Reference Values for the 1-Minute Sit-to-Stand test to Assess Functional Capacity and Short- Term Mortality in People with Fibrotic Interstitial Lung Diseases: A Prospective Real-World Cohort Study

Reference Values for the 1-Minute Sit-to-Stand test to Assess Functional Capacity and Short- Term Mortality in People with Fibrotic Interstitial Lung Diseases: A Prospective Real-World Cohort Study | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Reference Values for the 1-Minute Sit-to-Stand test to Assess Functional Capacity and Short- Term Mortality in People with Fibrotic Interstitial Lung Diseases: A Prospective Real-World Cohort Study Meng-Yun Tsai, Kuo-Tung Huang, Chiann-Yi Hsu, Yi-Hsuan Yu, Pin-Kuei Fu This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4931729/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 04 Feb, 2025 Read the published version in BMC Pulmonary Medicine → Version 1 posted 4 You are reading this latest preprint version Abstract Background: Early diagnosis of functional decline in fibrotic interstitial lung disease (F-ILD) is crucial for timely treatment and improved survival. While the 6-minute walk test (6MWT) is the gold standard for functional evaluation, it has limitations. The 1-minute sit-to-stand test (1MSTS) is easier to administer, but its correlation with the 6MWT in F-ILD patients is unclear. This study aims to evaluate the reference values of 1MSTS to assess functional capacity, 6-month mortality and its correlation with the 6MWT in F-ILD patients. Methods: This prospective study included subjects diagnosed with F-ILD through multidisciplinary team discussions. Assessments included the 1MSTS, 6MWT, pulmonary function test (PFT), GAP score, mMRC scale, and Charlson Comorbidity Index (CCI). The association between 1MSTS repetitions and variables was calculated using Spearman's rho. Bland-Altman plots assessed the agreement between 1MSTS repetitions and the 6MWT. ROC curve analysis evaluated predictors for 6-month mortality. Results: Of the 150 F-ILD patients, 37 (24.6%) had idiopathic pulmonary fibrosis (IPF), and 113 (75.4%) had connective tissue disease-related ILD (CTD-ILD). Using ≤ 20 repetitions as the cutoff for functional impairment, 36 (24.0%) patients were classified as impaired. The 6MWT distance significantly predicted 6-month mortality. Although the 1MSTS did not significantly predict 6-month survival, it showed strong correlations with GAP score (rs = -0.49, p < 0.001), mMRC scale (rs = -0.47, p < 0.001), and 6MWT distance (rs = 0.65, p < 0.001). Bland-Altman analysis showed agreement between 1MSTS repetitions and 6MWT distance. An AUC of 0.856 was achieved for predicting < 300 meters for the 6MWT distance by using ≤ 20 repetitions as the cutoff value for the 1MSTS. Conclusions: The findings suggest that ≤ 20 repetitions in the 1MSTS can be used as an indicator of functional impairment and has a good correlation with 6MWT distance, GAP score, and mMRC scale in assessing patients with F-ILD. Fibrotic interstitial lung disease 1-minute sit-to-stand test (1MSTS) 6-minute walk test (6MWT) Short-term mortality Functional assessment Figures Figure 1 Figure 2 Figure 3 Background Interstitial lung disease (ILD) is a heterogeneous group of disorders characterized by interstitial inflammation or fibrosis of the lungs, leading to decreased lung function and impaired gas exchange 1 , 2 . Early diagnosis of functional decline in fibrotic interstitial lung disease (F-ILD) is crucial for timely treatment and improved survival 3 . Among the subtypes of F-ILD, idiopathic pulmonary fibrosis (IPF) and connective tissue disease-related interstitial lung disease (CTD-ILD) are frequently diagnosed 4 . The progression of F-ILD is marked by progressive scarring of lung tissue, resulting in a decline in respiratory function and overall health 5 . The 6-minute walk test (6MWT) is widely recognized as the gold standard for functional evaluation in chronic heart failure 6 , pulmonary artery hypertension 7 and F-ILD 8 patients due to its ability to assess exercise tolerance and predict outcomes. Our recent publications also show that 6MWT can also identify patients who experience desaturation during exertion and predict outcomes based on the distance walked in six minutes 9 , 10 . However, the 6MWT has practical limitations, including the need for a long, unobstructed walking course and the physical capability of the patient to complete the test 11 . Furthermore, the 6MWT can be influenced by factors unrelated to pulmonary status, such as peripheral arterial disease, muscular strength, cognitive function, and nutritional status 12 , 13 . Therefore, it is important to find an alternative method to detect functional decline that is more accessible and feasible in various settings. The 1-minute sit-to-stand test (1MSTS) is a simple and quick assessment that requires only a chair and can be completed in a short time 14 . This test measures the number of times a patient can stand from a seated position within one minute, reflecting lower body strength and endurance 15 . Research has demonstrated a good correlation between the 1MSTS and exercise capacity in patients with chronic obstructive pulmonary disease (COPD) 16 , pulmonary artery hypertension 17 , and interstitial lung disease 18 . The 1MSTS is easier to administer and does not require the space or time needed for the 6MWT, making it a more practical option in many clinical settings. However, the correlation between 1MSTS and the 6MWT in F-ILD patients, and whether the 1MSTS can predict short-term mortality, remains unclear. Few studies have addressed this issue, and their findings are inconclusive due to limited case numbers, retrospective and varied study designs 18 – 20 . Establishing this correlation could validate the 1MSTS as a reliable alternative to the 6MWT for functional assessment in F-ILD, providing a more accessible method for evaluating patient condition and monitoring disease progression. The aim of the current study is to investigate the diagnostic value of the 1MSTS in predicting short-term mortality and its correlation with the 6MWT. Short-term mortality is defined as death occurring within six months following the performance of the 1MSTS and 6MWT. Method Study design, patient enrollment, and ethics The current data is derived from a subgroup analysis of a prospective, single-center, real-world registry study conducted at an ILD referral medical center in central Taiwan. The Registry of Interstitial Lung Disease (REGILD) has been enrolling both IPF and non-IPF populations since December 28, 2018. Diagnoses were confirmed through multidisciplinary team discussions (MDD) involving pulmonologists, rheumatologists, radiologists, and pathologists. Utilizing the REGILD cohort, several studies have been published exploring prognostic factors 9 , 10 , 21 – 23 . In the current study, we enrolled patients over 20 years of age diagnosed with F-ILD who had completed evaluations of the 6MWT and 1MSTS between November 1, 2022, and June 30, 2023. Patients were excluded if they did not complete the 1MSTS, 6MWT, or pulmonary function test, or if they were diagnosed with ILD other than IPF or CTD-ILD after MDD. This study was conducted in compliance with the Declaration of Helsinki and was approved by the Ethics Committee of Taichung Veterans General Hospital (IRB number: CE18325B; date of approval: December 18, 2018). ILD assessment protocol in the REGILD registry cohort Baseline clinical characteristics, including age, gender, smoking history, body mass index, physical examination findings, and comorbidities, were recorded on the day of enrollment. The follow-up protocol included pulmonary function tests (PFT) and the 1-minute sit-to-stand test (1MSTS) every six months. Additionally, patients underwent high-resolution computed tomography (HRCT) and cardiopulmonary exercise testing (CPET) at enrollment and annually. Questionnaires, such as the modified medical research council (mMRC) score, 36-Item Short Form Survey (SF-36), St. George's Respiratory Questionnaire (SGRQ), and the gender-age-physiology (GAP) index, were also evaluated at enrollment and annually. The comorbidities of enrolled patients were summarized using the Charlson Comorbidity Index (CCI) 24 . PFT, 6MWT and IMSTS procedure Forced vital capacity (FVC) and DLCO were obtained from spirometry results according to the recommendations of the American Thoracic Society (ATS) 25 . The 6-minute walk test (6MWT) was performed in accordance with ATS guidelines 13 . Patients were instructed to walk as far as possible in six minutes in a corridor between two orange traffic cones placed 30 meters apart. Data on oxygen saturation, including resting SpO2, nadir SpO2, exercise SpO2, and the walking distance in six minutes, were recorded. The 1-minute sit-to-stand test (1MSTS) was performed as described in a previous study 26 , using a standard height chair (46 cm) without armrests positioned against a wall. SaO2, heart rate, and modified Borg scale 27 measurements before and after the test, as well as the number of 1MSTS repetitions, were recorded. Statistical analysis Data are expressed as median (interquartile range, IQR) unless otherwise stated. Categorical variables were analyzed using the chi-squared test or Fisher’s exact test, as appropriate. Continuous variables were compared using the Mann–Whitney U test. Spearman's rho was calculated to measure the strength and direction of the association between 1MSTS repetitions and different parameters across the entire cohort. The Bland-Altman plot was used to assess the agreement between 1MSTS repetitions and the 6MWT. Receiver Operating Characteristic (ROC) curve analysis was conducted to evaluate predictors of 6-month mortality. Data analysis was performed using IBM SPSS software version 21.0 and MedCalc Software version 22.023. A two-sided p-value of < 0.05 was considered statistically significant. Result Baseline characteristics and the performance of IMSTS and 6MWT One hundred and ninety-three patients diagnosed with F-ILD who underwent evaluations of the 6MWT and 1MSTS between November 1, 2022, and June 30, 2023, were initially enrolled. We excluded 33 patients who were not classified as having IPF or CTD-ILD and 10 patients who had missing data or failed to complete the 6MWT and the 1MSTS. Consequently, a total of 150 patients were included in the final analysis (Figure. 1). The baseline characteristics of this cohort showed a median age of 64.5 years (IQR: 56.8–71.3), with 57.7% being female and 64% being non-smokers. The classification of F-ILD at enrollment included CTD-ILD (n = 113, 75.3%) and IPF (n = 37, 24.7%) (Table 1 ). Table 1 shows that the median number of repetitions in the 1MSTS was 24 (IQR: 20–31). Using ≤ 20 repetitions as the cutoff, 24% (36 out of 150) of patients were classified as functionally impaired. The 6MWT demonstrated a median distance of 421.5 meters (IQR: 323.8-495.3), with resting, exercise and nadir oxygen saturation levels at 96% (IQR: 95–98), 91% (IQR: 86.5–94), and 89% (IQR: 83–92), respectively. Short-term mortality, defined as death within six months following the 1MSTS and 6MWT examinations, occurred in 6 out of 150 patients (4.0%). Factors Associated with Patients Alive or Deceased Within Six Months Following the 1MSTS and 6MWT Examinations As seen in Table 2, epidemiological indicators such as smoking status (83.33% vs. 34.03%, p = 0.023), clubbing fingers (83.33% vs 26.39%, p = 0.008), and mMRC scores (1.50 vs. 0, p < 0.001) show statistically significant differences between those who survived and those who died within six months. Even though the number of deaths within six months in this study was only six, we found statistically significant differences in the 1MSTS-related indicators. The deceased group had lower pre-exercise SaO2 levels (94.0% vs. 96.0%, p = 0.006) and lower post-exercise SaO2 levels (88.5% vs. 93.5%, p = 0.044), as well as higher pre-exercise Borg Scale scores (3 vs. 0, p = 0.008) and higher post-exercise Borg Scale scores (5.50 vs. 3, p = 0.042) compared to the survival group (Table 2). Among the 6MWT indicators, although the deceased group had lower resting SpO2, exercise SpO2, and nadir SpO2 levels, these differences were not statistically significant compared to the survival group. The only indicator in the 6MWT that showed a statistically significant difference was the distance walked (302.50 meters vs. 427.50 meters, p = 0.019), with the deceased group walking significantly less than the survival group. ROC curve analysis was performed to evaluate the efficacy of the 6MWT distance for predicting 6-month mortality in this cohort. The cut-off value was 407 meters for the 6MWT, with an area under the curve (AUC) of 0.782 (95% CI 0.708–0.846). The sensitivity was 100% (95% CI 54.1–100) and the specificity was 56.94% (95% CI 48.4–65.2) for 6-month mortality (Table 4 and additional Fig. 1 ). Correlation between 1MSTS repetitions and other factors Table 3 presents the Spearman's rho correlations between 1MSTS repetitions and various factors, including the GAP index, mMRC scale, pulmonary function tests, and the 6MWT, both overall and within specific subgroups of ILD, namely CTD-ILD and IPF. Both GAP Score and mMRC Score show a strong negative correlation with 1MSTS repetitions (GAP: rs = -0.49, p < 0.001; mMRC: rs = -0.47, p < 0.001). This indicates that higher GAP and mMRC scores, which signify worse disease severity and dyspnea, are associated with fewer 1MSTS repetitions (Table 3). The correlations between FVC and FEV1 with 1MSTS repetitions show significant positive relationships (FVC: rs = 0.23, p = 0.006; FEV1: rs = 0.27, p = 0.001), indicating that better lung function is associated with more 1MSTS repetitions (Table 3). Additionally, DLCO and DLCO/VA also show significant positive correlations with 1MSTS repetitions (DLCO: rs = 0.30, p < 0.001; DLCO/VA: rs = 0.27, p = 0.001), suggesting that better gas exchange capability is associated with more repetitions (Table 3). The correlation between 6MWT distance and 1MSTS repetitions shows a very strong positive relationship (rs = 0.65, p < 0.001), indicating that greater walking distance is strongly associated with more 1MSTS repetitions (Table 3). Additionally, both resting and exercise SpO2 show significant positive correlations with 1MSTS repetitions (Resting SpO2: rs = 0.27, p = 0.001; Exercise SpO2: rs = 0.23, p = 0.004), suggesting that better oxygen saturation is linked to better performance on the 1MSTS. Furthermore, Nadir SpO2 also shows a significant positive correlation (rs = 0.23, p = 0.044), indicating that higher lowest oxygen saturation during the 6MWT is associated with more 1MSTS repetitions (Table 3). Correlation between 1MSTS repetitions and other factors in subgroup analysis of CTD-ILD and IPF populations. In the analysis of the CTD-ILD subgroup, Table 3 shows similar trends, with the GAP score, mMRC score, and most pulmonary function test parameters displaying significant correlations with 1MSTS repetitions. The 6MWT distance and resting SpO2 also show strong positive correlations with 1MSTS repetitions in patients with CTD-ILD. In the IPF subgroup, similar trends are observed with the GAP score (rs = -0.53, p = 0.001) and mMRC score (rs = -0.49, p = 0.006), and most pulmonary function test parameters showing significant positive correlations with 1MSTS repetitions (FVC: rs = 0.38, p = 0.019; FEV1: rs = 0.49, p = 0.002; DLCO: rs = 0.38, p = 0.042). The 6MWT distance shows a very strong positive correlation (rs = 0.65, p < 0.001), similar to the overall and CTD-ILD groups. Nadir SpO2 also shows a significant positive correlation (rs = 0.49, p = 0.022) with 1MSTS repetitions in patients with IPF. The results are consistent across the overall cohort and within the specific ILD subgroups (CTD-ILD and IPF), indicating the robustness of these findings. The agreement between the 1MSTS repetitions and the 6MWT distance and cutoff values to predict 6MWT distance The Bland-Altman plot compares the 1MSTS repetitions and the 6MWT distance, indicating the agreement between these two measures (Fig. 2 ). The central line represents the mean difference, showing no systematic bias, while the dashed lines mark the limits of agreement (± 1.96 standard deviations). Most data points lie within these limits, suggesting good agreement between the tests. The p-value of 1.000 indicates no statistically significant difference, confirming the strong correlation and supporting the use of 1MSTS as a reliable alternative to 6MWT for assessing functional capacity (Fig. 2 ). The cutoff points of 1MSTS repetitions to predict 6MWT distances by using ROC curve analysis demonstrated an AUC of 0.856 (95% CI 0.789–0.908), with a sensitivity of 75.0% (95% CI 55.1–89.3) and specificity of 78.7% (95% CI 70.4–85.6) when using 1MSTS repetitions ≤ 20 to predict 6MWT distances < 300 meters in F-ILD (Table 4 and Fig. 3 ). Discussion In this prospective real-world study, we enrolled 150 F-ILD patients whose functional status was evaluated using both the 1-minute sit-to-stand test (1MSTS) and the 6-minute walk test (6MWT). We followed up on their short-term mortality six months later. Our data revealed that the 6MWT distance significantly predicted 6-month mortality. Although the 1MSTS did not significantly predict 6-month survival, it showed strong correlations with the GAP score, mMRC scale, and 6MWT distance. Additionally, the correlation between 1MSTS repetitions and various physical parameters was consistent across the overall cohort and within specific ILD subgroups (CTD-ILD and IPF), indicating the robustness of these findings. Furthermore, we identified a cutoff value of 1MSTS repetitions ≤ 20 to predict 6MWT distances < 300 meters using ROC curve analysis, with an AUC of 0.856. To the best of our knowledge, this is the first study to address the correlation between 1MSTS and 6MWT and to provide real-world evidence for using 1MSTS repetitions ≤ 20 to predict 6MWT distances. The movement of standing up and sitting down is a crucial function of daily life, and the inability to perform these actions reflects a patient's functional impairment 28 . Consequently, the sit-to-stand (STS) test, a simple and practical assessment, has been widely adopted to evaluate functionality in community-dwelling elderly individuals 29 , 30 . Due to limited research on using STS in F-ILD, we referenced studies on COPD patients. The three most common protocols of the STS test applied in COPD patients are the 5-repetition STS (5-rep STS) test, the 30-second protocol (30-s STS), and the 1-minute protocol (1MSTS) 31 . Previous studies have shown that all three protocols have strong correlations with important clinical outcomes in subjects with COPD 14 . However, the 1MSTS was found to be more demanding, leading to greater desaturation and increased symptoms of dyspnea and fatigue at the end of the test 14 . Additionally, three studies have used 1MSTS to detect desaturation during the 6MWT in ILD patients 18 – 20 with positive findings. Based on these reasons, we chose 1MSTS to evaluate its correlation with and prediction of short-term mortality in the current study. Compared to previous studies that were limited in finding the correlation between 1MSTS and 6MWT in F-ILD 18 – 20 , the strength of our data not only demonstrates a strong correlation between these two tests but also shows a strong negative correlation between GAP score and mMRC score with 1MSTS repetitions (GAP: rs = -0.49, p < 0.001; mMRC: rs = -0.47, p < 0.001). This indicates that higher GAP and mMRC scores, which signify worse disease severity and dyspnea, are associated with fewer 1MSTS repetitions. Additionally, our data found strong positive correlations between FVC and FEV1 with 1MSTS repetitions (FVC: rs = 0.23, p = 0.006; FEV1: rs = 0.27, p = 0.001), indicating that better lung function is associated with more 1MSTS repetitions. Furthermore, we found that DLCO and DLCO/VA were significantly positively correlated with 1MSTS repetitions (DLCO: rs = 0.30, p < 0.001; DLCO/VA: rs = 0.27, p = 0.001), suggesting that better gas exchange capability is associated with more repetitions. Therefore, our study provides more valuable applications for 1MSTS in evaluating F-ILD patients. The current study is unique in that it conducts a subgroup analysis to compare the correlation between 1MSTS and various parameters across different causes of F-ILD, specifically in CTD-ILD and IPF. We verified these correlations in both subgroups. In CTD-ILD patients, we observed significant correlations between 1MSTS repetitions and the GAP score, mMRC score, and most pulmonary function test parameters. Additionally, 6MWT distance and resting SpO2 showed strong positive correlations with 1MSTS repetitions. Similar trends were found in the IPF subgroup, with significant correlations between 1MSTS repetitions and the GAP score (rs = -0.53, p = 0.001), mMRC score (rs = -0.49, p = 0.006), and most pulmonary function test parameters. The 6MWT distance also exhibited a very strong positive correlation (rs = 0.65, p < 0.001), and Nadir SpO2 showed a significant positive correlation (rs = 0.49, p = 0.022) with 1MSTS repetitions. These consistent results across the overall cohort and specific ILD subgroups (CTD-ILD and IPF) indicate the robustness of our findings. Unlike previous studies investigating the correlation between 1MSTS and 6MWT in terms of oxygen desaturation in pulmonary fibrosis patients 18 – 20 , the most important finding of this study is identifying the cut-off points for predicting six-month survival in F-ILD patients using 1MSTS repetitions and 6MWT distance. Although only 6 patients (4%) in this cohort died within six months after undergoing these tests, we found that a 6MWT distance of less than 407 meters can serve as predictors of six-month mortality, the AUC was 0.782 (95% CI 0.708–0.846) and with a sensitivity of sensitivity of 100% (84% CI 54.1–100) and specificity of 56.94% (95% CI 48.4–65.2). Even more, we found that 1MSTS repetitions of 23 or fewer and a 6MWT distance of less than 100 meters has similar predicting power, with an AUC of 0.856 (95% CI: 0.789–0.908), a sensitivity of 75.0% (95% CI 55.1–89.3) and specificity of 78.7% (95% CI 70.4–85.6). Although previous study had revealed the positive correlation between the distance of 6MWT and the repetitions of 1MSTS 19 , 20 , 32 , there were no evidence of clear cutoff point in those 2 parameters to predict 6 months mortality in patients with F-ILD. Our study is the first to find out the specific cutoff point to predict 6 months mortality in patients with F-ILD, whether by 6MWT or 1MSTS. While larger-scale studies are needed to confirm these findings, this discovery enhances the potential role of 1MSTS as a supplementary tool for functional assessment in F-ILD and the predictor of short-term mortality risk. There are several limitations to this study. First, it was conducted in a single center with only 150 patients, limiting its sample size and generalizability. Second, we excluded F-ILD types other than IPF and CTD-ILD, which restricts the applicability of our findings to other F-ILD types. Third, the etiology of CTD-ILD included systemic sclerosis, rheumatoid arthritis, Sjogrene's syndrome, and idiopathic inflammatory myopathies, making subgroup analysis based on different CTD-ILD etiologies challenging. Fourth, there were only six deceased patients in this cohort, which is a small number to achieve sufficient statistical power. However, we still found significant differences in the parameters of 1MSTS and 6MWT between the alive and deceased groups, indicating the importance of these indicators. In the future, multi-center studies with larger sample sizes are required to confirm the findings of this study. Additionally, considering that 1MSTS may impose a slightly lower load than the 6MWT, regular and frequent use of the 1MSTS and comparing the differences between subsequent exams should be considered. Conclusion Our findings show that while 6MWT distance significantly predicts six-month mortality, the 1MSTS strongly correlates with the GAP score, mMRC scale, and 6MWT distance. A cutoff of 1MSTS ≤ 20 repetitions predicts 6MWT distances < 400 meters, with an AUC of 0.856. This highlights 1MSTS as a potential supplementary tool for functional assessment and short-term mortality risk in F-ILD. Future multi-center studies are needed to confirm these findings Abbreviations 6MWT Six-minute walking test 6MWD Six-minute walking distance CI Confidence interval CTD-ILD Connective tissue disease-associated interstitial lung disease DLCO Diffusion capacity for carbon monoxide FVC Forced vital capacity FEV1 Forced expiratory volume in one second GAP Gender-Age-Physiology IPF Idiopathic pulmonary fibrosis IQR Interquartile range MDD Multidisciplinary discussion mMRC Modified Medical Research Council PFT Pulmonary function test REGILD Registry of Interstitial Lung Disease ROC Receiver operating characteristic Declarations Ethics approval Ethics approval and consent to participate: This study was conducted in compliance with the Declaration of Helsinki and approved by the Ethics Committee of Taichung Veterans General Hospital (IRB number: CE18325B; date of approval: December 18, 2018). All patients signed an informed consent form. Consent for publication: Not applicable. Data Availability Statement: The data that support the findings of this study are available from the corresponding author upon reasonable request. Competing of Interest: The authors declare that they have no conflict of interests. Funding: This study was supported by Taichung Veterans General Hospital (TCVGH-1137308C; TCVGH-1123104D; TCVGH-1128303D; TCVGH-1137308D) and National Science and Technology Council of Taiwan (NSTC 112-2314-B-075A-003 -MY3) Author Contributions: M.-Y. T, K-T. H, and P.-K. F were responsible for conducting the research and data review. Y.-H.Y and C.-Y.H were responsible for data collection and statistical analysis. M.-Y. T, C.-Y. H and P.-K. F were responsible for data coding and interpretation of the results. M.-Y. T, and P.-K.F. was responsible for the study design, along with interpretation of the results and preparation of the manuscript. All authors discussed the results and contributed to the preparation of the final manuscript. All authors read and approved the final manuscript. Clinical trial number: not applicable. References Cottin V, Wollin L, Fischer A, Quaresma M, Stowasser S, Harari S. Fibrosing interstitial lung diseases: knowns and unknowns. Eur respiratory review: official J Eur Respiratory Soc. 2019; 28. Wong AW, Ryerson CJ, Guler SA. Progression of fibrosing interstitial lung disease. Respir Res. 2020;21:32. Maher TM. Interstitial Lung Disease: A Review. JAMA. 2024;331:1655–65. Wijsenbeek M, Cottin V. Spectrum of Fibrotic Lung Diseases. N Engl J Med. 2020;383:958–68. Raghu G, Remy-Jardin M, Richeldi L, Thomson CC, Inoue Y, Johkoh T, et al. Idiopathic Pulmonary Fibrosis (an Update) and Progressive Pulmonary Fibrosis in Adults: An Official ATS/ERS/JRS/ALAT Clinical Practice Guideline. Am J Respir Crit Care Med. 2022;205:e18–47. Giannitsi S, Bougiakli M, Bechlioulis A, Kotsia A, Michalis LK, Naka KK. 6-minute walking test: a useful tool in the management of heart failure patients. Ther Adv Cardiovasc Dis. 2019;13:1753944719870084. Souza R, Channick RN, Delcroix M, Galie N, Ghofrani HA, Jansa P, et al. Association between six-minute walk distance and long-term outcomes in patients with pulmonary arterial hypertension: Data from the randomized SERAPHIN trial. PLoS ONE. 2018;13:e0193226. Harari S, Wells AU, Wuyts WA, Nathan SD, Kirchgaessler KU, Bengus M et al. The 6-min walk test as a primary end-point in interstitial lung disease. Eur respiratory review: official J Eur Respiratory Soc. 2022; 31. Liao YW, Liu MC, Wu YC, Hsu CY, Huang WN, Chen YH, et al. Factors influencing long-term outcomes in fibrotic interstitial lung disease (F-ILD) diagnosed through multidisciplinary discussion (MDD): a prospective cohort study. Eur J Med Res. 2024;29:91. Liao YW, Chen YM, Liu MC, Wu YC, Hsu CY, Fu PK, et al. Multidisciplinary-derived clinical score for accurate prediction of long-term mortality in fibrotic lung disease patients. Eur J Med Res. 2024;29:69. Holland AE, Spruit MA, Troosters T, Puhan MA, Pepin V, Saey D, et al. An official European Respiratory Society/American Thoracic Society technical standard: field walking tests in chronic respiratory disease. Eur Respir J. 2014;44:1428–46. Caballer VB, Lison JF, Rosado-Calatayud P, Amer-Cuenca JJ, Segura-Orti E. Factors associated with the 6-minute walk test in nursing home residents and community-dwelling older adults. J Phys therapy Sci. 2015;27:3571–8. Laboratories ATSCoPSfCPF. ATS statement: guidelines for the six-minute walk test. Am J Respir Crit Care Med. 2002;166:111–7. Morita AA, Bisca GW, Machado FVC, Hernandes NA, Pitta F, Probst VS. Best Protocol for the Sit-to-Stand Test in Subjects With COPD. Respir Care. 2018;63:1040–9. Vaidya T, Chambellan A, de Bisschop C. Sit-to-stand tests for COPD: A literature review. Respir Med. 2017;128:70–7. Reychler G, Boucard E, Peran L, Pichon R, Le Ber-Moy C, Ouksel H, et al. One minute sit-to-stand test is an alternative to 6MWT to measure functional exercise performance in COPD patients. Clin Respir J. 2018;12:1247–56. Keen C, Smith I, Hashmi-Greenwood M, Sage K, Kiely DG. Pulmonary Hypertension and Measurement of Exercise Capacity Remotely: Evaluation of the 1-min Sit-to-Stand Test (PERSPIRE) - a cohort study. ERJ open Res. 2023; 9. Oishi K, Matsunaga K, Asami-Noyama M, Yamamoto T, Hisamoto Y, Fujii T, et al. The 1-minute sit-to-stand test to detect desaturation during 6-minute walk test in interstitial lung disease. NPJ Prim care respiratory Med. 2022;32:5. Briand J, Behal H, Chenivesse C, Wemeau-Stervinou L, Wallaert B. The 1-minute sit-to-stand test to detect exercise-induced oxygen desaturation in patients with interstitial lung disease. Ther Adv Respir Dis. 2018;12:1753466618793028. Singh R, Aggarwal D, Dutta K, Jaggi S, Sodhi MK, Saini V. Assessment of the feasibility of 1-min sit-to-stand test in evaluating functional exercise capacity in interstitial lung disease patients. J Exerc rehabilitation. 2023;19:363–9. Li A, Ling L, Qin H, Arabi YM, Myatra SN, Egi M, et al. Prognostic evaluation of quick sequential organ failure assessment score in ICU patients with sepsis across different income settings. Crit Care. 2024;28:30. Tseng CW, Wang KL, Fu PK, Huang CY, Hsieh TY, Hsieh CW et al. GAP Score and CA-153 Associated with One-Year Mortality in Anti-MDA-5 Antibody-Positive Patients: A Real-World Experience. J Clin Med. 2021; 10. Cheng YY, Lee YC, Liao YW, Liu MC, Wu YC, Hsu CY et al. , . A Summed Score From Cardiopulmonary Exercise Test Parameters Predicts 1-Year Mortality in Newly Diagnosed Interstitial Lung Disease. Respiratory care. 2024. Glasheen WP, Cordier T, Gumpina R, Haugh G, Davis J, Renda A. Charlson Comorbidity Index: ICD-9 Update and ICD-10 Translation. American health & drug benefits. 2019; 12: 188 – 97. Graham BL, Steenbruggen I, Miller MR, Barjaktarevic IZ, Cooper BG, Hall GL, et al. Standardization of Spirometry 2019 Update. An Official American Thoracic Society and European Respiratory Society Technical Statement. Am J Respir Crit Care Med. 2019;200:e70–88. Vaidya T, de Bisschop C, Beaumont M, Ouksel H, Jean V, Dessables F, et al. Is the 1-minute sit-to-stand test a good tool for the evaluation of the impact of pulmonary rehabilitation? Determination of the minimal important difference in COPD. Int J Chronic Obstr Pulm Dis. 2016;11:2609–16. Kendrick KR, Baxi SC, Smith RM. Usefulness of the modified 0–10 Borg scale in assessing the degree of dyspnea in patients with COPD and asthma. J Emerg Nurs. 2000;26:216–22. Janssen WG, Bussmann HB, Stam HJ. Determinants of the sit-to-stand movement: a review. Phys Ther. 2002;82:866–79. Zhang F, Ferrucci L, Culham E, Metter EJ, Guralnik J, Deshpande N. Performance on five times sit-to-stand task as a predictor of subsequent falls and disability in older persons. J Aging Health. 2013;25:478–92. Millor N, Lecumberri P, Gomez M, Martinez A, Martinikorena J, Rodriguez-Manas L, et al. Gait Velocity and Chair Sit-Stand-Sit Performance Improves Current Frailty-Status Identification. IEEE Trans neural Syst rehabilitation engineering: publication IEEE Eng Med Biology Soc. 2017;25:2018–25. Puhan MA, Siebeling L, Zoller M, Muggensturm P, ter Riet G. Simple functional performance tests and mortality in COPD. Eur Respir J. 2013;42:956–63. Watson K, Winship P, Cavalheri V, Vicary C, Stray S, Bear N, et al. In adults with advanced lung disease, the 1-minute sit-to-stand test underestimates exertional desaturation compared with the 6-minute walk test: an observational study. J physiotherapy. 2023;69:108–13. Tables Table 1. Baseline characteristics in ILD patients Total (n=150) Age, years (median, IQR) 64.5 (56.8-71.3) Sex (n, %) Female 85 (56.7%) Male 65 (43.3%) Smoker (n, %) 54 (36.0%) pack-year 30.0 (14.4-54.4) Classification of ILD (n, %) CTD-ILD 113 (75.3%) IPF 37 (24.7%) Body mass index (kg/m 2 ) (median, IQR) 23.57 (21.2-25.8) Physical examination (n, %) Basal crackles 101 (67.3%) Clubbing finger 43 (28.7%) mMRC (median, IQR) 0 (0-0) GAP (median, IQR) 3 (1-4) CCI (median, IQR) 2 (1-4) 1-minute sit-to-stand test (median, IQR) SaO2-Pre 96 (95-98) SaO2-Post (MIN) 93 (90-95.8) HR-Pre 84.5 (77-94) HR-Post 105.5 (93-115.3) Borg Scale-Pre 0 (0-1) Borg Scale-Post 3 (2-5) 1MST repetitions 24 (20-31) 1MST repetitions < 20 (n, %) 36 (24.0%) Six-minute Walk Test (median, IQR) Resting SpO 2 (%) 96 (95-98) Exercise SpO 2 (%) 91 (86.5-94) Nadir SpO 2 (%) 89 (83-92) Distance (m) 421.5 (323.8-495.3) 6-month mortality (n, %) 6 (4.0%) Table 2. Characteristics of Patients Alive or Deceased Within Six Months Following the 1MSTS and 6MWT Examinations Alive (n=144) Deceased (n=6) p value Age, years (median, IQR) 65.00 (57-71.75) 63.50 (55.5-71.75) 0.950 Sex (n, %) 0.404 Female 83 (57.64%) 2 (33.33%) Male 61 (42.36%) 4 (66.67%) Smoker (n, %) 49 (34.03%) 5 (83.33%) 0.023* pack-year 30.00 (12.5-50) 52.50 (26.25-70) 0.198 Classification of ILD (n, %) 1.000 CTD-ILD 108 (75.00%) 5 (83.33%) IPF 36 (25.00%) 1 (16.67%) Body mass index (kg/m 2 )(median, IQR) 23.57 (21.24-25.72) 23.00 (15.92-28.05) 0.716 Physical examination (n, %) Basal crackles 95 (65.97%) 6 (100%) 0.178 Clubbing finger 38 (26.39%) 5 (83.33%) 0.008** GAP (median, IQR) 3 (1-4) 3 (2.5-5.25) 0.256 mMRC (median, IQR) 0 (0-0) 1.50 (0.75-2.25) <0.001** CCI (median, IQR) 2 (1-4) 2.50 (1-6) 0.724 1-minute sit-to-stand test(median, IQR) SaO2-Pre 96.00 (95-98) 94.00 (88-95.25) 0.006** SaO2-Post (MIN) 93.50 (90-96) 88.50 (84.75-91.75) 0.044* HR-Pre 84.00 (76.25-93) 93.50 (83.5-109.5) 0.089 HR-Post 105.00 (93-113) 111.00 (93.25-120.25) 0.611 Borg Scale-Pre 0 (0-1) 3 (0.75-3) 0.008** Borg Scale-Post 3 (2-5) 5.50 (3.75-8.5) 0.042* 1MST repetitions 25 (20-31) 20 (8.25-24) 0.065 1MST repetitions ≤ 20 (n,%) 33 (22.92%) 3 (50.00%) 0.150 Six-minute Walk Test(median, IQR) Resting SpO 2 (%) 96 (95-98) 95 (90.8-97.5) 0.260 Exercise SpO 2 (%) 91 (87-94) 88 (77.8-96.5) 0.536 Nadir SpO 2 (%) 89 (83.5-92) 79 (70-0) 0.225 Distance (m) 427.5 (325.5-496) 302.50 (247.3-369.3) 0.019* Distance (m) < 407 (n,%) 62 (43.06%) 6 (100%) 0.008** Mann-Whitney U test. Fisher's exact test. * p <0.05, ** p <0.01. Table 3. The correlation between 1MSTS repetitions and other factors Overall Classification of ILD CTD-ILD IPF r s p value r s p value r s p value GAP -0.49 <0.001** -0.46 <0.001** -0.53 0.001** mMRC -0.47 <0.001** -0.42 <0.001** -0.49 0.006** Pulmonary Function test FVC (L) 0.23 0.006** 0.17 0.075 0.38 0.019* FVC (% predicted) 0.16 0.052 0.18 0.051 0.22 0.189 FEV1 (L) 0.27 0.001** 0.18 0.051 0.49 0.002** FEV1 (% predicted) 0.18 0.028* 0.18 0.057 0.30 0.071 FEV1/FVC (% predicted) 0.07 0.367 0.04 0.676 0.15 0.381 DLCO (% predicted) 0.30 <0.001** 0.27 0.005** 0.38 0.042* DLCO/VA (% predicted) 0.27 0.001** 0.25 0.009** 0.34 0.075 TLC (L) 0.16 0.073 0.15 0.139 0.19 0.340 TLC (% predicted) 0.07 0.412 0.14 0.175 -0.09 0.656 Six-minute Walk Test Resting SpO 2 (%) 0.27 0.001** 0.28 0.003** 0.22 0.199 Nadir SpO 2 (%) 0.23 0.044* 0.13 0.347 0.49 0.022* Exercise SpO 2 (%) 0.23 0.004** 0.19 0.050 0.30 0.073 Distance (m) 0.65 <0.001** 0.64 <0.001** 0.65 <0.001** Spearman's rho test. * p <0.05, ** p <0.01. Table 4. The cutoff points of 1MSTS repetitions to predict 6MWT distances by using ROC curve analysis 1MSTS repetitions 6MWT Distance (m) AUC (95% CI) Sensitivity (95% CI) Specificity (95% CI) ≤20 < 300 0.856 (0.789-0.908) 75.00 (55.10-89.30) 78.69 (70.40-85.60) ≤23 < 400 0.816 (0.745-0.875) 78.46 (66.50 - 87.70) 76.47 (66.00 - 85.00) ≤23 < 500 0.826 (0.756-0.883) 60.00 (50.4 0- 69.00) 94.29 (80.80 - 99.30) Additional Declarations No competing interests reported. Supplementary Files AdditionalFigure1.jpg Additional Figure 1. Kaplan-Meier curve analysis of 6-month mortality using a cutoff value of 407 meters for the 6MWT distance. Cite Share Download PDF Status: Published Journal Publication published 04 Feb, 2025 Read the published version in BMC Pulmonary Medicine → Version 1 posted Editorial decision: Revision requested 03 Sep, 2024 Editor assigned by journal 03 Sep, 2024 Submission checks completed at journal 03 Sep, 2024 First submitted to journal 17 Aug, 2024 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4931729","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":349002270,"identity":"46cd4645-a081-4c42-8310-e0064b9f3a68","order_by":0,"name":"Meng-Yun Tsai","email":"","orcid":"","institution":"Kaohsiung Chang Gung Memorial Hospital, Chang Gung University College of Medicine","correspondingAuthor":false,"prefix":"","firstName":"Meng-Yun","middleName":"","lastName":"Tsai","suffix":""},{"id":349002271,"identity":"7788bc29-8f31-4bab-ba36-d0c00a44a41b","order_by":1,"name":"Kuo-Tung Huang","email":"","orcid":"","institution":"Kaohsiung Chang Gung Memorial Hospital, Chang Gung University College of Medicine","correspondingAuthor":false,"prefix":"","firstName":"Kuo-Tung","middleName":"","lastName":"Huang","suffix":""},{"id":349002272,"identity":"d0bb68e2-fe13-4135-9e65-433c6827d706","order_by":2,"name":"Chiann-Yi Hsu","email":"","orcid":"","institution":"Taichung Veterans General Hospital","correspondingAuthor":false,"prefix":"","firstName":"Chiann-Yi","middleName":"","lastName":"Hsu","suffix":""},{"id":349002273,"identity":"0c9f8565-0ece-4ade-b2e3-5f368792c8ae","order_by":3,"name":"Yi-Hsuan Yu","email":"","orcid":"","institution":"Taichung Veterans General Hospital","correspondingAuthor":false,"prefix":"","firstName":"Yi-Hsuan","middleName":"","lastName":"Yu","suffix":""},{"id":349002274,"identity":"9618430b-ae59-4c9a-b202-b6581a540ada","order_by":4,"name":"Pin-Kuei Fu","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAxElEQVRIiWNgGAWjYBADORBx4AFxipnBpDFYSwIpWhIbQCRRWgyO9x+8zVNxJ31+2OGHQFvs5HQbCGk5c5jZmufMs9yNt9MMgFqSjc0OENJyI5lNmrftcO7G2QkgLQcStxHUcv8xUMu/w+mGs9M/EKnlBjNQS8PhBHnpHCJtkTyTbGw559hhww3SOQUHEgyI8Avf8YMPb7ypOSwvPzt984cPFXZyBLUoABVIgF0IVmlAQDkIyDdAtYAYo2AUjIJRMAqwAgBz1Eh5QIQoiQAAAABJRU5ErkJggg==","orcid":"","institution":"Taichung Veterans General Hospital","correspondingAuthor":true,"prefix":"","firstName":"Pin-Kuei","middleName":"","lastName":"Fu","suffix":""}],"badges":[],"createdAt":"2024-08-18 03:54:23","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4931729/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4931729/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1186/s12890-025-03521-3","type":"published","date":"2025-02-04T15:57:55+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":66953742,"identity":"9c2759f2-db3e-47f4-bbc7-550187d6b216","added_by":"auto","created_at":"2024-10-18 10:45:56","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":377558,"visible":true,"origin":"","legend":"\u003cp\u003eThe flow chart of patient enrollment\u003c/p\u003e\n\u003cp\u003eCTD-ILD: Connective tissue disease associated interstitial lung disease; IPF: Idiopathic pulmonary fibrosis; MDD: multidisciplinary team discussion; 1MSTS: one minute sit-to-stand test; 6MWT: six minutes walking test.\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-4931729/v1/a97e5052fd3798854dba5af0.png"},{"id":66953738,"identity":"9ab5eded-1a6a-42f3-9805-68f4b500b05f","added_by":"auto","created_at":"2024-10-18 10:45:56","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":102118,"visible":true,"origin":"","legend":"\u003cp\u003eBland-Altman analysis showed agreement between 1-MSTS repetitions and 6MWT distance.\u003c/p\u003e","description":"","filename":"floatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-4931729/v1/73da86ac614c403050a36292.png"},{"id":66953740,"identity":"740255ea-eb65-4067-bf22-bfec9d3d6b58","added_by":"auto","created_at":"2024-10-18 10:45:56","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":162227,"visible":true,"origin":"","legend":"\u003cp\u003eThe cutoff values of 1MSTS repetitions for predicting 6MWT distances using ROC curve analysis.\u003c/p\u003e\n\u003cp\u003eAUC: Area under curve\u003c/p\u003e","description":"","filename":"floatimage3.png","url":"https://assets-eu.researchsquare.com/files/rs-4931729/v1/ebdac22735dfbc29011f1eec.png"},{"id":75930465,"identity":"e6db53ee-2616-4561-adfb-0b8704a72ab8","added_by":"auto","created_at":"2025-02-10 16:12:07","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1591762,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4931729/v1/3bc18652-19a7-4301-8103-36a50135c4a3.pdf"},{"id":66954356,"identity":"75380a3b-a8a7-4b45-b7fb-a7a54fa1c12d","added_by":"auto","created_at":"2024-10-18 10:53:56","extension":"jpg","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":77645,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eAdditional Figure 1.\u003c/strong\u003e Kaplan-Meier curve analysis of 6-month mortality using a cutoff value of 407 meters for the 6MWT distance.\u003c/p\u003e","description":"","filename":"AdditionalFigure1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4931729/v1/33e2720de12eddb4bec7fe1c.jpg"}],"financialInterests":"No competing interests reported.","formattedTitle":"Reference Values for the 1-Minute Sit-to-Stand test to Assess Functional Capacity and Short- Term Mortality in People with Fibrotic Interstitial Lung Diseases: A Prospective Real-World Cohort Study","fulltext":[{"header":"Background","content":"\u003cp\u003eInterstitial lung disease (ILD) is a heterogeneous group of disorders characterized by interstitial inflammation or fibrosis of the lungs, leading to decreased lung function and impaired gas exchange \u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e. Early diagnosis of functional decline in fibrotic interstitial lung disease (F-ILD) is crucial for timely treatment and improved survival \u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e. Among the subtypes of F-ILD, idiopathic pulmonary fibrosis (IPF) and connective tissue disease-related interstitial lung disease (CTD-ILD) are frequently diagnosed \u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e. The progression of F-ILD is marked by progressive scarring of lung tissue, resulting in a decline in respiratory function and overall health \u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eThe 6-minute walk test (6MWT) is widely recognized as the gold standard for functional evaluation in chronic heart failure \u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/sup\u003e, pulmonary artery hypertension \u003csup\u003e\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003e and F-ILD \u003csup\u003e\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e patients due to its ability to assess exercise tolerance and predict outcomes. Our recent publications also show that 6MWT can also identify patients who experience desaturation during exertion and predict outcomes based on the distance walked in six minutes \u003csup\u003e\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u003c/sup\u003e. However, the 6MWT has practical limitations, including the need for a long, unobstructed walking course and the physical capability of the patient to complete the test \u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e. Furthermore, the 6MWT can be influenced by factors unrelated to pulmonary status, such as peripheral arterial disease, muscular strength, cognitive function, and nutritional status \u003csup\u003e\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/sup\u003e. Therefore, it is important to find an alternative method to detect functional decline that is more accessible and feasible in various settings.\u003c/p\u003e \u003cp\u003eThe 1-minute sit-to-stand test (1MSTS) is a simple and quick assessment that requires only a chair and can be completed in a short time \u003csup\u003e\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u003c/sup\u003e. This test measures the number of times a patient can stand from a seated position within one minute, reflecting lower body strength and endurance \u003csup\u003e\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u003c/sup\u003e. Research has demonstrated a good correlation between the 1MSTS and exercise capacity in patients with chronic obstructive pulmonary disease (COPD) \u003csup\u003e\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e, pulmonary artery hypertension \u003csup\u003e\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u003c/sup\u003e, and interstitial lung disease \u003csup\u003e\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u003c/sup\u003e. The 1MSTS is easier to administer and does not require the space or time needed for the 6MWT, making it a more practical option in many clinical settings. However, the correlation between 1MSTS and the 6MWT in F-ILD patients, and whether the 1MSTS can predict short-term mortality, remains unclear. Few studies have addressed this issue, and their findings are inconclusive due to limited case numbers, retrospective and varied study designs \u003csup\u003e\u003cspan additionalcitationids=\"CR19\" citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u003c/sup\u003e. Establishing this correlation could validate the 1MSTS as a reliable alternative to the 6MWT for functional assessment in F-ILD, providing a more accessible method for evaluating patient condition and monitoring disease progression.\u003c/p\u003e \u003cp\u003eThe aim of the current study is to investigate the diagnostic value of the 1MSTS in predicting short-term mortality and its correlation with the 6MWT. Short-term mortality is defined as death occurring within six months following the performance of the 1MSTS and 6MWT.\u003c/p\u003e"},{"header":"Method","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStudy design, patient enrollment, and ethics\u003c/h2\u003e \u003cp\u003eThe current data is derived from a subgroup analysis of a prospective, single-center, real-world registry study conducted at an ILD referral medical center in central Taiwan. The Registry of Interstitial Lung Disease (REGILD) has been enrolling both IPF and non-IPF populations since December 28, 2018. Diagnoses were confirmed through multidisciplinary team discussions (MDD) involving pulmonologists, rheumatologists, radiologists, and pathologists. Utilizing the REGILD cohort, several studies have been published exploring prognostic factors\u003csup\u003e\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan additionalcitationids=\"CR22\" citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eIn the current study, we enrolled patients over 20 years of age diagnosed with F-ILD who had completed evaluations of the 6MWT and 1MSTS between November 1, 2022, and June 30, 2023. Patients were excluded if they did not complete the 1MSTS, 6MWT, or pulmonary function test, or if they were diagnosed with ILD other than IPF or CTD-ILD after MDD. This study was conducted in compliance with the Declaration of Helsinki and was approved by the Ethics Committee of Taichung Veterans General Hospital (IRB number: CE18325B; date of approval: December 18, 2018).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eILD assessment protocol in the REGILD registry cohort\u003c/h2\u003e \u003cp\u003eBaseline clinical characteristics, including age, gender, smoking history, body mass index, physical examination findings, and comorbidities, were recorded on the day of enrollment. The follow-up protocol included pulmonary function tests (PFT) and the 1-minute sit-to-stand test (1MSTS) every six months. Additionally, patients underwent high-resolution computed tomography (HRCT) and cardiopulmonary exercise testing (CPET) at enrollment and annually. Questionnaires, such as the modified medical research council (mMRC) score, 36-Item Short Form Survey (SF-36), St. George's Respiratory Questionnaire (SGRQ), and the gender-age-physiology (GAP) index, were also evaluated at enrollment and annually. The comorbidities of enrolled patients were summarized using the Charlson Comorbidity Index (CCI) \u003csup\u003e\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003ePFT, 6MWT and IMSTS procedure\u003c/h2\u003e \u003cp\u003eForced vital capacity (FVC) and DLCO were obtained from spirometry results according to the recommendations of the American Thoracic Society (ATS) \u003csup\u003e\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u003c/sup\u003e. The 6-minute walk test (6MWT) was performed in accordance with ATS guidelines \u003csup\u003e\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/sup\u003e. Patients were instructed to walk as far as possible in six minutes in a corridor between two orange traffic cones placed 30 meters apart. Data on oxygen saturation, including resting SpO2, nadir SpO2, exercise SpO2, and the walking distance in six minutes, were recorded. The 1-minute sit-to-stand test (1MSTS) was performed as described in a previous study \u003csup\u003e\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u003c/sup\u003e, using a standard height chair (46 cm) without armrests positioned against a wall. SaO2, heart rate, and modified Borg scale \u003csup\u003e\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u003c/sup\u003e measurements before and after the test, as well as the number of 1MSTS repetitions, were recorded.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis\u003c/h2\u003e \u003cp\u003eData are expressed as median (interquartile range, IQR) unless otherwise stated. Categorical variables were analyzed using the chi-squared test or Fisher\u0026rsquo;s exact test, as appropriate. Continuous variables were compared using the Mann\u0026ndash;Whitney U test. Spearman's rho was calculated to measure the strength and direction of the association between 1MSTS repetitions and different parameters across the entire cohort. The Bland-Altman plot was used to assess the agreement between 1MSTS repetitions and the 6MWT. Receiver Operating Characteristic (ROC) curve analysis was conducted to evaluate predictors of 6-month mortality. Data analysis was performed using IBM SPSS software version 21.0 and MedCalc Software version 22.023. A two-sided p-value of \u0026lt;\u0026thinsp;0.05 was considered statistically significant.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" type=\"Results\" class=\"Section2\"\u003e \u003ch2\u003eResult\u003c/h2\u003e \u003cdiv id=\"Sec8\" class=\"Section3\"\u003e \u003ch2\u003eBaseline characteristics and the performance of IMSTS and 6MWT\u003c/h2\u003e \u003cp\u003eOne hundred and ninety-three patients diagnosed with F-ILD who underwent evaluations of the 6MWT and 1MSTS between November 1, 2022, and June 30, 2023, were initially enrolled. We excluded 33 patients who were not classified as having IPF or CTD-ILD and 10 patients who had missing data or failed to complete the 6MWT and the 1MSTS. Consequently, a total of 150 patients were included in the final analysis (Figure. 1). The baseline characteristics of this cohort showed a median age of 64.5 years (IQR: 56.8\u0026ndash;71.3), with 57.7% being female and 64% being non-smokers. The classification of F-ILD at enrollment included CTD-ILD (n\u0026thinsp;=\u0026thinsp;113, 75.3%) and IPF (n\u0026thinsp;=\u0026thinsp;37, 24.7%) (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e shows that the median number of repetitions in the 1MSTS was 24 (IQR: 20\u0026ndash;31). Using\u0026thinsp;\u0026le;\u0026thinsp;20 repetitions as the cutoff, 24% (36 out of 150) of patients were classified as functionally impaired. The 6MWT demonstrated a median distance of 421.5 meters (IQR: 323.8-495.3), with resting, exercise and nadir oxygen saturation levels at 96% (IQR: 95\u0026ndash;98), 91% (IQR: 86.5\u0026ndash;94), and 89% (IQR: 83\u0026ndash;92), respectively. Short-term mortality, defined as death within six months following the 1MSTS and 6MWT examinations, occurred in 6 out of 150 patients (4.0%).\u003c/p\u003e \u003cp\u003e \u003cb\u003eFactors Associated with Patients Alive or Deceased Within Six Months Following the 1MSTS and 6MWT Examinations\u003c/b\u003e \u003c/p\u003e \u003cp\u003eAs seen in Table\u0026nbsp;2, epidemiological indicators such as smoking status (83.33% vs. 34.03%, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.023), clubbing fingers (83.33% vs 26.39%, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.008), and mMRC scores (1.50 vs. 0, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001) show statistically significant differences between those who survived and those who died within six months. Even though the number of deaths within six months in this study was only six, we found statistically significant differences in the 1MSTS-related indicators. The deceased group had lower pre-exercise SaO2 levels (94.0% vs. 96.0%, p\u0026thinsp;=\u0026thinsp;0.006) and lower post-exercise SaO2 levels (88.5% vs. 93.5%, p\u0026thinsp;=\u0026thinsp;0.044), as well as higher pre-exercise Borg Scale scores (3 vs. 0, p\u0026thinsp;=\u0026thinsp;0.008) and higher post-exercise Borg Scale scores (5.50 vs. 3, p\u0026thinsp;=\u0026thinsp;0.042) compared to the survival group (Table\u0026nbsp;2).\u003c/p\u003e \u003cp\u003eAmong the 6MWT indicators, although the deceased group had lower resting SpO2, exercise SpO2, and nadir SpO2 levels, these differences were not statistically significant compared to the survival group. The only indicator in the 6MWT that showed a statistically significant difference was the distance walked (302.50 meters vs. 427.50 meters, p\u0026thinsp;=\u0026thinsp;0.019), with the deceased group walking significantly less than the survival group. ROC curve analysis was performed to evaluate the efficacy of the 6MWT distance for predicting 6-month mortality in this cohort. The cut-off value was 407 meters for the 6MWT, with an area under the curve (AUC) of 0.782 (95% CI 0.708\u0026ndash;0.846). The sensitivity was 100% (95% CI 54.1\u0026ndash;100) and the specificity was 56.94% (95% CI 48.4\u0026ndash;65.2) for 6-month mortality (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e4\u003c/span\u003e and additional Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003ch2\u003eCorrelation between 1MSTS repetitions and other factors\u003c/h2\u003e \u003cp\u003eTable\u0026nbsp;3 presents the Spearman's rho correlations between 1MSTS repetitions and various factors, including the GAP index, mMRC scale, pulmonary function tests, and the 6MWT, both overall and within specific subgroups of ILD, namely CTD-ILD and IPF. Both GAP Score and mMRC Score show a strong negative correlation with 1MSTS repetitions (GAP: rs = -0.49, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001; mMRC: rs = -0.47, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). This indicates that higher GAP and mMRC scores, which signify worse disease severity and dyspnea, are associated with fewer 1MSTS repetitions (Table\u0026nbsp;3).\u003c/p\u003e \u003cp\u003eThe correlations between FVC and FEV1 with 1MSTS repetitions show significant positive relationships (FVC: rs\u0026thinsp;=\u0026thinsp;0.23, p\u0026thinsp;=\u0026thinsp;0.006; FEV1: rs\u0026thinsp;=\u0026thinsp;0.27, p\u0026thinsp;=\u0026thinsp;0.001), indicating that better lung function is associated with more 1MSTS repetitions (Table\u0026nbsp;3). Additionally, DLCO and DLCO/VA also show significant positive correlations with 1MSTS repetitions (DLCO: rs\u0026thinsp;=\u0026thinsp;0.30, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001; DLCO/VA: rs\u0026thinsp;=\u0026thinsp;0.27, p\u0026thinsp;=\u0026thinsp;0.001), suggesting that better gas exchange capability is associated with more repetitions (Table\u0026nbsp;3).\u003c/p\u003e \u003cp\u003eThe correlation between 6MWT distance and 1MSTS repetitions shows a very strong positive relationship (rs\u0026thinsp;=\u0026thinsp;0.65, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), indicating that greater walking distance is strongly associated with more 1MSTS repetitions (Table\u0026nbsp;3). Additionally, both resting and exercise SpO2 show significant positive correlations with 1MSTS repetitions (Resting SpO2: rs\u0026thinsp;=\u0026thinsp;0.27, p\u0026thinsp;=\u0026thinsp;0.001; Exercise SpO2: rs\u0026thinsp;=\u0026thinsp;0.23, p\u0026thinsp;=\u0026thinsp;0.004), suggesting that better oxygen saturation is linked to better performance on the 1MSTS. Furthermore, Nadir SpO2 also shows a significant positive correlation (rs\u0026thinsp;=\u0026thinsp;0.23, p\u0026thinsp;=\u0026thinsp;0.044), indicating that higher lowest oxygen saturation during the 6MWT is associated with more 1MSTS repetitions (Table\u0026nbsp;3).\u003c/p\u003e \u003cp\u003e \u003cb\u003eCorrelation between 1MSTS repetitions and other factors in subgroup analysis of CTD-ILD and IPF populations.\u003c/b\u003e \u003c/p\u003e \u003cp\u003eIn the analysis of the CTD-ILD subgroup, Table\u0026nbsp;3 shows similar trends, with the GAP score, mMRC score, and most pulmonary function test parameters displaying significant correlations with 1MSTS repetitions. The 6MWT distance and resting SpO2 also show strong positive correlations with 1MSTS repetitions in patients with CTD-ILD.\u003c/p\u003e \u003cp\u003eIn the IPF subgroup, similar trends are observed with the GAP score (rs = -0.53, p\u0026thinsp;=\u0026thinsp;0.001) and mMRC score (rs = -0.49, p\u0026thinsp;=\u0026thinsp;0.006), and most pulmonary function test parameters showing significant positive correlations with 1MSTS repetitions (FVC: rs\u0026thinsp;=\u0026thinsp;0.38, p\u0026thinsp;=\u0026thinsp;0.019; FEV1: rs\u0026thinsp;=\u0026thinsp;0.49, p\u0026thinsp;=\u0026thinsp;0.002; DLCO: rs\u0026thinsp;=\u0026thinsp;0.38, p\u0026thinsp;=\u0026thinsp;0.042). The 6MWT distance shows a very strong positive correlation (rs\u0026thinsp;=\u0026thinsp;0.65, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), similar to the overall and CTD-ILD groups. Nadir SpO2 also shows a significant positive correlation (rs\u0026thinsp;=\u0026thinsp;0.49, p\u0026thinsp;=\u0026thinsp;0.022) with 1MSTS repetitions in patients with IPF. The results are consistent across the overall cohort and within the specific ILD subgroups (CTD-ILD and IPF), indicating the robustness of these findings.\u003c/p\u003e \u003cp\u003e \u003cb\u003eThe agreement between the 1MSTS repetitions and the 6MWT distance and cutoff values to predict 6MWT distance\u003c/b\u003e \u003c/p\u003e \u003cp\u003eThe Bland-Altman plot compares the 1MSTS repetitions and the 6MWT distance, indicating the agreement between these two measures (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). The central line represents the mean difference, showing no systematic bias, while the dashed lines mark the limits of agreement (\u0026plusmn;\u0026thinsp;1.96 standard deviations). Most data points lie within these limits, suggesting good agreement between the tests. The p-value of 1.000 indicates no statistically significant difference, confirming the strong correlation and supporting the use of 1MSTS as a reliable alternative to 6MWT for assessing functional capacity (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). The cutoff points of 1MSTS repetitions to predict 6MWT distances by using ROC curve analysis demonstrated an AUC of 0.856 (95% CI 0.789\u0026ndash;0.908), with a sensitivity of 75.0% (95% CI 55.1\u0026ndash;89.3) and specificity of 78.7% (95% CI 70.4\u0026ndash;85.6) when using 1MSTS repetitions\u0026thinsp;\u0026le;\u0026thinsp;20 to predict 6MWT distances\u0026thinsp;\u0026lt;\u0026thinsp;300 meters in F-ILD (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e4\u003c/span\u003e and Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eIn this prospective real-world study, we enrolled 150 F-ILD patients whose functional status was evaluated using both the 1-minute sit-to-stand test (1MSTS) and the 6-minute walk test (6MWT). We followed up on their short-term mortality six months later. Our data revealed that the 6MWT distance significantly predicted 6-month mortality. Although the 1MSTS did not significantly predict 6-month survival, it showed strong correlations with the GAP score, mMRC scale, and 6MWT distance. Additionally, the correlation between 1MSTS repetitions and various physical parameters was consistent across the overall cohort and within specific ILD subgroups (CTD-ILD and IPF), indicating the robustness of these findings. Furthermore, we identified a cutoff value of 1MSTS repetitions\u0026thinsp;\u0026le;\u0026thinsp;20 to predict 6MWT distances\u0026thinsp;\u0026lt;\u0026thinsp;300 meters using ROC curve analysis, with an AUC of 0.856. To the best of our knowledge, this is the first study to address the correlation between 1MSTS and 6MWT and to provide real-world evidence for using 1MSTS repetitions\u0026thinsp;\u0026le;\u0026thinsp;20 to predict 6MWT distances.\u003c/p\u003e \u003cp\u003eThe movement of standing up and sitting down is a crucial function of daily life, and the inability to perform these actions reflects a patient's functional impairment \u003csup\u003e\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e\u003c/sup\u003e. Consequently, the sit-to-stand (STS) test, a simple and practical assessment, has been widely adopted to evaluate functionality in community-dwelling elderly individuals \u003csup\u003e\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e, \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e\u003c/sup\u003e. Due to limited research on using STS in F-ILD, we referenced studies on COPD patients. The three most common protocols of the STS test applied in COPD patients are the 5-repetition STS (5-rep STS) test, the 30-second protocol (30-s STS), and the 1-minute protocol (1MSTS) \u003csup\u003e\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e\u003c/sup\u003e. Previous studies have shown that all three protocols have strong correlations with important clinical outcomes in subjects with COPD \u003csup\u003e\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u003c/sup\u003e. However, the 1MSTS was found to be more demanding, leading to greater desaturation and increased symptoms of dyspnea and fatigue at the end of the test \u003csup\u003e\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u003c/sup\u003e. Additionally, three studies have used 1MSTS to detect desaturation during the 6MWT in ILD patients \u003csup\u003e\u003cspan additionalcitationids=\"CR19\" citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u003c/sup\u003e with positive findings. Based on these reasons, we chose 1MSTS to evaluate its correlation with and prediction of short-term mortality in the current study.\u003c/p\u003e \u003cp\u003eCompared to previous studies that were limited in finding the correlation between 1MSTS and 6MWT in F-ILD \u003csup\u003e\u003cspan additionalcitationids=\"CR19\" citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u003c/sup\u003e, the strength of our data not only demonstrates a strong correlation between these two tests but also shows a strong negative correlation between GAP score and mMRC score with 1MSTS repetitions (GAP: rs = -0.49, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001; mMRC: rs = -0.47, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). This indicates that higher GAP and mMRC scores, which signify worse disease severity and dyspnea, are associated with fewer 1MSTS repetitions. Additionally, our data found strong positive correlations between FVC and FEV1 with 1MSTS repetitions (FVC: rs\u0026thinsp;=\u0026thinsp;0.23, p\u0026thinsp;=\u0026thinsp;0.006; FEV1: rs\u0026thinsp;=\u0026thinsp;0.27, p\u0026thinsp;=\u0026thinsp;0.001), indicating that better lung function is associated with more 1MSTS repetitions. Furthermore, we found that DLCO and DLCO/VA were significantly positively correlated with 1MSTS repetitions (DLCO: rs\u0026thinsp;=\u0026thinsp;0.30, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001; DLCO/VA: rs\u0026thinsp;=\u0026thinsp;0.27, p\u0026thinsp;=\u0026thinsp;0.001), suggesting that better gas exchange capability is associated with more repetitions. Therefore, our study provides more valuable applications for 1MSTS in evaluating F-ILD patients.\u003c/p\u003e \u003cp\u003eThe current study is unique in that it conducts a subgroup analysis to compare the correlation between 1MSTS and various parameters across different causes of F-ILD, specifically in CTD-ILD and IPF. We verified these correlations in both subgroups. In CTD-ILD patients, we observed significant correlations between 1MSTS repetitions and the GAP score, mMRC score, and most pulmonary function test parameters. Additionally, 6MWT distance and resting SpO2 showed strong positive correlations with 1MSTS repetitions. Similar trends were found in the IPF subgroup, with significant correlations between 1MSTS repetitions and the GAP score (rs = -0.53, p\u0026thinsp;=\u0026thinsp;0.001), mMRC score (rs = -0.49, p\u0026thinsp;=\u0026thinsp;0.006), and most pulmonary function test parameters. The 6MWT distance also exhibited a very strong positive correlation (rs\u0026thinsp;=\u0026thinsp;0.65, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), and Nadir SpO2 showed a significant positive correlation (rs\u0026thinsp;=\u0026thinsp;0.49, p\u0026thinsp;=\u0026thinsp;0.022) with 1MSTS repetitions. These consistent results across the overall cohort and specific ILD subgroups (CTD-ILD and IPF) indicate the robustness of our findings.\u003c/p\u003e \u003cp\u003eUnlike previous studies investigating the correlation between 1MSTS and 6MWT in terms of oxygen desaturation in pulmonary fibrosis patients\u003csup\u003e\u003cspan additionalcitationids=\"CR19\" citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u003c/sup\u003e, the most important finding of this study is identifying the cut-off points for predicting six-month survival in F-ILD patients using 1MSTS repetitions and 6MWT distance. Although only 6 patients (4%) in this cohort died within six months after undergoing these tests, we found that a 6MWT distance of less than 407 meters can serve as predictors of six-month mortality, the AUC was 0.782 (95% CI 0.708\u0026ndash;0.846) and with a sensitivity of sensitivity of 100% (84% CI 54.1\u0026ndash;100) and specificity of 56.94% (95% CI 48.4\u0026ndash;65.2). Even more, we found that 1MSTS repetitions of 23 or fewer and a 6MWT distance of less than 100 meters has similar predicting power, with an AUC of 0.856 (95% CI: 0.789\u0026ndash;0.908), a sensitivity of 75.0% (95% CI 55.1\u0026ndash;89.3) and specificity of 78.7% (95% CI 70.4\u0026ndash;85.6). Although previous study had revealed the positive correlation between the distance of 6MWT and the repetitions of 1MSTS \u003csup\u003e\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e, \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e\u003c/sup\u003e, there were no evidence of clear cutoff point in those 2 parameters to predict 6 months mortality in patients with F-ILD. Our study is the first to find out the specific cutoff point to predict 6 months mortality in patients with F-ILD, whether by 6MWT or 1MSTS. While larger-scale studies are needed to confirm these findings, this discovery enhances the potential role of 1MSTS as a supplementary tool for functional assessment in F-ILD and the predictor of short-term mortality risk.\u003c/p\u003e \u003cp\u003eThere are several limitations to this study. First, it was conducted in a single center with only 150 patients, limiting its sample size and generalizability. Second, we excluded F-ILD types other than IPF and CTD-ILD, which restricts the applicability of our findings to other F-ILD types. Third, the etiology of CTD-ILD included systemic sclerosis, rheumatoid arthritis, Sjogrene's syndrome, and idiopathic inflammatory myopathies, making subgroup analysis based on different CTD-ILD etiologies challenging. Fourth, there were only six deceased patients in this cohort, which is a small number to achieve sufficient statistical power. However, we still found significant differences in the parameters of 1MSTS and 6MWT between the alive and deceased groups, indicating the importance of these indicators. In the future, multi-center studies with larger sample sizes are required to confirm the findings of this study. Additionally, considering that 1MSTS may impose a slightly lower load than the 6MWT, regular and frequent use of the 1MSTS and comparing the differences between subsequent exams should be considered.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eOur findings show that while 6MWT distance significantly predicts six-month mortality, the 1MSTS strongly correlates with the GAP score, mMRC scale, and 6MWT distance. A cutoff of 1MSTS\u0026thinsp;\u0026le;\u0026thinsp;20 repetitions predicts 6MWT distances\u0026thinsp;\u0026lt;\u0026thinsp;400 meters, with an AUC of 0.856. This highlights 1MSTS as a potential supplementary tool for functional assessment and short-term mortality risk in F-ILD. Future multi-center studies are needed to confirm these findings\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cdiv class=\"DefinitionList\"\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e6MWT\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eSix-minute walking test\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e6MWD\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eSix-minute walking distance\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eCI\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eConfidence interval\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eCTD-ILD\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eConnective tissue disease-associated interstitial lung disease\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eDLCO\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eDiffusion capacity for carbon monoxide\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eFVC\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eForced vital capacity\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eFEV1\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eForced expiratory volume in one second\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eGAP\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eGender-Age-Physiology\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eIPF\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eIdiopathic pulmonary fibrosis\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eIQR\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eInterquartile range\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eMDD\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eMultidisciplinary discussion\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003emMRC\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eModified Medical Research Council\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003ePFT\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003ePulmonary function test\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eREGILD\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eRegistry of Interstitial Lung Disease\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eROC\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eReceiver operating characteristic\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eEthics approval and consent to participate: This study was conducted in compliance with the Declaration of Helsinki and approved by the Ethics Committee of Taichung Veterans General Hospital (IRB number: CE18325B; date of approval: December 18, 2018). All patients signed an informed consent form.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication:\u003c/strong\u003e Not applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData Availability Statement:\u003c/strong\u003e The data that support the findings of this study are available from the corresponding author upon reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting of Interest:\u0026nbsp;\u003c/strong\u003eThe authors declare that they have no conflict of interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding:\u003c/strong\u003e This study was supported by Taichung Veterans General Hospital (TCVGH-1137308C; TCVGH-1123104D; TCVGH-1128303D; TCVGH-1137308D) and National Science and Technology Council of Taiwan (NSTC 112-2314-B-075A-003 -MY3)\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor Contributions:\u0026nbsp;\u003c/strong\u003eM.-Y. T, K-T. H, and P.-K. F were responsible for conducting the research and data review. Y.-H.Y and C.-Y.H were responsible for data collection and statistical analysis. M.-Y. T, C.-Y. H and P.-K. F were responsible for data coding and interpretation of the results. M.-Y. T, and P.-K.F. was responsible for the study design, along with interpretation of the results and preparation of the manuscript. All authors discussed the results and contributed to the preparation of the final manuscript. All authors read and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eClinical trial number:\u003c/strong\u003e not applicable.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eCottin V, Wollin L, Fischer A, Quaresma M, Stowasser S, Harari S. Fibrosing interstitial lung diseases: knowns and unknowns. Eur respiratory review: official J Eur Respiratory Soc. 2019; 28.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWong AW, Ryerson CJ, Guler SA. Progression of fibrosing interstitial lung disease. Respir Res. 2020;21:32.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMaher TM. Interstitial Lung Disease: A Review. JAMA. 2024;331:1655\u0026ndash;65.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWijsenbeek M, Cottin V. Spectrum of Fibrotic Lung Diseases. N Engl J Med. 2020;383:958\u0026ndash;68.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRaghu G, Remy-Jardin M, Richeldi L, Thomson CC, Inoue Y, Johkoh T, et al. Idiopathic Pulmonary Fibrosis (an Update) and Progressive Pulmonary Fibrosis in Adults: An Official ATS/ERS/JRS/ALAT Clinical Practice Guideline. Am J Respir Crit Care Med. 2022;205:e18\u0026ndash;47.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGiannitsi S, Bougiakli M, Bechlioulis A, Kotsia A, Michalis LK, Naka KK. 6-minute walking test: a useful tool in the management of heart failure patients. Ther Adv Cardiovasc Dis. 2019;13:1753944719870084.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSouza R, Channick RN, Delcroix M, Galie N, Ghofrani HA, Jansa P, et al. Association between six-minute walk distance and long-term outcomes in patients with pulmonary arterial hypertension: Data from the randomized SERAPHIN trial. PLoS ONE. 2018;13:e0193226.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHarari S, Wells AU, Wuyts WA, Nathan SD, Kirchgaessler KU, Bengus M et al. The 6-min walk test as a primary end-point in interstitial lung disease. Eur respiratory review: official J Eur Respiratory Soc. 2022; 31.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLiao YW, Liu MC, Wu YC, Hsu CY, Huang WN, Chen YH, et al. Factors influencing long-term outcomes in fibrotic interstitial lung disease (F-ILD) diagnosed through multidisciplinary discussion (MDD): a prospective cohort study. Eur J Med Res. 2024;29:91.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLiao YW, Chen YM, Liu MC, Wu YC, Hsu CY, Fu PK, et al. Multidisciplinary-derived clinical score for accurate prediction of long-term mortality in fibrotic lung disease patients. Eur J Med Res. 2024;29:69.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHolland AE, Spruit MA, Troosters T, Puhan MA, Pepin V, Saey D, et al. An official European Respiratory Society/American Thoracic Society technical standard: field walking tests in chronic respiratory disease. Eur Respir J. 2014;44:1428\u0026ndash;46.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCaballer VB, Lison JF, Rosado-Calatayud P, Amer-Cuenca JJ, Segura-Orti E. Factors associated with the 6-minute walk test in nursing home residents and community-dwelling older adults. J Phys therapy Sci. 2015;27:3571\u0026ndash;8.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLaboratories ATSCoPSfCPF. ATS statement: guidelines for the six-minute walk test. Am J Respir Crit Care Med. 2002;166:111\u0026ndash;7.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMorita AA, Bisca GW, Machado FVC, Hernandes NA, Pitta F, Probst VS. Best Protocol for the Sit-to-Stand Test in Subjects With COPD. Respir Care. 2018;63:1040\u0026ndash;9.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eVaidya T, Chambellan A, de Bisschop C. Sit-to-stand tests for COPD: A literature review. Respir Med. 2017;128:70\u0026ndash;7.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eReychler G, Boucard E, Peran L, Pichon R, Le Ber-Moy C, Ouksel H, et al. One minute sit-to-stand test is an alternative to 6MWT to measure functional exercise performance in COPD patients. Clin Respir J. 2018;12:1247\u0026ndash;56.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKeen C, Smith I, Hashmi-Greenwood M, Sage K, Kiely DG. Pulmonary Hypertension and Measurement of Exercise Capacity Remotely: Evaluation of the 1-min Sit-to-Stand Test (PERSPIRE) - a cohort study. ERJ open Res. 2023; 9.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eOishi K, Matsunaga K, Asami-Noyama M, Yamamoto T, Hisamoto Y, Fujii T, et al. The 1-minute sit-to-stand test to detect desaturation during 6-minute walk test in interstitial lung disease. NPJ Prim care respiratory Med. 2022;32:5.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBriand J, Behal H, Chenivesse C, Wemeau-Stervinou L, Wallaert B. The 1-minute sit-to-stand test to detect exercise-induced oxygen desaturation in patients with interstitial lung disease. Ther Adv Respir Dis. 2018;12:1753466618793028.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSingh R, Aggarwal D, Dutta K, Jaggi S, Sodhi MK, Saini V. Assessment of the feasibility of 1-min sit-to-stand test in evaluating functional exercise capacity in interstitial lung disease patients. J Exerc rehabilitation. 2023;19:363\u0026ndash;9.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLi A, Ling L, Qin H, Arabi YM, Myatra SN, Egi M, et al. Prognostic evaluation of quick sequential organ failure assessment score in ICU patients with sepsis across different income settings. Crit Care. 2024;28:30.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTseng CW, Wang KL, Fu PK, Huang CY, Hsieh TY, Hsieh CW et al. GAP Score and CA-153 Associated with One-Year Mortality in Anti-MDA-5 Antibody-Positive Patients: A Real-World Experience. J Clin Med. 2021; 10.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCheng YY, Lee YC, Liao YW, Liu MC, Wu YC, Hsu CY et al. ,\u003cem\u003e. A Summed Score From Cardiopulmonary Exercise Test Parameters Predicts 1-Year Mortality in Newly Diagnosed Interstitial Lung Disease. Respiratory care. 2024.\u003c/em\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGlasheen WP, Cordier T, Gumpina R, Haugh G, Davis J, Renda A. Charlson Comorbidity Index: ICD-9 Update and ICD-10 Translation. American health \u0026amp; drug benefits. 2019; 12: 188\u0026thinsp;\u0026ndash;\u0026thinsp;97.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGraham BL, Steenbruggen I, Miller MR, Barjaktarevic IZ, Cooper BG, Hall GL, et al. Standardization of Spirometry 2019 Update. An Official American Thoracic Society and European Respiratory Society Technical Statement. Am J Respir Crit Care Med. 2019;200:e70\u0026ndash;88.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eVaidya T, de Bisschop C, Beaumont M, Ouksel H, Jean V, Dessables F, et al. Is the 1-minute sit-to-stand test a good tool for the evaluation of the impact of pulmonary rehabilitation? Determination of the minimal important difference in COPD. Int J Chronic Obstr Pulm Dis. 2016;11:2609\u0026ndash;16.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKendrick KR, Baxi SC, Smith RM. Usefulness of the modified 0\u0026ndash;10 Borg scale in assessing the degree of dyspnea in patients with COPD and asthma. J Emerg Nurs. 2000;26:216\u0026ndash;22.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eJanssen WG, Bussmann HB, Stam HJ. Determinants of the sit-to-stand movement: a review. Phys Ther. 2002;82:866\u0026ndash;79.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZhang F, Ferrucci L, Culham E, Metter EJ, Guralnik J, Deshpande N. Performance on five times sit-to-stand task as a predictor of subsequent falls and disability in older persons. J Aging Health. 2013;25:478\u0026ndash;92.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMillor N, Lecumberri P, Gomez M, Martinez A, Martinikorena J, Rodriguez-Manas L, et al. Gait Velocity and Chair Sit-Stand-Sit Performance Improves Current Frailty-Status Identification. IEEE Trans neural Syst rehabilitation engineering: publication IEEE Eng Med Biology Soc. 2017;25:2018\u0026ndash;25.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePuhan MA, Siebeling L, Zoller M, Muggensturm P, ter Riet G. Simple functional performance tests and mortality in COPD. Eur Respir J. 2013;42:956\u0026ndash;63.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWatson K, Winship P, Cavalheri V, Vicary C, Stray S, Bear N, et al. In adults with advanced lung disease, the 1-minute sit-to-stand test underestimates exertional desaturation compared with the 6-minute walk test: an observational study. J physiotherapy. 2023;69:108\u0026ndash;13.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"},{"header":"Tables","content":"\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" style=\"width: 472px;\"\u003e\n \u003cp\u003eTable 1. Baseline characteristics in ILD patients\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 264px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 209px;\"\u003e\n \u003cp\u003eTotal (n=150)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 264px;\"\u003e\n \u003cp\u003eAge, years (median, IQR)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 209px;\"\u003e\n \u003cp\u003e64.5 (56.8-71.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 264px;\"\u003e\n \u003cp\u003eSex (n, %)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 209px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 264px;\"\u003e\n \u003cp\u003eFemale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 209px;\"\u003e\n \u003cp\u003e85\u0026nbsp;(56.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 264px;\"\u003e\n \u003cp\u003eMale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 209px;\"\u003e\n \u003cp\u003e65\u0026nbsp;(43.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 264px;\"\u003e\n \u003cp\u003eSmoker (n, %)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 209px;\"\u003e\n \u003cp\u003e54\u0026nbsp;(36.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 264px;\"\u003e\n \u003cp\u003epack-year\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 209px;\"\u003e\n \u003cp\u003e30.0 (14.4-54.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 264px;\"\u003e\n \u003cp\u003eClassification of ILD (n, %)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 209px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 264px;\"\u003e\n \u003cp\u003eCTD-ILD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 209px;\"\u003e\n \u003cp\u003e113 (75.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 264px;\"\u003e\n \u003cp\u003eIPF\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 209px;\"\u003e\n \u003cp\u003e37 (24.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 264px;\"\u003e\n \u003cp\u003eBody mass index (kg/m\u003csup\u003e2\u003c/sup\u003e) (median, IQR)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 209px;\"\u003e\n \u003cp\u003e23.57 (21.2-25.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 264px;\"\u003e\n \u003cp\u003ePhysical examination (n, %)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 209px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 264px;\"\u003e\n \u003cp\u003eBasal crackles\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 209px;\"\u003e\n \u003cp\u003e101\u0026nbsp;(67.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 264px;\"\u003e\n \u003cp\u003eClubbing finger\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 209px;\"\u003e\n \u003cp\u003e43\u0026nbsp;(28.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 264px;\"\u003e\n \u003cp\u003emMRC (median, IQR)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 209px;\"\u003e\n \u003cp\u003e0 (0-0)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 264px;\"\u003e\n \u003cp\u003eGAP (median, IQR)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 209px;\"\u003e\n \u003cp\u003e3 (1-4)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 264px;\"\u003e\n \u003cp\u003eCCI (median, IQR)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 209px;\"\u003e\n \u003cp\u003e2 (1-4)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 264px;\"\u003e\n \u003cp\u003e1-minute sit-to-stand test (median, IQR)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 209px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 264px;\"\u003e\n \u003cp\u003eSaO2-Pre\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 209px;\"\u003e\n \u003cp\u003e96 (95-98)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 264px;\"\u003e\n \u003cp\u003eSaO2-Post (MIN)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 209px;\"\u003e\n \u003cp\u003e93 (90-95.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 264px;\"\u003e\n \u003cp\u003eHR-Pre\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 209px;\"\u003e\n \u003cp\u003e84.5 (77-94)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 264px;\"\u003e\n \u003cp\u003eHR-Post\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 209px;\"\u003e\n \u003cp\u003e105.5 (93-115.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 264px;\"\u003e\n \u003cp\u003eBorg Scale-Pre\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 209px;\"\u003e\n \u003cp\u003e0 (0-1)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 264px;\"\u003e\n \u003cp\u003eBorg Scale-Post\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 209px;\"\u003e\n \u003cp\u003e3 (2-5)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 264px;\"\u003e\n \u003cp\u003e1MST repetitions\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 209px;\"\u003e\n \u003cp\u003e24 (20-31)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 264px;\"\u003e\n \u003cp\u003e1MST repetitions \u0026lt; 20 (n, %)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 209px;\"\u003e\n \u003cp\u003e36\u0026nbsp;(24.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 264px;\"\u003e\n \u003cp\u003eSix-minute Walk Test (median, IQR)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 209px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 264px;\"\u003e\n \u003cp\u003eResting SpO\u003csub\u003e2\u003c/sub\u003e (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 209px;\"\u003e\n \u003cp\u003e96 (95-98)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 264px;\"\u003e\n \u003cp\u003eExercise SpO\u003csub\u003e2\u003c/sub\u003e (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 209px;\"\u003e\n \u003cp\u003e91 (86.5-94)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 264px;\"\u003e\n \u003cp\u003eNadir SpO\u003csub\u003e2\u003c/sub\u003e (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 209px;\"\u003e\n \u003cp\u003e89 (83-92)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 264px;\"\u003e\n \u003cp\u003eDistance (m)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 209px;\"\u003e\n \u003cp\u003e421.5 (323.8-495.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 264px;\"\u003e\n \u003cp\u003e6-month mortality (n, %)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 209px;\"\u003e\n \u003cp\u003e6\u0026nbsp;(4.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" align=\"\" width=\"100%\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"4\" style=\"width: 100%;\"\u003e\n \u003cp\u003eTable 2. Characteristics of Patients Alive or Deceased Within Six Months Following the 1MSTS and 6MWT Examinations\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 43%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 20%;\"\u003e\n \u003cp\u003eAlive (n=144)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 23%;\"\u003e\n \u003cp\u003eDeceased (n=6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13%;\"\u003e\n \u003cp\u003e\u003cem\u003ep\u003c/em\u003e value\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 43%;\"\u003e\n \u003cp\u003eAge, years (median, IQR)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20%;\"\u003e\n \u003cp\u003e65.00 (57-71.75)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 23%;\"\u003e\n \u003cp\u003e63.50 (55.5-71.75)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13%;\"\u003e\n \u003cp\u003e0.950\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 43%;\"\u003e\n \u003cp\u003eSex (n, %)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 23%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 13%;\"\u003e\n \u003cp\u003e0.404\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 43%;\"\u003e\n \u003cp\u003eFemale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20%;\"\u003e\n \u003cp\u003e83\u0026nbsp;(57.64%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 23%;\"\u003e\n \u003cp\u003e2\u0026nbsp;(33.33%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 43%;\"\u003e\n \u003cp\u003eMale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20%;\"\u003e\n \u003cp\u003e61\u0026nbsp;(42.36%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 23%;\"\u003e\n \u003cp\u003e4\u0026nbsp;(66.67%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 43%;\"\u003e\n \u003cp\u003eSmoker (n, %)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20%;\"\u003e\n \u003cp\u003e49\u0026nbsp;(34.03%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 23%;\"\u003e\n \u003cp\u003e5\u0026nbsp;(83.33%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13%;\"\u003e\n \u003cp\u003e0.023*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 43%;\"\u003e\n \u003cp\u003epack-year\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20%;\"\u003e\n \u003cp\u003e30.00 (12.5-50)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 23%;\"\u003e\n \u003cp\u003e52.50 (26.25-70)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13%;\"\u003e\n \u003cp\u003e0.198\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 43%;\"\u003e\n \u003cp\u003eClassification of ILD (n, %)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 23%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 13%;\"\u003e\n \u003cp\u003e1.000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 43%;\"\u003e\n \u003cp\u003eCTD-ILD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20%;\"\u003e\n \u003cp\u003e108\u0026nbsp;(75.00%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 23%;\"\u003e\n \u003cp\u003e5\u0026nbsp;(83.33%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 43%;\"\u003e\n \u003cp\u003eIPF\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20%;\"\u003e\n \u003cp\u003e36\u0026nbsp;(25.00%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 23%;\"\u003e\n \u003cp\u003e1\u0026nbsp;(16.67%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 43%;\"\u003e\n \u003cp\u003eBody mass index (kg/m\u003csup\u003e2\u003c/sup\u003e)(median, IQR)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20%;\"\u003e\n \u003cp\u003e23.57 (21.24-25.72)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 23%;\"\u003e\n \u003cp\u003e23.00 (15.92-28.05)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13%;\"\u003e\n \u003cp\u003e0.716\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 43%;\"\u003e\n \u003cp\u003ePhysical examination (n, %)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 23%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 13%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 43%;\"\u003e\n \u003cp\u003eBasal crackles\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20%;\"\u003e\n \u003cp\u003e95\u0026nbsp;(65.97%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 23%;\"\u003e\n \u003cp\u003e6\u0026nbsp;(100%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13%;\"\u003e\n \u003cp\u003e0.178\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 43%;\"\u003e\n \u003cp\u003eClubbing finger\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20%;\"\u003e\n \u003cp\u003e38\u0026nbsp;(26.39%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 23%;\"\u003e\n \u003cp\u003e5\u0026nbsp;(83.33%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13%;\"\u003e\n \u003cp\u003e0.008**\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 43%;\"\u003e\n \u003cp\u003eGAP (median, IQR)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20%;\"\u003e\n \u003cp\u003e3 (1-4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 23%;\"\u003e\n \u003cp\u003e3 (2.5-5.25)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13%;\"\u003e\n \u003cp\u003e0.256\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 43%;\"\u003e\n \u003cp\u003emMRC (median, IQR)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20%;\"\u003e\n \u003cp\u003e0 (0-0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 23%;\"\u003e\n \u003cp\u003e1.50 (0.75-2.25)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13%;\"\u003e\n \u003cp\u003e\u0026lt;0.001**\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 43%;\"\u003e\n \u003cp\u003eCCI (median, IQR)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20%;\"\u003e\n \u003cp\u003e2 (1-4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 23%;\"\u003e\n \u003cp\u003e2.50 (1-6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13%;\"\u003e\n \u003cp\u003e0.724\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 43%;\"\u003e\n \u003cp\u003e1-minute sit-to-stand test(median, IQR)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 23%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 13%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 43%;\"\u003e\n \u003cp\u003eSaO2-Pre\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20%;\"\u003e\n \u003cp\u003e96.00 (95-98)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 23%;\"\u003e\n \u003cp\u003e94.00 (88-95.25)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13%;\"\u003e\n \u003cp\u003e0.006**\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 43%;\"\u003e\n \u003cp\u003eSaO2-Post (MIN)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20%;\"\u003e\n \u003cp\u003e93.50 (90-96)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 23%;\"\u003e\n \u003cp\u003e88.50 (84.75-91.75)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13%;\"\u003e\n \u003cp\u003e0.044*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 43%;\"\u003e\n \u003cp\u003eHR-Pre\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20%;\"\u003e\n \u003cp\u003e84.00 (76.25-93)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 23%;\"\u003e\n \u003cp\u003e93.50 (83.5-109.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13%;\"\u003e\n \u003cp\u003e0.089\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 43%;\"\u003e\n \u003cp\u003eHR-Post\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20%;\"\u003e\n \u003cp\u003e105.00 (93-113)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 23%;\"\u003e\n \u003cp\u003e111.00 (93.25-120.25)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13%;\"\u003e\n \u003cp\u003e0.611\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 43%;\"\u003e\n \u003cp\u003eBorg Scale-Pre\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20%;\"\u003e\n \u003cp\u003e0 (0-1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 23%;\"\u003e\n \u003cp\u003e3 (0.75-3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13%;\"\u003e\n \u003cp\u003e0.008**\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 43%;\"\u003e\n \u003cp\u003eBorg Scale-Post\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20%;\"\u003e\n \u003cp\u003e3 (2-5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 23%;\"\u003e\n \u003cp\u003e5.50 (3.75-8.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13%;\"\u003e\n \u003cp\u003e0.042*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 43%;\"\u003e\n \u003cp\u003e1MST repetitions\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20%;\"\u003e\n \u003cp\u003e25 (20-31)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 23%;\"\u003e\n \u003cp\u003e20 (8.25-24)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13%;\"\u003e\n \u003cp\u003e0.065\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 43%;\"\u003e\n \u003cp\u003e1MST repetitions\u0026nbsp;\u0026le;\u0026nbsp;20 (n,%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20%;\"\u003e\n \u003cp\u003e33\u0026nbsp;(22.92%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 23%;\"\u003e\n \u003cp\u003e3\u0026nbsp;(50.00%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13%;\"\u003e\n \u003cp\u003e0.150\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 43%;\"\u003e\n \u003cp\u003eSix-minute Walk Test(median, IQR)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 23%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 13%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 43%;\"\u003e\n \u003cp\u003eResting SpO\u003csub\u003e2\u003c/sub\u003e (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20%;\"\u003e\n \u003cp\u003e96 (95-98)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 23%;\"\u003e\n \u003cp\u003e95 (90.8-97.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13%;\"\u003e\n \u003cp\u003e0.260\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 43%;\"\u003e\n \u003cp\u003eExercise SpO\u003csub\u003e2\u003c/sub\u003e (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20%;\"\u003e\n \u003cp\u003e91 (87-94)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 23%;\"\u003e\n \u003cp\u003e88 (77.8-96.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13%;\"\u003e\n \u003cp\u003e0.536\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 43%;\"\u003e\n \u003cp\u003eNadir SpO\u003csub\u003e2\u003c/sub\u003e (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20%;\"\u003e\n \u003cp\u003e89 (83.5-92)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 23%;\"\u003e\n \u003cp\u003e79 (70-0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13%;\"\u003e\n \u003cp\u003e0.225\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 43%;\"\u003e\n \u003cp\u003eDistance (m)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20%;\"\u003e\n \u003cp\u003e427.5 (325.5-496)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 23%;\"\u003e\n \u003cp\u003e302.50 (247.3-369.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13%;\"\u003e\n \u003cp\u003e0.019*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 43%;\"\u003e\n \u003cp\u003eDistance (m) \u0026lt; 407 (n,%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20%;\"\u003e\n \u003cp\u003e62\u0026nbsp;(43.06%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 23%;\"\u003e\n \u003cp\u003e6\u0026nbsp;(100%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13%;\"\u003e\n \u003cp\u003e0.008**\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"4\" style=\"width: 100%;\"\u003e\n \u003cp\u003eMann-Whitney U test. Fisher\u0026apos;s exact test. *\u003cem\u003ep\u003c/em\u003e\u0026lt;0.05, **\u003cem\u003ep\u003c/em\u003e\u0026lt;0.01.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"100%\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"7\" valign=\"bottom\" style=\"width: 100%;\"\u003e\n \u003cp\u003eTable 3. The correlation between 1MSTS repetitions and other factors\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 35%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd colspan=\"2\" rowspan=\"2\" style=\"width: 21%;\"\u003e\n \u003cp\u003eOverall\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"4\" style=\"width: 42%;\"\u003e\n \u003cp\u003eClassification of ILD\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 35%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 21%;\"\u003e\n \u003cp\u003eCTD-ILD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 21%;\"\u003e\n \u003cp\u003eIPF\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 35%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8%;\"\u003e\n \u003cp\u003er\u003csub\u003es\u003c/sub\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13%;\"\u003e\n \u003cp\u003e\u003cem\u003ep\u003c/em\u003e value\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8%;\"\u003e\n \u003cp\u003er\u003csub\u003es\u003c/sub\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13%;\"\u003e\n \u003cp\u003e\u003cem\u003ep\u003c/em\u003e value\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8%;\"\u003e\n \u003cp\u003er\u003csub\u003es\u003c/sub\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13%;\"\u003e\n \u003cp\u003e\u003cem\u003ep\u003c/em\u003e value\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 35%;\"\u003e\n \u003cp\u003eGAP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8%;\"\u003e\n \u003cp\u003e-0.49\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13%;\"\u003e\n \u003cp\u003e\u0026lt;0.001**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8%;\"\u003e\n \u003cp\u003e-0.46\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13%;\"\u003e\n \u003cp\u003e\u0026lt;0.001**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8%;\"\u003e\n \u003cp\u003e-0.53\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13%;\"\u003e\n \u003cp\u003e0.001**\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 35%;\"\u003e\n \u003cp\u003emMRC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8%;\"\u003e\n \u003cp\u003e-0.47\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13%;\"\u003e\n \u003cp\u003e\u0026lt;0.001**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8%;\"\u003e\n \u003cp\u003e-0.42\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13%;\"\u003e\n \u003cp\u003e\u0026lt;0.001**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8%;\"\u003e\n \u003cp\u003e-0.49\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13%;\"\u003e\n \u003cp\u003e0.006**\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 35%;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePulmonary Function test\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 13%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 8%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 13%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 8%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 13%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 35%;\"\u003e\n \u003cp\u003eFVC (L)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8%;\"\u003e\n \u003cp\u003e0.23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13%;\"\u003e\n \u003cp\u003e0.006**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8%;\"\u003e\n \u003cp\u003e0.17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13%;\"\u003e\n \u003cp\u003e0.075\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8%;\"\u003e\n \u003cp\u003e0.38\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13%;\"\u003e\n \u003cp\u003e0.019*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 35%;\"\u003e\n \u003cp\u003eFVC (% predicted)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8%;\"\u003e\n \u003cp\u003e0.16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13%;\"\u003e\n \u003cp\u003e0.052\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8%;\"\u003e\n \u003cp\u003e0.18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13%;\"\u003e\n \u003cp\u003e0.051\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8%;\"\u003e\n \u003cp\u003e0.22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13%;\"\u003e\n \u003cp\u003e0.189\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 35%;\"\u003e\n \u003cp\u003eFEV1 (L)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8%;\"\u003e\n \u003cp\u003e0.27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13%;\"\u003e\n \u003cp\u003e0.001**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8%;\"\u003e\n \u003cp\u003e0.18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13%;\"\u003e\n \u003cp\u003e0.051\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8%;\"\u003e\n \u003cp\u003e0.49\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13%;\"\u003e\n \u003cp\u003e0.002**\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 35%;\"\u003e\n \u003cp\u003eFEV1 (% predicted)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8%;\"\u003e\n \u003cp\u003e0.18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13%;\"\u003e\n \u003cp\u003e0.028*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8%;\"\u003e\n \u003cp\u003e0.18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13%;\"\u003e\n \u003cp\u003e0.057\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8%;\"\u003e\n \u003cp\u003e0.30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13%;\"\u003e\n \u003cp\u003e0.071\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 35%;\"\u003e\n \u003cp\u003eFEV1/FVC (% predicted)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8%;\"\u003e\n \u003cp\u003e0.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13%;\"\u003e\n \u003cp\u003e0.367\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8%;\"\u003e\n \u003cp\u003e0.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13%;\"\u003e\n \u003cp\u003e0.676\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8%;\"\u003e\n \u003cp\u003e0.15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13%;\"\u003e\n \u003cp\u003e0.381\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 35%;\"\u003e\n \u003cp\u003eDLCO (% predicted)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8%;\"\u003e\n \u003cp\u003e0.30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13%;\"\u003e\n \u003cp\u003e\u0026lt;0.001**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8%;\"\u003e\n \u003cp\u003e0.27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13%;\"\u003e\n \u003cp\u003e0.005**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8%;\"\u003e\n \u003cp\u003e0.38\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13%;\"\u003e\n \u003cp\u003e0.042*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 35%;\"\u003e\n \u003cp\u003eDLCO/VA (% predicted)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8%;\"\u003e\n \u003cp\u003e0.27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13%;\"\u003e\n \u003cp\u003e0.001**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8%;\"\u003e\n \u003cp\u003e0.25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13%;\"\u003e\n \u003cp\u003e0.009**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8%;\"\u003e\n \u003cp\u003e0.34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13%;\"\u003e\n \u003cp\u003e0.075\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 35%;\"\u003e\n \u003cp\u003eTLC (L)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8%;\"\u003e\n \u003cp\u003e0.16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13%;\"\u003e\n \u003cp\u003e0.073\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8%;\"\u003e\n \u003cp\u003e0.15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13%;\"\u003e\n \u003cp\u003e0.139\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8%;\"\u003e\n \u003cp\u003e0.19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13%;\"\u003e\n \u003cp\u003e0.340\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 35%;\"\u003e\n \u003cp\u003eTLC (% predicted)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8%;\"\u003e\n \u003cp\u003e0.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13%;\"\u003e\n \u003cp\u003e0.412\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8%;\"\u003e\n \u003cp\u003e0.14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13%;\"\u003e\n \u003cp\u003e0.175\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8%;\"\u003e\n \u003cp\u003e-0.09\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13%;\"\u003e\n \u003cp\u003e0.656\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 35%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSix-minute Walk Test\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 13%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 8%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 13%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 8%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 13%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 35%;\"\u003e\n \u003cp\u003eResting SpO\u003csub\u003e2\u003c/sub\u003e (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8%;\"\u003e\n \u003cp\u003e0.27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13%;\"\u003e\n \u003cp\u003e0.001**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8%;\"\u003e\n \u003cp\u003e0.28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13%;\"\u003e\n \u003cp\u003e0.003**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8%;\"\u003e\n \u003cp\u003e0.22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13%;\"\u003e\n \u003cp\u003e0.199\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 35%;\"\u003e\n \u003cp\u003eNadir SpO\u003csub\u003e2\u003c/sub\u003e (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8%;\"\u003e\n \u003cp\u003e0.23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13%;\"\u003e\n \u003cp\u003e0.044*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8%;\"\u003e\n \u003cp\u003e0.13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13%;\"\u003e\n \u003cp\u003e0.347\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8%;\"\u003e\n \u003cp\u003e0.49\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13%;\"\u003e\n \u003cp\u003e0.022*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 35%;\"\u003e\n \u003cp\u003eExercise SpO\u003csub\u003e2\u003c/sub\u003e (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8%;\"\u003e\n \u003cp\u003e0.23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13%;\"\u003e\n \u003cp\u003e0.004**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8%;\"\u003e\n \u003cp\u003e0.19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13%;\"\u003e\n \u003cp\u003e0.050\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8%;\"\u003e\n \u003cp\u003e0.30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13%;\"\u003e\n \u003cp\u003e0.073\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 35%;\"\u003e\n \u003cp\u003eDistance (m)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8%;\"\u003e\n \u003cp\u003e0.65\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13%;\"\u003e\n \u003cp\u003e\u0026lt;0.001**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8%;\"\u003e\n \u003cp\u003e0.64\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13%;\"\u003e\n \u003cp\u003e\u0026lt;0.001**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8%;\"\u003e\n \u003cp\u003e0.65\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13%;\"\u003e\n \u003cp\u003e\u0026lt;0.001**\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"7\" valign=\"bottom\" style=\"width: 100%;\"\u003e\n \u003cp\u003eSpearman\u0026apos;s rho test. *\u003cem\u003ep\u003c/em\u003e\u0026lt;0.05, **\u003cem\u003ep\u003c/em\u003e\u0026lt;0.01.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" align=\"\" width=\"98%\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"5\" style=\"width: 100%;\"\u003e\n \u003cp\u003eTable 4. The cutoff points of 1MSTS repetitions to predict 6MWT distances by using ROC curve analysis\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 17%;\"\u003e\n \u003cp\u003e1MSTS\u0026nbsp;\u003c/p\u003e\n \u003cp\u003erepetitions\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20%;\"\u003e\n \u003cp\u003e6MWT\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eDistance (m)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16%;\"\u003e\n \u003cp\u003eAUC\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e(95% CI)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 22%;\"\u003e\n \u003cp\u003eSensitivity\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e(95% CI)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 23%;\"\u003e\n \u003cp\u003eSpecificity\u003c/p\u003e\n \u003cp\u003e(95% CI)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 17%;\"\u003e\n \u003cp\u003e\u0026le;20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20%;\"\u003e\n \u003cp\u003e\u0026lt; 300\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16%;\"\u003e\n \u003cp\u003e0.856\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e(0.789-0.908)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 22%;\"\u003e\n \u003cp\u003e75.00\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e(55.10-89.30)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 23%;\"\u003e\n \u003cp\u003e78.69\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e(70.40-85.60)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 17%;\"\u003e\n \u003cp\u003e\u0026le;23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20%;\"\u003e\n \u003cp\u003e\u0026lt; 400\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16%;\"\u003e\n \u003cp\u003e0.816\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e(0.745-0.875)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 22%;\"\u003e\n \u003cp\u003e78.46\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e(66.50\u0026nbsp;-\u0026nbsp;87.70)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 23%;\"\u003e\n \u003cp\u003e76.47\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e(66.00\u0026nbsp;-\u0026nbsp;85.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 17%;\"\u003e\n \u003cp\u003e\u0026le;23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20%;\"\u003e\n \u003cp\u003e\u0026lt; 500\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16%;\"\u003e\n \u003cp\u003e0.826\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e(0.756-0.883)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 22%;\"\u003e\n \u003cp\u003e60.00\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e(50.4\u0026nbsp;0-\u0026nbsp;69.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 23%;\"\u003e\n \u003cp\u003e94.29\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e(80.80\u0026nbsp;-\u0026nbsp;99.30)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-pulmonary-medicine","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"pulm","sideBox":"Learn more about [BMC Pulmonary Medicine](http://bmcpulmmed.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/pulm/default.aspx","title":"BMC Pulmonary Medicine","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Fibrotic interstitial lung disease, 1-minute sit-to-stand test (1MSTS), 6-minute walk test (6MWT), Short-term mortality, Functional assessment","lastPublishedDoi":"10.21203/rs.3.rs-4931729/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4931729/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground:\u003c/h2\u003e \u003cp\u003eEarly diagnosis of functional decline in fibrotic interstitial lung disease (F-ILD) is crucial for timely treatment and improved survival. While the 6-minute walk test (6MWT) is the gold standard for functional evaluation, it has limitations. The 1-minute sit-to-stand test (1MSTS) is easier to administer, but its correlation with the 6MWT in F-ILD patients is unclear. This study aims to evaluate the reference values of 1MSTS to assess functional capacity, 6-month mortality and its correlation with the 6MWT in F-ILD patients.\u003c/p\u003e\u003ch2\u003eMethods:\u003c/h2\u003e \u003cp\u003eThis prospective study included subjects diagnosed with F-ILD through multidisciplinary team discussions. Assessments included the 1MSTS, 6MWT, pulmonary function test (PFT), GAP score, mMRC scale, and Charlson Comorbidity Index (CCI). The association between 1MSTS repetitions and variables was calculated using Spearman's rho. Bland-Altman plots assessed the agreement between 1MSTS repetitions and the 6MWT. ROC curve analysis evaluated predictors for 6-month mortality.\u003c/p\u003e\u003ch2\u003eResults:\u003c/h2\u003e \u003cp\u003eOf the 150 F-ILD patients, 37 (24.6%) had idiopathic pulmonary fibrosis (IPF), and 113 (75.4%) had connective tissue disease-related ILD (CTD-ILD). Using\u0026thinsp;\u0026le;\u0026thinsp;20 repetitions as the cutoff for functional impairment, 36 (24.0%) patients were classified as impaired. The 6MWT distance significantly predicted 6-month mortality. Although the 1MSTS did not significantly predict 6-month survival, it showed strong correlations with GAP score (rs = -0.49, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), mMRC scale (rs = -0.47, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), and 6MWT distance (rs\u0026thinsp;=\u0026thinsp;0.65, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Bland-Altman analysis showed agreement between 1MSTS repetitions and 6MWT distance. An AUC of 0.856 was achieved for predicting\u0026thinsp;\u0026lt;\u0026thinsp;300 meters for the 6MWT distance by using\u0026thinsp;\u0026le;\u0026thinsp;20 repetitions as the cutoff value for the 1MSTS.\u003c/p\u003e\u003ch2\u003eConclusions:\u003c/h2\u003e \u003cp\u003eThe findings suggest that \u0026le;\u0026thinsp;20 repetitions in the 1MSTS can be used as an indicator of functional impairment and has a good correlation with 6MWT distance, GAP score, and mMRC scale in assessing patients with F-ILD.\u003c/p\u003e","manuscriptTitle":"Reference Values for the 1-Minute Sit-to-Stand test to Assess Functional Capacity and Short- Term Mortality in People with Fibrotic Interstitial Lung Diseases: A Prospective Real-World Cohort Study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-10-18 10:45:51","doi":"10.21203/rs.3.rs-4931729/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2024-09-03T14:14:08+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-09-03T11:09:54+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2024-09-03T11:08:38+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Pulmonary Medicine","date":"2024-08-18T03:52:56+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-pulmonary-medicine","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"pulm","sideBox":"Learn more about [BMC Pulmonary Medicine](http://bmcpulmmed.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/pulm/default.aspx","title":"BMC Pulmonary Medicine","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"f4c44564-5a93-41e0-b892-5ad32b8f2b88","owner":[],"postedDate":"October 18th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2025-02-10T16:03:32+00:00","versionOfRecord":{"articleIdentity":"rs-4931729","link":"https://doi.org/10.1186/s12890-025-03521-3","journal":{"identity":"bmc-pulmonary-medicine","isVorOnly":false,"title":"BMC Pulmonary Medicine"},"publishedOn":"2025-02-04 15:57:55","publishedOnDateReadable":"February 4th, 2025"},"versionCreatedAt":"2024-10-18 10:45:51","video":"","vorDoi":"10.1186/s12890-025-03521-3","vorDoiUrl":"https://doi.org/10.1186/s12890-025-03521-3","workflowStages":[]},"version":"v1","identity":"rs-4931729","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4931729","identity":"rs-4931729","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}