impairments in Pulmonary Function: A Systematic Review,” Journal of Bone and Mineral Research 22, no. 3 (2007): 447–457, 10.1359/JBMR.061202. [DOI] [PubMed] [Google Scholar]
- 7. Williams K. M., Darukhanavala A., Hicks R., and Kelly A., “An Update on Methods for Assessing Bone Quality and Health in Cystic Fibrosis,” Journal of Clinical & Translational Endocrinology 27 (2022): 100281, 10.1016/j.jcte.2021.100281. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 8. Gomes A., Hutcheon D., and Ziegler J., “Association Between Fat‐Free Mass and Pulmonary Function in Patients With Cystic Fibrosis: A Narrative Review,” Nutrition in Clinical Practice 34 (2019): 715–727, 10.1002/ncp.10251. [DOI] [PubMed] [Google Scholar]
- 9. Swallow E. B., Reyes D., Hopkinson N. S., et al., “Quadriceps Strength Predicts Mortality in Patients With Moderate to Severe Chronic Obstructive Pulmonary Disease,” Thorax 62, no. 2 (2007): 115–120, 10.1136/thx.2006.062026. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 10. Hesselberg L. M., Kyvsgaard J. N., Stokholm J., Bisgaard H., Bønnelykke K., and Chawes B., “Handgrip Strength Associates With Effort‐Dependent Lung Function Measures Among Adolescents With and Without Asthma,” Scientific Reports 13, no. 1 (2023): 13044, 10.1038/s41598-023-40320-4. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 11. Han C. H. and Chung J. H., “Association Between Hand Grip Strength and Spirometric Parameters: Korean National Health and Nutrition Examination Survey (KNHANES),” Journal of Thoracic Disease 10, no. 11 (2018): 6002–6009, 10.21037/jtd.2018.10.09. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 12. Guler S. A., Hur S. A., Lear S. A., Camp P. G., and Ryerson C. J., “Body Composition, Muscle Function, and Physical Performance in Fibrotic Interstitial Lung Disease: A Prospective Cohort Study,” Respiratory Research 20, no. 1 (2019): 56, 10.1186/s12931-019-1019-9. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 13. Strandkvist V. J., Backman H., Röding J., Stridsman C., and Lindberg A., “Hand Grip Strength Is Associated With Forced Expiratory Volume in 1 Second Among Subjects With COPD: Report From a Population‐Based Cohort Study,” International Journal of Chronic Obstructive Pulmonary Disease 11 (2016): 2527–2534, 10.2147/COPD.S114154. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 14. Cruz‐Jentoft A. J., Baeyens J. P., Bauer J. M., et al., “Sarcopenia: European Consensus on Definition and Diagnosis: Report of the European Working Group on Sarcopenia in Older People,” Age and Ageing 39, no. 4 (2010): 412–423, 10.1093/ageing/afq034. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 15. Cruz‐Jentoft A. J., Bahat G., Bauer J., et al., “Sarcopenia: Revised European Consensus on Definition and Diagnosis,” Age and Ageing 48, no. 1 (2019): 16–31, 10.1093/AGEING/AFY169. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 16. Goswami R., “Primer on the Metabolic Bone Diseases and Disorders of Mineral Metabolism,” Indian Journal of Medical Research 144, no. 3 (2016): 489–490, 10.4103/0971-5916.198664. [DOI] [Google Scholar]
- 17. O'Brien C. A., Jia D., Plotkin L. I., et al., “Glucocorticoids Act Directly on Osteoblasts and Osteocytes to Induce Their Apoptosis and Reduce Bone Formation and Strength,” Endocrinology 145, no. 4 (2004): 1835–1841, 10.1210/en.2003-0990. [DOI] [PubMed] [Google Scholar]
- 18. Bonadonna S., Burattin A., Nuzzo M., et al., “Chronic Glucocorticoid Treatment Alters Spontaneous Pulsatile Parathyroid Hormone Secretory Dynamics in Human Subjects,” European Journal of Endocrinology 152 (2005): 199–205, 10.1530/eje.1.01841. [DOI] [PubMed] [Google Scholar]
- 19. Marty E., Liu Y., Samuel A., Or O., and Lane J., “A Review of Sarcopenia: Enhancing Awareness of an Increasingly Prevalent Disease,” Bone 105 (2017): 276–286, 10.1016/j.bone.2017.09.008. [DOI] [PubMed] [Google Scholar]
- 20. Kyle U. G., Nicod L., Raguso C., Hans D., and Pichard C., “Prevalence of Low Fat‐Free Mass Index and High and Very High Body Fat Mass Index Following Lung Transplantation,” Acta Diabetologica 40, no. Suppl 1 (2003): S258–S260, 10.1007/s00592-003-0080-4. [DOI] [PubMed] [Google Scholar]
- 21. Nikkuni E., Hirama T., Hayasaka K., et al., “Recovery of Physical Function in Lung Transplant Recipients With Sarcopenia,” BMC Pulmonary Medicine 21, no. 1 (2021): 1–10, 10.1186/s12890-021-01442-5. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 22. Fu K., Lu C., Sun Y. Z., Hu S. M., and Zhu G. J., “Fat Mass and Fat Free Mass on Ventilatory Function in Adults,” Sheng Li Xue Bao 62, no. 2 (2010): 122–128. [PubMed] [Google Scholar]
- 23. Shin D. H., Yoo J. W., Choi M. R., and Lee Y. J., “Relationship Between Handgrip Strength and Pulmonary Function in Apparently Healthy Older Women,” Journal of the American Geriatrics Society 66, no. 7 (2018): 1367–1371, 10.1111/JGS.15410. [DOI] [PubMed] [Google Scholar]
- 24. Attaway A. H., Welch N., Yadav R., et al., “Quantitative Computed Tomography Assessment of Pectoralis and Erector Spinae Muscle Area and Disease Severity in Chronic Obstructive Pulmonary Disease Referred for Lung Volume Reduction,” COPD: Journal of Chronic Obstructive Pulmonary Disease 18, no. 2 (2021): 191–200, 10.1080/15412555.2021.1897560. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 25. Abidi Y., Kovats Z., Bohacs A., et al., “Lung Transplant Rehabilitation – A Review,” Life (Basel) 13, no. 2 (2023): 506, 10.3390/life13020506. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 26. Wang P., Gao B., Wang S., et al., “Effectiveness of Pulmonary Rehabilitation on Exercise Capacity in Adult Patients With Lung Transplantation: A Systematic Review and Single‐Arm Meta‐Analysis,” Journal of Thoracic Disease 16, no. 9 (2024): 5727–5741, 10.21037/jtd-24-568. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 27. Pehlivan E., Mutluay F., Balcı A., and Kılıç L., “The Effects of Inspiratory Muscle Training on Exercise Capacity, Dyspnea and Respiratory Functions in Lung Transplantation Candidates: A Randomized Controlled Trial,” Clinical Rehabilitation 32, no. 10 (2018): 1328–1339, 10.1177/0269215518777560. [DOI] [PubMed] [Google Scholar]
- 28. Wickerson L., Mathur S., Singer L. G., and Brooks D., “Physical Activity Levels Early After Lung Transplantation,” Physical Therapy 95, no. 4 (2015): 517–525, 10.2522/ptj.20140173. [DOI] [PubMed] [Google Scholar]
- 29. Sovtic A., Minic P., Markovic‐Sovtic G., and Trajkovic G. Z., “Respiratory Muscle Strength and Exercise Performance in Cystic Fibrosis–A Cross Sectional Study,” Frontiers in Pediatrics 6 (2018): 244, 10.3389/fped.2018.00244. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 30. Ceolin C., Acunto V., Simonato C., et al., “New Perspectives in the Association Between Anthropometry and Mortality: The Role of Calf Circumference,” Journal of Frailty & Aging 13 (2024): 108–115, 10.14283/jfa.2024.4. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 31. Weimann A., Braga M., Harsanyi L., et al., “ESPEN Guidelines on Enteral Nutrition: Surgery Including Organ Transplantation,” Clinical Nutrition 25, no. 2 (2006): 224–244, 10.1016/j.clnu.2006.01.015. [DOI] [PubMed] [Google Scholar]
- 32. Weimann A., Braga M., Carli F., et al., “ESPEN Practical Guideline: Clinical Nutrition in Surgery,” Clinical Nutrition 40, no. 7 (2021): 4745–4761, 10.1016/j.clnu.2021.03.031. [DOI] [PubMed] [Google Scholar]
- 33. Jomphe V., Lands L. C., and Mailhot G., “Nutritional Requirements of Lung Transplant Recipients: Challenges and Considerations,” Nutrients 10, no. 6 (2018): 790, 10.3390/nu10060790. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 34. Weber Gulling M., Schaefer M., Bishop‐Simo L., and Keller B. C., “Optimizing Nutrition Assessment to Create Better Outcomes in Lung Transplant Recipients: A Review of Current Practices,” Nutrients 11, no. 12 (2019): 2884, 10.3390/nu11122884. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 35. LoMauro A. and Aliverti A., “Sex Differences in Respiratory Function,” Breathe (Sheffield, England) 14, no. 2 (2018): 131–140, 10.1183/20734735.000318. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 36. Pellegrino A., Tiidus P. M., and Vandenboom R., “Mechanisms of Estrogen Influence on Skeletal Muscle: Mass, Regeneration, and Mitochondrial Function,” Sports Medicine 52, no. 12 (2022): 2853–2869, 10.1007/s40279-022-01733-9. [DOI] [PubMed] [Google Scholar]
- 37. Howard E. E., Shankaran M., Evans W. J., et al., “Effects of Testosterone on Mixed‐Muscle Protein Synthesis and Proteome Dynamics During Energy Deficit,” Journal of Clinical Endocrinology and Metabolism 107, no. 8 (2022): e3254–e3263, 10.1210/clinem/dgac295. [DOI] [PubMed] [Google Scholar]
- 38. Jomard C. and Gondin J., “Influence of Sexual Dimorphism on Satellite Cell Regulation and Inflammatory Response During Skeletal Muscle Regeneration,” Physiological Reports 11, no. 19 (2023): e15798, 10.14814/phy2.15798. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 39. Lam G. Y., Goodwin J., Wilcox P. G., and Quon B. S., “Sex Disparities in Cystic Fibrosis: Review on the Effect of Female Sex Hormones on Lung Pathophysiology and Outcomes,” ERJ Open Research 7, no. 1 (2021): 00475‐2020, 10.1183/23120541.00475-2020. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 40. Gonzales J. U. and Scheuermann B. W., “Gender Differences in the Fatigability of the Inspiratory Muscles,” Medicine and Science in Sports and Exercise 38, no. 3 (2006): 472–479, 10.1249/01.mss.0000189318.80061.fe. [DOI] [PubMed] [Google Scholar]
Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Supplementary Materials
Figure S1: Violin plots showing the distribution of pulmonary function parameters over time.
Table S1: Linear mixed models for changes in lung volumes over time in patients with cystic fibrosis, stratified by gender.
Data Availability Statement
All data generated or analysed during this study are included in this published article (and its Supporting Information).