Persisting exercise ventilatory inefficiency in subjects recovering from COVID-19. Longitudinal Data Analysis 34 Months Post-Discharge Running title: Persisting Exercise Ventilatory Inefficiency in post-COVID Subjects

Persisting exercise ventilatory inefficiency in subjects recovering from COVID-19. Longitudinal Data Analysis 34 Months Post-Discharge Running title: Persisting Exercise Ventilatory Inefficiency in post-COVID Subjects | 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 Persisting exercise ventilatory inefficiency in subjects recovering from COVID-19. Longitudinal Data Analysis 34 Months Post-Discharge Running title: Persisting Exercise Ventilatory Inefficiency in post-COVID Subjects Gianluigi Dorelli, Giulia Sartori, Giulia Fasoli, Nicolò Ridella, and 8 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-3928238/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 8 You are reading this latest preprint version Abstract Background SARS-CoV-2 infection has raised concerns about long-term health repercussions. Exercise ventilatory inefficiency (EV in ) has emerged as a notable long-termi sequela, potentially impacting respiratory and cardiovascular health. This study aims to assess the long-term presence of EVin after 34 months and its association with cardiorespiratory health in post-COVID patients. Methods In a longitudinal study on 32 selected post-COVID subjects, we performed two cardiopulmonary exercise tests (CPETs) at 6 months (T0) and 34 months (T1) after hospital discharge. The study sought to explore the long-term persistence of EV in and its correlation with respiratory and cardiovascular responses during exercise. Measurements included also V̇O 2peak end-tidal pressure of CO 2 (PET CO2 ) levels, oxygen uptake efficiency slope (OUES) and other cardiorespiratory parameters, with statistical significance set at p<0.05. The presence of EV in at both T0 and T1 defines a persisting EV in (pEV in ). Results Out of the cohort, five subjects (16%) have pEV in at 34 months. Subjects with pEV in , compared to those with ventilatory efficiency (Ev ef ) have lower values of PET CO2 throughout exercise, showing hyperventilation. Ev ef subjects demonstrated selective improvements in DL CO and oxygen pulse, suggesting recovery in cardiorespiratory function over time. In contrast, those with pEv in did not exhibit these improvements. Notably, significant correlations were found between hyperventilation (measured by PET CO2 ), oxygen pulse and OUES, indicating the potential prognostic value of OUES and Ev in in post-COVID follow-ups. Conclusions The study highlights the clinical importance of long-term follow-up for post-COVID patients, as a significant group exhibit persistent EV in , which correlates with altered and potentially unfavorable cardiovascular responses to exercise. These findings advocate for the continued investigation into the long-term health impacts of COVID-19, especially regarding persistent ventilatory inefficiencies and their implications on patient health outcomes. COVID-19 Cardiopulmonary exercise test Exercise ventilatory inefficiency Hyperventilation End-tidal pressure of CO2 Oxygen pulse. Figures Figure 1 Figure 2 Introduction Post-COVID condition refers to a range of symptoms and clinical findings that persist following the acute phase of SARS-CoV-2 infection [ 1 ]. In these patients, the cardiopulmonary exercise test (CPET) has highlighted a reduction of maximal exercise capacity and oxygen uptake (V̇O 2peak ) and has been helpful to elucidate the underlying pathophysiological mechanisms leading to exercise intolerance and unexplained perceived dyspnea [ 1 , 2]. CPET has demonstrated that exercise hyperventilation and ventilatory inefficiency (Ev in ) are a contributor to numerous disabling signs and symptoms in post-COVID patients, such as persisting breathlessness and long-lasting exercise intolerance [ 3 , 4]. Exercise ventilation efficiency is assessed by examining how minute ventilation (V̇E) correlates with the amount of carbon dioxide produced (V̇CO 2 ). This relationship is quantified using three metrics: the slope of V̇E against V̇CO 2 (V̇E/V̇CO 2slope ), the lowest value observed (nadir) for this ratio, and the carbon dioxide ventilatory equivalent at the first ventilatory threshold (V̇E/V̇CO 2 at θL) [5]. These metrics are well-established for evaluating mismatches in ventilation and pulmonary perfusion during exercise in patients with heart and lung conditions [6]. High values of V̇E/V̇CO 2 relationship commonly indicate EV in , which is a condition of breathing dysfunction related to excessive ventilation [5]. Ventilatory inefficiency is a global indicator of cardiorespiratory response to exercise and a well-recognized prognostic marker in chronic patients second only to V̇O 2peak [ 7]. As pointed out by Weatherald et al, EV in is also an hallmark of pulmonary vascular disease, such as pulmonary arterial hypertension and chronic thromboembolic pulmonary hypertension where it is an excellent prognostic marker [8]. Understanding the pathophysiological origins of EV in is essential to comprehending the exercise response in post-COVID syndrome. A significant number of evidence indicate that a subset of asymptomatic COVID-19 survivors exhibit EV in , with prevalences reported at 29% and 17% at 6 and 12 months post-discharge, respectively [ 9 – 11 ]. Compared to those without exercise ventilatory inefficiency, those with ventilatory efficiency (Ev ef ), post-COVID patients with Ev in show lower values of end-tidal pressure of CO 2 (PET CO2 ) throughout exercise and display hypocapnia and respiratory alkalosis, which may correlate with an impairment in diffusing capacity (DL CO ) [ 3 , 4 , 11 , 12 ]. Moreover, evidence at 12 months following severe COVID-19 infections indicate that numerous patients, despite achieving normal V̇O 2peak levels, exhibit signs of Ev in , notably linked to signs of underlying pulmonary microvascular disease and increased dead space ventilation [13]. Such vascular complications are believed to stem from endothelial dysfunction and a hypercoagulable state, both of which are acute sequelae of the systemic inflammatory response to SARS-CoV-2 infection [13]. In addition to V̇O 2peak and V̇ E /V̇ CO2 relationship, impairments of the respiratory and cardiovascular response to exercise, could be also evaluated through the oxygen pulse (O 2 pulse), and aerobic efficiency, which are also a common parameters to assess the cardiovascular risk in certain populations [14, 15]. O 2 pulse is the ratio between oxygen uptake and heart rate (HR): it reflects the amount of oxygen extracted by the tissue per heartbeat and could be used in some clinical population as a non-invasive estimator of stroke volume, or peripheral oxygen utilization [7]. Despite these parameters are less strong indicators for evaluating overall survival in general population, some recent long-term longitudinal studies show that low O 2 pulse at peak and oxygen uptake efficiency slope (OUES) values have been associated with increased cardiovascular and all-cause mortality in certain population [ 14 – 16 ] These data need to be further confirmed by other similar longitudinal studies: however some evidence show that Post-COVID patients has a reduced aerobic capacity and O 2 pulse independent from V̇O 2peak levels [17]. While this data could not be interpreted in terms of long-term implication, they could be a subclinical signs of altered cardiovascular response due to the infection in these patients [18]. The enduring clinical significance of EV in and the cardiovascular response to exercise in post-COVID patients remains an area of ongoing investigation [ 13 , 19 ]. The persistence of these conditions after 1 year following hospital discharge underscores the need for pathophysiological investigations and sustained longitudinal studies. Our study aims to explore the persistence of EV in in Post-COVID patients and to unravel its potential long-term repercussions on respiratory and cardiovascular health. Our first hypothesis is that EV in may persist chronically after COVID-19 infection. Evidence suggests that it could be a sign of acute SARS-CoV-2 infection and a subclinical impairment of exercise response which involve both the cardiovascular and the respiratory systems and this leads to our second hypothesis. We also hypothesized that EV in is a sign of a broader dysfunction in the cardiorespiratory response, which may also correlate with signs of an increased cardiovascular risk. We evaluated the resting and exercise ventilatory and cardiovascular responses in a cohort of selected post-COVID patients at 34 months from hospitalization. In this evaluation, we compared the data with a previous evaluation performed 6 months after discharge. Methods Selection of patients Data were collected from the RESPICOVID initiative, a prospective observational study conducted at the Respiratory Medicine Unit of the University of Verona and Azienda Ospedaliera Universitaria Integrata of Verona (Italy), involving patients hospitalized for COVID-19 pneumonia during the first two waves of the pandemic emergency in Italy. A dedicated outpatient clinic has been organized, and all subjects discharged were considered. The present longitudinal analysis with repeated measures has been designed to evaluate the long-term persistence of ventilatory inefficiency in subjects enrolled in the RESPICOVID-2 study [ 10 ]. Only subjects who performed both CPETs (at T0 and T1) were considered. Figure 1 shows the study flow diagram. To better define the EV in and cardiovascular response to exercise, we excluded any potential physiological or pathological variable influencing exercise adaptations [ 6 ]. We have then excluded subjects meeting the following criteria: a) age exceeding 65 years; b) concurrent presence of respiratory and non-respiratory chronic diseases, respiratory failure, or need for long-term oxygen therapy; c) a body mass index (BMI) ≥ 35 kg/m 2 ; and d) an inability to perform a CPET with a peak respiratory exchange ratio (RER) < 1.05 (to exclude poor motivation). Among chronic diseases, only stable arterial hypertension was accepted. Measurements All measures were prospectively collected beginning in July 2020, approximately 6 months after the subjects’ discharge (T0), and repeated until March 2023, 34 months after the discharge (T1). Only subjects with both CPET measures (T0 and T1) were considered for the analysis. Preliminary data about measures performed at T0 have been reported previously [ 10 ]. The local Ethics Committee approved the study protocol (no. 2785CESC), which was performed according to the Good Clinical Practice recommendations and the requirements of the Declaration of Helsinki. Written informed consent was obtained from all subjects. Lung function Lung function procedures were performed according to international recommendations [ 20 – 22 ]. A flow-sensing spirometer connected to a computer for data analysis (Jaeger MasterScreen PFT System) was used to measure lung function. Forced vital capacity (FVC), forced expiratory volume in the first second (FEV 1 ), and total lung capacity (TLC) were recorded. FEV 1 /FVC ratio was taken as the index of airflow obstruction. The single-breath method measured the diffusion capacity for carbon monoxide (DL CO ). FEV 1 , FVC, TLC, and DL CO were expressed as percentages of the predicted values [ 21 , 22 ]. Cardiopulmonary exercise test According to the ATS/ACCP Statement, for the CPET measures, we used a cycle ergometer (E100, Cosmed Srl, Rome, Italy) with a ramp protocol of 10 to 25 watts increment every minute and based on the predicted peak power output, to achieve an exercise time between 8–12 minutes [ 23 ]. Patient were monitored 3 minutes before the ramp protocol (rest phase) and 5 minutes after (cool down phase). Subjects were asked to avoid caffeine, alcohol, cigarettes, and strenuous exercise 24 hours before the day of testing and avoid eating for the 2 hours before the test. Subjects suspended β-blockers before testing but could take their current antihypertensive therapies. During the test, subjects were asked to maintain a pedal frequency of 65 per minute and were continuously monitored [ 23 ]. Subjects were continuously monitored with a 12-lead electrocardiogram (ECG) and a pulse oximeter; blood pressure was measured every two minutes. Stopping criteria consisted of symptoms, such as unsustainable perceived dyspnoea or leg fatigue, chest pain, a significant ST-segment depression at ECG, or a drop in systolic blood pressure or oxygen saturation ≤ 84% [ 23 ]. Cardio-respiratory measures were sampled continuously with a breath-by-breath method using a gas analysis system (Quark CPET, Cosmed Srl, Rome, Italy). Oxygen uptake was expressed in mL/kg/min and as a percentage of predicted. The ventilatory response during exercise was through the relationship of V̇ E against V̇ CO2 obtained every 10 seconds, excluding data above the respiratory compensation point (RCP). We gathered data of V̇ E /V̇ CO2 slope and Y-intercept (V̇ E /V̇ CO2 intercept ) values obtained from the regression function. V̇ E /V̇ CO2 was also been evaluated at nadir (V̇ E /V̇ CO2 nadir ) and the first ventilatory threshold (V̇ E /V̇ CO2 at θ L ) [7]. For the definition of the EV in , we used the regression equation of V̇ E / V̇ CO2 slope for healthy subjects, considering three standard deviations as the upper limit [5]. Then, we considered subjects having a lower range of V̇ E /V̇ CO2 slope (EV ef ) and subjects with over the upper limit of V̇ E /V̇ CO2 slope (EV in ). Subjects having EV in at T0 and T1 were defined as persisting ventilatory inefficiency subjects (pEV in ). The end-tidal pressure of CO 2 (PET CO2 , in mmHg) was measured as the mean of PET CO2 during the 3-minute rest period and the last 20 seconds of the test and was recorded at any time during CPET (at rest, at θ L , at the respiratory compensation point - RCP, and at peak of exercise). The cardiovascular response to exercise was expressed by HR, O 2 pulse, OUES, oxygen uptake and workload relationship (V̇ O2 /W slope ) and HR after 1 minute of recovery (heart rate recovery, HRR). O 2 pulse was calculated by dividing instantaneous V̇O 2 by HR [7]. The OUES describes the relationship between V̇ O2 and V̇ E during incremental exercise, via a log transformation of V̇ E , and was expressed in L/min as the gradient of the linear relationship of log 10 V̇ E to V̇ O2 [24]. V̇ O2 /W slope was calculated as the slope of oxygen uptake as a function of Watts [7, 24]. OUES thus represents the absolute rate of increase in oxygen uptake per 10-fold increase in minute ventilation. HRR in bpm was defined as the reduction in the HR from the peak exercise level to the rate 1 min after the end of exercise [25] At the end of the exercise, dyspnoea and leg fatigue were measured by a Borg 6–20 rate perceived exertion (RPE) scale [ 26 ]. Perceived peak dyspnoea and fatigue data have been described as RPE and peak workload ratio. We considered a test as maximal if subjects had a plateau of the V̇O 2 for more than 20 seconds, a Respiratory Exchange Ratio (RER) > 1.15, and a Borg RPE score > 18 [23]. Self-Reported Questionnaire The modified Medical Research Council (mMRC) questionnaire was administered to measure perceived breathlessness, with a range from 0 (shortness of breath with strenuous exercise) to 4 (too breathless to leave the house) [ 27 ]. Statistical analysis A preliminary Shapiro-Wilk test was performed. Data are reported as percentages for categorical variables, as mean (SD) or median [IQR-interquartile range] for continuous variables with a normal or non-normal distribution, respectively. Categorical variables were compared using the Chi-square test or the Fisher exact test, while the independent t -test or the non-parametric Mann-Whitney test assessed continuous variables. Relationships between variables were assessed using Pearson’s correlation coefficient ( r ). All analyses were performed using IBM SPSS, version 17.0 (IBM Corp., Armonk, NY, USA), with p-values of < 0.05 considered statistically significant. Results We evaluated the same thirty-two post-COVID subjects at T0 (median time from discharge 184 days) and T1 (median 1015 days). At T0, of 32 subjects, 8 had EV in (25%), while at T1 5 subjects (16%) had a pEV in . Subjects with pEV in , in comparison to subjects with EV ef , had significantly higher values of a baseline of V̇E/V̇CO 2 slope , V̇ E /V̇ CO2 nadir , and V̇E/V̇CO 2 at θ L with lower values of V̇E/V̇CO 2 intercept . No other variables, including those related to COVID-19 hospitalization, differed between subjects with pEV in and subjects with EV ef . Baseline variables were reported in Table 1 . Table 1 General, functional and CPET-related baseline variables. Variables All subjects (N = 32) Subjects with EV ef (N = 27) Subjects with pEV in (N = 5) p-value Age, y 55.2 [ 9 ] 55 [5.5] 58 [13.1] 0.550 Male, n (%) 24 (75) 20 (74) 4 (80) > 0.999 Current or former smokers, n (%) 18 (56) 15 (56) 3 (60) > 0.999 Arterial hypertension * , n (%) 10 (31) 9 (33) 1 (20) > 0.999 BMI, kg/m 2 26.8 ± 3.3 26.7 ± 3.4 27.3 ± 3.2 0.734 FEV 1 , % predicted 115.7 ± 13.9 114.2 ± 13.8 126.2 ± 9.9 0.107 FVC, % predicted 119 [ 21 ] 117.5 [ 19 ] 124.5 [ 18 ] 0.376 FEV 1 /FVC, % 79.3 ± 5.8 78.8 ± 5.9 82.3 ± 5.4 0.279 TLC, % predicted 102.7 ± 11.9 103 ± 11.8 100.5 ± 13.2 0.697 DL CO , % predicted 92.6 ± 13.4 92.7 ± 13 91.7 ± 17.5 0.897 PaO 2 , mmHg 101.9 ± 11.8 103 ± 11.7 96.4 ± 12 0.261 PaCO 2 , mmHg 38.7 ± 3.1 38.5 ± 3.2 39.6 ± 3 0.482 6MWT, total distance walked meters 587.8 ± 84.3 592.4 ± 82.3 562.8 ± 101 0.480 mMRC, score 1 [0] 1 [0] 1 [ 1 ] 0.880 Workload, watts 166.6 ± 50.8 169.9 ± 52.1 148.8 ± 43.4 0.401 V̇ O2 at peak, ml 2114.9 ± 548.3 2143.6 ± 561.7 1960.2 ± 493.7 0.501 V̇ O2 at peak, ml/kg/min 26.2 ± 5.2 27 ± 5.7 24.7 ± 7.2 0.427 V̇ O2 at peak, % predicted 98.7 ± 15 100 ± 15.8 91.6 ± 6.1 0.255 V̇ O2 /W slope 9.71 ± 1.31 9.81 ± 1.23 9.18 ± 1.75 0.330 V̇ E /V̇ CO2 slope 28 ± 4 26.9 ± 3.3 33.9 ± 1.6 < 0.001 V̇ E /V̇ CO2 nadir 26.8 ± 2.6 26.2 ± 2.2 30.5 ± 2 < 0.001 V̇ E /V̇ CO2 at θ L 28.1 ± 2.7 27.6 ± 2.5 31 ± 1.7 0.008 V̇ E /V̇ CO2 intercept 2.79 ± 3.6 3.35 ± 3.4 -0.24 ± 3.6 0.042 V̇ E at rest, L/min 15.9 ± 5.9 15.6 ± 5.8 17.6 ± 7.2 0.489 V̇ E at peak, L/min 85 [40.2] 84.1 [36.6] 101.3 [38.6] 0.159 RR change § , breath/min 19 ± 7 18.5 ± 7.3 22.2 ± 4.1 0.282 O 2 pulse at peak, mL/bpm 13.5 ± 3 13.5 ± 3.2 12.6 ± 2.3 0.579 OUES, L/min 1.09 ± 0.22 1.11 ± 0.21 0.98 ± 0.20 0.242 HR max 156.7 ± 14.3 157.3 ± 14.2 153.6 ± 13.9 0.593 HRR, beats/minute 23.8 ± 6.3 24.4 ± 6.3 20.6 ± 6 0.227 HR/V̇ O2 slope, L −1 50.1 [33.8] 50.1 [31.8] 77.5 [56] 0.361 Perceived peak dyspnea # 17 [ 4 ] 17 [ 4 ] 17 [3.5] 0.525 Perceived peak fatigue # 18 [ 2 ] 18 [ 2 ] 18 [ 3 ] > 0.999 Variables related to COVID-19 hospitalisation Length of hospital stay, days 6 [ 5 ] 6.1 [ 5 ] 6 [ 11 ] 0.677 Needing of oxygen therapy, n (%) 22 (68) 18 (67) 4 (80) > 0.999 Needing of ventilatory support, n (%) 13 (41) 11 (41) 2 (40) > 0.999 Needing of ICU admission, n (%) 5 (16) 3 (11) 2 (40) 0.163 PaO 2 /FiO 2 at admission (n = 16) 305.9 ± 102.2 305.7 ± 107.2 307.9 ± 84.2 0.986 PaO 2 /FiO 2 0.999 PaCO 2 at admission (n = 16) 34.2 ± 5.6 34.1 ± 4.9 35 ± 12.7 0.940 Data are shown as the number of subjects (%), means ± SD or medians [IQR-interquartile range]. In bold are reported significant values. * Subjects with arterial hypertension were treated with ACE inhibitors (N = 6, 19%), β-blockers (N = 4, 12%), and Ca 2+ antagonist (N = 3, 9%); § Calculated as value at peak less value at rest; # Described as a Borg 6–20 perceived exertion rate score. Abbreviations: EV ef defines exercise ventilatory efficiency; pEV in , persisting exercise ventilatory inefficiency; BMI body mass index; FEV 1 , forced expiratory volume at 1 st second; FVC, forced vital capacity; TLC, total lung capacity; DL CO , diffusion capacity for carbon monoxide; PaO 2 , partial arterial oxygen pressure; PaCO 2 , partial pressure of arterial carbon dioxide; 6MWT, six-minute walking test; mMRC, modified Medical Research Council dyspnea score; V̇ O2 , oxygen uptake; V̇ E /V̇ CO2 slope , the slope of V̇ E to carbon dioxide output-V̇ CO2 ratio; θ L , the first ventilatory threshold; V̇ E /V̇ CO2 intercept , point of intercept of V̇ E to carbon dioxide output-V̇ CO2 ratio; V̇ E , minute ventilation; RR, respiratory rate; OUES, oxygen uptake efficiency slope; HRR, heart rate recovery; ICU, intensive care unit. In all subjects, comparing T1 vs T0 (Table 2 ), there was an increment of BMI, DL CO % predicted, V̇ O2 at peak % predicted, and O 2 pulse at peak, with a reduction of FEV 1 and FVC (both % predicted), V̇E/V̇CO 2 at θ L and V̇ E at rest. In EV ef , selective changes between T1 and T0 were evident in the following variables: BMI, DL CO % predicted, O 2 pulse at peak, V̇ E /V̇ CO2 at θ L and V̇ E at rest. No selective changes were evident in subjects with pEV in . Table 2 CPET-related differences between T0 and T1. All subjects (N = 32) Subjects with EV ef (N = 27) Subjects with pEV in (N = 5) Variables T0 T1 p-value Mean difference (T1-T0) 95% CI p-value Mean difference (T1-T0) 95% CI p-value BMI, kg/m 2 26.8 ± 3.3 27.6 ± 3.6 < 0.001 0.97 0.43 to 1.53 < 0.001 0.20 -0.34 to 0.74 0.368 FEV 1 , % predicted 115.7 ± 13.9 113.1 ± 12.3 0.023 -2.2 -4.4 to 0.04 0.054 -5.5 -19.8 to 8.8 0.311 FVC, % predicted 119 [ 21 ] 115 [ 11 ] 0.010 -0.37 -8.3 to 7.6 0.925 -4 -13.9 to 5.9 0.289 FEV 1 /FVC, % 79.3 ± 5.8 79.2 ± 4.9 0.910 0.2 -1.1 to 1.5 0.774 -1.8 -3.8 to 0.25 0.069 TLC, % predicted 102.7 ± 11.9 101.7 ± 10.8 0.413 -1.2 -3.7 to 1.1 0.292 1.2 -12.3 to 14.8 0.789 DL CO , % predicted 92.6 ± 13.4 97.2 ± 12.1 0.004 5.2 2.1 to 8.4 0.002 1.7 -18.1 to 21.7 0.798 mMRC, score 1 [0] 1 [0] 0.705 0 -1.9 to 1.9 > 0.999 0.2 0.3 to 0.7 0.374 Workload, watts 166.6 ± 50.8 164.4 ± 44.9 0.462 -3.5 -10.6 to 3.6 0.327 4.4 -5-5 to 14.3 0.285 V̇ O2 at peak, ml 2114.9 ± 548.3 2188.2 ± 545.2 0.068 76.3 -16.3 to 168.9 0.102 56.8 -91.9 to 205.5 0.349 V̇ O2 at peak, ml/kg/min 26.2 ± 5.2 26.7 ± 5.9 0.333 -0.61 -1.8 to 0.5 0.287 0.24 -1.69 to 2.17 0.748 V̇ O2 at peak, % predicted 98.7 ± 15 101.9 ± 13 0.032 2.88 -0.54 to 6.3 0.095 5 -0.4 to 10.4 0.062 V̇ O2 /W slope 9.71 ± 1.31 10.34 ± 1.42 0.033 0.50 -0.15 to 1.15 0.128 1.27 0.20 to 2.34 0.030 V̇ E /V̇ CO2 slope 28 ± 4 27.8 ± 3.9 0.756 -0.36 -1.77 to 1.04 0.598 0.78 -1.8 to 3.4 0.451 V̇ E /V̇ CO2 nadir 26.8 ± 2.6 26.3 ± 3.1 0.161 -0.51 -1.36 to 0.33 0.224 -0.52 -2.27 to 1.24 0.458 V̇ E /V̇ CO2 at θ L 28.1 ± 2.7 27.2 ± 3 0.028 -1.06 -1.94 to -0.18 0.020 0.04 -2.37 to 2.45 0.966 V̇ E /V̇ CO2 intercept 2.79 ± 3.6 3.26 ± 3.8 0.520 0.54 -1.1 to 2.2 0.514 0.06 -3.9 to 4 0.968 V̇ E at rest, L/min 15.9 ± 5.9 12.4 ± 2.8 0.002 -3.3 -0.98 to -5.7 0.007 -4.3 -11.9 to 3.3 0.191 V̇ E at peak, L/min 86.3 [42.8] 88.7 [39.6] 0.695 0.62 -4.90 to 6.15 0.818 -0.88 -18.4 to 16.7 0.896 RR change § , breath/min 19 ± 7 18.6 ± 4.9 0.688 0.42 -1.6 to 2.5 0.680 -4.94 -13.9 to 4.08 0.203 O 2 pulse at peak, mL/bpm 13.5 ± 3 14.2 ± 3.5 0.031 0.80 -0.09 to 1.5 0.027 0.04 -1.46 to 1.54 0.943 OUES, L/min 1.09 ± 0.22 1.12 ± 0.24 0.186 0.03 -0.02 to 0.08 0.264 0.03 -0.04 to 0.11 0.331 HR max 156.7 ± 14.3 155.2 ± 13.5 0.397 -2.7 -6.4 to 1.01 0.147 5 -8.6 to 18.6 0.365 HRR, beats/minute 23.8 ± 6.3 25.5 ± 6.7 0.192 1.59 -1.32 to 4.5 0.272 2.2 -6 to 10.4 0.500 Perceived peak dyspnea # 17 [ 4 ] 17 [ 4 ] 0.182 -0.25 -1.4 to 0.8 0.640 0.2 -1.4 to 1.8 0.749 Perceived peak fatigue # 18 [ 2 ] 18 [2.75] 0.212 0.18 -0.6 to 1.03 0.658 0.01 -1.2 to 1.2 > 0.999 Data are shown as the number of subjects (%), means ± SD or medians [IQR-interquartile range]. The difference between T1 and T0 are expressed as mean and confidence intervals at 95%. In bold are reported significant values. § Calculated as value at peak less value at rest; # Described as a Borg 6–20 perceived exertion rate score and peak workload ratio. Abbreviations: EV ef defines exercise ventilatory efficiency; pEV in , persisting exercise ventilatory inefficiency; BMI body mass index; FEV 1 , forced expiratory volume at 1 st second; FVC, forced vital capacity; TLC, total lung capacity; DL CO , diffusion capacity for carbon monoxide; mMRC, modified Medical Research Council dyspnea score; V̇ O2 , oxygen uptake; V̇ E /V̇ CO2 slope , the slope of V̇ E to carbon dioxide output-V̇ CO2 ratio; θ L , the first ventilatory threshold; V̇ E /V̇ CO2 intercept , point of intercept of V̇ E to carbon dioxide output-V̇ CO2 ratio; V̇ E , minute ventilation; RR, respiratory rate; OUES, oxygen uptake efficiency slope; HRR, heart rate recovery. PET CO2 was significantly lower in patients with EV in than EV ef at any time point of the exercise (at rest, at θ L , at RCP and peak) at T1, while at T0 were different at rest, at RCP, and peak (Fig. 2 ). At T1, PET CO2 at rest ( r 0.366; p = 0.039 and r 0.353; p = 0.048), such as at θ L ( r 0.532; p = 0.002 and r 0.586; p < 0.001), at RCP ( r 0.514; p = 0.004 and r 0.565; p = 0.001), and peak ( r 0.427; p = 0.015 and r 0.480; p = 0.005) were significantly and respectively correlated with O 2 pulse at peak and OUES (Table 3 ). Table 3 Correlations among variables of ventilatory inefficiency (V̇ E /V̇ CO2 slope ), hyperventilation (PET CO2 ) and cardiovascular response to exercise (OUES, O 2 pulse at peak), all evaluated at T1. PET CO2 at rest PET CO2 at θ L PET CO2 at RCP PET CO2 at peak O 2 pulse at peak OUES V̇ E /V̇ CO2 slope r -0.395 p = 0.025 r -0.723 p < 0.001 r -0.801 p < 0.001 r -0.579 p = 0.001 r -0.271 p = 0.134 r -0.339 p = 0.057 PET CO2 at rest - r 0.535 p = 0.002 r 0.432 p = 0.019 r 0.574 p = 0.001 r 0.366 p = 0.039 r 0.353 p = 0.048 PET CO2 at θ L - - r 0.941 p < 0.001 r 0.821 p < 0.001 r 0.532 p = 0.002 r 0.586 p < 0.001 PET CO2 at RCP - - - r 0.815 p < 0.001 r 0.514 p = 0.004 r 0.565 p = 0.001 PET CO2 at peak - - - -- r 0.427 p = 0.015 r 0.480 p = 0.005 O 2 pulse at peak - - - - - r 0.939 p < 0.001 OUES - - - - - - In bold are reported significant values. Discussion Our study starts from the hypothesis that EV in may be a persistent ventilo-perfusory alteration after COVID-19. In a selected cohort of Post-COVID patients, at almost three years of follow-up, we demonstrated that a pEV in may be present in 16% of subjects. These subjects have the phenomenon of hyperventilation, documented by lower levels of PET CO2 . The patient cohort, comprising individuals with both EV ef and EV in , exhibited consistently normal maximal exercise capacity, as well as normal levels of FEV 1 , FVC, TLC at both 6 months (T0) and 34 months after discharge (T1). This persistent exercise hyperventilation correlate with to an exacerbated cardiovascular response to exercise, which was the second hypothesis of this study. Ventilatory Inefficiency and Hyperventilation A reduction in maximal exercise capacity and V̇ O2peak has been reported as the main CPET feature of symptomatic post-COVID patients [1]. However, some of the asymptomatic post-COVID patients, despite maintaining preserved lung functionality, maximal exercise capacity and V̇O 2peak , exhibit EV in [10, 11]. Research has indicated that exercise ventilatory inefficiency may be a significant feature also in apparently healthy COVID-19 survivors: however, its clinical role has not yet been fully elucidated [19]. In healthy subjects, EV in is uncommon and anthropometric variables may influence it. Usually, higher V̇E/V̇CO 2slope than the normal range is an indicator of EV in [6, 28].EV in in cardiopulmonary chronic conditions may be caused mainly by two reasons: 1) An altered arterial partial carbon dioxide pressure (PaCO 2 ) set-point and chemosensitivity (usually a consequence of chronic hypoxemia), and 2) an abnormally high dead space fraction during exercise caused by a ventilatory-perfusion mismatch, which could involve the ventilation, or the pulmonary perfusion [8, 28]. Hyperventilation is a frequent manifestation of subjects recovering from COVID-19, and it is frequently associated with ventilatory inefficiency; both have been reported as a possible mechanism of persisting disabling signs and symptoms limiting exercise capacity due to an increase in the cost of ventilation [ 3 , 4 , 29 ]. The exact cause of this hyperventilation remains unknown. As a consequence of infection, an imbalance in the ventilatory control has been hypothesized as a cause of the hyperventilation in post-COVID subjects, related to either heightened activation of activator systems (including automatic and cortical ventilatory control, peripheral afferents, and sensory cortex) or suppression of inhibitory systems (endorphins) [ 3 ]. In COVID-19 survivors, there is also a close relationship between hypocapnia resulting from resting hyperventilation and residual DL CO , which are the most common functional abnormality in the early convalescence phase [ 12 , 30 ]. Compared with non-severe cases, patients with severe COVID-19 had a higher impairment in DL CO , which likely indicates a restrictive pattern, and a decrease in TLC [ 30 ]. Although the ventilatory response was unrelated to disease severity, higher values of V̇ E /V̇ CO2 slope have been found in a follow-up of seven months as a negative predictor in a cohort of patients developing pulmonary fibrosis [31]. We now report a close association between hyperventilation at each phase of the exercise and the EV in as a permanent and distinctive sign of a proportion of asymptomatic survivors (Fig. 2 ). This phenomenon is probably related to a perpetual altered PaCO 2 set-point and chemosensitivity, or to an alteration of the ventilatory-perfusion mismatch, in which a residual lung function impairment in DL CO may play a significant role [6, 12 , 28].In our data, we confirm the role of DL CO and the excess ventilation by the selective improvement after 34 months in EV ef subjects only (Table 2 ). In line with the assessments made in a shorter period after one year of discharge, the EV in prevalence in our survivors (16%) is similar to that described by Ingul CB and colleagues (17%), with similar considerations about hyperventilation (PET CO2 ) [ 11 ]. Of note, Ingul CB and colleagues found a close relationship between the perceived dyspnea and EV in : this relationship is not confirmed in our asymptomatic patients cohort, in which the level of dyspnea is very low (median mMRC 1) [ 11 ]. While perceived dyspnea is typically multifaceted in nature, our methodology, which involved the selection of subjects without comorbidities and variables that might affect the ventilatory efficiency—like a subject's weight—could have impacted these findings [ 6 , 32 ]. For instance, Ingul's study included a cohort with 29% obese patients, in contrast to our study, which comprised only three out of 32 subjects (approximately 9%) being obese (data not shown) [ 11 ]. Persistent viral presence, long-term inflammation, microclots, and hypoxia may contribute to developing symptoms in obese subjects [ 33 ]. Moreover, obesity, related to the alteration of mechanical lung function, may affect the subject’s dyspnoea perception a priori [ 34 ]. Cardiovascular response to exercise in patient with pEVin COVID patients are at risk for cardiovascular disease during acute phase of the infection [ 18 ]. Due to the damage of pulmonary endothelium and microclots during the disease, we cannot exclude long-term cardiovascular complications in these patients. EV in is a well-recognized hallmark of pulmonary vascular disease and increased dead-space ventilation [ 28 ]. Despite normal V̇O 2peak levels in subject recovered from severe COVID after one year of follow-up, dead space ventilation correlate with D-Dimer plasma concentrations during hospital stay [13]. At six months of discharge, higher values of V̇ E /V̇ CO2 slope have been linked to diminished HRR, suggesting that post-COVID subjectswith EV in may have a cardiac autonomic dysfunction, a general predictor of mortality in adults without heart disease history [10, 25]. Moreover, studies evaluating the hemodynamic response during exercise confirm that normotensive post-COVID patients present a significantly higher blood pressure response in the post-exercise recovery of the CPET, with an achieved lower O 2 pulse at peak than controls without a history of COVID-19 [17]. O 2 pulse may have non-specific interpretation and attention should be paid when discussing this variable alone. However, recent data show that low levels of O 2 pulse during exercise may be related to an increase in cardiovascular and all-cause mortality in some population [14]. This leads speculating reduced O 2 pulse peak values in COVID-19 recovered subjects could be a significant measure of health outcome. Low O 2 pulse at peak is a consequence of a reduced V̇O 2peak during short-term follow-up. Already at 6 months of follow-up up to a year after hospital discharge for COVID-19, O 2 pulse and V̇O 2peak increased significantly [1, 10]. In our longer follow-up, we document a significant global improvement of the O 2 pulse from 6 to 34 months, despite no significant increase in VO 2peak . It should be noted that the increase was mainly in EV ef patients, speculating that subjects with pEV in still have a potential impairment in cardiovascular response, or oxygen tissue utilization (Table 2 ). Moreover, we demonstrate a significant correlation between the O 2 pulse at peak and PET CO2 (Table 3 ). Similarly to O 2 pulse, OUES values represent an individual's cardiorespiratory reserve and indicate how effectively oxygen is extracted and utilized by the body [ 24 ]. The prognostic potential of OUES has been examined in some clinical populations, such as patients with heart failure and very recently, the determination of OUES on healthy males has proved its prediction in all-cause mortality [ 16 , 35 ]. Our data about the correlation between the hyperventilation and OUES, similarly for O 2 pulse, define this variable as potentially prognostic for COVID survivors. Data about the exercise training on parameters of cardiovascular response in patients with chronic obstructive pulmonary disease (COPD) report OUES - but also O 2 pulse - as susceptible to changes, as a sign of an enhancement of ventilatory function upon exercise [ 36 ]. In the context of post-COVID patients, although in a single survivor patient from critical COVID-19 illness, and the data requires scientific confirmation, home-based exercise training has been demonstrated to produce a remarkable increment not only of V̇ O2 peak but also of the OUES, with a consensual reduction in V̇ E /V̇ CO2 and exertional dyspnea [37]. Our study’s strength is related to evaluating the EV in for a very long time from COVID-19 discharge (pEV in ). Although we report a small number of patients (an explicit limitation), this was related to a selective approach excluding patients having a condition potentially influencing the exercise ventilation assessment. We included a healthy population with a normal exercise capacity and pulmonary function tests. This may also be considered a study strength because we excluded any potential cause of ventilatory inefficiency. Finally, we lack same-time data concerning the structural pulmonary (by thorax computed tomography scan) and cardiac (by echocardiography) damage. There is a possibility that these data could have confirmed a coexistent organic residual alteration. In conclusion, our longitudinal data analysis on COVID-19 survivors, performed at 34 months from discharge, confirms the persistence of exercise ventilatory inefficiency in 16% of subjects. These subjects exhibit a hyperventilation status that correlates closely with an altered and unfavorable cardiovascular response to exercise. These observations underscore the importance of prolonged follow-up studies in individuals recovering from COVID-19. Declarations Ethics approval and consent to participate Written consent was obtained before the first visit and the protocol was approved by the local ethics committee, Comitato etico per la Sperimentazione Clinica (CESC). The study was performed in accordance with the Declaration of Helsinki and Good Clinical Practice guidelines. Clinical trial registration number: 2785CESC. Consent for publication All patients gave informed consent. Availability of data and materials All data generated or analyzed during this study are included in this published article. Competing interests The authors report no relationships that could be construed as a conflict of interest. Funding This study received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors. Author contribution Substantial contributions to the conception or design of the study and the acquisition, analysis, or interpretation of data: GD, GS, GF, NR, NB, MB, MF, MV, LDC, CC, BG, EC. Drafting the study or revising it critically for important intellectual content: GD, GS, GF, NR, NB, MB, MF, MV, LDC, CC, BG, EC. Final approval of the version to be published: GD, GS, GF, NR, NB, MB, MF, MV, LDC, CC, BG, EC Agreement to be accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved: GD, GS, GF, NR, NB, MB, MF, MV, LDC, CC, BG, EC. All authors take responsibility for all aspects of the reliability and freedom from bias of the data presented and their discussed interpretation. References Davis HE, Mccorkell L, Vogel JM, Topol EJ. Long COVID: major findings, mechanisms and recommendations. Nat Reviews Microbiol |. 2023;21:133–46. Mancini DM, Brunjes DL, Lala A, Trivieri MG, Contreras JP, Natelson BH. Use of Cardiopulmonary Stress Testing for Patients With Unexplained Dyspnea Post-Coronavirus Disease. 2021. https://doi.org/10.1016/j.jchf.2021.10.002 . Motiejunaite J, Balagny P, Arnoult F, Mangin L, Bancal C, Vidal-Petiot E, et al. Hyperventilation as one of the mechanisms of persistent dyspnoea in SARS-CoV-2 survivors. Eur Respir J. 2021;58:2101578. Motiejunaite J, Balagny P, Arnoult F, Mangin L, Bancal C, d’Ortho M-P et al. Hyperventilation: A Possible Explanation for Long-Lasting Exercise Intolerance in Mild COVID-19 Survivors? Front Physiol. 2021;11. Sun X-GG, Hansen JE, Garatachea N, Storer TW, Wasserman K. Ventilatory Efficiency during Exercise in Healthy Subjects. https://doi.org/101164/rccm2202033. 2012;166:1443–8. Laveneziana P, Naeije R, Stickland MK, Phillips DB, Collins SÉ. Measurement and Interpretation of Exercise Ventilatory Efficiency. Front Physiol | www frontiersin org. 2020;1. Wasserman K, Hansen JE, Sue DY, Stringer WW, Sietsema KE, Sun XG et al. Principles of exercise testing and interpretation: Including pathophysiology and clinical applications: Fifth edition. 2011. Weatherald J, Farina S, Bruno N, Laveneziana P. Cardiopulmonary exercise testing in pulmonary hypertension. Ann Am Thorac Soc. 2017;14 July:84–92. Szekely Y, Lichter Y, Sadon S, Lupu L, Taieb P, Banai A, et al. Cardiorespiratory Abnormalities in Patients Recovering from Coronavirus Disease 2019. J Am Soc Echocardiogr. 2021;34:1273–1284e9. Dorelli G, Braggio M, Gabbiani D, Busti F, Caminati M, Senna G et al. Importance of Cardiopulmonary Exercise Testing amongst Subjects Recovering from COVID-19. 2021. https://doi.org/10.3390/diagnostics11030507 . Ingul CB, Edvardsen A, Follestad T, Trebinjac D, Ankerstjerne OAW, Brønstad E, et al. Changes in cardiopulmonary exercise capacity and limitations 3–12 months after COVID-19. Eur Respir J. 2023;61:2200745. Crisafulli E, Gabbiani D, Magnani G, Dorelli G, Busti F, Sartori G, et al. Residual Lung Function Impairment Is Associated with Hyperventilation in Patients Recovered from Hospitalised COVID-19: A Cross-Sectional Study. J Clin Med. 2021;10:1–6. Noureddine S, Roux-Claudé P, Laurent L, Ritter O, Dolla P, Karaer S, et al. Evaluation of long-term sequelae by cardiopulmonary exercise testing 12 months after hospitalization for severe COVID-19. BMC Pulm Med. 2023;23:1–13. Laukkanen JA, Araújo CGS, Kurl S, Khan H, Jae SY, Guazzi M, et al. Relative peak exercise oxygen pulse is related to sudden cardiac death, cardiovascular and all-cause mortality in middle-aged men. Eur J Prev Cardiol. 2018;25:772–82. Peterman JE, Harber MP, Chaudhry S, Arena R, Kaminsky LA. Peak oxygen pulse and mortality risk in healthy women and men: The Ball State Adult Fitness Longitudinal Lifestyle Study (BALL ST). Prog Cardiovasc Dis. 2021;68:19–24. Peterman JE, Novelli DS, Fleenor BS, Whaley MH, Kaminsky LA, Harber MP. Oxygen Uptake Efficiency Slope as a Predictor of Mortality Risk. J Cardiopulm Rehabil Prev. 2023;43:282–9. Miętkiewska-Szwacka K, Domin R, Kwissa M, Żołyński M, Niziński J, Turska E, et al. Effect of COVID-19 on Blood Pressure Profile and Oxygen Pulse during and after the Cardiopulmonary Exercise Test in Healthy Adults. J Clin Med. 2023;12:4483. Harrison SL, Buckley BJR, Rivera-Caravaca JM, Zhang J, Lip GYH. Cardiovascular risk factors, cardiovascular disease, and COVID-19: an umbrella review of systematic reviews. Eur Heart J Qual Care Clin Outcomes. 2021. https://doi.org/10.1093/ehjqcco/qcab029 . Crisafulli E, Dorelli G, Sartori G, Dalle Carbonare L. Exercise ventilatory inefficiency may be a relevant CPET-feature in COVID-19 survivors. Int J Cardiol. 2021;343:200. Miller MR, Hankinson J, Brusasco V, Burgos F, Casaburi R, Coates A et al. Standardisation spirometry. https://doi.org/10.1183/09031936.05.00034805 . Quanjer PH, Tammeling GJ, Cotes JE, Pedersen OF, Peslin R, Yernault JC. Lung volumes and forced ventilatory flows. Report Working Party Standardization of Lung Function Tests, European Community for Steel and Coal. Official Statement of the European Respiratory Society. The European respiratory journal. Supplement. 1993;16:5–40. Cotes JE, Chinn DJ, Quanjer PH, Roca J, Yernault J-C. Standardization of the measurement of transfer factor (diffusing capacity). Eur Respir J. 1993;6(Suppl 16):41–52. Weisman IM, Marciniuk D, Martinez FJ, Sciurba F, Sue D, Myers J, et al. ATS/ACCP Statement on Cardiopulmonary Exercise Testing. Am J Respir Crit Care Med. 2003;167:211–77. Baba R. The Oxygen Uptake Efficiency Slope and Its Value in the Assessment of Cardiorespiratory Functional Reserve. Congestive Heart Fail. 2000;6:256–8. Cole CR, Blackstone EH, Pashkow FJ, Snader CE, Lauer MS. Heart-Rate Recovery Immediately after Exercise as a Predictor of Mortality. N Engl J Med. 1999;341:1351–7. Borg G. Psychophysical scaling with applications in physical work and the perception of exertion. Work Environ Health. 1990;16:441–554. Standardized Questionaries on Respiratory Symptoms. Br Med J. 1960;2:1665. Weatherald J, Sattler C, Garcia G, Laveneziana P. Ventilatory response to exercise in cardiopulmonary disease: the role of chemosensitivity and dead space. Eur Respir J. 2018;51:1700860. Taverne J, Salvator H, Leboulch C, Barizien N, Ballester M, Imhaus E, et al. High incidence of hyperventilation syndrome after COVID-19. J Thorac Dis. 2021;13:3918–22. Huang Y, Tan C, Wu J, Chen M, Wang Z, Luo L, et al. Impact of coronavirus disease 2019 on pulmonary function in early convalescence phase. Respir Res. 2020;21:163. Liu M, Lv F, Huang Y, Xiao K. Follow-Up Study of the Chest CT Characteristics of COVID-19 Survivors Seven Months After Recovery. Front Med (Lausanne). 2021;8:636298. Parshall MB, Schwartzstein RM, Adams L, Banzett RB, Manning HL, Bourbeau J, et al. An Official American Thoracic Society Statement: Update on the Mechanisms, Assessment, and Management of Dyspnea. Am J Respir Crit Care Med. 2012;185:435–52. Xiang M, Wu X, Jing H, Novakovic VA, Shi J. The intersection of obesity and (long) COVID-19: Hypoxia, thrombotic inflammation, and vascular endothelial injury. Front Cardiovasc Med. 2023;10. Dixon AE, Peters U. The effect of obesity on lung function. Expert Rev Respir Med. 2018;12:755–67. Arena R, Brubaker P, Moore B, Kitzman D. The oxygen uptake efficiency slope is reduced in older patients with heart failure and a normal ejection fraction. Int J Cardiol. 2010;144:101–2. Ramponi S, Tzani P, Aiello M, Marangio E, Clini E, Chetta A. Pulmonary Rehabilitation Improves Cardiovascular Response to Exercise in COPD. Respiration. 2013;86:17–24. Longobardi I, do Prado DML, Goessler KF, Meletti MM, de Oliveira Júnior GN, de Andrade DCO, et al. Oxygen uptake kinetics and chronotropic responses to exercise are impaired in survivors of severe COVID-19. Am J Physiol Heart Circ Physiol. 2022;323:H569–76. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Review Version 1 posted Editorial decision: Revision requested 02 Apr, 2024 Reviews received at journal 11 Mar, 2024 Reviewers agreed at journal 10 Mar, 2024 Reviewers invited by journal 08 Mar, 2024 Editor assigned by journal 07 Mar, 2024 Editor invited by journal 26 Feb, 2024 Submission checks completed at journal 26 Feb, 2024 First submitted to journal 04 Feb, 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-3928238","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":275035056,"identity":"245669fd-4a39-4a88-b1ed-5d75d9c0d87c","order_by":0,"name":"Gianluigi Dorelli","email":"","orcid":"","institution":"University of Verona","correspondingAuthor":false,"prefix":"","firstName":"Gianluigi","middleName":"","lastName":"Dorelli","suffix":""},{"id":275035057,"identity":"e5c70169-96cf-4867-830e-6f5d32a4847c","order_by":1,"name":"Giulia Sartori","email":"","orcid":"","institution":"University of Verona and Azienda Ospedaliera Universitaria Integrata of Verona","correspondingAuthor":false,"prefix":"","firstName":"Giulia","middleName":"","lastName":"Sartori","suffix":""},{"id":275035058,"identity":"e240f0fd-2055-4fd9-9d6c-e193359e35ad","order_by":2,"name":"Giulia Fasoli","email":"","orcid":"","institution":"University of Verona","correspondingAuthor":false,"prefix":"","firstName":"Giulia","middleName":"","lastName":"Fasoli","suffix":""},{"id":275035059,"identity":"1e58467b-83e5-43c2-9c45-fb47ae283eca","order_by":3,"name":"Nicolò Ridella","email":"","orcid":"","institution":"University of Verona and Azienda Ospedaliera Universitaria Integrata of Verona","correspondingAuthor":false,"prefix":"","firstName":"Nicolò","middleName":"","lastName":"Ridella","suffix":""},{"id":275035060,"identity":"c29c669c-69d0-41b7-90d2-08c896f2d6fe","order_by":4,"name":"Nicola Bianchini","email":"","orcid":"","institution":"University of Verona and Azienda Ospedaliera Universitaria Integrata of Verona","correspondingAuthor":false,"prefix":"","firstName":"Nicola","middleName":"","lastName":"Bianchini","suffix":""},{"id":275035061,"identity":"0772b3f3-0071-4ae0-b090-33d1485c5f01","order_by":5,"name":"Michele Braggio","email":"","orcid":"","institution":"University of Verona","correspondingAuthor":false,"prefix":"","firstName":"Michele","middleName":"","lastName":"Braggio","suffix":""},{"id":275035062,"identity":"d2f05085-e258-4ac6-8cc6-9ce5c87f2c3b","order_by":6,"name":"Marcello Ferrari","email":"","orcid":"","institution":"University of Verona","correspondingAuthor":false,"prefix":"","firstName":"Marcello","middleName":"","lastName":"Ferrari","suffix":""},{"id":275035063,"identity":"014c45d8-5e0c-4491-bf8f-82666a28aa42","order_by":7,"name":"Massimo Venturelli","email":"","orcid":"","institution":"University of Verona","correspondingAuthor":false,"prefix":"","firstName":"Massimo","middleName":"","lastName":"Venturelli","suffix":""},{"id":275035064,"identity":"ce5ebf47-2dfb-43e2-9b0e-c89df39e1e4c","order_by":8,"name":"Luca Dalle Carbonare","email":"","orcid":"","institution":"University of Verona","correspondingAuthor":false,"prefix":"","firstName":"Luca","middleName":"Dalle","lastName":"Carbonare","suffix":""},{"id":275035065,"identity":"48cfba6b-211c-4ef5-b7db-6e999a2886d9","order_by":9,"name":"Carlo Capelli","email":"","orcid":"","institution":"University of Verona","correspondingAuthor":false,"prefix":"","firstName":"Carlo","middleName":"","lastName":"Capelli","suffix":""},{"id":275035066,"identity":"1842be71-60cb-4ef8-83d8-da75432b1719","order_by":10,"name":"Bruno Grassi","email":"","orcid":"","institution":"University of Udine","correspondingAuthor":false,"prefix":"","firstName":"Bruno","middleName":"","lastName":"Grassi","suffix":""},{"id":275035067,"identity":"728513a8-581c-4870-bdaf-6e0ecc6b6733","order_by":11,"name":"Ernesto Crisafulli","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABAUlEQVRIie3QP2rDMByG4Z8RyMuXanVQyBlUDCklgl5FpeBubY5gCHgynQO5R+cErW4v0KWh0KlDvRQFMjSunSm25g56J0noQX+IQqH/XZQTaZpcMLYhUscF5tttTiQjcMZNR3zGnAYNIahu1k+EfNnu9k6TWNvltzMWPMaPXCzsI8Vi00fGTw93KUxGyettMS4bwkbPcqXsdT5wMVVhJslYUogKGrmOQGVq6C03Fa72riXL+vB3Cj69RAEzQktyiZbwI9GDJKmQSmQZkioq5MTcN5+czhvCGVN9RJS4rJ3WU1HGH/WXmU+FsLs3HBIlxPa995gunC9x3/5QKBQKefsFtllE6G/EbaQAAAAASUVORK5CYII=","orcid":"","institution":"University of Verona and Azienda Ospedaliera Universitaria Integrata of Verona","correspondingAuthor":true,"prefix":"","firstName":"Ernesto","middleName":"","lastName":"Crisafulli","suffix":""}],"badges":[],"createdAt":"2024-02-04 16:49:04","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-3928238/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-3928238/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":51775560,"identity":"60423767-01c0-406c-95a8-8ac3db741494","added_by":"auto","created_at":"2024-02-28 20:43:38","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":177838,"visible":true,"origin":"","legend":"\u003cp\u003eStudy flow diagram\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eAbbreviations:\u003c/em\u003e BMI defines body mass index; CPET, cardiopulmonary exercise test.\u003c/p\u003e","description":"","filename":"Figure1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-3928238/v1/84ca74e542c48a296148bae3.jpg"},{"id":51775559,"identity":"41f18820-bd6a-4949-8d28-850107ac43b8","added_by":"auto","created_at":"2024-02-28 20:43:38","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":134079,"visible":true,"origin":"","legend":"\u003cp\u003eBoxplots of PET\u003csub\u003eCO2\u003c/sub\u003e at any time point of CPET evaluations.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eAbbreviations:\u003c/em\u003e EV\u003cem\u003eef\u003c/em\u003e defines the exercise ventilatory efficiency; pEV\u003cem\u003ein\u003c/em\u003e, persisting exercise ventilatory inefficiency; PET\u003csub\u003eCO2\u003c/sub\u003e, end-tidal pressure of CO\u003csub\u003e2\u003c/sub\u003e; θ\u003csub\u003eL\u003c/sub\u003e, at the first ventilatory threshold; RCP, respiratory compensation point.\u003c/p\u003e","description":"","filename":"Figure2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-3928238/v1/46ca359450db2dc91deaee24.jpg"},{"id":51776276,"identity":"0418a76e-000f-4813-89ab-e553333fb2fb","added_by":"auto","created_at":"2024-02-28 20:51:39","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":632105,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-3928238/v1/0c88124d-af84-41a8-9501-5e5e2cd19445.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Persisting exercise ventilatory inefficiency in subjects recovering from COVID-19. Longitudinal Data Analysis 34 Months Post-Discharge Running title: Persisting Exercise Ventilatory Inefficiency in post-COVID Subjects","fulltext":[{"header":"Introduction","content":"\u003cp\u003ePost-COVID condition refers to a range of symptoms and clinical findings that persist following the acute phase of SARS-CoV-2 infection [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. In these patients, the cardiopulmonary exercise test (CPET) has highlighted a reduction of maximal exercise capacity and oxygen uptake (V̇O\u003csub\u003e2peak\u003c/sub\u003e) and has been helpful to elucidate the underlying pathophysiological mechanisms leading to exercise intolerance and unexplained perceived dyspnea [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, 2]. CPET has demonstrated that exercise hyperventilation and ventilatory inefficiency (Ev\u003cem\u003ein\u003c/em\u003e) are a contributor to numerous disabling signs and symptoms in post-COVID patients, such as persisting breathlessness and long-lasting exercise intolerance [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, 4].\u003c/p\u003e \u003cp\u003eExercise ventilation efficiency is assessed by examining how minute ventilation (V̇E) correlates with the amount of carbon dioxide produced (V̇CO\u003csub\u003e2\u003c/sub\u003e). This relationship is quantified using three metrics: the slope of V̇E against V̇CO\u003csub\u003e2\u003c/sub\u003e (V̇E/V̇CO\u003csub\u003e2slope\u003c/sub\u003e), the lowest value observed (nadir) for this ratio, and the carbon dioxide ventilatory equivalent at the first ventilatory threshold (V̇E/V̇CO\u003csub\u003e2\u003c/sub\u003e at θL) [5]. These metrics are well-established for evaluating mismatches in ventilation and pulmonary perfusion during exercise in patients with heart and lung conditions [6]. High values of V̇E/V̇CO\u003csub\u003e2\u003c/sub\u003e relationship commonly indicate EV\u003cem\u003ein\u003c/em\u003e, which is a condition of breathing dysfunction related to excessive ventilation [5].\u003c/p\u003e \u003cp\u003eVentilatory inefficiency is a global indicator of cardiorespiratory response to exercise and a well-recognized prognostic marker in chronic patients second only to V̇O\u003csub\u003e2peak [\u003c/sub\u003e7]. As pointed out by Weatherald et al, EV\u003cem\u003ein\u003c/em\u003e is also an hallmark of pulmonary vascular disease, such as pulmonary arterial hypertension and chronic thromboembolic pulmonary hypertension where it is an excellent prognostic marker [8].\u003c/p\u003e \u003cp\u003eUnderstanding the pathophysiological origins of EV\u003cem\u003ein\u003c/em\u003e is essential to comprehending the exercise response in post-COVID syndrome. A significant number of evidence indicate that a subset of asymptomatic COVID-19 survivors exhibit EV\u003cem\u003ein\u003c/em\u003e, with prevalences reported at 29% and 17% at 6 and 12 months post-discharge, respectively [\u003cspan additionalcitationids=\"CR10\" citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. Compared to those without exercise ventilatory inefficiency, those with ventilatory efficiency (Ev\u003cem\u003eef\u003c/em\u003e), post-COVID patients with Ev\u003cem\u003ein\u003c/em\u003e show lower values of end-tidal pressure of CO\u003csub\u003e2\u003c/sub\u003e (PET\u003csub\u003eCO2\u003c/sub\u003e) throughout exercise and display hypocapnia and respiratory alkalosis, which may correlate with an impairment in diffusing capacity (DL\u003csub\u003eCO\u003c/sub\u003e) [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eMoreover, evidence at 12 months following severe COVID-19 infections indicate that numerous patients, despite achieving normal V̇O\u003csub\u003e2peak\u003c/sub\u003e levels, exhibit signs of Ev\u003cem\u003ein\u003c/em\u003e, notably linked to signs of underlying pulmonary microvascular disease and increased dead space ventilation [13]. Such vascular complications are believed to stem from endothelial dysfunction and a hypercoagulable state, both of which are acute sequelae of the systemic inflammatory response to SARS-CoV-2 infection [13].\u003c/p\u003e \u003cp\u003eIn addition to V̇O\u003csub\u003e2peak\u003c/sub\u003e and V̇\u003csub\u003eE\u003c/sub\u003e/V̇\u003csub\u003eCO2\u003c/sub\u003e relationship, impairments of the respiratory and cardiovascular response to exercise, could be also evaluated through the oxygen pulse (O\u003csub\u003e2\u003c/sub\u003e pulse), and aerobic efficiency, which are also a common parameters to assess the cardiovascular risk in certain populations [14, 15]. O\u003csub\u003e2\u003c/sub\u003e pulse is the ratio between oxygen uptake and heart rate (HR): it reflects the amount of oxygen extracted by the tissue per heartbeat and could be used in some clinical population as a non-invasive estimator of stroke volume, or peripheral oxygen utilization [7].\u003c/p\u003e \u003cp\u003eDespite these parameters are less strong indicators for evaluating overall survival in general population, some recent long-term longitudinal studies show that low O\u003csub\u003e2\u003c/sub\u003e pulse at peak and oxygen uptake efficiency slope (OUES) values have been associated with increased cardiovascular and all-cause mortality in certain population [\u003cspan additionalcitationids=\"CR15\" citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e] These data need to be further confirmed by other similar longitudinal studies: however some evidence show that Post-COVID patients has a reduced aerobic capacity and O\u003csub\u003e2\u003c/sub\u003e pulse independent from V̇O\u003csub\u003e2peak\u003c/sub\u003e levels [17]. While this data could not be interpreted in terms of long-term implication, they could be a subclinical signs of altered cardiovascular response due to the infection in these patients [18].\u003c/p\u003e \u003cp\u003eThe enduring clinical significance of EV\u003cem\u003ein\u003c/em\u003e and the cardiovascular response to exercise in post-COVID patients remains an area of ongoing investigation [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. The persistence of these conditions after 1 year following hospital discharge underscores the need for pathophysiological investigations and sustained longitudinal studies.\u003c/p\u003e \u003cp\u003eOur study aims to explore the persistence of EV\u003cem\u003ein\u003c/em\u003e in Post-COVID patients and to unravel its potential long-term repercussions on respiratory and cardiovascular health.\u003c/p\u003e \u003cp\u003eOur first hypothesis is that EV\u003cem\u003ein\u003c/em\u003e may persist chronically after COVID-19 infection. Evidence suggests that it could be a sign of acute SARS-CoV-2 infection and a subclinical impairment of exercise response which involve both the cardiovascular and the respiratory systems and this leads to our second hypothesis. We also hypothesized that EV\u003cem\u003ein\u003c/em\u003e is a sign of a broader dysfunction in the cardiorespiratory response, which may also correlate with signs of an increased cardiovascular risk.\u003c/p\u003e \u003cp\u003eWe evaluated the resting and exercise ventilatory and cardiovascular responses in a cohort of selected post-COVID patients at 34 months from hospitalization. In this evaluation, we compared the data with a previous evaluation performed 6 months after discharge.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eSelection of patients\u003c/h2\u003e \u003cp\u003eData were collected from the RESPICOVID initiative, a prospective observational study conducted at the Respiratory Medicine Unit of the University of Verona and Azienda Ospedaliera Universitaria Integrata of Verona (Italy), involving patients hospitalized for COVID-19 pneumonia during the first two waves of the pandemic emergency in Italy. A dedicated outpatient clinic has been organized, and all subjects discharged were considered. The present longitudinal analysis with repeated measures has been designed to evaluate the long-term persistence of ventilatory inefficiency in subjects enrolled in the RESPICOVID-2 study [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. Only subjects who performed both CPETs (at T0 and T1) were considered. Figure\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e shows the study flow diagram.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eTo better define the EV\u003cem\u003ein\u003c/em\u003e and cardiovascular response to exercise, we excluded any potential physiological or pathological variable influencing exercise adaptations [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. We have then excluded subjects meeting the following criteria: \u003cem\u003ea)\u003c/em\u003e age exceeding 65 years; \u003cem\u003eb)\u003c/em\u003e concurrent presence of respiratory and non-respiratory chronic diseases, respiratory failure, or need for long-term oxygen therapy; \u003cem\u003ec)\u003c/em\u003e a body mass index (BMI)\u0026thinsp;\u0026ge;\u0026thinsp;35 kg/m\u003csup\u003e2\u003c/sup\u003e; and \u003cem\u003ed)\u003c/em\u003e an inability to perform a CPET with a peak respiratory exchange ratio (RER)\u0026thinsp;\u0026lt;\u0026thinsp;1.05 (to exclude poor motivation). Among chronic diseases, only stable arterial hypertension was accepted.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eMeasurements\u003c/h3\u003e\n\u003cp\u003eAll measures were prospectively collected beginning in July 2020, approximately 6 months after the subjects\u0026rsquo; discharge (T0), and repeated until March 2023, 34 months after the discharge (T1). Only subjects with both CPET measures (T0 and T1) were considered for the analysis. Preliminary data about measures performed at T0 have been reported previously [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. The local Ethics Committee approved the study protocol (no. 2785CESC), which was performed according to the Good Clinical Practice recommendations and the requirements of the Declaration of Helsinki. Written informed consent was obtained from all subjects.\u003c/p\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eLung function\u003c/h2\u003e \u003cp\u003eLung function procedures were performed according to international recommendations [\u003cspan additionalcitationids=\"CR21\" citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. A flow-sensing spirometer connected to a computer for data analysis (Jaeger MasterScreen PFT System) was used to measure lung function. Forced vital capacity (FVC), forced expiratory volume in the first second (FEV\u003csub\u003e1\u003c/sub\u003e), and total lung capacity (TLC) were recorded. FEV\u003csub\u003e1\u003c/sub\u003e/FVC ratio was taken as the index of airflow obstruction. The single-breath method measured the diffusion capacity for carbon monoxide (DL\u003csub\u003eCO\u003c/sub\u003e). FEV\u003csub\u003e1\u003c/sub\u003e, FVC, TLC, and DL\u003csub\u003eCO\u003c/sub\u003e were expressed as percentages of the predicted values [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eCardiopulmonary exercise test\u003c/h2\u003e \u003cp\u003eAccording to the ATS/ACCP Statement, for the CPET measures, we used a cycle ergometer (E100, Cosmed Srl, Rome, Italy) with a ramp protocol of 10 to 25 watts increment every minute and based on the predicted peak power output, to achieve an exercise time between 8\u0026ndash;12 minutes [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. Patient were monitored 3 minutes before the ramp protocol (rest phase) and 5 minutes after (cool down phase). Subjects were asked to avoid caffeine, alcohol, cigarettes, and strenuous exercise 24 hours before the day of testing and avoid eating for the 2 hours before the test. Subjects suspended β-blockers before testing but could take their current antihypertensive therapies. During the test, subjects were asked to maintain a pedal frequency of 65 per minute and were continuously monitored [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. Subjects were continuously monitored with a 12-lead electrocardiogram (ECG) and a pulse oximeter; blood pressure was measured every two minutes. Stopping criteria consisted of symptoms, such as unsustainable perceived dyspnoea or leg fatigue, chest pain, a significant ST-segment depression at ECG, or a drop in systolic blood pressure or oxygen saturation\u0026thinsp;\u0026le;\u0026thinsp;84% [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. Cardio-respiratory measures were sampled continuously with a breath-by-breath method using a gas analysis system (Quark CPET, Cosmed Srl, Rome, Italy). Oxygen uptake was expressed in mL/kg/min and as a percentage of predicted. The ventilatory response during exercise was through the relationship of V̇\u003csub\u003eE\u003c/sub\u003e against V̇\u003csub\u003eCO2\u003c/sub\u003e obtained every 10 seconds, excluding data above the respiratory compensation point (RCP). We gathered data of V̇\u003csub\u003eE\u003c/sub\u003e/V̇\u003csub\u003eCO2 slope\u003c/sub\u003e and Y-intercept (V̇\u003csub\u003eE\u003c/sub\u003e/V̇\u003csub\u003eCO2 intercept\u003c/sub\u003e) values obtained from the regression function. V̇\u003csub\u003eE\u003c/sub\u003e/V̇\u003csub\u003eCO2\u003c/sub\u003e was also been evaluated at nadir (V̇\u003csub\u003eE\u003c/sub\u003e/V̇\u003csub\u003eCO2 nadir\u003c/sub\u003e) and the first ventilatory threshold (V̇\u003csub\u003eE\u003c/sub\u003e/V̇\u003csub\u003eCO2\u003c/sub\u003e at θ\u003csub\u003eL\u003c/sub\u003e) [7].\u003c/p\u003e \u003cp\u003eFor the definition of the EV\u003cem\u003ein\u003c/em\u003e, we used the regression equation of V̇\u003csub\u003eE\u003c/sub\u003e/ V̇\u003csub\u003eCO2 slope\u003c/sub\u003e for healthy subjects, considering three standard deviations as the upper limit [5]. Then, we considered subjects having a lower range of V̇\u003csub\u003eE\u003c/sub\u003e/V̇\u003csub\u003eCO2 slope\u003c/sub\u003e (EV\u003cem\u003eef\u003c/em\u003e) and subjects with over the upper limit of V̇\u003csub\u003eE\u003c/sub\u003e/V̇\u003csub\u003eCO2 slope\u003c/sub\u003e (EV\u003cem\u003ein\u003c/em\u003e). Subjects having EV\u003cem\u003ein\u003c/em\u003e at T0 and T1 were defined as persisting ventilatory inefficiency subjects (pEV\u003cem\u003ein\u003c/em\u003e).\u003c/p\u003e \u003cp\u003eThe end-tidal pressure of CO\u003csub\u003e2\u003c/sub\u003e (PET\u003csub\u003eCO2\u003c/sub\u003e, in mmHg) was measured as the mean of PET\u003csub\u003eCO2\u003c/sub\u003e during the 3-minute rest period and the last 20 seconds of the test and was recorded at any time during CPET (at rest, at θ\u003csub\u003eL\u003c/sub\u003e, at the respiratory compensation point - RCP, and at peak of exercise).\u003c/p\u003e \u003cp\u003eThe cardiovascular response to exercise was expressed by HR, O\u003csub\u003e2\u003c/sub\u003e pulse, OUES, oxygen uptake and workload relationship (V̇\u003csub\u003eO2\u003c/sub\u003e/W\u003csub\u003eslope\u003c/sub\u003e) and HR after 1 minute of recovery (heart rate recovery, HRR). O\u003csub\u003e2\u003c/sub\u003e pulse was calculated by dividing instantaneous V̇O\u003csub\u003e2\u003c/sub\u003e by HR [7]. The OUES describes the relationship between V̇\u003csub\u003eO2\u003c/sub\u003e and V̇\u003csub\u003eE\u003c/sub\u003e during incremental exercise, via a log transformation of V̇\u003csub\u003eE\u003c/sub\u003e, and was expressed in L/min as the gradient of the linear relationship of log\u003csub\u003e10\u003c/sub\u003e V̇\u003csub\u003eE\u003c/sub\u003e to V̇\u003csub\u003eO2\u003c/sub\u003e [24]. V̇\u003csub\u003eO2\u003c/sub\u003e/W\u003csub\u003eslope\u003c/sub\u003e was calculated as the slope of oxygen uptake as a function of Watts [7, 24]. OUES thus represents the absolute rate of increase in oxygen uptake per 10-fold increase in minute ventilation. HRR in bpm was defined as the reduction in the HR from the peak exercise level to the rate 1 min after the end of exercise [25]\u003c/p\u003e \u003cp\u003eAt the end of the exercise, dyspnoea and leg fatigue were measured by a Borg 6\u0026ndash;20 rate perceived exertion (RPE) scale [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. Perceived peak dyspnoea and fatigue data have been described as RPE and peak workload ratio. We considered a test as maximal if subjects had a plateau of the V̇O\u003csub\u003e2\u003c/sub\u003e for more than 20 seconds, a Respiratory Exchange Ratio (RER)\u0026thinsp;\u0026gt;\u0026thinsp;1.15, and a Borg RPE score\u0026thinsp;\u0026gt;\u0026thinsp;18 [23].\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003eSelf-Reported Questionnaire\u003c/h2\u003e \u003cp\u003eThe modified Medical Research Council (mMRC) questionnaire was administered to measure perceived breathlessness, with a range from 0 (shortness of breath with strenuous exercise) to 4 (too breathless to leave the house) [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis\u003c/h2\u003e \u003cp\u003eA preliminary Shapiro-Wilk test was performed. Data are reported as percentages for categorical variables, as mean (SD) or median [IQR-interquartile range] for continuous variables with a normal or non-normal distribution, respectively. Categorical variables were compared using the Chi-square test or the Fisher exact test, while the independent \u003cem\u003et\u003c/em\u003e-test or the non-parametric Mann-Whitney test assessed continuous variables. Relationships between variables were assessed using Pearson\u0026rsquo;s correlation coefficient (\u003cem\u003er\u003c/em\u003e).\u003c/p\u003e \u003cp\u003eAll analyses were performed using IBM SPSS, version 17.0 (IBM Corp., Armonk, NY, USA), with p-values of \u0026lt;\u0026thinsp;0.05 considered statistically significant.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003eWe evaluated the same thirty-two post-COVID subjects at T0 (median time from discharge 184 days) and T1 (median 1015 days). At T0, of 32 subjects, 8 had EV\u003cem\u003ein\u003c/em\u003e (25%), while at T1 5 subjects (16%) had a pEV\u003cem\u003ein\u003c/em\u003e. Subjects with pEV\u003cem\u003ein\u003c/em\u003e, in comparison to subjects with EV\u003cem\u003eef\u003c/em\u003e, had significantly higher values of a baseline of V̇E/V̇CO\u003csub\u003e2 slope\u003c/sub\u003e, V̇\u003csub\u003eE\u003c/sub\u003e/V̇\u003csub\u003eCO2 nadir\u003c/sub\u003e, and V̇E/V̇CO\u003csub\u003e2\u003c/sub\u003e at θ\u003csub\u003eL\u003c/sub\u003e with lower values of V̇E/V̇CO\u003csub\u003e2 intercept\u003c/sub\u003e. No other variables, including those related to COVID-19 hospitalization, differed between subjects with pEV\u003cem\u003ein\u003c/em\u003e and subjects with EV\u003cem\u003eef\u003c/em\u003e. Baseline variables were reported in Table \u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\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\u003eGeneral, functional and CPET-related baseline variables.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\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=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\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\u003eAll subjects\u003c/p\u003e \u003cp\u003e(N\u0026thinsp;=\u0026thinsp;32)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSubjects with EV\u003cem\u003eef\u003c/em\u003e (N\u0026thinsp;=\u0026thinsp;27)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eSubjects with pEV\u003cem\u003ein\u003c/em\u003e (N\u0026thinsp;=\u0026thinsp;5)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003ep-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, y\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e55.2 [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e55 [5.5]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e58 [13.1]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.550\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e24 (75)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e20 (74)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4 (80)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;0.999\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCurrent or former smokers, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e18 (56)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e15 (56)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3 (60)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;0.999\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eArterial hypertension\u003csup\u003e*\u003c/sup\u003e, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10 (31)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9 (33)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1 (20)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;0.999\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\u003e26.8\u0026thinsp;\u0026plusmn;\u0026thinsp;3.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e26.7\u0026thinsp;\u0026plusmn;\u0026thinsp;3.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e27.3\u0026thinsp;\u0026plusmn;\u0026thinsp;3.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.734\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFEV\u003csub\u003e1\u003c/sub\u003e, % predicted\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e115.7\u0026thinsp;\u0026plusmn;\u0026thinsp;13.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e114.2\u0026thinsp;\u0026plusmn;\u0026thinsp;13.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e126.2\u0026thinsp;\u0026plusmn;\u0026thinsp;9.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.107\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFVC, % predicted\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e119 [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e117.5 [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e124.5 [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.376\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\u003e79.3\u0026thinsp;\u0026plusmn;\u0026thinsp;5.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e78.8\u0026thinsp;\u0026plusmn;\u0026thinsp;5.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e82.3\u0026thinsp;\u0026plusmn;\u0026thinsp;5.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.279\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTLC, % predicted\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e102.7\u0026thinsp;\u0026plusmn;\u0026thinsp;11.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e103\u0026thinsp;\u0026plusmn;\u0026thinsp;11.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e100.5\u0026thinsp;\u0026plusmn;\u0026thinsp;13.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.697\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDL\u003csub\u003eCO\u003c/sub\u003e, % predicted\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e92.6\u0026thinsp;\u0026plusmn;\u0026thinsp;13.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e92.7\u0026thinsp;\u0026plusmn;\u0026thinsp;13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e91.7\u0026thinsp;\u0026plusmn;\u0026thinsp;17.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.897\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePaO\u003csub\u003e2\u003c/sub\u003e, mmHg\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e101.9\u0026thinsp;\u0026plusmn;\u0026thinsp;11.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e103\u0026thinsp;\u0026plusmn;\u0026thinsp;11.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e96.4\u0026thinsp;\u0026plusmn;\u0026thinsp;12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.261\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePaCO\u003csub\u003e2\u003c/sub\u003e, mmHg\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e38.7\u0026thinsp;\u0026plusmn;\u0026thinsp;3.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e38.5\u0026thinsp;\u0026plusmn;\u0026thinsp;3.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e39.6\u0026thinsp;\u0026plusmn;\u0026thinsp;3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.482\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e6MWT, total distance walked meters\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e587.8\u0026thinsp;\u0026plusmn;\u0026thinsp;84.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e592.4\u0026thinsp;\u0026plusmn;\u0026thinsp;82.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e562.8\u0026thinsp;\u0026plusmn;\u0026thinsp;101\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.480\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003emMRC, score\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1 [0]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1 [0]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1 [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.880\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWorkload, watts\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e166.6\u0026thinsp;\u0026plusmn;\u0026thinsp;50.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e169.9\u0026thinsp;\u0026plusmn;\u0026thinsp;52.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e148.8\u0026thinsp;\u0026plusmn;\u0026thinsp;43.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.401\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eV̇\u003csub\u003eO2\u003c/sub\u003e at peak, ml\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2114.9\u0026thinsp;\u0026plusmn;\u0026thinsp;548.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2143.6\u0026thinsp;\u0026plusmn;\u0026thinsp;561.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1960.2\u0026thinsp;\u0026plusmn;\u0026thinsp;493.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.501\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eV̇\u003csub\u003eO2\u003c/sub\u003e at peak, ml/kg/min\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e26.2\u0026thinsp;\u0026plusmn;\u0026thinsp;5.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e27\u0026thinsp;\u0026plusmn;\u0026thinsp;5.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e24.7\u0026thinsp;\u0026plusmn;\u0026thinsp;7.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.427\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eV̇\u003csub\u003eO2\u003c/sub\u003e at peak, % predicted\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e98.7\u0026thinsp;\u0026plusmn;\u0026thinsp;15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e100\u0026thinsp;\u0026plusmn;\u0026thinsp;15.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e91.6\u0026thinsp;\u0026plusmn;\u0026thinsp;6.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.255\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eV̇\u003csub\u003eO2\u003c/sub\u003e/W\u003csub\u003eslope\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e9.71\u0026thinsp;\u0026plusmn;\u0026thinsp;1.31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9.81\u0026thinsp;\u0026plusmn;\u0026thinsp;1.23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e9.18\u0026thinsp;\u0026plusmn;\u0026thinsp;1.75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.330\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eV̇\u003csub\u003eE\u003c/sub\u003e/V̇\u003csub\u003eCO2 slope\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e28\u0026thinsp;\u0026plusmn;\u0026thinsp;4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e26.9\u0026thinsp;\u0026plusmn;\u0026thinsp;3.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e33.9\u0026thinsp;\u0026plusmn;\u0026thinsp;1.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eV̇\u003csub\u003eE\u003c/sub\u003e/V̇\u003csub\u003eCO2 nadir\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e26.8\u0026thinsp;\u0026plusmn;\u0026thinsp;2.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e26.2\u0026thinsp;\u0026plusmn;\u0026thinsp;2.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e30.5\u0026thinsp;\u0026plusmn;\u0026thinsp;2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eV̇\u003csub\u003eE\u003c/sub\u003e/V̇\u003csub\u003eCO2\u003c/sub\u003e at θ\u003csub\u003eL\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e28.1\u0026thinsp;\u0026plusmn;\u0026thinsp;2.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e27.6\u0026thinsp;\u0026plusmn;\u0026thinsp;2.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e31\u0026thinsp;\u0026plusmn;\u0026thinsp;1.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.008\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eV̇\u003csub\u003eE\u003c/sub\u003e/V̇\u003csub\u003eCO2 intercept\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.79\u0026thinsp;\u0026plusmn;\u0026thinsp;3.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.35\u0026thinsp;\u0026plusmn;\u0026thinsp;3.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.24\u0026thinsp;\u0026plusmn;\u0026thinsp;3.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.042\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eV̇\u003csub\u003eE\u003c/sub\u003e at rest, L/min\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e15.9\u0026thinsp;\u0026plusmn;\u0026thinsp;5.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e15.6\u0026thinsp;\u0026plusmn;\u0026thinsp;5.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e17.6\u0026thinsp;\u0026plusmn;\u0026thinsp;7.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.489\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eV̇\u003csub\u003eE\u003c/sub\u003e at peak, L/min\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e85 [40.2]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e84.1 [36.6]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e101.3 [38.6]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.159\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRR change\u003csup\u003e\u0026sect;\u003c/sup\u003e, breath/min\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e19\u0026thinsp;\u0026plusmn;\u0026thinsp;7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e18.5\u0026thinsp;\u0026plusmn;\u0026thinsp;7.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e22.2\u0026thinsp;\u0026plusmn;\u0026thinsp;4.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.282\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eO\u003csub\u003e2\u003c/sub\u003e pulse at peak, mL/bpm\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e13.5\u0026thinsp;\u0026plusmn;\u0026thinsp;3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e13.5\u0026thinsp;\u0026plusmn;\u0026thinsp;3.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e12.6\u0026thinsp;\u0026plusmn;\u0026thinsp;2.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.579\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOUES, L/min\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.09\u0026thinsp;\u0026plusmn;\u0026thinsp;0.22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.11\u0026thinsp;\u0026plusmn;\u0026thinsp;0.21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.98\u0026thinsp;\u0026plusmn;\u0026thinsp;0.20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.242\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHR\u003csub\u003emax\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e156.7\u0026thinsp;\u0026plusmn;\u0026thinsp;14.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e157.3\u0026thinsp;\u0026plusmn;\u0026thinsp;14.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e153.6\u0026thinsp;\u0026plusmn;\u0026thinsp;13.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.593\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHRR, beats/minute\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e23.8\u0026thinsp;\u0026plusmn;\u0026thinsp;6.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e24.4\u0026thinsp;\u0026plusmn;\u0026thinsp;6.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e20.6\u0026thinsp;\u0026plusmn;\u0026thinsp;6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.227\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHR/V̇\u003csub\u003eO2\u003c/sub\u003e slope, L\u003csup\u003e\u0026minus;1\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e50.1 [33.8]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e50.1 [31.8]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e77.5 [56]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.361\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePerceived peak dyspnea\u003csup\u003e#\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e17 [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e17 [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e17 [3.5]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.525\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePerceived peak fatigue\u003csup\u003e#\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e18 [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e18 [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e18 [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;0.999\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e \u003cp\u003e\u003cem\u003eVariables related to COVID-19 hospitalisation\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLength of hospital stay, days\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6 [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6.1 [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6 [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.677\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNeeding of oxygen therapy, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e22 (68)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e18 (67)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4 (80)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;0.999\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNeeding of ventilatory support, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e13 (41)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e11 (41)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2 (40)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;0.999\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNeeding of ICU admission, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5 (16)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3 (11)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2 (40)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.163\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePaO\u003csub\u003e2\u003c/sub\u003e/FiO\u003csub\u003e2\u003c/sub\u003e at admission (n\u0026thinsp;=\u0026thinsp;16)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e305.9\u0026thinsp;\u0026plusmn;\u0026thinsp;102.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e305.7\u0026thinsp;\u0026plusmn;\u0026thinsp;107.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e307.9\u0026thinsp;\u0026plusmn;\u0026thinsp;84.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.986\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePaO\u003csub\u003e2\u003c/sub\u003e/FiO\u003csub\u003e2\u003c/sub\u003e\u0026thinsp;\u0026lt;\u0026thinsp;300, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e9 (53)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8 (53)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1 (50)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;0.999\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePaCO\u003csub\u003e2\u003c/sub\u003e at admission (n\u0026thinsp;=\u0026thinsp;16)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e34.2\u0026thinsp;\u0026plusmn;\u0026thinsp;5.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e34.1\u0026thinsp;\u0026plusmn;\u0026thinsp;4.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e35\u0026thinsp;\u0026plusmn;\u0026thinsp;12.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.940\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003eData are shown as the number of subjects (%), means\u0026thinsp;\u0026plusmn;\u0026thinsp;SD or medians [IQR-interquartile range]. In bold are reported significant values.\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003e\u003csup\u003e*\u003c/sup\u003eSubjects with arterial hypertension were treated with ACE inhibitors (N\u0026thinsp;=\u0026thinsp;6, 19%), β-blockers (N\u0026thinsp;=\u0026thinsp;4, 12%), and Ca\u003csup\u003e2+\u003c/sup\u003e antagonist (N\u0026thinsp;=\u0026thinsp;3, 9%); \u003csup\u003e\u0026sect;\u003c/sup\u003eCalculated as value at peak less value at rest; \u003csup\u003e#\u003c/sup\u003eDescribed as a Borg 6\u0026ndash;20 perceived exertion rate score.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e\u003cp\u003e\u003cem\u003eAbbreviations:\u003c/em\u003e EV\u003cem\u003eef\u003c/em\u003e defines exercise ventilatory efficiency; pEV\u003cem\u003ein\u003c/em\u003e, persisting exercise ventilatory inefficiency; BMI body mass index; FEV\u003csub\u003e1\u003c/sub\u003e, forced expiratory volume at 1\u003csup\u003est\u003c/sup\u003e second; FVC, forced vital capacity; TLC, total lung capacity; DL\u003csub\u003eCO\u003c/sub\u003e, diffusion capacity for carbon monoxide; PaO\u003csub\u003e2\u003c/sub\u003e, partial arterial oxygen pressure; PaCO\u003csub\u003e2\u003c/sub\u003e, partial pressure of arterial carbon dioxide; 6MWT, six-minute walking test; mMRC, modified Medical Research Council dyspnea score;\u0026nbsp;V̇\u003csub\u003eO2\u003c/sub\u003e, oxygen uptake;\u0026nbsp;V̇\u003csub\u003eE\u003c/sub\u003e/V̇\u003csub\u003eCO2 slope\u003c/sub\u003e, the slope of\u0026nbsp;V̇\u003csub\u003eE\u003c/sub\u003e to carbon dioxide output-V̇\u003csub\u003eCO2\u003c/sub\u003e ratio;\u0026nbsp;\u0026theta;\u003csub\u003eL\u003c/sub\u003e,\u0026nbsp;the first ventilatory threshold;\u0026nbsp;V̇\u003csub\u003eE\u003c/sub\u003e/V̇\u003csub\u003eCO2 intercept\u003c/sub\u003e, point of intercept of\u0026nbsp;V̇\u003csub\u003eE\u003c/sub\u003e to carbon dioxide output-V̇\u003csub\u003eCO2\u003c/sub\u003e ratio;\u0026nbsp;V̇\u003csub\u003eE\u003c/sub\u003e, minute ventilation; RR, respiratory rate; OUES, oxygen uptake efficiency slope; HRR, heart rate recovery; ICU, intensive care unit.\u003c/p\u003e \u003cp\u003eIn all subjects, comparing T1 \u003cem\u003evs\u003c/em\u003e T0 (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e), there was an increment of BMI, DL\u003csub\u003eCO\u003c/sub\u003e % predicted, V̇\u003csub\u003eO2\u003c/sub\u003e at peak % predicted, and O\u003csub\u003e2\u003c/sub\u003e pulse at peak, with a reduction of FEV\u003csub\u003e1\u003c/sub\u003e and FVC (both % predicted), V̇E/V̇CO\u003csub\u003e2\u003c/sub\u003e at θ\u003csub\u003eL\u003c/sub\u003e and V̇\u003csub\u003eE\u003c/sub\u003e at rest. In EV\u003cem\u003eef\u003c/em\u003e, selective changes between T1 and T0 were evident in the following variables: BMI, DL\u003csub\u003eCO\u003c/sub\u003e % predicted, O\u003csub\u003e2\u003c/sub\u003e pulse at peak, V̇\u003csub\u003eE\u003c/sub\u003e/V̇\u003csub\u003eCO2\u003c/sub\u003e at θ\u003csub\u003eL\u003c/sub\u003e and V̇\u003csub\u003eE\u003c/sub\u003e at rest. No selective changes were evident in subjects with pEV\u003cem\u003ein\u003c/em\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\u003eCPET-related differences between T0 and T1.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"10\"\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=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003eAll subjects (N\u0026thinsp;=\u0026thinsp;32)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c7\" namest=\"c5\"\u003e \u003cp\u003eSubjects with EV\u003cem\u003eef\u003c/em\u003e (N\u0026thinsp;=\u0026thinsp;27)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c10\" namest=\"c8\"\u003e \u003cp\u003eSubjects with pEV\u003cem\u003ein\u003c/em\u003e (N\u0026thinsp;=\u0026thinsp;5)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariables\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eT0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eT1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eMean difference (T1-T0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e95% CI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eMean difference\u003c/p\u003e \u003cp\u003e(T1-T0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e95% CI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003ep-value\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\u003e26.8\u0026thinsp;\u0026plusmn;\u0026thinsp;3.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e27.6\u0026thinsp;\u0026plusmn;\u0026thinsp;3.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.97\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.43 to 1.53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e-0.34 to 0.74\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.368\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFEV\u003csub\u003e1\u003c/sub\u003e, % predicted\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e115.7\u0026thinsp;\u0026plusmn;\u0026thinsp;13.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e113.1\u0026thinsp;\u0026plusmn;\u0026thinsp;12.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.023\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-2.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-4.4 to 0.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.054\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-5.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e-19.8 to 8.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.311\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFVC, % predicted\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e119 [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e115 [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.010\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-8.3 to 7.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.925\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e-13.9 to 5.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.289\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\u003e79.3\u0026thinsp;\u0026plusmn;\u0026thinsp;5.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e79.2\u0026thinsp;\u0026plusmn;\u0026thinsp;4.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.910\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-1.1 to 1.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.774\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-1.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e-3.8 to 0.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.069\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTLC, % predicted\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e102.7\u0026thinsp;\u0026plusmn;\u0026thinsp;11.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e101.7\u0026thinsp;\u0026plusmn;\u0026thinsp;10.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.413\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-1.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-3.7 to 1.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.292\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e-12.3 to 14.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.789\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDL\u003csub\u003eCO\u003c/sub\u003e, % predicted\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e92.6\u0026thinsp;\u0026plusmn;\u0026thinsp;13.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e97.2\u0026thinsp;\u0026plusmn;\u0026thinsp;12.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.004\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e5.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.1 to 8.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e0.002\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e-18.1 to 21.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.798\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003emMRC, score\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1 [0]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1 [0]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.705\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-1.9 to 1.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;0.999\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.3 to 0.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.374\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWorkload, watts\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e166.6\u0026thinsp;\u0026plusmn;\u0026thinsp;50.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e164.4\u0026thinsp;\u0026plusmn;\u0026thinsp;44.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.462\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-3.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-10.6 to 3.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.327\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e4.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e-5-5 to 14.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.285\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eV̇\u003csub\u003eO2\u003c/sub\u003e at peak, ml\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2114.9\u0026thinsp;\u0026plusmn;\u0026thinsp;548.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2188.2\u0026thinsp;\u0026plusmn;\u0026thinsp;545.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.068\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e76.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-16.3 to 168.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.102\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e56.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e-91.9 to 205.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.349\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eV̇\u003csub\u003eO2\u003c/sub\u003e at peak, ml/kg/min\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e26.2\u0026thinsp;\u0026plusmn;\u0026thinsp;5.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e26.7\u0026thinsp;\u0026plusmn;\u0026thinsp;5.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.333\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.61\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-1.8 to 0.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.287\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e-1.69 to 2.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.748\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eV̇\u003csub\u003eO2\u003c/sub\u003e at peak, % predicted\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e98.7\u0026thinsp;\u0026plusmn;\u0026thinsp;15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e101.9\u0026thinsp;\u0026plusmn;\u0026thinsp;13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.032\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.88\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.54 to 6.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.095\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e-0.4 to 10.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.062\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eV̇\u003csub\u003eO2\u003c/sub\u003e/W\u003csub\u003eslope\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e9.71\u0026thinsp;\u0026plusmn;\u0026thinsp;1.31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10.34\u0026thinsp;\u0026plusmn;\u0026thinsp;1.42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.033\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.15 to 1.15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.128\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.20 to 2.34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u003cb\u003e0.030\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eV̇\u003csub\u003eE\u003c/sub\u003e/V̇\u003csub\u003eCO2 slope\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e28\u0026thinsp;\u0026plusmn;\u0026thinsp;4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e27.8\u0026thinsp;\u0026plusmn;\u0026thinsp;3.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.756\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-1.77 to 1.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.598\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.78\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e-1.8 to 3.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.451\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eV̇\u003csub\u003eE\u003c/sub\u003e/V̇\u003csub\u003eCO2 nadir\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e26.8\u0026thinsp;\u0026plusmn;\u0026thinsp;2.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e26.3\u0026thinsp;\u0026plusmn;\u0026thinsp;3.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.161\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.51\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-1.36 to 0.33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.224\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-0.52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e-2.27 to 1.24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.458\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eV̇\u003csub\u003eE\u003c/sub\u003e/V̇\u003csub\u003eCO2\u003c/sub\u003e at θ\u003csub\u003eL\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e28.1\u0026thinsp;\u0026plusmn;\u0026thinsp;2.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e27.2\u0026thinsp;\u0026plusmn;\u0026thinsp;3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.028\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-1.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-1.94 to -0.18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e0.020\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e-2.37 to 2.45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.966\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eV̇\u003csub\u003eE\u003c/sub\u003e/V̇\u003csub\u003eCO2 intercept\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.79\u0026thinsp;\u0026plusmn;\u0026thinsp;3.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.26\u0026thinsp;\u0026plusmn;\u0026thinsp;3.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.520\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.54\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-1.1 to 2.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.514\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e-3.9 to 4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.968\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eV̇\u003csub\u003eE\u003c/sub\u003e at rest, L/min\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e15.9\u0026thinsp;\u0026plusmn;\u0026thinsp;5.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e12.4\u0026thinsp;\u0026plusmn;\u0026thinsp;2.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.002\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-3.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.98 to -5.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e0.007\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-4.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e-11.9 to 3.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.191\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eV̇\u003csub\u003eE\u003c/sub\u003e at peak, L/min\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e86.3 [42.8]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e88.7 [39.6]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.695\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-4.90 to 6.15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.818\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-0.88\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e-18.4 to 16.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.896\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRR change\u003csup\u003e\u0026sect;\u003c/sup\u003e, breath/min\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e19\u0026thinsp;\u0026plusmn;\u0026thinsp;7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e18.6\u0026thinsp;\u0026plusmn;\u0026thinsp;4.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.688\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-1.6 to 2.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.680\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-4.94\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e-13.9 to 4.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.203\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eO\u003csub\u003e2\u003c/sub\u003e pulse at peak, mL/bpm\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e13.5\u0026thinsp;\u0026plusmn;\u0026thinsp;3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e14.2\u0026thinsp;\u0026plusmn;\u0026thinsp;3.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.031\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.09 to 1.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e0.027\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e-1.46 to 1.54\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.943\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOUES, L/min\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.09\u0026thinsp;\u0026plusmn;\u0026thinsp;0.22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.12\u0026thinsp;\u0026plusmn;\u0026thinsp;0.24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.186\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.02 to 0.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.264\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e-0.04 to 0.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.331\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHR\u003csub\u003emax\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e156.7\u0026thinsp;\u0026plusmn;\u0026thinsp;14.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e155.2\u0026thinsp;\u0026plusmn;\u0026thinsp;13.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.397\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-2.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-6.4 to 1.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.147\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e-8.6 to 18.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.365\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHRR, beats/minute\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e23.8\u0026thinsp;\u0026plusmn;\u0026thinsp;6.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e25.5\u0026thinsp;\u0026plusmn;\u0026thinsp;6.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.192\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-1.32 to 4.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.272\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e2.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e-6 to 10.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.500\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePerceived peak dyspnea\u003csup\u003e#\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e17 [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e17 [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.182\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-1.4 to 0.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.640\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e-1.4 to 1.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.749\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePerceived peak fatigue\u003csup\u003e#\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e18 [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e18 [2.75]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.212\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.6 to 1.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.658\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e-1.2 to 1.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;0.999\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"10\"\u003eData are shown as the number of subjects (%), means\u0026thinsp;\u0026plusmn;\u0026thinsp;SD or medians [IQR-interquartile range]. The difference between T1 and T0 are expressed as mean and confidence intervals at 95%. In bold are reported significant values.\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"10\"\u003e\u003csup\u003e\u0026sect;\u003c/sup\u003eCalculated as value at peak less value at rest; \u003csup\u003e#\u003c/sup\u003eDescribed as a Borg 6\u0026ndash;20 perceived exertion rate score and peak workload ratio.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e\u003cp\u003e\u003cem\u003eAbbreviations:\u0026nbsp;\u003c/em\u003eEV\u003cem\u003eef\u003c/em\u003e defines exercise ventilatory efficiency; pEV\u003cem\u003ein\u003c/em\u003e, persisting exercise ventilatory inefficiency; BMI body mass index; FEV\u003csub\u003e1\u003c/sub\u003e, forced expiratory volume at 1\u003csup\u003est\u003c/sup\u003e second; FVC, forced vital capacity; TLC, total lung capacity; DL\u003csub\u003eCO\u003c/sub\u003e, diffusion capacity for carbon monoxide; mMRC, modified Medical Research Council dyspnea score;\u0026nbsp;V̇\u003csub\u003eO2\u003c/sub\u003e, oxygen uptake;\u0026nbsp;V̇\u003csub\u003eE\u003c/sub\u003e/V̇\u003csub\u003eCO2 slope\u003c/sub\u003e, the slope of\u0026nbsp;V̇\u003csub\u003eE\u003c/sub\u003e to carbon dioxide output-V̇\u003csub\u003eCO2\u003c/sub\u003e ratio;\u0026nbsp;\u0026theta;\u003csub\u003eL\u003c/sub\u003e,\u0026nbsp;the first ventilatory threshold;\u0026nbsp;V̇\u003csub\u003eE\u003c/sub\u003e/V̇\u003csub\u003eCO2 intercept\u003c/sub\u003e, point of intercept of\u0026nbsp;V̇\u003csub\u003eE\u003c/sub\u003e to carbon dioxide output-V̇\u003csub\u003eCO2\u003c/sub\u003e ratio;\u0026nbsp;V̇\u003csub\u003eE\u003c/sub\u003e, minute ventilation; RR, respiratory rate; OUES, oxygen uptake efficiency slope; HRR, heart rate recovery.\u003c/p\u003e \u003cp\u003ePET\u003csub\u003eCO2\u003c/sub\u003e was significantly lower in patients with EV\u003cem\u003ein\u003c/em\u003e than EV\u003cem\u003eef\u003c/em\u003e at any time point of the exercise (at rest, at θ\u003csub\u003eL\u003c/sub\u003e, at RCP and peak) at T1, while at T0 were different at rest, at RCP, and peak (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eAt T1, PET\u003csub\u003eCO2\u003c/sub\u003e at rest (\u003cem\u003er\u003c/em\u003e 0.366; p\u0026thinsp;=\u0026thinsp;0.039 and \u003cem\u003er\u003c/em\u003e 0.353; p\u0026thinsp;=\u0026thinsp;0.048), such as at θ\u003csub\u003eL\u003c/sub\u003e (\u003cem\u003er\u003c/em\u003e 0.532; p\u0026thinsp;=\u0026thinsp;0.002 and \u003cem\u003er\u003c/em\u003e 0.586; p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), at RCP (\u003cem\u003er\u003c/em\u003e 0.514; p\u0026thinsp;=\u0026thinsp;0.004 and \u003cem\u003er\u003c/em\u003e 0.565; p\u0026thinsp;=\u0026thinsp;0.001), and peak (\u003cem\u003er\u003c/em\u003e 0.427; p\u0026thinsp;=\u0026thinsp;0.015 and \u003cem\u003er\u003c/em\u003e 0.480; p\u0026thinsp;=\u0026thinsp;0.005) were significantly and respectively correlated with O\u003csub\u003e2\u003c/sub\u003e pulse at peak and OUES (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eCorrelations among variables of ventilatory inefficiency (V̇\u003csub\u003eE\u003c/sub\u003e/V̇\u003csub\u003eCO2 slope\u003c/sub\u003e), hyperventilation (PET\u003csub\u003eCO2\u003c/sub\u003e) and cardiovascular response to exercise (OUES, O\u003csub\u003e2\u003c/sub\u003e pulse at peak), all evaluated at T1.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\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=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\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\u003ePET\u003csub\u003eCO2\u003c/sub\u003e at rest\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePET\u003csub\u003eCO2\u003c/sub\u003e at θ\u003csub\u003eL\u003c/sub\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003ePET\u003csub\u003eCO2\u003c/sub\u003e at RCP\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003ePET\u003csub\u003eCO2\u003c/sub\u003e at peak\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eO\u003csub\u003e2\u003c/sub\u003e pulse at peak\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eOUES\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eV̇\u003csub\u003eE\u003c/sub\u003e/V̇\u003csub\u003eCO2 slope\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003er\u003c/em\u003e -0.395\u003c/p\u003e \u003cp\u003e\u003cb\u003ep\u0026thinsp;=\u0026thinsp;0.025\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003er\u003c/em\u003e -0.723\u003c/p\u003e \u003cp\u003e\u003cb\u003ep\u0026thinsp;\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003er\u003c/em\u003e -0.801\u003c/p\u003e \u003cp\u003e\u003cb\u003ep\u0026thinsp;\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cem\u003er\u003c/em\u003e -0.579\u003c/p\u003e \u003cp\u003e\u003cb\u003ep\u0026thinsp;=\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cem\u003er\u003c/em\u003e -0.271\u003c/p\u003e \u003cp\u003ep\u0026thinsp;=\u0026thinsp;0.134\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cem\u003er\u003c/em\u003e -0.339\u003c/p\u003e \u003cp\u003ep\u0026thinsp;=\u0026thinsp;0.057\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePET\u003csub\u003eCO2\u003c/sub\u003e at rest\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003er\u003c/em\u003e 0.535\u003c/p\u003e \u003cp\u003e\u003cb\u003ep\u0026thinsp;=\u0026thinsp;0.002\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003er\u003c/em\u003e 0.432\u003c/p\u003e \u003cp\u003e\u003cb\u003ep\u0026thinsp;=\u0026thinsp;0.019\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cem\u003er\u003c/em\u003e 0.574\u003c/p\u003e \u003cp\u003e\u003cb\u003ep\u0026thinsp;=\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cem\u003er\u003c/em\u003e 0.366\u003c/p\u003e \u003cp\u003e\u003cb\u003ep\u0026thinsp;=\u0026thinsp;0.039\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cem\u003er\u003c/em\u003e 0.353\u003c/p\u003e \u003cp\u003e\u003cb\u003ep\u0026thinsp;=\u0026thinsp;0.048\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePET\u003csub\u003eCO2\u003c/sub\u003e at θ\u003csub\u003eL\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003er\u003c/em\u003e 0.941\u003c/p\u003e \u003cp\u003e\u003cb\u003ep\u0026thinsp;\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cem\u003er\u003c/em\u003e 0.821\u003c/p\u003e \u003cp\u003e\u003cb\u003ep\u0026thinsp;\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cem\u003er\u003c/em\u003e 0.532\u003c/p\u003e \u003cp\u003e\u003cb\u003ep\u0026thinsp;=\u0026thinsp;0.002\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cem\u003er\u003c/em\u003e 0.586\u003c/p\u003e \u003cp\u003e\u003cb\u003ep\u0026thinsp;\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePET\u003csub\u003eCO2\u003c/sub\u003e at RCP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cem\u003er\u003c/em\u003e 0.815\u003c/p\u003e \u003cp\u003e\u003cb\u003ep\u0026thinsp;\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cem\u003er\u003c/em\u003e 0.514\u003c/p\u003e \u003cp\u003e\u003cb\u003ep\u0026thinsp;=\u0026thinsp;0.004\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cem\u003er\u003c/em\u003e 0.565\u003c/p\u003e \u003cp\u003e\u003cb\u003ep\u0026thinsp;=\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePET\u003csub\u003eCO2\u003c/sub\u003e at peak\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e--\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cem\u003er\u003c/em\u003e 0.427\u003c/p\u003e \u003cp\u003e\u003cb\u003ep\u0026thinsp;=\u0026thinsp;0.015\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cem\u003er\u003c/em\u003e 0.480\u003c/p\u003e \u003cp\u003e\u003cb\u003ep\u0026thinsp;=\u0026thinsp;0.005\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eO\u003csub\u003e2\u003c/sub\u003e pulse at peak\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cem\u003er\u003c/em\u003e 0.939\u003c/p\u003e \u003cp\u003e\u003cb\u003ep\u0026thinsp;\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOUES\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"7\"\u003eIn bold are reported significant values.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eOur study starts from the hypothesis that EV\u003cem\u003ein\u003c/em\u003e may be a persistent ventilo-perfusory alteration after COVID-19. In a selected cohort of Post-COVID patients, at almost three years of follow-up, we demonstrated that a pEV\u003cem\u003ein\u003c/em\u003e may be present in 16% of subjects. These subjects have the phenomenon of hyperventilation, documented by lower levels of PET\u003csub\u003eCO2\u003c/sub\u003e. The patient cohort, comprising individuals with both EV\u003cem\u003eef\u003c/em\u003e and EV\u003cem\u003ein\u003c/em\u003e, exhibited consistently normal maximal exercise capacity, as well as normal levels of FEV\u003csub\u003e1\u003c/sub\u003e, FVC, TLC at both 6 months (T0) and 34 months after discharge (T1). This persistent exercise hyperventilation correlate with to an exacerbated cardiovascular response to exercise, which was the second hypothesis of this study.\u003c/p\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eVentilatory Inefficiency and Hyperventilation\u003c/h2\u003e \u003cp\u003eA reduction in maximal exercise capacity and V̇\u003csub\u003eO2peak\u003c/sub\u003e has been reported as the main CPET feature of symptomatic post-COVID patients [1]. However, some of the asymptomatic post-COVID patients, despite maintaining preserved lung functionality, maximal exercise capacity and V̇O\u003csub\u003e2peak\u003c/sub\u003e, exhibit EV\u003cem\u003ein\u003c/em\u003e [10, 11]. Research has indicated that exercise ventilatory inefficiency may be a significant feature also in apparently healthy COVID-19 survivors: however, its clinical role has not yet been fully elucidated [19].\u003c/p\u003e \u003cp\u003eIn healthy subjects, EV\u003cem\u003ein\u003c/em\u003e is uncommon and anthropometric variables may influence it. Usually, higher V̇E/V̇CO\u003csub\u003e2slope\u003c/sub\u003e than the normal range is an indicator of EV\u003cem\u003ein\u003c/em\u003e [6, 28].EV\u003cem\u003ein\u003c/em\u003e in cardiopulmonary chronic conditions may be caused mainly by two reasons: \u003cem\u003e1)\u003c/em\u003e An altered arterial partial carbon dioxide pressure (PaCO\u003csub\u003e2\u003c/sub\u003e) set-point and chemosensitivity (usually a consequence of chronic hypoxemia), and \u003cem\u003e2)\u003c/em\u003e an abnormally high dead space fraction during exercise caused by a ventilatory-perfusion mismatch, which could involve the ventilation, or the pulmonary perfusion [8, 28].\u003c/p\u003e \u003cp\u003eHyperventilation is a frequent manifestation of subjects recovering from COVID-19, and it is frequently associated with ventilatory inefficiency; both have been reported as a possible mechanism of persisting disabling signs and symptoms limiting exercise capacity due to an increase in the cost of ventilation [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]. The exact cause of this hyperventilation remains unknown. As a consequence of infection, an imbalance in the ventilatory control has been hypothesized as a cause of the hyperventilation in post-COVID subjects, related to either heightened activation of activator systems (including automatic and cortical ventilatory control, peripheral afferents, and sensory cortex) or suppression of inhibitory systems (endorphins) [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. In COVID-19 survivors, there is also a close relationship between hypocapnia resulting from resting hyperventilation and residual DL\u003csub\u003eCO\u003c/sub\u003e, which are the most common functional abnormality in the early convalescence phase [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. Compared with non-severe cases, patients with severe COVID-19 had a higher impairment in DL\u003csub\u003eCO\u003c/sub\u003e, which likely indicates a restrictive pattern, and a decrease in TLC [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. Although the ventilatory response was unrelated to disease severity, higher values of V̇\u003csub\u003eE\u003c/sub\u003e/V̇\u003csub\u003eCO2 slope\u003c/sub\u003e have been found in a follow-up of seven months as a negative predictor in a cohort of patients developing pulmonary fibrosis [31]. We now report a close association between hyperventilation at each phase of the exercise and the EV\u003cem\u003ein\u003c/em\u003e as a permanent and distinctive sign of a proportion of asymptomatic survivors (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). This phenomenon is probably related to a perpetual altered PaCO\u003csub\u003e2\u003c/sub\u003e set-point and chemosensitivity, or to an alteration of the ventilatory-perfusion mismatch, in which a residual lung function impairment in DL\u003csub\u003eCO\u003c/sub\u003e may play a significant role [6, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, 28].In our data, we confirm the role of DL\u003csub\u003eCO\u003c/sub\u003e and the excess ventilation by the selective improvement after 34 months in EV\u003cem\u003eef\u003c/em\u003e subjects only (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIn line with the assessments made in a shorter period after one year of discharge, the EV\u003cem\u003ein\u003c/em\u003e prevalence in our survivors (16%) is similar to that described by Ingul CB and colleagues (17%), with similar considerations about hyperventilation (PET\u003csub\u003eCO2\u003c/sub\u003e) [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. Of note, Ingul CB and colleagues found a close relationship between the perceived dyspnea and EV\u003cem\u003ein\u003c/em\u003e: this relationship is not confirmed in our asymptomatic patients cohort, in which the level of dyspnea is very low (median mMRC 1) [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. While perceived dyspnea is typically multifaceted in nature, our methodology, which involved the selection of subjects without comorbidities and variables that might affect the ventilatory efficiency\u0026mdash;like a subject's weight\u0026mdash;could have impacted these findings [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]. For instance, Ingul's study included a cohort with 29% obese patients, in contrast to our study, which comprised only three out of 32 subjects (approximately 9%) being obese (data not shown) [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. Persistent viral presence, long-term inflammation, microclots, and hypoxia may contribute to developing symptoms in obese subjects [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]. Moreover, obesity, related to the alteration of mechanical lung function, may affect the subject\u0026rsquo;s dyspnoea perception a priori [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eCardiovascular response to exercise in patient with pEVin\u003c/h2\u003e \u003cp\u003eCOVID patients are at risk for cardiovascular disease during acute phase of the infection [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. Due to the damage of pulmonary endothelium and microclots during the disease, we cannot exclude long-term cardiovascular complications in these patients. EV\u003cem\u003ein\u003c/em\u003e is a well-recognized hallmark of pulmonary vascular disease and increased dead-space ventilation [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. Despite normal V̇O\u003csub\u003e2peak\u003c/sub\u003e levels in subject recovered from severe COVID after one year of follow-up, dead space ventilation correlate with D-Dimer plasma concentrations during hospital stay [13]. At six months of discharge, higher values of V̇\u003csub\u003eE\u003c/sub\u003e/V̇\u003csub\u003eCO2 slope\u003c/sub\u003e have been linked to diminished HRR, suggesting that post-COVID subjectswith EV\u003cem\u003ein\u003c/em\u003e may have a cardiac autonomic dysfunction, a general predictor of mortality in adults without heart disease history [10, 25]. Moreover, studies evaluating the hemodynamic response during exercise confirm that normotensive post-COVID patients present a significantly higher blood pressure response in the post-exercise recovery of the CPET, with an achieved lower O\u003csub\u003e2\u003c/sub\u003e pulse at peak than controls without a history of COVID-19 [17]. O\u003csub\u003e2\u003c/sub\u003e pulse may have non-specific interpretation and attention should be paid when discussing this variable alone. However, recent data show that low levels of O\u003csub\u003e2\u003c/sub\u003e pulse during exercise may be related to an increase in cardiovascular and all-cause mortality in some population [14]. This leads speculating reduced O\u003csub\u003e2\u003c/sub\u003e pulse peak values in COVID-19 recovered subjects could be a significant measure of health outcome. Low O\u003csub\u003e2\u003c/sub\u003e pulse at peak is a consequence of a reduced V̇O\u003csub\u003e2peak\u003c/sub\u003e during short-term follow-up. Already at 6 months of follow-up up to a year after hospital discharge for COVID-19, O\u003csub\u003e2\u003c/sub\u003e pulse and V̇O\u003csub\u003e2peak\u003c/sub\u003e increased significantly [1, 10]. In our longer follow-up, we document a significant global improvement of the O\u003csub\u003e2\u003c/sub\u003e pulse from 6 to 34 months, despite no significant increase in VO\u003csub\u003e2peak\u003c/sub\u003e. It should be noted that the increase was mainly in EV\u003cem\u003eef\u003c/em\u003e patients, speculating that subjects with pEV\u003cem\u003ein\u003c/em\u003e still have a potential impairment in cardiovascular response, or oxygen tissue utilization (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Moreover, we demonstrate a significant correlation between the O\u003csub\u003e2\u003c/sub\u003e pulse at peak and PET\u003csub\u003eCO2\u003c/sub\u003e (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eSimilarly to O\u003csub\u003e2\u003c/sub\u003e pulse, OUES values represent an individual's cardiorespiratory reserve and indicate how effectively oxygen is extracted and utilized by the body [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. The prognostic potential of OUES has been examined in some clinical populations, such as patients with heart failure and very recently, the determination of OUES on healthy males has proved its prediction in all-cause mortality [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e]. Our data about the correlation between the hyperventilation and OUES, similarly for O\u003csub\u003e2\u003c/sub\u003e pulse, define this variable as potentially prognostic for COVID survivors.\u003c/p\u003e \u003cp\u003eData about the exercise training on parameters of cardiovascular response in patients with chronic obstructive pulmonary disease (COPD) report OUES - but also O\u003csub\u003e2\u003c/sub\u003e pulse - as susceptible to changes, as a sign of an enhancement of ventilatory function upon exercise [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e]. In the context of post-COVID patients, although in a single survivor patient from critical COVID-19 illness, and the data requires scientific confirmation, home-based exercise training has been demonstrated to produce a remarkable increment not only of V̇\u003csub\u003eO2\u003c/sub\u003e peak but also of the OUES, with a consensual reduction in V̇\u003csub\u003eE\u003c/sub\u003e/V̇\u003csub\u003eCO2\u003c/sub\u003e and exertional dyspnea [37].\u003c/p\u003e \u003cp\u003eOur study\u0026rsquo;s strength is related to evaluating the EV\u003cem\u003ein\u003c/em\u003e for a very long time from COVID-19 discharge (pEV\u003cem\u003ein\u003c/em\u003e). Although we report a small number of patients (an explicit limitation), this was related to a selective approach excluding patients having a condition potentially influencing the exercise ventilation assessment. We included a healthy population with a normal exercise capacity and pulmonary function tests. This may also be considered a study strength because we excluded any potential cause of ventilatory inefficiency. Finally, we lack same-time data concerning the structural pulmonary (by thorax computed tomography scan) and cardiac (by echocardiography) damage. There is a possibility that these data could have confirmed a coexistent organic residual alteration.\u003c/p\u003e \u003cp\u003eIn conclusion, our longitudinal data analysis on COVID-19 survivors, performed at 34 months from discharge, confirms the persistence of exercise ventilatory inefficiency in 16% of subjects. These subjects exhibit a hyperventilation status that correlates closely with an altered and unfavorable cardiovascular response to exercise. These observations underscore the importance of prolonged follow-up studies in individuals recovering from COVID-19.\u003c/p\u003e \u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cem\u003eEthics approval and consent to participate\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eWritten consent was obtained before the first visit and the protocol was approved by the local ethics committee, Comitato etico per la Sperimentazione Clinica (CESC).\u0026nbsp;The study was performed in accordance with the Declaration of Helsinki and Good Clinical Practice guidelines. Clinical trial registration number:\u0026nbsp;2785CESC.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eConsent for publication\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eAll patients gave informed consent.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eAvailability of data and materials\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eAll data generated or analyzed during this study are included in this published article.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eCompeting interests\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThe authors report no relationships that could be construed as a conflict of interest.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eFunding\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThis study received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eAuthor contribution\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eSubstantial contributions to the conception or design of the study and the acquisition, analysis, or interpretation of data: GD, GS, GF, NR, NB, MB, MF, MV, LDC, CC, BG, EC. Drafting the study or revising it critically for important intellectual content: GD, GS, GF, NR, NB, MB, MF, MV, LDC, CC, BG, EC. Final approval of the version to be published: GD, GS, GF, NR, NB, MB, MF, MV, LDC, CC, BG, EC\u003c/p\u003e\n\u003cp\u003eAgreement to be accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved: GD, GS, GF, NR, NB, MB, MF, MV, LDC, CC, BG, EC.\u003c/p\u003e\n\u003cp\u003eAll authors take responsibility for all aspects of the reliability and freedom from bias of the data presented and their discussed interpretation.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eDavis HE, Mccorkell L, Vogel JM, Topol EJ. Long COVID: major findings, mechanisms and recommendations. Nat Reviews Microbiol |. 2023;21:133\u0026ndash;46.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMancini DM, Brunjes DL, Lala A, Trivieri MG, Contreras JP, Natelson BH. Use of Cardiopulmonary Stress Testing for Patients With Unexplained Dyspnea Post-Coronavirus Disease. 2021. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.jchf.2021.10.002\u003c/span\u003e\u003cspan address=\"10.1016/j.jchf.2021.10.002\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMotiejunaite J, Balagny P, Arnoult F, Mangin L, Bancal C, Vidal-Petiot E, et al. Hyperventilation as one of the mechanisms of persistent dyspnoea in SARS-CoV-2 survivors. Eur Respir J. 2021;58:2101578.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMotiejunaite J, Balagny P, Arnoult F, Mangin L, Bancal C, d\u0026rsquo;Ortho M-P et al. Hyperventilation: A Possible Explanation for Long-Lasting Exercise Intolerance in Mild COVID-19 Survivors? Front Physiol. 2021;11.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSun X-GG, Hansen JE, Garatachea N, Storer TW, Wasserman K. Ventilatory Efficiency during Exercise in Healthy Subjects. https://doi.org/101164/rccm2202033. 2012;166:1443\u0026ndash;8.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLaveneziana P, Naeije R, Stickland MK, Phillips DB, Collins S\u0026Eacute;. Measurement and Interpretation of Exercise Ventilatory Efficiency. Front Physiol | www frontiersin org. 2020;1.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWasserman K, Hansen JE, Sue DY, Stringer WW, Sietsema KE, Sun XG et al. Principles of exercise testing and interpretation: Including pathophysiology and clinical applications: Fifth edition. 2011.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWeatherald J, Farina S, Bruno N, Laveneziana P. Cardiopulmonary exercise testing in pulmonary hypertension. Ann Am Thorac Soc. 2017;14 July:84\u0026ndash;92.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSzekely Y, Lichter Y, Sadon S, Lupu L, Taieb P, Banai A, et al. Cardiorespiratory Abnormalities in Patients Recovering from Coronavirus Disease 2019. J Am Soc Echocardiogr. 2021;34:1273\u0026ndash;1284e9.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDorelli G, Braggio M, Gabbiani D, Busti F, Caminati M, Senna G et al. Importance of Cardiopulmonary Exercise Testing amongst Subjects Recovering from COVID-19. 2021. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.3390/diagnostics11030507\u003c/span\u003e\u003cspan address=\"10.3390/diagnostics11030507\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eIngul CB, Edvardsen A, Follestad T, Trebinjac D, Ankerstjerne OAW, Br\u0026oslash;nstad E, et al. Changes in cardiopulmonary exercise capacity and limitations 3\u0026ndash;12 months after COVID-19. Eur Respir J. 2023;61:2200745.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCrisafulli E, Gabbiani D, Magnani G, Dorelli G, Busti F, Sartori G, et al. Residual Lung Function Impairment Is Associated with Hyperventilation in Patients Recovered from Hospitalised COVID-19: A Cross-Sectional Study. J Clin Med. 2021;10:1\u0026ndash;6.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNoureddine S, Roux-Claud\u0026eacute; P, Laurent L, Ritter O, Dolla P, Karaer S, et al. Evaluation of long-term sequelae by cardiopulmonary exercise testing 12 months after hospitalization for severe COVID-19. BMC Pulm Med. 2023;23:1\u0026ndash;13.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLaukkanen JA, Ara\u0026uacute;jo CGS, Kurl S, Khan H, Jae SY, Guazzi M, et al. Relative peak exercise oxygen pulse is related to sudden cardiac death, cardiovascular and all-cause mortality in middle-aged men. Eur J Prev Cardiol. 2018;25:772\u0026ndash;82.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePeterman JE, Harber MP, Chaudhry S, Arena R, Kaminsky LA. Peak oxygen pulse and mortality risk in healthy women and men: The Ball State Adult Fitness Longitudinal Lifestyle Study (BALL ST). Prog Cardiovasc Dis. 2021;68:19\u0026ndash;24.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePeterman JE, Novelli DS, Fleenor BS, Whaley MH, Kaminsky LA, Harber MP. Oxygen Uptake Efficiency Slope as a Predictor of Mortality Risk. J Cardiopulm Rehabil Prev. 2023;43:282\u0026ndash;9.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMiętkiewska-Szwacka K, Domin R, Kwissa M, Żołyński M, Niziński J, Turska E, et al. Effect of COVID-19 on Blood Pressure Profile and Oxygen Pulse during and after the Cardiopulmonary Exercise Test in Healthy Adults. J Clin Med. 2023;12:4483.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHarrison SL, Buckley BJR, Rivera-Caravaca JM, Zhang J, Lip GYH. Cardiovascular risk factors, cardiovascular disease, and COVID-19: an umbrella review of systematic reviews. Eur Heart J Qual Care Clin Outcomes. 2021. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1093/ehjqcco/qcab029\u003c/span\u003e\u003cspan address=\"10.1093/ehjqcco/qcab029\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCrisafulli E, Dorelli G, Sartori G, Dalle Carbonare L. Exercise ventilatory inefficiency may be a relevant CPET-feature in COVID-19 survivors. Int J Cardiol. 2021;343:200.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMiller MR, Hankinson J, Brusasco V, Burgos F, Casaburi R, Coates A et al. Standardisation spirometry. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1183/09031936.05.00034805\u003c/span\u003e\u003cspan address=\"10.1183/09031936.05.00034805\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eQuanjer PH, Tammeling GJ, Cotes JE, Pedersen OF, Peslin R, Yernault JC. Lung volumes and forced ventilatory flows. Report Working Party Standardization of Lung Function Tests, European Community for Steel and Coal. Official Statement of the European Respiratory Society. The European respiratory journal. Supplement. 1993;16:5\u0026ndash;40.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCotes JE, Chinn DJ, Quanjer PH, Roca J, Yernault J-C. Standardization of the measurement of transfer factor (diffusing capacity). Eur Respir J. 1993;6(Suppl 16):41\u0026ndash;52.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWeisman IM, Marciniuk D, Martinez FJ, Sciurba F, Sue D, Myers J, et al. ATS/ACCP Statement on Cardiopulmonary Exercise Testing. Am J Respir Crit Care Med. 2003;167:211\u0026ndash;77.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBaba R. The Oxygen Uptake Efficiency Slope and Its Value in the Assessment of Cardiorespiratory Functional Reserve. Congestive Heart Fail. 2000;6:256\u0026ndash;8.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCole CR, Blackstone EH, Pashkow FJ, Snader CE, Lauer MS. Heart-Rate Recovery Immediately after Exercise as a Predictor of Mortality. N Engl J Med. 1999;341:1351\u0026ndash;7.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBorg G. Psychophysical scaling with applications in physical work and the perception of exertion. Work Environ Health. 1990;16:441\u0026ndash;554.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eStandardized Questionaries on Respiratory Symptoms. Br Med J. 1960;2:1665.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWeatherald J, Sattler C, Garcia G, Laveneziana P. Ventilatory response to exercise in cardiopulmonary disease: the role of chemosensitivity and dead space. Eur Respir J. 2018;51:1700860.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTaverne J, Salvator H, Leboulch C, Barizien N, Ballester M, Imhaus E, et al. High incidence of hyperventilation syndrome after COVID-19. J Thorac Dis. 2021;13:3918\u0026ndash;22.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHuang Y, Tan C, Wu J, Chen M, Wang Z, Luo L, et al. Impact of coronavirus disease 2019 on pulmonary function in early convalescence phase. Respir Res. 2020;21:163.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLiu M, Lv F, Huang Y, Xiao K. Follow-Up Study of the Chest CT Characteristics of COVID-19 Survivors Seven Months After Recovery. Front Med (Lausanne). 2021;8:636298.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eParshall MB, Schwartzstein RM, Adams L, Banzett RB, Manning HL, Bourbeau J, et al. An Official American Thoracic Society Statement: Update on the Mechanisms, Assessment, and Management of Dyspnea. Am J Respir Crit Care Med. 2012;185:435\u0026ndash;52.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eXiang M, Wu X, Jing H, Novakovic VA, Shi J. The intersection of obesity and (long) COVID-19: Hypoxia, thrombotic inflammation, and vascular endothelial injury. Front Cardiovasc Med. 2023;10.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDixon AE, Peters U. The effect of obesity on lung function. Expert Rev Respir Med. 2018;12:755\u0026ndash;67.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eArena R, Brubaker P, Moore B, Kitzman D. The oxygen uptake efficiency slope is reduced in older patients with heart failure and a normal ejection fraction. Int J Cardiol. 2010;144:101\u0026ndash;2.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRamponi S, Tzani P, Aiello M, Marangio E, Clini E, Chetta A. Pulmonary Rehabilitation Improves Cardiovascular Response to Exercise in COPD. Respiration. 2013;86:17\u0026ndash;24.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLongobardi I, do Prado DML, Goessler KF, Meletti MM, de Oliveira J\u0026uacute;nior GN, de Andrade DCO, et al. Oxygen uptake kinetics and chronotropic responses to exercise are impaired in survivors of severe COVID-19. Am J Physiol Heart Circ Physiol. 2022;323:H569\u0026ndash;76.\u003c/span\u003e\u003c/li\u003e\u003c/ol\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":"COVID-19, Cardiopulmonary exercise test, Exercise ventilatory inefficiency, Hyperventilation, End-tidal pressure of CO2, Oxygen pulse.","lastPublishedDoi":"10.21203/rs.3.rs-3928238/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-3928238/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eBackground\u003c/p\u003e\n\u003cp\u003eSARS-CoV-2 infection has raised concerns about long-term health repercussions. Exercise ventilatory inefficiency (EV\u003cem\u003ein\u003c/em\u003e) has emerged as a notable long-termi sequela, potentially impacting respiratory and cardiovascular health. This study aims to assess the long-term presence of EVin after 34 months and its association with cardiorespiratory health in post-COVID patients.\u003c/p\u003e\n\u003cp\u003eMethods\u003c/p\u003e\n\u003cp\u003eIn a longitudinal study on 32 selected post-COVID subjects, we performed two cardiopulmonary exercise tests (CPETs) at 6 months (T0) and 34 months (T1) after hospital discharge. The study sought to explore the long-term persistence of EV\u003cem\u003ein\u003c/em\u003e and its correlation with respiratory and cardiovascular responses during exercise. Measurements included also V̇O\u003csub\u003e2peak\u003c/sub\u003e end-tidal pressure of CO\u003csub\u003e2\u003c/sub\u003e (PET\u003csub\u003eCO2\u003c/sub\u003e) levels, oxygen uptake efficiency slope (OUES) and other cardiorespiratory parameters, with statistical significance set at p\u0026lt;0.05. The presence of EV\u003cem\u003ein\u003c/em\u003e at both T0 and T1 defines a persisting EV\u003cem\u003ein\u003c/em\u003e (pEV\u003cem\u003ein\u003c/em\u003e).\u003c/p\u003e\n\u003cp\u003eResults\u003c/p\u003e\n\u003cp\u003eOut of the cohort, five subjects (16%) have pEV\u003cem\u003ein \u003c/em\u003eat 34 months. Subjects with pEV\u003cem\u003ein\u003c/em\u003e, compared to those with ventilatory efficiency (Ev\u003cem\u003eef\u003c/em\u003e) have lower values of PET\u003csub\u003eCO2\u003c/sub\u003e throughout exercise, showing hyperventilation. Ev\u003cem\u003eef\u003c/em\u003e subjects demonstrated selective improvements in DL\u003csub\u003eCO\u003c/sub\u003e and oxygen pulse, suggesting recovery in cardiorespiratory function over time. In contrast, those with pEv\u003cem\u003ein\u003c/em\u003e did not exhibit these improvements. Notably, significant correlations were found between hyperventilation (measured by PET\u003csub\u003eCO2\u003c/sub\u003e), oxygen pulse and OUES, indicating the potential prognostic value of OUES and Ev\u003cem\u003ein\u003c/em\u003e in post-COVID follow-ups.\u003c/p\u003e\n\u003cp\u003eConclusions\u003c/p\u003e\n\u003cp\u003eThe study highlights the clinical importance of long-term follow-up for post-COVID patients, as a significant group exhibit persistent EV\u003cem\u003ein\u003c/em\u003e, which correlates with altered and potentially unfavorable cardiovascular responses to exercise. These findings advocate for the continued investigation into the long-term health impacts of COVID-19, especially regarding persistent ventilatory inefficiencies and their implications on patient health outcomes.\u003c/p\u003e","manuscriptTitle":"Persisting exercise ventilatory inefficiency in subjects recovering from COVID-19. Longitudinal Data Analysis 34 Months Post-Discharge Running title: Persisting Exercise Ventilatory Inefficiency in post-COVID Subjects","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-02-28 20:43:33","doi":"10.21203/rs.3.rs-3928238/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2024-04-02T04:52:09+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-03-11T20:03:33+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"32b3eb2a-322c-4f7a-aee3-2d1dc8e0100d","date":"2024-03-10T10:48:43+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2024-03-08T07:15:58+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-03-07T22:02:01+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2024-02-26T14:54:37+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2024-02-26T14:52:22+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Pulmonary Medicine","date":"2024-02-04T16:42:20+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":"17da91f6-01c2-47a4-bc4c-fadbd344fe5c","owner":[],"postedDate":"February 28th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2024-05-21T06:19:25+00:00","versionOfRecord":[],"versionCreatedAt":"2024-02-28 20:43:33","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-3928238","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-3928238","identity":"rs-3928238","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}