Application of MEFV Curve in the Intrathoracic Large Airway Obstruction: a retrospective study

Application of MEFV Curve in the Intrathoracic Large Airway Obstruction: a retrospective 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 Application of MEFV Curve in the Intrathoracic Large Airway Obstruction: a retrospective study Ying Gong, Liping Xue, Xu Wu, Zhiwen Shen, Chun Li, Yuanlin Song, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4537297/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background Maximum expiratory flow-volume (MEFV) curve played an important part in diagnosing the intrathoracic large airway obstruction (ILAO). This study aimed to explore potential discriminative indicators for ILAO by MEFV curve. Methods In this retrospective observational study, we collected pulmonary function tests of patients with ILAO or chronic obstructive pulmonary disease (COPD). They were randomly classified into model and validation groups. The predictive model for ILAO was established by forced expiratory flow (FEF) 50% /FEF 25% and Empey’s index, and subsequently validated. Results Between January, 2012, and December, 2021, 63 patients with ILAO and 64 with COPD were included. The peak expiratory flow (PEF), FEF 50% , FEF 75% , FEF 25 − 75% , FEF ratios and Empey’s index were significantly different in two group. In the model group, the receiver operating characteristic (ROC) curve results showed that the areas under the curve (AUCs) were as follows: FEF 50% /FEF 25% 0.935(P = 0.000), FEF 75% /FEF 50% 0.623 (P = 0.091), FEF 75% /FEF 25% 0.795 (P < 0.001) and Empey’s index 0.922 (P < 0.001). When FEF 50% /FEF 25% was ≥ 0.960, sensitivity and specificity were 93.8% and 87.5%. When Empey’s index was ≥ 7.415, sensitivity and specificity were 84.4% and 100%. When FEF 50% /FEF 25% ≥0.960 and Empey’s index was ≥ 7.415, sensitivity and specificity were 81.3% and 87.5%. The predictive performance of FEF 50% /FEF 25%, Empey’s index and the combined parameters were calculated in the validation group, with high sensitivity and acceptable specificity. Conclusions The predictive model for ILAO established using FEF 50% /FEF 25% and Empey’s index demonstrates good practical value, which makes FEF 50% /FEF 25% and Empey’s index potential discriminative indicators for ILAO. Large Airway Obstruction MEFV Curve FEF Ratios Empey’s Index FEF50%/FEF25% Figures Figure 1 Figure 2 Figure 3 BACKGROUND The airways are divided into large and medium/small airways according to anatomical characteristics. Large airways, which refer to airways with a diameter greater than 2 mm, including upper airways and the main bronchi around the carina, are characterized by smaller cross-sectional areas, high resistance, tough and rigid tissues, as well as support from cartilaginous rings( 1 ). Obstruction in large airways can be caused by various factors such as tumors, endobronchial tuberculosis and foreign bodies. It lacks specificity in clinical symptoms and signs despite being common in clinical practice, and patients commonly present varying degrees of wheezing. Moreover, the condition progresses slowly, which often leads to misdiagnosis or underdiagnosis, particularly as it can be mistaken for chronic airway disease caused by peripheral small airway obstruction like chronic obstructive pulmonary disease (COPD) and other conditions. The early assessment of large airway obstruction in clinical practice remains a great challenge. In recent advances, bronchoscopy was proposed as a necessary procedure for the diagnosis of large airway obstruction. Only through bronchoscopy, can the nature, location and extent of a lesion be visually demonstrated. As an invasive procedure, however, it cannot reflect respiratory physiological function( 2 , 3 ). Pulmonary function testing, one of the important ancillary examinations for respiratory system diseases, is widely used for the diagnosis and assessment of disease severity or prognosis, as well as the preoperative evaluation of surgical endurance. Nevertheless, little research has been conducted on the application of pulmonary function testing in the context of large airway obstruction. This study aimed to explore the utility of the maximum expiratory flow-volume (MEFV) curve in the intrathoracic large airway obstruction (ILAO) retrospectively. Further, efforts were made to establish a predictive model to validate its predictive performance and identify potential discriminative indicators for ILAO. METHODS Study Design and Patient Characteristics This retrospective observational study was conducted in Zhongshan Hospital Fudan University. The study was approved by the Medical Ethics Committee of Zhongshan Hospital, Fudan University (Clinical Trial Number: B2022-264R) and all patients provided written informed consents. This study was conducted in accordance with the Declaration of Helsinki. Patients with ILAO were confirmed to suffer from ILAO through bronchoscopy, chest computerized tomography (CT) or surgical procedures and have no concurrent respiratory system diseases. Patients with COPD satisfied the diagnostic criteria for COPD as outlined in the 2023 Global Initiative for Chronic Obstructive Lung Disease (GOLD) guidelines( 4 ) and had no concurrent diseases that would influence the results of lung function tests. Information acquisition Clinical data were collected using a retrospective analysis approach. Demographic information, including patient gender, age, height, weight and body mass index (BMI), was recorded in detail, along with the data from lung function tests. Pulmonary function test Pulmonary function tests (PFTs) were conducted using the MS-PFT pulmonary function testing instrument produced by the German company Jaeger. These tests adhered to the pulmonary function testing standards formulated by the American Thoracic Society/European Respiratory Society (ATS/ERS)( 5 ). Environmental (including temperature, humidity, atmospheric pressure, etc.), volume and gas calibrations were carried out as required before daily testing. The standard procedure for lung function testing involved instructing patients to take a deep inhalation to total lung capacity and then perform a forced rapid exhalation until reaching residual volume. Then, patients were instructed to inhale forcefully back to total lung capacity to obtain a complete MEFV curve. This process was repeated three or more times to record the best value. Main parameters included forced vital capacity (FVC), forced expiratory volume in one second (FEV 1 ), peak expiratory flow (PEF), instantaneous expiratory flow at 25% of FVC (FEF 25% ), instantaneous expiratory flow at 50% of FVC (FEF 50% ), instantaneous expiratory flow at 75% of FVC (FEF 75% ) and the average expiratory flow between 25% and 75% of FVC (FEF 25 − 75% ). These values were expressed as a percentage of the predicted values. The FEV in 1 second to FVC ratio (FEV 1 /FVC) was represented using the measured value. Forced expiratory flow ratio and Empey’s index Commonly referred to as the “forced expiratory flow (FEF) ratio”, the FEF ratio at different time points, represents the ratio between the measured values of instantaneous expiratory flow at several different time points during forced exhalation and the predicted values such as FEF 50% /FEF 25% , FEF 75% /FEF 50% and FEF 75% /FEF 25% . Empey’s index is calculated as the measured value of FEV 1 divided by the measured value of PEF, namely FEV 1 /PEF (ml·L − 1 ·min − 1 )( 6 ). Statistical analysis The data were statistically analyzed using Statistical Package for the Social Sciences (SPSS) 22.0 software. Categorical data were indicated by percentages, and a variance test was used to make between-group comparisons. Pearson correlation analysis was utilized to evaluate the correlation between two variables. The predictive performance of each model was assessed by using the areas under the curve (AUCs), sensitivity and specificity of receiver operating characteristic (ROC) curves. A total of patients with ILAO and with COPD were divided at random into model and validation groups at a ratio of 1:1. The model group was used for establishing a predictive model for ILAO, while the validation one was utilized for assessing the predictive performance of the model. A significance level of P < 0.05 was considered to show statistical significance. RESULTS Baseline characteristics of the enrolled subjects In this study, 63 cases with ILAO who had sought medical care at the Tracheoscopy and Interventional Respiratory Disease Clinic of Zhongshan Hospital, Fudan University between January 2012 and December 2021 and 64 cases with COPD who had attended the COPD outpatient clinic were selected. Among patients with ILAO, 21, 10, 3, 11, 2 and 16 had pulmonary tumors, airway tumors, tracheobronchial amyloidosis, recurrent relapsing polychondritis, esophageal achalasia and airway scar stenosis, respectively. The baseline characteristics of the two groups are shown in Table 1 . The pulmonary ventilation function of the two groups was classified as follows based on the GOLD( 7 ): Among the 63 patients with ILAO, 33, 20 and 7 met the diagnostic criteria for obstructive, mixed and restrictive ventilatory dysfunction, respectively, and 3 had essentially normal lung ventilatory function. Among the 64 patients with COPD, 50 and 14 met the diagnostic criteria for obstructive and mixed ventilatory dysfunction, respectively. Table 1 Baseline characteristics of enrolled subjects Variables ILAO (n = 63) COPD (n = 64) P -value Age (yrs) 56.54 ± 12.97 60.47 ± 10.31 0.062 Sex (% men) 45 (71.4%) 54 (84.4%) 0.122 Height (cm) 168.00 ± 6.96 168.34 ± 5.77 0.762 Weight (Kg) 64.44 ± 12.94 67.75 ± 12.02 0.138 BMI (kg/m 2 ) 22.73 ± 3.86 23.90 ± 3.88 0.089 FVC%pred (%) 81.48 ± 18.84 77.96 ± 11.71 0.208 FEV 1 %pred (%) 54.03 ± 21.44 56.08 ± 12.79 0.512 FEV 1 /FVC (%) 54.22 ± 18.13 55.68 ± 8.92 0.566 PEF%pred (%) 31.69 ± 14.99 51.78 ± 14.57 0.000 FEF 25 %pred (%) 26.33 ± 14.42 30.61 ± 14.29 0.085 FEF 50 %pred (%) 33.38 ± 17.11 23.36 ± 10.20 0.000 FEF 75 %pred (%) 51.07 ± 27.77 26.66 ± 7.65 0.000 FEF 25 − 75 %pred (%) 35.66 ± 19.73 23.00 ± 8.19 0.000 FEF 50% /FEF 25% 1.31 ± 0.25 0.80 ± 0.15 0.000 FEF 75% /FEF 50% 1.61 ± 0.62 1.27 ± 0.45 0.000 FEF 75% /FEF 25% 2.17 ± 1.16 1.04 ± 0.48 0.001 Empey’s index 11.11 ± 3.65 5.97 ± 0.89 0.000 Data are presented as n (%) or mean ± SD. ILAO, intrathoracic large airway obstruction; COPD, chronic obstructive pulmonary disease; FVC, forced vital capacity; FEV 1 , forced expiratory volume in 1 s; PEF, peak expiratory flow; FEF, forced expiratory flow; FEF 25 , FEF at 25% of FVC exhaled; FEF 50 , FEF at 50% of FVC exhaled; FEF 75 , FEF at 75% of FVC exhaled; Empey’s index, FEV 1 /PEF (ml·L − 1·min − 1). Correlation coefficients between different ratios and pulmonary ventilation parameters of the two groups In the correlation analysis, both FEF 50% /FEF 25% and Empey’s index were positively associated with FVC (P < 0.05) but not correlated with FEV 1 for patients with ILAO. On the other hand, both FEF 50% /FEF 25% and Empey’s index were negatively associated with FEV 1 (P < 0.05) but not correlated with FVC for patients with COPD, as shown in Fig. 1 . Establishment and verification of the predictive model of ILAO A predictive model for ILAO was established with the model group. ROC curves were plotted by using the sensitivity and specificity determined from the FEF ratio (FEF 50% /FEF 25% ) and Empey’s index. The results showed that the cut-off values for FEF 50% /FEF 25% and Empey’s index were determined to be 0.960 and 7.415, respectively. Simultaneously, sensitivity and specificity were 81.3% and 87.5%, respectively, when FEF 50% /FEF 25% was ≥ 0.960 and Empey’s index was ≥ 7.415. The predictive performance of three ILAO prediction models was validated separately in the validation group. When the model of both FEF 50% /FEF 25% ≥0.960 and Empey’s index ≥ 7.415 was used, sensitivity and specificity were 67.7% and 81.3%, respectively, and positive and negative predictive values were 77.8% and 72.2%, respectively. The results are shown in Table 2 and Fig. 2 . Table 2 AUC and 95% CI of the FEF X % predicted and the Empey’s index to predict ILAO in model group and validation group AUC 95% CI cut-off Sensitivity(%) Specificity(%) PPV(%) NPV(%) Model group FEF 50% /FEF 25% 0.935 0.873–0.996 ## 0.960 93.8 87.5 FEF 75% /FEF 50% 0.623 0.484–0.762 FEF 75% /FEF 25% 0.795 0.686–0.903 ## Empey’s index 0.922 0.846–0.998 ## 7.415 84.4 100.0 Validation group FEF 50% /FEF 25% 0.992 0.978-1.000 ## 0.960 96.7 84.4 85.3 93.1 Empey’s index 0.879 0.793–0.966 ## 7.415 74.2 90.6 88.5 78.4 Definition #= P <0.05, ##= P <0.01, 95%CI = 95%Confidence interval;PPV = Positive Predictive Value;NPV = Negative Predictive Value. DISCUSSION Through the comparison between MFEV curves in patients with ILAO and COPD, it was found that flow parameters such as PEF, FEF 50% , FEF 75% and FEF 25 − 75% were conducive to better classifying the characteristics of MEFV curve in ILAO. This study is the first to analyze FEF ratios, specifically FEF 50% /FEF 25% , FEF 75% /FEF 50% and FEF 75% /FEF 25% . These ratios play a distinguishing role in airflow limitation resulting from large or small airway lesions. In particular, FEF 50% /FEF 25% and Empey’s index have satisfactory applicability for diagnosing the early ILAO. When a large airway lesion is obstructed, factors such as the size and location of the airway obstruction, the property of the lesion and the phase of forced expiration can all influence the MEFV curve( 8 ). As early as 1973, Miller and Hyatt described three different abnormal patterns of MEFV curves in their research: the variable extrathoracic, variable intrathoracic and fixed ILAO( 9 ). Therefore, clinicians make initial assessments of the location of airway lesions( 7 , 10 ) by evaluating the characteristics of different shapes of MEFV curves. In the case of central fixed airway obstruction and central variable airway obstruction, the MEFV curve shows a characteristic plateau-like change in the expiratory phase( 7 , 10 , 11 ). This change featuring a near-zero slope often occurs rapidly after the initial peak. The slope reproduces in the degree of unrelated forced expiration( 9 ). COPD is characterized by lung hyperinflation caused by expiratory flow limitation, which is primarily due to increased resistance in peripheral small airways and decreased lung elastic recoil( 12 ). MEFV curves in COPD typically exhibit reduced PEF at the beginning of the expiratory phase and a decrease in the descending limb flow. This flow reduction is often non-linear and correlates with the severity of obstruction. The damage to small airway structures will result in the intensification of airway closure and the decrease of both residual and functional residual volumes. The expiratory limb of the MEFV curve also demonstrates a distinct inflection point, followed by a sustained low-flow state( 13 ). This presentation can sometimes resemble the severe ILAO, as shown in Fig. 3 . To distinguish ILAO, the use of classic indicators such as FEV 1 , FEV 1 /FVC and FVC alone cannot comprehensively and objectively assess lung ventilation function, which potentially leads to the missing of valuable clinical information. It was observed that seven of the 63 patients with ILAO were misclassified as having restrictive ventilatory impairment due to the early termination of expiration leading to reduced FVC. Additionally, three patients were mistakenly categorized as having essentially normal lung ventilation because they only exhibited reduced PEF and FEF 25% . Moreover, 53 patients accounted for 84%. FEV 1 /FVC reduction is normally the primary focus in lung function reports, which gives rise to a classification of obstructive ventilatory impairment. That may cause ILAO to be easily overlooked by clinicians. This finding is consistent with previous research( 14 , 15 ) that FEV 1 is not particularly sensitive in diagnosing ILAO compared with PEF. As early as 1969, Miller and Hyatt conducted simulated experiments on healthy individuals and discovered that FEV 1 only showed a significant decrease when the tracheal diameter was less than 6 mm. The sensitivity of MEFV curves for detecting ILAO is not very high because the curve shape only becomes abnormal when the tracheal diameter is smaller than 8 mm( 14 ). Stoller also noticed that characteristic plateau-like changes are more likely to occur in the MEFV curve when the tracheal diameter is less than 8 mm (indicating the airway narrowing of more than 50%)( 16 ). In the case of ILAO, PEF is affected at the start of expiration at a high lung volume during a forceful exhalation, and FEV 1 % may still fall within the normal range at the moment( 14 , 15 ). According to a study from 1972, ILAO is likely present when Empey’s index exceeds 10, and a higher value suggests a more severe degree of ILAO( 6 , 17 ). Similar results were confirmed by Brookes and Fairfax( 18 ). In addition, some research suggests that Empey’s index ≥ 8 is related to the location, type and severity of ILAO( 19 ). This study determined the critical value of Empey’s index for diagnosing ILAO as 7.415 by ROC curves, with a specificity of 100%. This finding is in line with the discovery of Miller, who found that specificity reaches 94% when Empey’s index exceeds 8( 20 ). In this study, it was found that patients with ILAO have significantly lower PEF but higher FEF 50% , FEF 75% and FEF 25 − 75% than those with COPD, as shown in Fig. 3 . When ILAO is present, the expiratory flow at high lung volumes is dependent on the strength and influenced by the whole chest cage resistance, and the increased resistance at the narrowed site significantly reduces PEF at high lung volumes. Expiratory flow depends more on the resistance of peripheral airways at low lung volumes. During this phase, the degree of strength and resistance in central airways has no impact on expiratory flow( 6 ). Specific quantitative values were also used to show the shape characteristics of the MEFV curve, and a predictive model for ILAO was established for the first time. A comparison was made between the application of FEF ratios and Empey’s index for ILAO by ROC curves. It was noticed that the AUC for FEF 50% /FEF 25% is similar to that for Empey’s index and even larger than Empey’s index, and both of them exceeded 0.9. This suggests that FEF 50% /FEF 25% may play a similar role to Empey’s index in airway obstruction( 6 , 17 – 19 ). The specificity of the three predictive models for ILAO is higher than 78% found in previous studies based on the characteristics of MEFV curves( 20 ). Using the combination of qualitative and quantitative indicators for assessment can improve specificity and sensitivity( 19 ). In the overall sample, the correlation study also found that FEF 50% /FEF 25% in patients with COPD was negatively correlated with FEV 1 . In the case of severe COPD obstruction, a significant increase occurs in small airway resistance( 21 ), which ultimately leads to airway closure( 22 ). Additionally, the MEFV curve exhibits a noticeable inflection point in PEF, followed by a low-flow plateau( 23 – 25 ). As a result, FEF 50% /FEF 25% approaches 1. In contrast, FEF 50% /FEF 25% is unrelated to FEV 1 for patients with ILAO. When FEF 50% /FEF 25% is close to 1, it signifies that the decrease in FEF 50% and FEF 25% occurs in proportion. This concurs with the characteristics of a plateau-like change in the MEFV curve when expiratory airflow encounters ILAO in the first half of the forced expiration( 7 , 10 ). When FEF 50% /FEF 25% is greater than 1, it further suggests the possibility of ILAO. The predictive performance of the three models for ILAO was separately validated from the validation group. It showed good consistency with the model group, which indicated the strong discriminative ability and certain generalizability and clinical application of these three ILAO prediction models. Certain limitations exist in this study. The value of FEF 50% /FEF 25% and Empey’s index in the context of ILAO still require further validation in larger clinical cases. Furthermore, the relationships between the degree and length of tracheal stenosis caused by central airway disease and the parameters of the FEF ratio (FEF 50% /FEF 25% ), Empey’s index and characteristic changes in the MEFV curve warrant subgroup investigations. In summary, the MEFV curve is a simple, easily accessible, non-invasive and cost-effective pulmonary function test. Characteristic changes in the shape of MEFV curve help distinguish ILAO from peripheral small airway obstruction. The prediction models for ILAO established using FEF 50% /FEF 25% and Empey’s index exhibit good clinical value. It is expected that FEF 50% /FEF 25% and Empey’s index become a potential indicator to diagnose ILAO. Abbreviations ATS/ERS American Thoracic Society/European Respiratory Society AUCs Areas under the curve BMI Body Mass Index COPD Chronic obstructive pulmonary disease CT Computerized tomography FEF Forced expiratory flow FEF 25% Instantaneous expiratory flow at 25% of FVC FEF 50% Instantaneous expiratory flow at 50% of FVC FEF 75% Instantaneous expiratory flow at 75% of FVC FEF 25 − 75% Average expiratory flow between 25% and 75% of FVC FEV 1 Forced expiratory volume in one second FVC Forced vital capacity GOLD Global Initiative for Chronic Obstructive Lung Disease ILAO Intrathoracic large airway obstruction MEFV Maximum expiratory flow-volume PEF Peak expiratory flow PFTs Pulmonary function tests ROC Receiver operating characteristic Declarations Acknowledgements: The authors would like to express sincere thanks to all the staff of all the hospitals, and also to the patients for their contributions to the study. Authors’ Contribution: Li Li was the principal investigator of the study, with full responsibility for the contents of the manuscript, and contributed to all aspects of the manuscript. Ying Gong, Liping Xue and Xu Wu were responsible for the literature search, figures, data curation, data analysis, and data interpretation. Ying Gong and Weipeng Jiang wrote the original draft of this manuscript and all authors then critically reviewed it for important intellectual content. Zhiwen Shen, Chun Li and Yuanlin Song contributed to the study design, and acquisition, analysis, or interpretation of data. Ying Gong and Li Li have directly accessed and verified the data reported in the manuscript. All the authors reviewed and approved the final manuscript. Funding This study was supported by National key R&D plan (2020YFC2003700), Science and Technology Commission of Shanghai Municipality (20DZ2261200) and Shanghai Municipal Key Clinical Specialty (shslczdzk02201). Availability of data and materials The datasets used and/or analysed during the current study are available from the corresponding author on reasonable request. Ethics approval and consent to participate The study was approved by the Medical Ethics committee of Zhongshan Hospital Fudan University (Clinical Trial Number: B2022-264R) and all patients provided written informed consent. Consent for publication Not applicable. Competing interests No conflicts of interest to declare for the all authors . Author details a Department of Pulmonary and Critical Care Medicine, Zhongshan Hospital, Fudan University, Shanghai, 200032, China b Shanghai Respiratory Research Institute, Shanghai, 200032, China References Eber E. Evaluation of the upper airway. Paediatr Respir Rev. 2004;5(1):9–16. Ernst A, Feller-Kopman D, Becker HD, Mehta AC. Central airway obstruction. Am J Respir Crit Care Med. 2004;169(12):1278–97. Cavaliere S, Venuta F, Foccoli P, Toninelli C, La Face B. 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Small-airway obstruction and emphysema in chronic obstructive pulmonary disease. N Engl J Med. 2011;365(17):1567–75. Hogg JC, Chu F, Utokaparch S, Woods R, Elliott WM, Buzatu L, et al. The nature of small-airway obstruction in chronic obstructive pulmonary disease. N Engl J Med. 2004;350(26):2645–53. Campbell AH, Faulks LW. Expiratory air-flow pattern in tracheobronchial collapse. Am Rev Respir Dis. 1965;92(5):781–91. Grandevia B. The spirogram of gross expiratory tracheobronchial collapse in emphysema. Q J Med. 1963;32:23–31. Jayamanne DS, Epstein H, Goldring RM. Flow-volume curve contour in COPD: correlation with pulmonary mechanics. Chest. 1980;77(6):749–57. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted 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. 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Li","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA8UlEQVRIiWNgGAWjYBACPmYGxgMJFUCWBIhrABRhYGDDq4WNmYHhQMIZuBYDkHoCWoD4AGMbTAsDMVrYgVoezquzZ5BuPvy5oOCPPBsD+7MHDDV38DsscRtbYoPMsTTpGQYGhm0MPOYGDMeeEdLCk2B/I8eMmcfAAOhIHjYJxobDBLTMkbBnkMgx/gzUYt8GdBgRWhoMGBskcgykgVoSgUFhRkALY8OBhGMJiQ0SaSC/GCe3MfOYSSQcw62Fn//wwYc/aoAhJpEMDLE/crb97O3PJD7U4NbCwMDYAGcyw8kEPBpQADOxCkfBKBgFo2BkAQAPAUMPdyDIfwAAAABJRU5ErkJggg==","orcid":"","institution":"Fudan University","correspondingAuthor":true,"prefix":"","firstName":"Li","middleName":"","lastName":"Li","suffix":""}],"badges":[],"createdAt":"2024-06-06 04:52:50","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4537297/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4537297/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":60615324,"identity":"bcbec173-1077-4710-8dda-787507c4282a","added_by":"auto","created_at":"2024-07-18 20:11:37","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":228425,"visible":true,"origin":"","legend":"\u003cp\u003eCorrelation coefficients between different ratios and lung ventilation parameters of the ILAO group and the COPD group\u003c/p\u003e","description":"","filename":"Figure1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4537297/v1/93e6f519687edca42bc9dc7f.jpg"},{"id":60615325,"identity":"89f4453f-3e15-41c9-a7dd-1a9e865e9ffe","added_by":"auto","created_at":"2024-07-18 20:11:37","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":55664,"visible":true,"origin":"","legend":"\u003cp\u003eROC curves of the FEF\u003csub\u003eX\u003c/sub\u003e% predicted and the Empey’s index to predict ILAO\u003c/p\u003e\n\u003cp\u003e(A) ROC curves in model group\u003c/p\u003e\n\u003cp\u003e(B) ROC curves in validation group\u003c/p\u003e","description":"","filename":"Figure2.png","url":"https://assets-eu.researchsquare.com/files/rs-4537297/v1/723759697ae1dd5dcfa924c1.png"},{"id":60615323,"identity":"ac3235ac-7e92-487d-8d4f-d75d6b4c968c","added_by":"auto","created_at":"2024-07-18 20:11:37","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":160663,"visible":true,"origin":"","legend":"\u003cp\u003eThe MEFV curves of ILAO and COPD\u003c/p\u003e","description":"","filename":"Figure3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4537297/v1/64c0cabffd5a437e7f278c9b.jpg"},{"id":75521091,"identity":"ebaa3181-e6b4-4637-96dd-e00bab0c5dac","added_by":"auto","created_at":"2025-02-05 12:09:00","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1232342,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4537297/v1/aabdd876-b001-47d3-a3e9-2d2feeb5b0f0.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Application of MEFV Curve in the Intrathoracic Large Airway Obstruction: a retrospective study","fulltext":[{"header":"BACKGROUND","content":"\u003cp\u003eThe airways are divided into large and medium/small airways according to anatomical characteristics. Large airways, which refer to airways with a diameter greater than 2 mm, including upper airways and the main bronchi around the carina, are characterized by smaller cross-sectional areas, high resistance, tough and rigid tissues, as well as support from cartilaginous rings(\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e). Obstruction in large airways can be caused by various factors such as tumors, endobronchial tuberculosis and foreign bodies. It lacks specificity in clinical symptoms and signs despite being common in clinical practice, and patients commonly present varying degrees of wheezing. Moreover, the condition progresses slowly, which often leads to misdiagnosis or underdiagnosis, particularly as it can be mistaken for chronic airway disease caused by peripheral small airway obstruction like chronic obstructive pulmonary disease (COPD) and other conditions. The early assessment of large airway obstruction in clinical practice remains a great challenge.\u003c/p\u003e \u003cp\u003eIn recent advances, bronchoscopy was proposed as a necessary procedure for the diagnosis of large airway obstruction. Only through bronchoscopy, can the nature, location and extent of a lesion be visually demonstrated. As an invasive procedure, however, it cannot reflect respiratory physiological function(\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e \u003cp\u003ePulmonary function testing, one of the important ancillary examinations for respiratory system diseases, is widely used for the diagnosis and assessment of disease severity or prognosis, as well as the preoperative evaluation of surgical endurance. Nevertheless, little research has been conducted on the application of pulmonary function testing in the context of large airway obstruction. This study aimed to explore the utility of the maximum expiratory flow-volume (MEFV) curve in the intrathoracic large airway obstruction (ILAO) retrospectively. Further, efforts were made to establish a predictive model to validate its predictive performance and identify potential discriminative indicators for ILAO.\u003c/p\u003e"},{"header":"METHODS","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStudy Design and Patient Characteristics\u003c/h2\u003e \u003cp\u003eThis retrospective observational study was conducted in Zhongshan Hospital Fudan University. The study was approved by the Medical Ethics Committee of Zhongshan Hospital, Fudan University (Clinical Trial Number: B2022-264R) and all patients provided written informed consents. This study was conducted in accordance with the Declaration of Helsinki.\u003c/p\u003e \u003cp\u003ePatients with ILAO were confirmed to suffer from ILAO through bronchoscopy, chest computerized tomography (CT) or surgical procedures and have no concurrent respiratory system diseases.\u003c/p\u003e \u003cp\u003ePatients with COPD satisfied the diagnostic criteria for COPD as outlined in the 2023 Global Initiative for Chronic Obstructive Lung Disease (GOLD) guidelines(\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e) and had no concurrent diseases that would influence the results of lung function tests.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eInformation acquisition\u003c/h2\u003e \u003cp\u003eClinical data were collected using a retrospective analysis approach. Demographic information, including patient gender, age, height, weight and body mass index (BMI), was recorded in detail, along with the data from lung function tests.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003ePulmonary function test\u003c/h2\u003e \u003cp\u003ePulmonary function tests (PFTs) were conducted using the MS-PFT pulmonary function testing instrument produced by the German company Jaeger. These tests adhered to the pulmonary function testing standards formulated by the American Thoracic Society/European Respiratory Society (ATS/ERS)(\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e). Environmental (including temperature, humidity, atmospheric pressure, etc.), volume and gas calibrations were carried out as required before daily testing.\u003c/p\u003e \u003cp\u003eThe standard procedure for lung function testing involved instructing patients to take a deep inhalation to total lung capacity and then perform a forced rapid exhalation until reaching residual volume. Then, patients were instructed to inhale forcefully back to total lung capacity to obtain a complete MEFV curve. This process was repeated three or more times to record the best value.\u003c/p\u003e \u003cp\u003eMain parameters included forced vital capacity (FVC), forced expiratory volume in one second (FEV\u003csub\u003e1\u003c/sub\u003e), peak expiratory flow (PEF), instantaneous expiratory flow at 25% of FVC (FEF\u003csub\u003e25%\u003c/sub\u003e), instantaneous expiratory flow at 50% of FVC (FEF\u003csub\u003e50%\u003c/sub\u003e), instantaneous expiratory flow at 75% of FVC (FEF\u003csub\u003e75%\u003c/sub\u003e) and the average expiratory flow between 25% and 75% of FVC (FEF\u003csub\u003e25\u0026thinsp;\u0026minus;\u0026thinsp;75%\u003c/sub\u003e). These values were expressed as a percentage of the predicted values. The FEV in 1 second to FVC ratio (FEV\u003csub\u003e1\u003c/sub\u003e/FVC) was represented using the measured value.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eForced expiratory flow ratio and Empey\u0026rsquo;s index\u003c/h2\u003e \u003cp\u003eCommonly referred to as the \u0026ldquo;forced expiratory flow (FEF) ratio\u0026rdquo;, the FEF ratio at different time points, represents the ratio between the measured values of instantaneous expiratory flow at several different time points during forced exhalation and the predicted values such as FEF\u003csub\u003e50%\u003c/sub\u003e/FEF\u003csub\u003e25%\u003c/sub\u003e, FEF\u003csub\u003e75%\u003c/sub\u003e/FEF\u003csub\u003e50%\u003c/sub\u003e and FEF\u003csub\u003e75%\u003c/sub\u003e/FEF\u003csub\u003e25%\u003c/sub\u003e.\u003c/p\u003e \u003cp\u003eEmpey\u0026rsquo;s index is calculated as the measured value of FEV\u003csub\u003e1\u003c/sub\u003e divided by the measured value of PEF, namely FEV\u003csub\u003e1\u003c/sub\u003e/PEF (ml\u0026middot;L\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e\u0026middot;min\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e)(\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis\u003c/h2\u003e \u003cp\u003eThe data were statistically analyzed using Statistical Package for the Social Sciences (SPSS) 22.0 software. Categorical data were indicated by percentages, and a variance test was used to make between-group comparisons. Pearson correlation analysis was utilized to evaluate the correlation between two variables. The predictive performance of each model was assessed by using the areas under the curve (AUCs), sensitivity and specificity of receiver operating characteristic (ROC) curves. A total of patients with ILAO and with COPD were divided at random into model and validation groups at a ratio of 1:1. The model group was used for establishing a predictive model for ILAO, while the validation one was utilized for assessing the predictive performance of the model. A significance level of P\u0026thinsp;\u0026lt;\u0026thinsp;0.05 was considered to show statistical significance.\u003c/p\u003e \u003c/div\u003e"},{"header":"RESULTS","content":"\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003eBaseline characteristics of the enrolled subjects\u003c/h2\u003e \u003cp\u003e In this study, 63 cases with ILAO who had sought medical care at the Tracheoscopy and Interventional Respiratory Disease Clinic of Zhongshan Hospital, Fudan University between January 2012 and December 2021 and 64 cases with COPD who had attended the COPD outpatient clinic were selected. Among patients with ILAO, 21, 10, 3, 11, 2 and 16 had pulmonary tumors, airway tumors, tracheobronchial amyloidosis, recurrent relapsing polychondritis, esophageal achalasia and airway scar stenosis, respectively. The baseline characteristics of the two groups are shown in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. The pulmonary ventilation function of the two groups was classified as follows based on the GOLD(\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e): Among the 63 patients with ILAO, 33, 20 and 7 met the diagnostic criteria for obstructive, mixed and restrictive ventilatory dysfunction, respectively, and 3 had essentially normal lung ventilatory function. Among the 64 patients with COPD, 50 and 14 met the diagnostic criteria for obstructive and mixed ventilatory dysfunction, respectively.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eBaseline characteristics of enrolled subjects\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eILAO (n\u0026thinsp;=\u0026thinsp;63)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCOPD (n\u0026thinsp;=\u0026thinsp;64)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e-value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge (yrs)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e56.54\u0026thinsp;\u0026plusmn;\u0026thinsp;12.97\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e60.47\u0026thinsp;\u0026plusmn;\u0026thinsp;10.31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.062\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSex (% men)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e45 (71.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e54 (84.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.122\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHeight (cm)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e168.00\u0026thinsp;\u0026plusmn;\u0026thinsp;6.96\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e168.34\u0026thinsp;\u0026plusmn;\u0026thinsp;5.77\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.762\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWeight (Kg)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e64.44\u0026thinsp;\u0026plusmn;\u0026thinsp;12.94\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e67.75\u0026thinsp;\u0026plusmn;\u0026thinsp;12.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.138\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBMI (kg/m\u003csup\u003e2\u003c/sup\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e22.73\u0026thinsp;\u0026plusmn;\u0026thinsp;3.86\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e23.90\u0026thinsp;\u0026plusmn;\u0026thinsp;3.88\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.089\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFVC%pred (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e81.48\u0026thinsp;\u0026plusmn;\u0026thinsp;18.84\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e77.96\u0026thinsp;\u0026plusmn;\u0026thinsp;11.71\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.208\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFEV\u003csub\u003e1\u003c/sub\u003e%pred (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e54.03\u0026thinsp;\u0026plusmn;\u0026thinsp;21.44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e56.08\u0026thinsp;\u0026plusmn;\u0026thinsp;12.79\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.512\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFEV\u003csub\u003e1\u003c/sub\u003e/FVC (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e54.22\u0026thinsp;\u0026plusmn;\u0026thinsp;18.13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e55.68\u0026thinsp;\u0026plusmn;\u0026thinsp;8.92\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.566\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePEF%pred (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e31.69\u0026thinsp;\u0026plusmn;\u0026thinsp;14.99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e51.78\u0026thinsp;\u0026plusmn;\u0026thinsp;14.57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFEF\u003csub\u003e25\u003c/sub\u003e%pred (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e26.33\u0026thinsp;\u0026plusmn;\u0026thinsp;14.42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e30.61\u0026thinsp;\u0026plusmn;\u0026thinsp;14.29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.085\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFEF\u003csub\u003e50\u003c/sub\u003e%pred (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e33.38\u0026thinsp;\u0026plusmn;\u0026thinsp;17.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e23.36\u0026thinsp;\u0026plusmn;\u0026thinsp;10.20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFEF\u003csub\u003e75\u003c/sub\u003e%pred (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e51.07\u0026thinsp;\u0026plusmn;\u0026thinsp;27.77\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e26.66\u0026thinsp;\u0026plusmn;\u0026thinsp;7.65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFEF\u003csub\u003e25\u0026thinsp;\u0026minus;\u0026thinsp;75\u003c/sub\u003e%pred (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e35.66\u0026thinsp;\u0026plusmn;\u0026thinsp;19.73\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e23.00\u0026thinsp;\u0026plusmn;\u0026thinsp;8.19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFEF\u003csub\u003e50%\u003c/sub\u003e/FEF\u003csub\u003e25%\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.31\u0026thinsp;\u0026plusmn;\u0026thinsp;0.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.80\u0026thinsp;\u0026plusmn;\u0026thinsp;0.15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFEF\u003csub\u003e75%\u003c/sub\u003e/FEF\u003csub\u003e50%\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.61\u0026thinsp;\u0026plusmn;\u0026thinsp;0.62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.27\u0026thinsp;\u0026plusmn;\u0026thinsp;0.45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFEF\u003csub\u003e75%\u003c/sub\u003e/FEF\u003csub\u003e25%\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.17\u0026thinsp;\u0026plusmn;\u0026thinsp;1.16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.04\u0026thinsp;\u0026plusmn;\u0026thinsp;0.48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEmpey\u0026rsquo;s index\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e11.11\u0026thinsp;\u0026plusmn;\u0026thinsp;3.65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.97\u0026thinsp;\u0026plusmn;\u0026thinsp;0.89\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eData are presented as n (%) or mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD. ILAO, intrathoracic large airway obstruction; COPD, chronic obstructive pulmonary disease; FVC, forced vital capacity; FEV\u003csub\u003e1\u003c/sub\u003e, forced expiratory volume in 1 s; PEF, peak expiratory flow; FEF, forced expiratory flow; FEF\u003csub\u003e25\u003c/sub\u003e, FEF at 25% of FVC exhaled; FEF\u003csub\u003e50\u003c/sub\u003e, FEF at 50% of FVC exhaled; FEF\u003csub\u003e75\u003c/sub\u003e, FEF at 75% of FVC exhaled; Empey\u0026rsquo;s index, FEV\u003csub\u003e1\u003c/sub\u003e/PEF (ml\u0026middot;L\u0026thinsp;\u0026minus;\u0026thinsp;1\u0026middot;min\u0026thinsp;\u0026minus;\u0026thinsp;1).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003eCorrelation coefficients between different ratios and pulmonary ventilation parameters of the two groups\u003c/h2\u003e \u003cp\u003eIn the correlation analysis, both FEF\u003csub\u003e50%\u003c/sub\u003e/FEF\u003csub\u003e25%\u003c/sub\u003e and Empey\u0026rsquo;s index were positively associated with FVC (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05) but not correlated with FEV\u003csub\u003e1\u003c/sub\u003e for patients with ILAO. On the other hand, both FEF\u003csub\u003e50%\u003c/sub\u003e/FEF\u003csub\u003e25%\u003c/sub\u003e and Empey\u0026rsquo;s index were negatively associated with FEV\u003csub\u003e1\u003c/sub\u003e (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05) but not correlated with FVC for patients with COPD, as shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eEstablishment and verification of the predictive model of ILAO\u003c/h2\u003e \u003cp\u003eA predictive model for ILAO was established with the model group. ROC curves were plotted by using the sensitivity and specificity determined from the FEF ratio (FEF\u003csub\u003e50%\u003c/sub\u003e/FEF\u003csub\u003e25%\u003c/sub\u003e) and Empey\u0026rsquo;s index. The results showed that the cut-off values for FEF\u003csub\u003e50%\u003c/sub\u003e/FEF\u003csub\u003e25%\u003c/sub\u003e and Empey\u0026rsquo;s index were determined to be 0.960 and 7.415, respectively. Simultaneously, sensitivity and specificity were 81.3% and 87.5%, respectively, when FEF\u003csub\u003e50%\u003c/sub\u003e/FEF\u003csub\u003e25%\u003c/sub\u003e was \u0026ge;\u0026thinsp;0.960 and Empey\u0026rsquo;s index was \u0026ge;\u0026thinsp;7.415. The predictive performance of three ILAO prediction models was validated separately in the validation group. When the model of both FEF\u003csub\u003e50%\u003c/sub\u003e/FEF\u003csub\u003e25%\u003c/sub\u003e\u0026ge;0.960 and Empey\u0026rsquo;s index\u0026thinsp;\u0026ge;\u0026thinsp;7.415 was used, sensitivity and specificity were 67.7% and 81.3%, respectively, and positive and negative predictive values were 77.8% and 72.2%, respectively. The results are shown in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e and Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eAUC and 95% CI of the FEF\u003csub\u003eX\u003c/sub\u003e% predicted and the Empey\u0026rsquo;s index to predict ILAO in model group and validation group\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"8\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAUC\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e95% CI\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003ecut-off\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eSensitivity(%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eSpecificity(%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003ePPV(%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eNPV(%)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eModel group\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFEF\u003csub\u003e50%\u003c/sub\u003e/FEF\u003csub\u003e25%\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.935\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.873\u0026ndash;0.996\u003csup\u003e##\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.960\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e93.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e87.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFEF\u003csub\u003e75%\u003c/sub\u003e/FEF\u003csub\u003e50%\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.623\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.484\u0026ndash;0.762\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFEF\u003csub\u003e75%\u003c/sub\u003e/FEF\u003csub\u003e25%\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.795\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.686\u0026ndash;0.903\u003csup\u003e##\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEmpey\u0026rsquo;s index\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.922\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.846\u0026ndash;0.998\u003csup\u003e##\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e7.415\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e84.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e100.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eValidation group\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFEF\u003csub\u003e50%\u003c/sub\u003e/FEF\u003csub\u003e25%\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.992\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.978-1.000\u003csup\u003e##\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.960\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e96.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e84.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e85.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e93.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEmpey\u0026rsquo;s index\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.879\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.793\u0026ndash;0.966\u003csup\u003e##\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e7.415\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e74.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e90.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e88.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e78.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eDefinition\u003c/strong\u003e \u003cp\u003e#=\u003cem\u003eP\u003c/em\u003e\u0026lt;0.05, ##=\u003cem\u003eP\u003c/em\u003e\u0026lt;0.01, 95%CI\u0026thinsp;=\u0026thinsp;95%Confidence interval;PPV\u0026thinsp;=\u0026thinsp;Positive Predictive Value;NPV\u0026thinsp;=\u0026thinsp;Negative Predictive Value.\u003c/p\u003e \u003c/div\u003e"},{"header":"DISCUSSION","content":"\u003cp\u003eThrough the comparison between MFEV curves in patients with ILAO and COPD, it was found that flow parameters such as PEF, FEF\u003csub\u003e50%\u003c/sub\u003e, FEF\u003csub\u003e75%\u003c/sub\u003e and FEF\u003csub\u003e25\u0026thinsp;\u0026minus;\u0026thinsp;75%\u003c/sub\u003e were conducive to better classifying the characteristics of MEFV curve in ILAO. This study is the first to analyze FEF ratios, specifically FEF\u003csub\u003e50%\u003c/sub\u003e/FEF\u003csub\u003e25%\u003c/sub\u003e, FEF\u003csub\u003e75%\u003c/sub\u003e/FEF\u003csub\u003e50%\u003c/sub\u003e and FEF\u003csub\u003e75%\u003c/sub\u003e/FEF\u003csub\u003e25%\u003c/sub\u003e. These ratios play a distinguishing role in airflow limitation resulting from large or small airway lesions. In particular, FEF\u003csub\u003e50%\u003c/sub\u003e/FEF\u003csub\u003e25%\u003c/sub\u003e and Empey\u0026rsquo;s index have satisfactory applicability for diagnosing the early ILAO.\u003c/p\u003e \u003cp\u003eWhen a large airway lesion is obstructed, factors such as the size and location of the airway obstruction, the property of the lesion and the phase of forced expiration can all influence the MEFV curve(\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e). As early as 1973, Miller and Hyatt described three different abnormal patterns of MEFV curves in their research: the variable extrathoracic, variable intrathoracic and fixed ILAO(\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e). Therefore, clinicians make initial assessments of the location of airway lesions(\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e) by evaluating the characteristics of different shapes of MEFV curves. In the case of central fixed airway obstruction and central variable airway obstruction, the MEFV curve shows a characteristic plateau-like change in the expiratory phase(\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e). This change featuring a near-zero slope often occurs rapidly after the initial peak. The slope reproduces in the degree of unrelated forced expiration(\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e). COPD is characterized by lung hyperinflation caused by expiratory flow limitation, which is primarily due to increased resistance in peripheral small airways and decreased lung elastic recoil(\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e). MEFV curves in COPD typically exhibit reduced PEF at the beginning of the expiratory phase and a decrease in the descending limb flow. This flow reduction is often non-linear and correlates with the severity of obstruction. The damage to small airway structures will result in the intensification of airway closure and the decrease of both residual and functional residual volumes. The expiratory limb of the MEFV curve also demonstrates a distinct inflection point, followed by a sustained low-flow state(\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e). This presentation can sometimes resemble the severe ILAO, as shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eTo distinguish ILAO, the use of classic indicators such as FEV\u003csub\u003e1\u003c/sub\u003e, FEV\u003csub\u003e1\u003c/sub\u003e/FVC and FVC alone cannot comprehensively and objectively assess lung ventilation function, which potentially leads to the missing of valuable clinical information. It was observed that seven of the 63 patients with ILAO were misclassified as having restrictive ventilatory impairment due to the early termination of expiration leading to reduced FVC. Additionally, three patients were mistakenly categorized as having essentially normal lung ventilation because they only exhibited reduced PEF and FEF\u003csub\u003e25%\u003c/sub\u003e. Moreover, 53 patients accounted for 84%. FEV\u003csub\u003e1\u003c/sub\u003e/FVC reduction is normally the primary focus in lung function reports, which gives rise to a classification of obstructive ventilatory impairment. That may cause ILAO to be easily overlooked by clinicians. This finding is consistent with previous research(\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e) that FEV\u003csub\u003e1\u003c/sub\u003e is not particularly sensitive in diagnosing ILAO compared with PEF. As early as 1969, Miller and Hyatt conducted simulated experiments on healthy individuals and discovered that FEV\u003csub\u003e1\u003c/sub\u003e only showed a significant decrease when the tracheal diameter was less than 6 mm. The sensitivity of MEFV curves for detecting ILAO is not very high because the curve shape only becomes abnormal when the tracheal diameter is smaller than 8 mm(\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e). Stoller also noticed that characteristic plateau-like changes are more likely to occur in the MEFV curve when the tracheal diameter is less than 8 mm (indicating the airway narrowing of more than 50%)(\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIn the case of ILAO, PEF is affected at the start of expiration at a high lung volume during a forceful exhalation, and FEV\u003csub\u003e1\u003c/sub\u003e% may still fall within the normal range at the moment(\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e). According to a study from 1972, ILAO is likely present when Empey\u0026rsquo;s index exceeds 10, and a higher value suggests a more severe degree of ILAO(\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e). Similar results were confirmed by Brookes and Fairfax(\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e). In addition, some research suggests that Empey\u0026rsquo;s index\u0026thinsp;\u0026ge;\u0026thinsp;8 is related to the location, type and severity of ILAO(\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e). This study determined the critical value of Empey\u0026rsquo;s index for diagnosing ILAO as 7.415 by ROC curves, with a specificity of 100%. This finding is in line with the discovery of Miller, who found that specificity reaches 94% when Empey\u0026rsquo;s index exceeds 8(\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIn this study, it was found that patients with ILAO have significantly lower PEF but higher FEF\u003csub\u003e50%\u003c/sub\u003e, FEF\u003csub\u003e75%\u003c/sub\u003e and FEF\u003csub\u003e25\u0026thinsp;\u0026minus;\u0026thinsp;75%\u003c/sub\u003e than those with COPD, as shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e. When ILAO is present, the expiratory flow at high lung volumes is dependent on the strength and influenced by the whole chest cage resistance, and the increased resistance at the narrowed site significantly reduces PEF at high lung volumes. Expiratory flow depends more on the resistance of peripheral airways at low lung volumes. During this phase, the degree of strength and resistance in central airways has no impact on expiratory flow(\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eSpecific quantitative values were also used to show the shape characteristics of the MEFV curve, and a predictive model for ILAO was established for the first time. A comparison was made between the application of FEF ratios and Empey\u0026rsquo;s index for ILAO by ROC curves. It was noticed that the AUC for FEF\u003csub\u003e50%\u003c/sub\u003e/FEF\u003csub\u003e25%\u003c/sub\u003e is similar to that for Empey\u0026rsquo;s index and even larger than Empey\u0026rsquo;s index, and both of them exceeded 0.9. This suggests that FEF\u003csub\u003e50%\u003c/sub\u003e/FEF\u003csub\u003e25%\u003c/sub\u003e may play a similar role to Empey\u0026rsquo;s index in airway obstruction(\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan additionalcitationids=\"CR18\" citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe specificity of the three predictive models for ILAO is higher than 78% found in previous studies based on the characteristics of MEFV curves(\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e). Using the combination of qualitative and quantitative indicators for assessment can improve specificity and sensitivity(\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIn the overall sample, the correlation study also found that FEF\u003csub\u003e50%\u003c/sub\u003e/FEF\u003csub\u003e25%\u003c/sub\u003e in patients with COPD was negatively correlated with FEV\u003csub\u003e1\u003c/sub\u003e. In the case of severe COPD obstruction, a significant increase occurs in small airway resistance(\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e), which ultimately leads to airway closure(\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e). Additionally, the MEFV curve exhibits a noticeable inflection point in PEF, followed by a low-flow plateau(\u003cspan additionalcitationids=\"CR24\" citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e). As a result, FEF\u003csub\u003e50%\u003c/sub\u003e/FEF\u003csub\u003e25%\u003c/sub\u003e approaches 1. In contrast, FEF\u003csub\u003e50%\u003c/sub\u003e/FEF\u003csub\u003e25%\u003c/sub\u003e is unrelated to FEV\u003csub\u003e1\u003c/sub\u003e for patients with ILAO. When FEF\u003csub\u003e50%\u003c/sub\u003e/FEF\u003csub\u003e25%\u003c/sub\u003e is close to 1, it signifies that the decrease in FEF\u003csub\u003e50%\u003c/sub\u003e and FEF\u003csub\u003e25%\u003c/sub\u003e occurs in proportion. This concurs with the characteristics of a plateau-like change in the MEFV curve when expiratory airflow encounters ILAO in the first half of the forced expiration(\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e). When FEF\u003csub\u003e50%\u003c/sub\u003e/FEF\u003csub\u003e25%\u003c/sub\u003e is greater than 1, it further suggests the possibility of ILAO.\u003c/p\u003e \u003cp\u003eThe predictive performance of the three models for ILAO was separately validated from the validation group. It showed good consistency with the model group, which indicated the strong discriminative ability and certain generalizability and clinical application of these three ILAO prediction models.\u003c/p\u003e \u003cp\u003eCertain limitations exist in this study. The value of FEF\u003csub\u003e50%\u003c/sub\u003e/FEF\u003csub\u003e25%\u003c/sub\u003e and Empey\u0026rsquo;s index in the context of ILAO still require further validation in larger clinical cases. Furthermore, the relationships between the degree and length of tracheal stenosis caused by central airway disease and the parameters of the FEF ratio (FEF\u003csub\u003e50%\u003c/sub\u003e/FEF\u003csub\u003e25%\u003c/sub\u003e), Empey\u0026rsquo;s index and characteristic changes in the MEFV curve warrant subgroup investigations.\u003c/p\u003e \u003cp\u003eIn summary, the MEFV curve is a simple, easily accessible, non-invasive and cost-effective pulmonary function test. Characteristic changes in the shape of MEFV curve help distinguish ILAO from peripheral small airway obstruction. The prediction models for ILAO established using FEF\u003csub\u003e50%\u003c/sub\u003e/FEF\u003csub\u003e25%\u003c/sub\u003e and Empey\u0026rsquo;s index exhibit good clinical value. It is expected that FEF\u003csub\u003e50%\u003c/sub\u003e/FEF\u003csub\u003e25%\u003c/sub\u003e and Empey\u0026rsquo;s index become a potential indicator to diagnose ILAO.\u003c/p\u003e"},{"header":"Abbreviations","content":" \u003cp\u003eATS/ERS American Thoracic Society/European Respiratory Society\u003c/p\u003e \u003cp\u003eAUCs Areas under the curve\u003c/p\u003e \u003cp\u003eBMI Body Mass Index\u003c/p\u003e \u003cp\u003eCOPD Chronic obstructive pulmonary disease\u003c/p\u003e \u003cp\u003eCT Computerized tomography\u003c/p\u003e \u003cp\u003eFEF Forced expiratory flow\u003c/p\u003e \u003cp\u003eFEF\u003csub\u003e25%\u003c/sub\u003e Instantaneous expiratory flow at 25% of FVC\u003c/p\u003e \u003cp\u003eFEF\u003csub\u003e50%\u003c/sub\u003e Instantaneous expiratory flow at 50% of FVC\u003c/p\u003e \u003cp\u003eFEF\u003csub\u003e75%\u003c/sub\u003e Instantaneous expiratory flow at 75% of FVC\u003c/p\u003e \u003cp\u003eFEF\u003csub\u003e25\u0026thinsp;\u0026minus;\u0026thinsp;75%\u003c/sub\u003e Average expiratory flow between 25% and 75% of FVC\u003c/p\u003e \u003cp\u003eFEV\u003csub\u003e1\u003c/sub\u003e Forced expiratory volume in one second\u003c/p\u003e \u003cp\u003eFVC Forced vital capacity\u003c/p\u003e \u003cp\u003eGOLD Global Initiative for Chronic Obstructive Lung Disease\u003c/p\u003e \u003cp\u003eILAO Intrathoracic large airway obstruction\u003c/p\u003e \u003cp\u003eMEFV Maximum expiratory flow-volume\u003c/p\u003e \u003cp\u003ePEF Peak expiratory flow\u003c/p\u003e \u003cp\u003ePFTs Pulmonary function tests\u003c/p\u003e \u003cp\u003eROC Receiver operating characteristic\u003c/p\u003e "},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgements:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors would like to express sincere thanks to all the staff of all the hospitals, and also to the patients for their contributions to the study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026rsquo; Contribution:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eLi Li was the principal investigator of the study, with full responsibility for the contents of the manuscript, and contributed to all aspects of the manuscript. Ying Gong, Liping Xue and Xu Wu were responsible for the literature search, figures, data curation, data analysis, and data interpretation. Ying Gong and Weipeng Jiang wrote the original draft of this manuscript and all authors then critically reviewed it for important intellectual content. Zhiwen Shen, Chun Li and Yuanlin Song contributed to the study design, and acquisition, analysis, or interpretation of data. Ying Gong and Li Li have directly accessed and verified the data reported in the manuscript. All the authors reviewed and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was supported by National key R\u0026amp;D plan (2020YFC2003700), Science and Technology Commission of Shanghai Municipality (20DZ2261200) and Shanghai Municipal Key Clinical Specialty (shslczdzk02201).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets used and/or analysed during the current study are available from the corresponding author on reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe study was approved by the Medical Ethics committee of Zhongshan Hospital Fudan University (Clinical Trial Number: B2022-264R) and all patients provided written informed consent.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNo conflicts of interest to declare for the all authors\u003cstrong\u003e.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor details\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003ea Department of Pulmonary and Critical Care Medicine, Zhongshan Hospital, Fudan University, Shanghai, 200032, China\u003c/p\u003e\n\u003cp\u003eb Shanghai Respiratory Research Institute, Shanghai, 200032, China\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eEber E. Evaluation of the upper airway. Paediatr Respir Rev. 2004;5(1):9\u0026ndash;16.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eErnst A, Feller-Kopman D, Becker HD, Mehta AC. Central airway obstruction. Am J Respir Crit Care Med. 2004;169(12):1278\u0026ndash;97.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCavaliere S, Venuta F, Foccoli P, Toninelli C, La Face B. Endoscopic treatment of malignant airway obstructions in 2,008 patients. Chest. 1996;110(6):1536\u0026ndash;42.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGlobal strategy for the diagnosis. management and prevention of chronic obstructive pulmonary disease (2023 report) 2022 [ \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://goldcopd.org/archived-reports/\u003c/span\u003e\u003cspan address=\"https://goldcopd.org/archived-reports/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\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(8):e70\u0026ndash;88.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eEmpey DW. Assessment of upper airways obstruction. BMJ. 1972;3(5825):503\u0026ndash;5.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePulmonary Function Group CRS. Guidelines for Pulmonary Function Testing (Part 2) -Spirometry %J Chinese Journal of Tuberculosis and Respiratory Diseases %J. Chin J Tuberculosis Respiratory Dis. 2014;37(7):481\u0026ndash;6.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAcres JC, Kryger MH. Clinical significance of pulmonary function tests: upper airway obstruction. Chest. 1981;80(2):207\u0026ndash;11.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMiller RD, Hyatt RE. Evaluation of obstructing lesions of the trachea and larynx by flow-volume loops. Am Rev Respir Dis. 1973;108(3):475\u0026ndash;81.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMiller MR, Hankinson J, Brusasco V, Burgos F, Casaburi R, Coates A, et al. Standardisation of spirometry. Eur Respir J. 2005;26(2):319\u0026ndash;38.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHyatt RE. Evaluation of major airway lesions using the flow-volume loop. The Annals of otology, rhinology, and laryngology. 1975;84(5 Pt 1):635\u0026ndash;42.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDas N, Topalovic M, Aerts JM, Janssens W. Area under the forced expiratory flow-volume loop in spirometry indicates severe hyperinflation in COPD patients. Int J Chron Obstruct Pulmon Dis. 2019;14:409\u0026ndash;18.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMurgu SD, Colt HG. Tracheobronchomalacia and excessive dynamic airway collapse. Respirology. 2006;11(4):388\u0026ndash;406.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMiller RD, Hyatt RE. Obstructing lesions of the larynx and trachea: clinical and physiologic characteristics. 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Contribution of flow-volume curves to the detection of central airway obstruction. Jornal brasileiro de pneumologia: publicacao oficial da Sociedade Brasileira de Pneumologia e Tisilogia. 2013;39(4):447\u0026ndash;54.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMiller MR, Pincock AC, Oates GD, Wilkinson R, Skene-Smith H. Upper airway obstruction due to goitre: detection, prevalence and results of surgical management. Q J Med. 1990;74(274):177\u0026ndash;88.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMcDonough JE, Yuan R, Suzuki M, Seyednejad N, Elliott WM, Sanchez PG, et al. Small-airway obstruction and emphysema in chronic obstructive pulmonary disease. N Engl J Med. 2011;365(17):1567\u0026ndash;75.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHogg JC, Chu F, Utokaparch S, Woods R, Elliott WM, Buzatu L, et al. The nature of small-airway obstruction in chronic obstructive pulmonary disease. N Engl J Med. 2004;350(26):2645\u0026ndash;53.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCampbell AH, Faulks LW. Expiratory air-flow pattern in tracheobronchial collapse. Am Rev Respir Dis. 1965;92(5):781\u0026ndash;91.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGrandevia B. The spirogram of gross expiratory tracheobronchial collapse in emphysema. Q J Med. 1963;32:23\u0026ndash;31.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eJayamanne DS, Epstein H, Goldring RM. Flow-volume curve contour in COPD: correlation with pulmonary mechanics. Chest. 1980;77(6):749\u0026ndash;57.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Large Airway Obstruction, MEFV Curve, FEF Ratios, Empey’s Index, FEF50%/FEF25%","lastPublishedDoi":"10.21203/rs.3.rs-4537297/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4537297/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eMaximum expiratory flow-volume (MEFV) curve played an important part in diagnosing the intrathoracic large airway obstruction (ILAO). This study aimed to explore potential discriminative indicators for ILAO by MEFV curve.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eIn this retrospective observational study, we collected pulmonary function tests of patients with ILAO or chronic obstructive pulmonary disease (COPD). They were randomly classified into model and validation groups. The predictive model for ILAO was established by forced expiratory flow (FEF)\u003csub\u003e50%\u003c/sub\u003e/FEF\u003csub\u003e25%\u003c/sub\u003e and Empey\u0026rsquo;s index, and subsequently validated.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eBetween January, 2012, and December, 2021, 63 patients with ILAO and 64 with COPD were included. The peak expiratory flow (PEF), FEF\u003csub\u003e50%\u003c/sub\u003e, FEF\u003csub\u003e75%\u003c/sub\u003e, FEF\u003csub\u003e25\u0026thinsp;\u0026minus;\u0026thinsp;75%\u003c/sub\u003e, FEF ratios and Empey\u0026rsquo;s index were significantly different in two group. In the model group, the receiver operating characteristic (ROC) curve results showed that the areas under the curve (AUCs) were as follows: FEF\u003csub\u003e50%\u003c/sub\u003e/FEF\u003csub\u003e25%\u003c/sub\u003e 0.935(P\u0026thinsp;=\u0026thinsp;0.000), FEF\u003csub\u003e75%\u003c/sub\u003e/FEF\u003csub\u003e50%\u003c/sub\u003e 0.623 (P\u0026thinsp;=\u0026thinsp;0.091), FEF\u003csub\u003e75%\u003c/sub\u003e/FEF\u003csub\u003e25%\u003c/sub\u003e 0.795 (P\u0026thinsp;\u0026lt;\u0026thinsp;0.001) and Empey\u0026rsquo;s index 0.922 (P\u0026thinsp;\u0026lt;\u0026thinsp;0.001). When FEF\u003csub\u003e50%\u003c/sub\u003e/FEF\u003csub\u003e25%\u003c/sub\u003e was \u0026ge;\u0026thinsp;0.960, sensitivity and specificity were 93.8% and 87.5%. When Empey\u0026rsquo;s index was \u0026ge;\u0026thinsp;7.415, sensitivity and specificity were 84.4% and 100%. When FEF\u003csub\u003e50%\u003c/sub\u003e/FEF\u003csub\u003e25%\u003c/sub\u003e\u0026ge;0.960 and Empey\u0026rsquo;s index was \u0026ge;\u0026thinsp;7.415, sensitivity and specificity were 81.3% and 87.5%. The predictive performance of FEF\u003csub\u003e50%\u003c/sub\u003e/FEF\u003csub\u003e25%,\u003c/sub\u003e Empey\u0026rsquo;s index and the combined parameters were calculated in the validation group, with high sensitivity and acceptable specificity.\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e \u003cp\u003eThe predictive model for ILAO established using FEF\u003csub\u003e50%\u003c/sub\u003e/FEF\u003csub\u003e25%\u003c/sub\u003e and Empey\u0026rsquo;s index demonstrates good practical value, which makes FEF\u003csub\u003e50%\u003c/sub\u003e/FEF\u003csub\u003e25%\u003c/sub\u003e and Empey\u0026rsquo;s index potential discriminative indicators for ILAO.\u003c/p\u003e","manuscriptTitle":"Application of MEFV Curve in the Intrathoracic Large Airway Obstruction: a retrospective study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-07-18 20:11:32","doi":"10.21203/rs.3.rs-4537297/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"86c53745-2d63-4b7d-866b-fa396a0c2156","owner":[],"postedDate":"July 18th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-02-05T12:08:17+00:00","versionOfRecord":[],"versionCreatedAt":"2024-07-18 20:11:32","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-4537297","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4537297","identity":"rs-4537297","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}