Next Article in Journal
Statin Use in Relation to COVID-19 and Other Respiratory Infections: Muscle and Other Considerations
Next Article in Special Issue
SARS-CoV-2 Related Myocarditis: What We Know So Far
Previous Article in Journal
Semen Cryopreservation for Men Banking for Oligozoospermia, Cancers, and Other Conditions: 24 Years’ Experience of an Italian Bank
Previous Article in Special Issue
Cardiopulmonary Exercise Testing in Children and Young Adolescents after a Multisystem Inflammatory Syndrome: Physical Deconditioning or Residual Pathology?
 
 
Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
Journals
JCM
Volume 12
Issue 14
10.3390/jcm12144658
jcm-logo
Submit to this Journal Review for this Journal Propose a Special Issue
► Article Menu

Article Menu

share Share announcement Help format_quote Cite question_answer Discuss in SciProfiles thumb_up
...
Endorse textsms
...
Comment
first_page
settings
Order Article Reprints
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Dyspnea in Post-Acute COVID-19: A Multi-Parametric Cardiopulmonary Evaluation

by
Antonella Cecchetto
1,*,
Gabriella Guarnieri
2,
Gianpaolo Torreggiani
1,
Andrea Vianello
2,
Giulia Baroni
1,
Chiara Palermo
1,
Leonardo Bertagna De Marchi
2,
Giulia Lorenzoni
1,
Patrizia Bartolotta
1,
Emanuele Bertaglia
1,
Filippo Donato
1,
Patrizia Aruta
1,
Sabino Iliceto
1 and
Donato Mele
1
1
Department of Cardiac Thoracic Vascular Sciences and Public Health, University of Padua, 35128 Padua, Italy
2
Respiratory Pathophysiology Division, University of Padua, 35128 Padua, Italy
*
Author to whom correspondence should be addressed.
J. Clin. Med. 2023, 12(14), 4658; https://doi.org/10.3390/jcm12144658
Submission received: 8 June 2023 / Revised: 1 July 2023 / Accepted: 7 July 2023 / Published: 13 July 2023
(This article belongs to the Special Issue COVID-19-Associated Myocardial Injury and Other Cardiovascular Diseases)
Browse Figure
Versions Notes

Abstract

:
Post-acute COVID-19 is characterized by the persistence of dyspnea, but the pathophysiology is unclear. We evaluated the prevalence of dyspnea during follow-up and factors at admission and follow-up associated with dyspnea persistence. After five months from discharge, 225 consecutive patients hospitalized for moderate to severe COVID-19 pneumonia were assessed clinically and by laboratory tests, echocardiography, six-minute walking test (6MWT), and pulmonary function tests. Fifty-one patients reported persistent dyspnea. C-reactive protein (p = 0.025, OR 1.01 (95% CI 1.00–1.02)) at admission, longer duration of hospitalization (p = 0.005, OR 1.05 (95% CI 1.01–1.10)) and higher body mass index (p = 0.001, OR 1.15 (95% CI 1.06–1.28)) were independent predictors of dyspnea. Absolute drop in SpO2 at 6MWT (p = 0.001, OR 1.37 (95% CI 1.13–1.69)), right ventricular (RV) global longitudinal strain (p = 0.016, OR 1.12 (95% CI 1.02–1.25)) and RV global longitudinal strain/systolic pulmonary artery pressure ratio (p = 0.034, OR 0.14 (95% CI 0.02–0.86)) were independently associated with post-acute COVID-19 dyspnea. In conclusion, dyspnea is present in many patients during follow-up after hospitalization for COVID-19 pneumonia. While higher body mass index, C-reactive protein at admission, and duration of hospitalization are predictors of persistent dyspnea, desaturation at 6MWT, and echocardiographic RV dysfunction are associated with this symptom during the follow-up period.

Graphical Abstract

1. Introduction

The clinical course of COVID-19 in its acute phase is now delineated in sufficient detail; instead, less is known about its late phase [1]. The World Health Organization defines the post-acute sequelae of SARS-CoV-2 infection (PASC) as a condition that arises 12 weeks after infection, persists for at least eight weeks, and cannot be explained by alternative diagnoses [2].
Dyspnea is a common symptom of PASC with high incidence and a significant impact on quality of life [3,4]. The underlying mechanisms of dyspnea in this contest are still poorly understood and are probably multifactorial. Potential mechanisms include cardiac and pulmonary dysfunction, whereas pulmonary fibrosis and vascular changes after recovery have been described on chest-computed tomography (CT) [5,6]. Moreover, earlier reports showed an increased prevalence of high cardiac troponin levels, a biomarker of myocardial injury, which was associated with impaired left ventricular (LV) and right ventricular (RV) function, leading to higher morbidity and mortality rates, including possible long-term consequences [7].
Previous studies show conflicting results about pulmonary involvement. Dyspnea can persist despite improvements in cardiopulmonary function; in fact, it was demonstrated that at a three-month follow-up, the pulmonary function test parameters and chest CT abnormalities improved, independent of improvements in six-minute walk distance or dyspnea [8,9]. Another study reported the persistence of dyspnea, impaired six-minute walk distance, and reduced health-related quality of life, but without accompanying pulmonary function abnormalities [10]. Some studies showed no difference between healthy controls and patients with post-COVID dyspnea [11], and others found exercise intolerance with evidence of circulatory and breathing pattern abnormalities [12,13]. At least, it is not excluded that symptoms may be attributed to pre-existing conditions [14].
In this study, we decided to evaluate patients affected by moderate to severe COVID-19 pneumonia to establish the prevalence of dyspnea at follow-up and to identify clinical, laboratory, and instrumental factors at admission and follow-up associated with the persistence of dyspnea, to better clarify the underlying mechanisms. We hypothesized that patients with more severe pneumonia were more symptomatic at follow-up due to pulmonary compromise. Instead, no cardiac sequelae were associated with dyspnea. These findings would help clinicians to better understand the heterogeneous causes of persistent dyspnea after COVID-19 pneumonia in order to focus on the treatment.

2. Materials and Methods

2.1. Study Protocol

This is a single-center observational cohort study. The study was approved by the Ethics Committee on Human Research of Padua University (protocol code n. 20009). Because of the retrospective observational nature of the study, written consent was not required.
All patients had an established diagnosis of COVID-19 (positive polymerase chain reaction test of the nasopharyngeal swab or bronchoalveolar lavage fluid) and survived the acute event. Consecutive individuals recovering from COVID-19 pneumonia were evaluated in a dedicated outpatient clinic.
Inclusion criteria were: (1) COVID-19 pneumonia diagnosis as described above; (2) hospital discharge from the Respiratory Pathophysiology Unit of the Padua University Hospital between 18 February 2020 and 10 November 2021; (3) moderate to critical acute disease according to the National Institutes of Health definitions. Mild disease: mild clinical symptoms, no signs of pneumonia on imaging. Moderate disease: fever and respiratory symptoms, etc., with pneumonia signs on imaging. Severe disease: patients with any of the following conditions: respiratory distress with respiratory rate > 30 breaths/min; peripheral capillary oxygen saturation (SpO2) < 93% at rest; a ratio of arterial oxygen partial pressure (PAO2) to fractional inspired oxygen (FiO2) or PAO2/FiO2 < 300 mmHg. Critical disease: patients with respiratory failure requiring mechanical ventilation; shock; or other organ failure requiring admission to the Intensive Care Unit (ICU).
Exclusion criteria were: age < 18 years, poor-quality echocardiographic images, presence of dyspnea before admission, and anemia on blood test.
All patients underwent comprehensive medical assessment with a detailed medical history, physical examination, and blood tests (including full blood count, renal and liver function tests, troponin, B-type natriuretic peptide (BNP), C-reactive protein (CPR), and D-dimer). In particular, clinical examination assessed the persistence of self-reported dyspnea using the modified Medical Research Council (mMRC) score [15]. The scale ranges from 0 (no dyspnea) to 4 (severe dyspnea). Dyspnea was defined as an mMRC ≥ 1. We also performed a comprehensive cardiopulmonary evaluation that included complete rest transthoracic echocardiography, functional lung test, and six-minute walking test (6-MWT). We used a standardized data-collection tool to gather information from the patient’s electronic hospital records on demographics, body mass index (BMI), comorbidities, medication history, smoking history, severity of illness, maximum respiratory support requirements, length of hospitalization, and biomarkers relative to the acute phase of the disease (troponin, BNP, CPR, and D-dimer).

2.2. Transthoracic Echocardiography

The echocardiogram was performed on the same day as the clinical and pulmonary evaluation. Echocardiographic image acquisition was performed using a Vivid E9 echo scanner (GE Vingmed Ultrasound, Horten, Norway) by one experienced researcher. Data sets were digitally stored and exported on a dedicated workstation equipped with the EchoPac BT 13 software (GE Vingmed Ultrasound, Horten, Norway). A comprehensive assessment of biventricular and atrial size, LV diastolic function, LV and RV systolic function was performed using two-dimensional (2D) and three-dimensional (3D) conventional echocardiography and 2D speckle tracking echocardiography (2D STE) for longitudinal strain (LS) measurement, in accordance with the guidelines of the European Association of Cardiovascular Imaging (EACVI) and the American Society of Echocardiography (ASE) [16].
The following measures were obtained: the LV end-systolic volume, end-diastolic volume, and ejection fraction (EF); the ratio of early transmitral peak flow velocity (E wave) to late transmitral peak flow velocity (A wave) and the ratio of early transmitral peak E wave to early diastolic medial septal and lateral peak tissue Doppler velocity (e’); the left atrial volume; the right atrial volume and area; the RV end-diastolic area, end-systolic area, fractional area change, end-diastolic volume, end-systolic volume, and EF; the tricuspid annular plane systolic excursion; the systolic pulmonary artery pressure (sPAP); the pulmonary artery acceleration time; and the pulmonary vascular resistance. In addition, the probability of pulmonary hypertension was estimated in accordance with international guidelines [17]. Regarding LS analysis, LV global longitudinal strain (LVGLS), RV-free wall strain (RVFWS), RV global longitudinal strain (RVGLS), and its afterload correction (RVGLS/sPAP) were measured.

2.3. Pulmonary Functional Test

Pulmonary functional tests and lung diffusing capacity for carbon monoxide (DLCO) measurement were performed using calibrated equipment (MasterLab Pro; Erich Jaeger GmbH; Höchberg, Germany), according to the European Respiratory Society (ERS) and American Thoracic Society (ATS) recommendations [18,19]. The predicted normal values of Quanjer [20] and equations of Cotes for DLCO [21] were used. Among the various measures provided by the spirometry, vital capacity (VC), total lung capacity (TLC), DLCO, carbon monoxide transfer coefficient (KCO), and Tiffeneau index were included in the analysis. To assess respiratory muscles function, maximal inspiratory pressure (MIP) and expiratory mouth pressure (MEP) were measured [22]. For each patient, measures were also expressed as a percentage of the theoretical value.

2.4. Six-Minute Walking Test

The 6MWT was performed according to recommended guidelines [23], with baseline and after exercise, SpO2 measurement obtained by pulse oximetry on index fingers. Walking capacity was considered abnormal when below the cut-off value for a similar cohort of healthy patients (484 mt) [24]. Desaturation was defined as a drop of ≥4% or a reduction of <90% in SpO2.

2.5. Statistical Analysis

Data were reported as the median and interquartile range (IQR, I–III quartile) for continuous variables and as absolute values and percentages for categorical variables. The relationships among different measures were assessed using Spearman’s correlation. Univariable and multivariable logistic regression analyses were used to estimate the effect of different variables of the acute phase and follow-up on the persistence of dyspnea evaluated at follow-up. Multivariable model selection was done according to the Bayesian Information Criterion (BIC), starting from a set of candidate predictors. Such predictors were identified according to clinical judgment and literature review to be factors potentially associated with the outcome of interest. The BIC is a well-established methodology for model selection within clinical data [25]. The results were reported as odds ratios (ORs) with 95% confidence intervals (CIs). Statistical significance was taken as p < 0.05. Statistical analysis was performed using the R software version 4.1.0 222.

3. Results

3.1. Baseline Characteristics

From 18 February 2020 to 10 November 2021, during the first wave of the pandemic, 229 consecutive patients were initially enrolled. Three patients were excluded because of the poor quality of the echocardiographic images, and one patient died before the follow-up visit. Therefore, 225 patients were available for follow-up. All patients were Caucasians. The median time of assessment was 154 days (IQR 113–225) from hospitalization. Patients were mainly overweight adults without a history of cardiovascular disease but with at least one cardiovascular risk factor. During hospitalization, 188 (84%) received O2-therapy, and 56 (26%) patients underwent mechanical ventilation. All patients manifested signs of infection; 36 (16%) and 144 (64%) presented, respectively, troponin and BNP increased above the reference values. Patients’ characteristics are shown in Table 1, according to the presence of dyspnea at follow-up, and recently detailed in a previous publication [26].

3.2. Clinical Evaluation at Follow-Up

One hundred and fifteen patients (51%) reported persistent dyspnea five months after hospitalization. Of them, 43 (19%) reported an mMRC score = 1; 38 (17%) an mMRC score = 2; 22 (10%) an mMRC score = 3; and 12 (5%) an mMRC score = 4.

3.3. Cardiopulmonary Evaluation at Follow-Up

At the follow-up visit, 10% of patients presented LV dilatation, 9% LVEF reduction, 12% LV diastolic dysfunction, 28% RV dilatation, and 8% RVEF reduction. Thirty-six percent of patients had LVGLS reduction (>−18%), and 32% had RVGLS reduction (>−20%). Only 7% of the cohort demonstrated an intermediate and high probability of pulmonary hypertension. The values of transthoracic echocardiography measures at the follow-up visit are reported in Table 2.
Regarding the pulmonary functional test, patients were characterized by normal pulmonary volumes without signs of a lung-restrictive pattern. A trend toward reduction in lung diffusion capacity (55% of patients) and in respiratory muscle strength both during inhalation (28% of patients) and exhalation (64%) was observed. At the 6MWT, a reduction in the total walking distance occurred in 41% of patients and desaturation in 32% of patients (4% with SpO2 < 90% and 28% with a drop ≥4%). Among patients with a reduction of walking distance, 30% presented an absolute drop in SpO2 and 1% a final SpO2 < 90%. Only 4% of patients with final distance walked within normal limits presented an absolute drop in SpO2. The pulmonary functional test and 6MWT measures obtained at the follow-up evaluation are detailed in Table 3.

3.4. Acute Predictors of Persistent Dyspnea at Follow-Up

Clinical and laboratory characteristics of patients at hospitalization were tested for the association with persisting dyspnea during follow-up (Table 4).
In the multivariable analysis, higher BMI and longer hospitalization period significantly predicted the persistence of dyspnea during follow-up. Persistence of dyspnea during follow-up was also significantly and independently predicted by CRP.

3.5. Association between Persistent Dyspnea and Cardiopulmonary Measures at Follow-Up

In the univariable logistic regression analysis, persistent dyspnea was significantly associated with an alteration of respiratory parameters and especially with a decrease in lung diffusion capacity. Moreover, the presence of dyspnea was significantly associated with a reduction of respiratory muscle strength in the expiratory compartment. Distance and final saturation during the 6MWT were also significantly associated with the symptom. In the multivariable analysis, only the absolute drop in SpO2 at 6MWT, RVGLS, and RVGLS/sPAP was significantly associated with post-acute COVID-19 dyspnea. Results of the univariable and multivariable analysis for post-acute COVID-19 dyspnea are reported in Table 5.

4. Discussion

In this study, we evaluated a middle-aged cohort of patients affected by moderate to severe COVID-19 pneumonia, mostly with cardiovascular risk factors but without a history of cardiovascular disease. The main findings of this study are: (I) approximately half of the patients reported dyspnea during the first five months after hospitalization; (II) the severity of COVID-19 during the acute phase and being overweight predicted the persistence of dyspnea in the context of PASC; (III) the only echocardiographic measures associated with dyspnea during the follow-up period were RVGLS and RVGLS/sPAP.
Dyspnea is a peculiar symptom of the syndrome called PASC or “Long-COVID”. In our sample, 51% of patients experienced dyspnea during the first five months after hospitalization for COVID-19. In our study, dyspnea prevalence was slightly higher than previously observed (6,27). Carfì et al. [6] reported dyspnea in 43.4% of patients 60 days after the onset of the first COVID-19 symptom. Zheng et al. [27] described post-COVID breathlessness in 26% and 41% of patients, depending on the method used to evaluate it. These discrepancies could be attributable to the fact that our cohort included only hospitalized patients, characterized by moderate to critically ill related to COVID-19 infection, and to the different follow-up duration.
In our patients, a more severe COVID-19 during the acute phase (higher CRP and longer hospitalization) was predictive of dyspnea during the follow-up period, as observed in previous studies. Arnold et al. [28], for example, reported ongoing symptoms in 59%, 75%, and 89% of patients, respectively, with mild, moderate, and severe COVID-19, defined on the basis of the type of ventilation used. Conversely, we did not find a significant association between cardiovascular comorbidity and persistence of symptoms, differently from other studies [29,30,31], except for the association with higher BMI values [32]. These differences could be attributed to the heterogeneity of the patients considered in literature studies, characterized by different age, disease severity, type of symptoms, and individual comorbidities.
Regarding PASC, there is no clear consensus on whether dyspnea can be considered secondary to cardiopulmonary dysfunction or a self-reported symptom. In fact, in the literature studies, a minority of symptomatic patients had abnormal functional tests. Arnold et al. [28] described persistent symptoms (breathlessness and fatigue) in 74% of the patients 8–12 weeks post-admission; however, clinically significant abnormalities in chest radiographs, exercise tests, blood tests, and spirometry were less frequent (35%), especially in patients not requiring supplementary O2 during their acute infection (7%).
Mood abnormalities may also play a causative role in post-COVID dyspnea, in addition to cardiorespiratory abnormalities [33]. We tried to understand if dyspnea was objectively identifiable using functional tests and if it was associated with pulmonary or cardiac impairment. In our patients, desaturation at 6MWT was associated with dyspnea. In the literature investigations, the difference in walking distance was associated with significant subjective dyspnea [10]. These results define 6MWT as a reliable test to objectify dyspnea.
We confirmed a relationship between the persistence of dyspnea and an impairment of pulmonary function. In fact, the reduction of lung diffusion capacity and respiratory muscle strength was related to dyspnea. These results partially disagree with those of Lam et al. [10], who reported a PASC phenotype characterized by persistent dyspnea, and impaired 6MWT distance but without pulmonary function abnormalities. At the same time, the correlation between dyspnea and respiratory parameters alteration is consistent with part of the current literature studies [8,34]. Lerum et al. [8] confirmed a significant reduction of DLCO in 24% of patients three months after discharge, without differences between ICU and non-ICU participants. Robey et al. [34] confirmed an abnormal DLCO 4 months after COVID-19 infection, highest in the ICU cohort (64% ICU vs. 38% non-ICU patients).
Pathological changes in the diaphragm of COVID-19 patients post-mortem have been reported [35], and survivors from severe COVID-19 were observed to have impaired diaphragm contractility and diaphragmatic atrophy [36]. Furthermore, several studies have found decreased inspiratory muscle strength [37,38,39]. The correlation between dyspnea and expiratory muscle weakness that we described may be attributed to the occurrence of interstitial lung disease after COVID-19 or to physical deconditioning [40]. In fact, deconditioning was identified as a factor causing dyspnea in studies that evaluated persistent symptoms after COVID-19 using cardiopulmonary exercise testing [41]. COVID-19 infection is thought to cause muscle breakdown due to systemic inflammation, the so-called cytokine storm. Despite the limited literature studies that have examined MIP and MEP in patients with COVID-19, expiratory muscle weakness in dyspneic patients suggests the importance of target rehabilitation.
According to our findings, the rest echocardiographic measures were not associated with dyspnea, except for RVGLS and RVGLS/sPAP. The hearts of our patients presented normal LV and RV volumes, systolic and diastolic function, and a low probability of pulmonary hypertension in both patients with and without dyspnea. Beaudry et al. did not identify structural or functional cardiac changes in dyspneic patients; however, they did not evaluate subclinical myocardial injury and did not show respiratory alterations. This may be due to the fact that less severe non-hospitalized, young, non-obese, and comorbidity-free patients were enrolled [11]. The correlation between RVGLS impairment and the presence of dyspnea could be the consequence of more severe pulmonary disease as the result of increased stress inflicted on the RV in acute COVID-19. Ozer et al. previously demonstrated the relationship between the severity of pneumonia and subclinical impairment of RV function in hospitalized patients [42]. Tryfou et al. found impairment of RVGLS in patients hospitalized for COVID-19 pneumonia, while non-hospitalized patients had a normal RVGLS value [43]. RVGLS can be a predictive measure of severe disease, as suggested by a previous study, which confirmed that RVGLS was related to survival in patients with COVID-19 pneumonia, with a cut-off value of 20% [44].
Recent studies show that RV to pulmonary circulation coupling can be estimated non-invasively by echocardiography, using parameters of RV systolic function indexed to the sPAP, like TAPSE/sPAP and RVGLS/sPAP. The concept of RV to pulmonary circulation coupling refers to the relationship between RV contractility and RV afterload [45]. The RV, in contrast to the LV, is more susceptible to the increased afterload related to pulmonary diseases [46,47]. In this context, Polito et al. demonstrated that poor RV-arterial coupling, in terms of TAPSE/sPAP, may help to identify COVID-19 patients at higher risk of mortality during hospitalization [48]. Our study analyzed for the first time the role of indexing RVGLS to sPAP in the setting of patients recovered from COVID-19 pneumonia, demonstrating the association between persistent dyspnea with this measure. This suggests that interventions focusing on dyspnea management may be appropriate for the phenotype of post-acute COVID-19 patients. Only patients with a severe form of COVID-19-related pneumonia and persistence of respiratory function impairment could benefit from an instrumental evaluation of RV function with advanced transthoracic echocardiography techniques. The presence of RVGLS and RVGLS/sPAP abnormalities indicates the need for further cardiac and pulmonary evaluation and/or follow-up.
Some limitations of this study should be highlighted. Our study did not include a multi-parametric evaluation in the acute phase of hospitalization due to the restrictions posed by the COVID-19 infection. Instrumental examinations were not available prior to hospitalization. We included only hospitalized patients who successfully recovered from COVID-19, disregarding patients with higher severity who died during hospitalization. Cardiopulmonary stress testing was not performed to better understand the mechanisms involved in dyspnea. It might be useful to validate the results of the study by comparison with a population of COVID-19 patients with mild pulmonary impairment. However, at present, hospitalized COVID-19 patients have decreased considerably. Lastly, our longitudinal sample evaluation could be further improved by extending the follow-up.

5. Conclusions

We described a picture that falls under the PASC condition, documenting the persistence of dyspnea during the follow-up period in a significant number of hospitalized patients with COVID-19. Dyspnea was measurable by 6MWT and was associated with a respiratory function impairment, including a reduction of expiratory muscle strength. The only echocardiographic measures associated with dyspnea were RVGLS and RVGLS/sPAP.

Author Contributions

Conceptualization, A.C., G.G. and A.V.; methodology, A.C., G.G. and D.M.; formal analysis, G.L. and P.B.; data curation, G.T., G.B., F.D., C.P., P.A. and L.B.D.M.; writing—original draft preparation, A.C.; writing—review and editing, E.B.; supervision, D.M. and S.I. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Institutional Review Board Statement

The study was conducted in accordance with the Declaration of Helsinki and approved by the Ethics Committee on Human Research of Padua University (protocol code n. 20009, 20 March 2023).

Informed Consent Statement

Because of the retrospective observational nature of the study, written consent was not required.

Data Availability Statement

The data presented in this study are available upon request from the corresponding author. The data are not publicly available due to privacy reasons.

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. Nalbandian, A.; Sehgal, K.; Gupta, A.; Madhavan, M.V.; McGroder, C.; Stevens, J.S.; Cook, J.R.; Nordvig, A.S.; Shalev, D.; Sehrawat, T.S.; et al. Post-acute COVID-19 syndrome. Nat. Med. 2021, 27, 601–615. [Google Scholar] [CrossRef] [PubMed]
  2. Al-Aly, Z.; Xie, Y.; Bowe, B. High-dimensional characterization of post-acute sequelae of COVID-19. Nature 2021, 594, 259–264. [Google Scholar] [CrossRef]
  3. Huang, C.; Huang, L.; Wang, Y.; Li, X.; Ren, L.; Gu, X.; Kang, L.; Guo, L.; Liu, M.; Zhou, X.; et al. 6-month consequences of COVID-19 in patients discharged from hospital: A cohort study. Lancet 2021, 397, 220–232. [Google Scholar] [CrossRef] [PubMed]
  4. Huang, L.; Yao, Q.; Gu, X.; Wang, Q.; Ren, L.; Wang, Y.; Hu, P.; Guo, L.; Liu, M.; Xu, J.; et al. 1-year outcomes in hospital survivors with COVID-19: A longitudinal cohort study. Lancet 2021, 398, 747–758. [Google Scholar] [CrossRef]
  5. Goërtz, Y.M.J.; Van Herck, M.; Delbressine, J.; Vaes, A.W.; Meys, R.; Machado, F.V.C.; Houben-Wilke, S.; Burtin, C.; Posthuma, R.; Franssen, F.M.E.; et al. Persistent symptoms 3 months after a SARS-CoV2 infection: The post-COVID-19 syndrome? ERJ Open Res. 2020, 6, 00542–2020. [Google Scholar] [CrossRef]
  6. Carfì, A.; Bernabei, R.; Landi, F.; Gemelli against COVID-19 Post-Acute Care Study Group. Persistent symptoms in patients after acute COVID-19. JAMA 2020, 324, 603–605. [Google Scholar] [CrossRef]
  7. Lala, A.; Johnson, K.W.; Januzzi, J.L.; Russak, A.J.; Paranjpe, I.; Richter, F.; Zhao, S.; Somani, S.; Van Vleck, T.; Vaid, A.; et al. Prevalence and Impact of Myocardial Injury in Patients Hospitalized with COVID-19 Infection. J. Am. Coll. Cardiol. 2020, 76, 533–546. [Google Scholar] [CrossRef] [PubMed]
  8. Lerum, T.V.; Aaløkken, T.M.; Brønstad, E.; Aarli, B.; Ikdahl, E.; Lund, K.M.A.; Durheim, M.T.; Rodriguez, J.R.; Meltzer, C.; Tonby, K.; et al. Dyspnoea, lung function and CT findings 3 months after hospital admission for COVID-19. Eur. Respir. J. 2021, 57, 2003448. [Google Scholar] [CrossRef]
  9. Shah, A.S.; Ryu, M.H.; Hague, C.J.; Murphy, D.T.; Johnston, J.C.; Ryerson, C.J.; Carlsten, C.; Wong, A.W. Changes in pulmonary function and patient-reported outcomes during COVID-19 recovery: A longitudinal, prospective cohort study. ERJ Open Res. 2021, 7, 00243–2021. [Google Scholar] [CrossRef]
  10. Lam, G.Y.; Befus, A.D.; Damant, R.W.; Ferrara, G.; Fuhr, D.P.; Stickland, M.K.; Varughese, R.A.; Wong, E.Y.; Smith, M.P. Exertional intolerance and dyspnea with preserved lung function: An emerging long COVID phenotype? Respir. Res. 2021, 22, 222. [Google Scholar] [CrossRef]
  11. Beaudry, R.I.; Brotto, A.R.; Varughese, R.A.; de Waal, S.; Fuhr, D.P.; Damant, R.W.; Ferrara, G.; Lam, G.Y.; Smith, M.P.; Stickland, M.K. Persistent dyspnea after COVID-19 is not related to cardiopulmonary impairment; A cross-sectional study of persistently dyspneic COVID-19, non-dyspneic COVID-19 and controls. Front Physiol. 2022, 13, 917886. [Google Scholar] [CrossRef] [PubMed]
  12. Singh, I.; Joseph, P.; Heerdt, P.M.; Cullinan, M.; Lutchmansingh, D.D.; Gulati, M.; Possick, J.D.; Systrom, D.M.; Waxman, A.B. Persistent Exertional Intolerance after COVID-19: Insights from Invasive Cardiopulmonary Exercise Testing. Chest 2022, 161, 54–63. [Google Scholar] [CrossRef] [PubMed]
  13. Mancini, D.M.; Brunjes, D.L.; Lala, A.; Trivieri, M.G.; Contreras, J.P.; Natelson, B.H. Use of Cardiopulmonary Stress Testing for Patients with Unexplained Dyspnea Post-Coronavirus Disease. JACC Heart Fail. 2021, 9, 927–937. [Google Scholar] [CrossRef]
  14. Matta, J.; Wiernik, E.; Robineau, O.; Carrat, F.; Touvier, M.; Severi, G.; de Lamballerie, X.; Blanché, H.; Deleuze, J.F.; Gouraud, C.; et al. Association of self-reported COVID-19 infection and SARS-CoV-2 serology test results with persistent physical symptoms among french adults during the COVID-19 pandemic. JAMA Intern. Med. 2022, 182, 19–25. [Google Scholar] [CrossRef]
  15. Bestall, J.C.; Paul, E.A.; Garrod, R.; Garnham, R.; Jones, P.W.; Wedzicha, J.A. Usefulness of the Medical Research Council (MRC) dyspnea scale as a measure of disability in patients with chronic obstructive pulmonary disease. Thorax 1999, 54, 5816. [Google Scholar] [CrossRef] [PubMed]
  16. Lang, R.M.; Badano, L.P.; Mor-Avi, V.; Afilalo, J.; Armstrong, A.; Ernande, L.; Flachskampf, F.A.; Foster, E.; Goldstein, S.A.; Kuznetsova, T.; et al. Recommendations for Cardiac Chamber Quantification by Echocardiography in Adults: An Update from the American Society of Echocardiography and the European Association of Cardiovascular Imaging. J. Am. Soc. Echocardiogr. 2015, 28, 1–39. [Google Scholar] [CrossRef]
  17. Humbert, M.; Kovacs, G.; Hoeper, M.M.; Badagliacca, R.; Berger, R.M.F.; Brida, M.; Carlsen, J.; Coats, A.J.S.; Escribano-Subias, P.; Ferrari, P.; et al. 2022 ESC/ERS Guidelines for the diagnosis and treatment of pulmonary hypertension Developed by the task force for the diagnosis and treatment of pulmonary hypertension of the European Society of Cardiology (ESC) and the European Respiratory Society (ERS). Eur. Heart J. 2022, 43, 3618–3731. [Google Scholar] [CrossRef]
  18. Miller, M.R.; Hankinson, J.; Brusasco, V.; Burgos, F.; Casaburi, R.; Coates, A.; Crapo, R.; Enright, P.; van der Grinten, C.P.M.; Gustafsson, P.; et al. Standardisation of spirometry. Eur. Respir. J. 2005, 26, 319–338. [Google Scholar] [CrossRef]
  19. Macintyre, N.; Crapo, R.O.; Viegi, G.; Johnson, D.C.; van der Grinten, C.P.M.; Brusasco, V.; Burgos, F.; Casaburi, R.; Coates, A.; Enright, P.; et al. Standardisation of single-breath determination of carbon monoxide uptake in the lung. Eur. Respir. J. 2005, 26, 720–735. [Google Scholar] [CrossRef]
  20. Quanjer, P.H.; Stanojevic, S.; Cole, T.J.; Baur, X.; Hall, G.L.; Culver, B.H.; Enright, P.L.; Hankinson, J.L.; Ip, M.S.M.; Zheng, J.; et al. Multi-ethnic reference values for spirometry for the 3–95-yr age range: The global lung function 2012 equations. Eur. Respir. J. 2012, 40, 1324–1343. [Google Scholar] [CrossRef]
  21. Cotes, J.E.; Chinn, D.J.; Quanjer, P.H.; Roca, J.; Yernault, J.C. Standardization of the measurement of transfer factor (diffusing capacity). Eur. Respir. J. 1993, 6 (Suppl. 16), 41–52. [Google Scholar] [CrossRef]
  22. Evans, J.A.; Whitelaw, W.A. The assessment of maximal respiratory mouth pressures in adults. Respir. Care 2009, 54, 1348–1359. [Google Scholar] [PubMed]
  23. Singh, S.J.; Puhan, M.A.; Andrianopoulos, V.; Hernandes, N.A.; Mitchell, K.E.; Hill, C.J.; Lee, A.L.; Camillo, C.A.; Troosters, T.; Spruit, M.A.; et al. An official systematic review of the European Respiratory Society/American Thoracic Society: Measurement properties of field walking tests in chronic respiratory disease. Eur. Respir. J. 2014, 44, 1447–1478. [Google Scholar] [CrossRef] [PubMed]
  24. Camarria, B.; Eastwood, P.R.; Cecins, N.M.; Thompson, P.J.; Jenkins, S. Six minute walk distance in healthy subjects aged 55–75 years. Respir. Med. 2006, 100, 658–665. [Google Scholar] [CrossRef]
  25. Stoica, P.; Selen, Y. Model-order selection: A review of information criterion rules. IEEE Signal Process. Mag. 2004, 21, 36–47. [Google Scholar] [CrossRef]
  26. Cecchetto, A.; Torreggiani, G.; Guarnieri, G.; Vianello, A.; Baroni, G.; Palermo, C.; Bertagna De Marchi, L.; Lorenzoni, G.; Bartolotta, P.; Bertaglia, E.; et al. Subclinical Myocardial Injury in Patients Recovered from COVID-19 Pneumonia: Predictors and Longitudinal Assessment. J. Cardiovasc. Dev. Dis. 2023, 10, 179. [Google Scholar] [CrossRef] [PubMed]
  27. Zheng, B.; Daines, L.; Han, Q.; Hurst, J.R.; Pfeffer, P.; Shankar-Hari, M.; Elneima, O.; Walker, S.; Brown, J.S.; Siddiqui, S.; et al. Prevalence, risk factors and treatments for post-COVID-19 breathlessness: A systematic review and meta-analysis. Eur. Respir. Rev. 2022, 31, 220071. [Google Scholar] [CrossRef]
  28. Arnold, D.T.; Hamilton, F.W.; Milne, A.; Morley, A.J.; Viner, J.; Attwood, M.; Noel, A.; Gunning, S.; Hatrick, J.; Hamilton, S.; et al. Patient outcomes after hospitalisation with COVID-19 and implications for follow-up: Results from a prospective UK cohort. Thorax 2021, 76, 399–401. [Google Scholar] [CrossRef]
  29. Michelen, M.; Manoharan, L.; Elkheir, N.; Cheng, V.; Dagens, A.; Hastie, C.; O’Hara, M.; Suett, J.; Dahmash, D.; Bugaeva, P.; et al. Characterising long COVID: A living systematic review. BMJ Glob. 2021, 6, e005427. [Google Scholar] [CrossRef]
  30. Sudre, H.D.; Murray, B.; Varsavsky, T.; Graham, M.S.; Penfold, R.S.; Bowyer, R.C.; Capdevila Pujol, J.; Klaser, K.; Antonelli, M.; Canas, L.S.; et al. Attributes and predictors of long COVID. Nat. Med. 2021, 27, 626–631. [Google Scholar] [CrossRef]
  31. Vimercati, L.; De Maria, L.; Quarato, M.; Caputi, A.; Gesualdo, L.; Migliore, G.; Cavone, D.; Sponselli, S.; Pipoli, A.; Inchingolo, F.; et al. Association between Long COVID and Overweight/Obesity. J. Clin. Med. 2021, 10, 4143. [Google Scholar] [CrossRef]
  32. Daitch, V.; Yelin, D.; Awwad, M.; Guaraldi, G.; Milic, J.; Mussini, C.; Falcone, M.; Tiseo, G.; Carrozzi, L.; Pistelli, F.; et al. Characteristics of long-COVID among older adults: A cross-sectional study. Int. J. Infect. Dis. 2022, 125, 287–293. [Google Scholar] [CrossRef] [PubMed]
  33. Grewal, J.S.; Carlsten, C.; Johnston, J.C.; Shah, A.S.; Wong, A.W.; Ryerson, C.J. Post-COVID dyspnea: Prevalence, predictors, and outcomes in a longitudinal, prospective cohort. BMC Pulm. Med. 2023, 23, 84. [Google Scholar] [CrossRef] [PubMed]
  34. Robey, R.C.; Kemp, K.; Hayton, P.; Mudawi, D.; Wang, R.; Greaves, M.; Yioe, V.; Rivera-Ortega, P.; Avram, C.; Chaudhuri, N. Pulmonary Sequelae at 4 Months After COVID-19 Infection: A Single-Centre Experience of a COVID Follow-Up Service. Adv. Ther. 2021, 38, 4505–4519. [Google Scholar] [CrossRef]
  35. Shi, Z.; de Vries, H.J.; Vlaar, A.P.J.; van der Hoeven, J.; Boon, R.A.; Heunks, L.M.A.; Ottenheijm, C.A.C. Diaphragm pathology in critically Ill patients with COVID-19 and postmortem findings from 3 medical centers. JAMA Intern. Med. 2021, 181, 122–124. [Google Scholar] [CrossRef] [PubMed]
  36. Farr, E.; Wolfe, A.R.; Deshmukh, S.; Rydberg, L.; Soriano, R.; Walter, J.M.; Boon, A.J.; Wolfe, L.F.; Franz, C.K. Diaphragm dysfunction in severe COVID-19 as determined by neuromuscular ultrasound. Ann. Clin. Transl. Neurol. 2021, 8, 1745–1749. [Google Scholar] [CrossRef]
  37. Abodonya, A.M.; Abdelbasset, W.K.; Awad, E.A.; Elalfy, I.E.; Salem, H.A.; Elsayed, S.H. Inspiratory muscle training for recovered COVID-19 patients after weaning from mechanical ventilation: A pilot control clinical study. Medicine 2021, 100, e25339. [Google Scholar] [CrossRef]
  38. Dosbabaa, F.; Hartmana, M.; Batalika, L.; Senkyra, V.; Radkovcovaa, I.; Richterd, S.; Brate, K.; Cahalinf, L.P.; Formigag, M.F. A temporal examination of inspiratory muscle strength and endurance in hospitalized COVID-19 patients. Heart Lung 2023, 60, 95–101. [Google Scholar] [CrossRef]
  39. Hennigs, J.K.; Huwe, M.; Hennigs, A.; Oqueka, T.; Simon, M.; Harbaum, L.; Körbelin, J.; Schmiedel, S.; zur Wiesch, J.S.; Addo, M.M.; et al. Respiratory muscle dysfunction in long COVID patients. Infection 2022, 50, 1391–1397. [Google Scholar] [CrossRef]
  40. Rinaldo, R.F.; Mondoni, M.; Parazzini, E.M.; Pitari, F.; Brambilla, E.; Luraschi, S.; Balbi, M.; Sferrazza Papa, G.M.; Sotgiu, G.; Guazzi, M.; et al. Deconditioning as main mechanism of impaired exercise response in COVID-19 survivors. Eur. Respir. J. 2021, 58, 2100870. [Google Scholar] [CrossRef]
  41. Skjørten, I.; Ankerstjerne, O.A.W.; Trebinjac, D.; Brønstad, E.; Rasch-Halvorsen, Ø.; Einvik, G.; Lerum, T.V.; Stavem, K.; Edvardsen, A.; Björk Ingul, C. Cardiopulmonary exercise capacity and limitations 3 months after COVID-19 hospitalisation. Eur. Respir. J. 2021, 58, 2100996. [Google Scholar] [CrossRef] [PubMed]
  42. Ozer, P.K.; Govdeli, E.A.; Baykiz, D.; Karaayvaz, E.B.; Medetalibeyoglu, A.; Catma, Y.; Elitok, A.; Cagatay, A.; Umman, B.; Oncul, A. Impairment of right ventricular longitudinal strain associated with severity of pneumonia in patients recovered from COVID-19. Int. J. Cardiovasc. Imaging 2021, 37, 2387–2397. [Google Scholar] [CrossRef] [PubMed]
  43. Tryfou, E.S.; Kostakou, P.M.; Chasikidis, C.G.; Kostopoulos, V.S.; Serafetinidis, I.I.; Ferdianaki, E.K.; Mihas, C.; Olympios, C.D.; Kouris, N.T. Biventricular myocardial function in COVID-19 recovered patients assessed by speckle tracking echocardiography: A prospective cohort echocardiography study. Int. J. Cardiovasc. Imaging 2022, 38, 995–1003. [Google Scholar] [CrossRef]
  44. Stockenhuber, A.; Vrettos, A.; Androschuck, V.; George, M.; Robertson, C.; Bowers, N.; Clifford, P.; Firoozan, F. A pilot study on right ventricular longitudinal strain as a predictor of outcome in COVID-19 patients with evidence of cardiac involvement. Echocardiography 2021, 38, 222–229. [Google Scholar] [CrossRef]
  45. Pestelli, G.; Fiorencis, A.; Trevisan, F.; Luisi, G.A.; Smarrazzo, M.; Mele, D. New measures of right ventricle-pulmonary artery coupling in heart failure: An all-cause mortality echocardiographic study. Int. J. Cardiol. 2021, 329, 234–241. [Google Scholar] [CrossRef] [PubMed]
  46. Guazzi, M.; Dixon, D.; Labate, V.; Beussink-Nelson, L.; Bandera, F.; Cuttica, M.J.; Shah, S.J. RV Contractile Function and its Coupling to Pulmonary Circulation in Heart Failure with Preserved Ejection Fraction: Stratification of Clinical Phenotypes and Outcomes. JACC Cardiovasc. Imaging 2017, 10, 1211–1221. [Google Scholar] [CrossRef]
  47. Iacoviello, M.; Monitillo, F.; Citarelli, G.; Leone, M.; Grande, D.; Antoncecchi, V.; Rizzo, C.; Terlizzese, P.; Romito, R.; Caldarola, P.; et al. Right ventriculo-arterial coupling assessed by two-dimensional strain: A new parameter of right ventricular function independently associated with prognosis in chronic heart failure patients. Int. J. Cardiol. 2017, 241, 318–321. [Google Scholar] [CrossRef]
  48. Polito, M.V.; Silverio, A.; Di Maio, M.; Bellino, M.; Scudiero, F.; Russo, V.; Rasile, B.; Alfano, C.; Citro, R.; Parodi, G.; et al. Prognostic Implications of Right Ventricular Function and Pulmonary Pressures Assessed by Echocardiography in Hospitalized Patients with COVID-19. J. Pers. Med. 2021, 11, 1245. [Google Scholar] [CrossRef]
Table
Table 1. Demographic and clinical characteristics at hospitalization according to the presence of dyspnea at follow-up.
Table 1. Demographic and clinical characteristics at hospitalization according to the presence of dyspnea at follow-up.
VariablesTotal
Patients
(n = 225)		Dyspnea Absent at FU
(n = 110)		Dyspnea Present at FU (n = 115)p Value
Age (y) (median IQR, (range))65 (55, 73)65 (54, 73)65 (55, 72)NS
Gender (n(%))
F 		88 (39%)36 (33%)52 (45%)NS
M 137 (61%)74 (67%)63 (55%)
Smoke (n (%))
no		125 (56%)64 (59%)61 (53%)NS
user11 (5%)8 (7.3%)3 (2.6%)
former smoker88 (39%)37 (34%)51 (44%)
Body mass index (kg/m2) (median IQR (range))28.1 (24, 31.4) 28.1 (25.1, 31.2)28.4 (24.5, 31.8)NS
Previous cardiovascular disease (n (%)) NS
Absent213 (95%)106 ((96%)107 (93%)
Present12 (5.3%)4 (3.6%)8 (7.0%)
Type of cardiovascular disease (n (%)) --
Ischemic8 (3.5%)
Valvular3 (1.3%)
Hypertrophic cardiomyopathy1 (0.4%)
Duration of hospitalization (days) (median IQR (range))18 (12, 28)17 (12, 25)20 (13, 35)NS
Respiratory ventilation (Type; (n (%)) NS
Absent36 (16%)12 (11%)24 (21%)
NC-SM25 (11%)12 (11%)13 (11%)
RM6 (3%)3 (2.8)3 (2.6%)
HFNC69 (31%)42 (40%)27 (24%)
NIV28 (13%)13 (12%)15 (13%)
MV56 (26%)24 (23%)32 (28%)
Troponin I (ng/L) (median IQR (range))
n.v. < 34 ng/L		9 (5, 26)8 (4, 17)12 (6, 65)0.035
CRP (mg/l) (median IQR (range))
n.v. < 5 mg/L		120 (81, 180)110 (78, 142)135 (86, 218)0.024
D-dimer (ng/mL) (median IQR (range))
n.v. < 500 ng/mL		662 (295, 1927) 564 (290, 1166)767 (324, 2620)NS
BNP (pg/mL) (median IQR (range))
n.v. < 125 pg/mL		70 (26, 120)40 (16, 102)80 (48, 210)0.001
Cardiovascular risk factors (n (%)) NS
Absent74 (33%)36 (33%)38 (33%)
Present151 (67%)74 (67%)77 (67%)
Cardiovascular risk factors type (n (%)) --
Hypertension101 (45%)
Dyslipidemia33 (14%)
Diabetes Mellitus34 (15%)
Obesity58 (26%)
CKD7 (3%)
B-type natriuretic peptide (BNP); chronic kidney disease (CKD); C-reactive protein (CRP); female (F); follow-up (FU); high-flow nasal cannula (HFNC); interquartile range (IQR); male (M); mechanical ventilation (MV); nasal cannula (NC); non-invasive ventilation (NIV); non-rebreather mask (RM); normal value (n.v.); not significant (NS); number (n); simple face mask (SM); years (y).
Table
Table 2. Transthoracic echocardiography measures at the follow-up evaluation, according to the presence of dyspnea.
Table 2. Transthoracic echocardiography measures at the follow-up evaluation, according to the presence of dyspnea.
MeasuresOverall
Patients (n = 225)		No Dyspnea at FU (n = 110)Dyspnea at FU (n = 115)p Value
LV EDVi biplane (mL/m2) (median IQR (range))51 (43, 58)52 (46, 59)50 (42, 57)NS
LV EDVi 3D (mL/m2) (median IQR (range))54 (47, 62)56 (48, 62)53 (46, 62)NS
LV ESVi biplane (mL/m2) (median IQR (range))20 (16, 23)20 (16, 24)20 (16, 22)NS
LV ESVi 3D (mL/m2) (median IQR (range))21 (18, 25)21 (18, 25)20 (18, 25)NS
LV EF biplane (%) (median IQR (range))61 (57, 65)61 (57, 65)61 (57, 64)NS
LV EF 3D (%) (median IQR (range))61 (58, 64)61 (58, 63)60 (57, 64)NS
LV GLS (%) (median IQR (range))−18.6 (−20.4, −17.0)−18.6 (−20.8, −17.0)−18.4 (−20.1, −26.7)NS
LV E/A ratio (median IQR (range))0.85 (0.71, 1.08)0.85 (0.71, 1.08)0.85 (0.70, 1.08)NS
LV E/e’ ratio (median IQR (range))7.5 (6.0, 9.1)7.7 (6.0, 8.9)7.1 (5.9, 9.7)NS
Left atrial volume index (mL/m2) median IQR (range))30 (25, 35)30 (27, 36)29 (24, 35)NS
RV EDAi (cm2/m2) (median IQR (range))11 (9, 12)11 (10, 12)11 (9, 12)NS
RV ESAi (cm2/m2) (median IQR (range))6 (5, 7)6 (5, 7)6 (5, 7)NS
FAC (%) (median IQR (range))44 (40, 47)44 (40, 47)44 (40, 48)NS
RV EDVi 3D (mL/m2) (median IQR (range))50 (41, 61)53 (42, 61)44 (39, 58)NS
RV ESVi 3D (mL/m2) (median IQR (range))23 (19, 30)25 (20, 32)23 (19, 29)NS
RV EF 3D (%) (median IQR (range))52 (47, 56)52 (48, 56)51 (47, 55)NS
RV FWS (%) (median IQR (range))−24.4(−27.0, −22.0)−25.0 (−27.3, −22.0)−24.0 (−26.0, −21.4)NS
RV GLS (%) (median IQR (range))−20.3 (−22.5, −18.4)−20.4 (−22.6, −18.7)−20.0 (−22.0, −18.2)NS
RV GLS/sPAP (%/mmHg) (median IQR (range))0.78 (0.97, 0.64)0.78 (0.93, 0.66)0.78 (1.04, 0.63)NS
TAPSE (mm) (median IQR (range))22 (20, 24)22 (20, 24)22 (19, 24)NS
TAPSE/sPAP (mm/mmHg)0.86 (0.71, 1.04)0.82 (0.71, 1.01)0.88 (0.71, 1.06)NS
Probability of pulmonary hypertension (n (%)) NS
-Low193 (93%)96 (93%)97 (92%)
-Intermediate11 (5.3%)6 (5.8%)5 (4.8%)
-Intermediate-high3 (1.4%)1 (1%)2 (1.9%)
-High1 (0.5%)0 (0%)1 (1%)
sPAP (mmHg) (median IQR (range))26 (21,29) 26 (22, 29)25 (21, 29)NS
PVR (WU) (median IQR (range))1.73
(1.49, 1.99)		1.77
(1.5, 2.00)		1.71
(1.42, 1.98)		NS
AT (msec) (median IQR (range))129
(116, 146)		130
(120, 145)		128
(114, 146)		NS
Acceleration time (AT); ejection fraction (EF); end-diastolic volume index (EDVi); end-systolic volume index (ESVi); fractional area change (FAC); interquartile range (IQR); left ventricle (LV); left ventricle global longitudinal strain (LVGLS); number (n); not significant (NS); pulmonary vascular resistance (PVR); right ventricle (RV); right ventricle end-diastolic area index (RVEDAi); right ventricle end-systolic area index (RVEDAi); right ventricle free-wall strain (RV FWS); right ventricle global longitudinal strain (RVGLS); systolic pulmonary artery pressure (sPAP); tricuspid annular plane excursion (TAPSE).
Table
Table 3. Pulmonary functional test and 6MWT measures at the follow-up evaluation, according to the presence of dyspnea.
Table 3. Pulmonary functional test and 6MWT measures at the follow-up evaluation, according to the presence of dyspnea.
MeasuresTotal
Patients (n = 225)		Dyspnea
Absent at FU (n = 110)		Dyspnea Present at FU (n = 115)p Value
VC (l) (median IQR (range))3.56 (2.86, 4.18) 3.63 (3.05, 4.27)3.34 (2.64, 4.05)NS
VC (%) (median IQR (range))102 (91, 114)104 (93, 115)101 (86, 113)NS
TLC (l) (median IQR (range))5.64 (4.64, 6.61) 5.85 (4.92, 6.66)5.37 (4.41, 6.51)0.044
TLC (%) (median IQR (range))95 (86, 103)96 (88, 103)94 (83, 103)NS
DLCO (mL/min/mmHg) (median IQR (range))19 (14, 23)20 (15, 24)18 (14, 22)0.036
DLCO (%) (median IQR (range))76 (61, 87)79 (66, 90)73 (58, 84)0.015
KCO (l) (median IQR (range))3.63 (2.94, 4.12)3.63 (2.99, 4.02)3.63 (2.93, 4.16)NS
MIP (cm H2O) (median IQR (range))74 (56, 103)83 (61, 103)70 (53, 103)NS
MEP (cm H2O) (median IQR (range))90 (68, 113)93 (73, 119)85 (63, 104)0.034
Tiffeneau index (%) (median IQR (range))0.84 (0.79, 0.88) 0.84 (0.80, 0.88)0.84 (0.79, 0.88)NS
Distance at 6MWT (m) (median IQR (range)) 420 (360, 480)450 (385, 495)420 (360, 480)NS
Final SpO2 at 6MWT (%) (median IQR (range))96 (95, 98)97 (96, 98)96 (94, 98)NS
Absolute drop in SpO2 at 6MWT (%) (median IQR (range))2 (1, 3)2 (1, 3)2 (1, 4)NS
Carbon monoxide transfer coefficient (KCO); interquartile range (IQR); lung diffusion capacity for carbon monoxide (DLCO); maximum expiratory pressure (MEP); maximum inspiratory pressure (MIP); number (n); not significant (NS); peripheral capillary oxygen saturation (SpO2); six-minute walking test (6MWT); total lung capacity (TLC); vital capacity (VC).
Table
Table 4. Acute predictors of persistent dyspnea.
Table 4. Acute predictors of persistent dyspnea.
Univariable AnalysisMultivariable Analysis
VariablesOR95% CIp ValueOR95% CIp Value
Age1.000.98, 1.02NS
Gender (male)0.580.33, 1.00NS
Smoke NS
-User0.390.08, 1.43
-Former smoker1.450.84, 2.52
BMI (kg/m2)1.020.97, 1.07NS1.151.06, 1.280.001
Previous CVD1.980.61, 7.61NS
Duration of
hospitalization		1.021.00, 1.040.0291.051.01, 1.100.005
Respiratory NS
Ventilation
-NC-SM0.540.19, 1.54
-RM0.500.08, 3.05
-HFNC0.320.13, 0.74
-NIV0.580.21, 1.59
-MV0.670.27, 1.61
Troponin I1.001.00, 1.00NS
CRP1.001.00, 1.010.0131.011.00, 1.020.025
D-dimer1.001.00, 1.00NS
BNP1.001.00, 1.00NS
Cardiovascular risk factors0.990.56, 1.72NS
Body mass index (BMI); B-type natriuretic peptide (BNP); cardiovascular disease (CVD); CI (confidence interval); C-reactive protein (CRP); high flow nasal cannula (HFNC); mechanical ventilation (MV); nasal cannula (NC); non-invasive ventilation (NIV); non-rebreather mask (RM); not significant (NS); odds ratio (OR); simple face mask (SM).
Table
Table 5. Association between persistent dyspnea and cardiopulmonary parameters at follow-up.
Table 5. Association between persistent dyspnea and cardiopulmonary parameters at follow-up.
Univariable AnalysisMultivariable Analysis
MeasuresOR95% CIp ValueOR95% CIp Value
Laboratory tests
CRP1.020.97, 1.07NS
D-dimer1.001.00, 1.00NS
Troponin I1.020.99, 1.07NS
BNP1.001.00, 1.00NS
6MWT
Distance1.000.99, 1.000.038
Final SpO20.880.78, 0.990.040
Absolute drop in SpO21.120.97, 1.30NS1.371.13, 1.690.001
Pulmonary functional tests
VC (l)1.020.97, 1.13NS
VC (%)0.990.97, 1.00NS
TLC (l)1.010.96, 1.11NS
TLC (%)0.980.96, 1.00NS
DLCO0.980.94, 1.01NS
DLCO (%)0.980.97, 1.000.007
KCO (l)1.060.95, 1.32NS
MIP1.000.99, 1.00NS
MEP0.990.98, 1.000.038
Tiffeneau index0.230.01, 8.41NS
Echocardiography
LV EDVi biplane0.980.96, 1.00NS
LV EDVi 3D0.980.96, 1.01NS
LV ESVi biplane0.970.93, 1.02NS
LV ESVi 3D1.000.96, 1.04NS
LV EF biplane0.990.94, 1.04NS
LV EF 3D0.980.92, 1.04NS
LV GLS1.060.97, 1.17NS
LV E/A ratio1.760.86, 4.00NS
LV E/e’ ratio1.050.94, 1.18NS
LAVi0.980.95, 1.00NS
RV EDAi0.910.79, 1.05NS
RV ESAi0.880.72, 1.05NS
FAC1.000.96, 1.05NS
RV EDVi 3D0.980.96, 1.00NS
RV ESVi 3D0.980.94, 1.02NS
RV EF 3D (%)0.980.93, 1.02NS
RV FWS1.030.98, 1.09NS
RV GLS1.020.98, 1.08NS1.121.02, 1.250.016
RV GLS/sPAP0.920.38, 2.18NS0.140.02, 0.860.034
TAPSE0.960.90, 1.02NS
TAPSE/sPAP1.230.45, 3.45NS
Probability of
pulmonary hypertension		 NS
-Low0.820.23, 2.83
-Intermediate1.980.19, 43.0
-HighNANA
sPAP0.990.95, 1.03NS
PVR0.830.46, 1.18NS
AT0.830.46, 1.18NS
Acceleration time (AT); B-type natriuretic peptide (BNP); carbon monoxide transfer coefficient (KCO); confidence interval (CI); C-reactive protein (CRP); ejection fraction (EF); end-diastolic volume index (EDVi); end-systolic volume index (ESVi); fractional area change (FAC); left atrial volume index (LAVi); left ventricle (LV); left ventricle global longitudinal strain (LVGLS); lung diffusion capacity for carbon monoxide (DLCO); maximum expiratory pressure (MEP); maximum inspiratory pressure (MIP); not applicable (NA); not significant (NS); odds ratio (OD); peripheral capillary oxygen saturation (SpO2); pulmonary vascular resistance (PVR); right ventricle (RV); right ventricle end-diastolic area index (RVEDAi); right ventricle end-systolic area index (RVESAi); right ventricle free-wall strain (RV FWS); right ventricle global longitudinal strain (RVGLS); systolic pulmonary artery pressure (sPAP); six-minute walking test (6MWT); total lung capacity (TLC); tricuspid annular plane excursion (TAPSE); vital capacity (VC).
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

Share and Cite

MDPI and ACS Style

Cecchetto, A.; Guarnieri, G.; Torreggiani, G.; Vianello, A.; Baroni, G.; Palermo, C.; Bertagna De Marchi, L.; Lorenzoni, G.; Bartolotta, P.; Bertaglia, E.; et al. Dyspnea in Post-Acute COVID-19: A Multi-Parametric Cardiopulmonary Evaluation. J. Clin. Med. 2023, 12, 4658. https://doi.org/10.3390/jcm12144658

AMA Style

Cecchetto A, Guarnieri G, Torreggiani G, Vianello A, Baroni G, Palermo C, Bertagna De Marchi L, Lorenzoni G, Bartolotta P, Bertaglia E, et al. Dyspnea in Post-Acute COVID-19: A Multi-Parametric Cardiopulmonary Evaluation. Journal of Clinical Medicine. 2023; 12(14):4658. https://doi.org/10.3390/jcm12144658

Chicago/Turabian Style

Cecchetto, Antonella, Gabriella Guarnieri, Gianpaolo Torreggiani, Andrea Vianello, Giulia Baroni, Chiara Palermo, Leonardo Bertagna De Marchi, Giulia Lorenzoni, Patrizia Bartolotta, Emanuele Bertaglia, and et al. 2023. "Dyspnea in Post-Acute COVID-19: A Multi-Parametric Cardiopulmonary Evaluation" Journal of Clinical Medicine 12, no. 14: 4658. https://doi.org/10.3390/jcm12144658

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop