Literature DB >> 34273962

Residual respiratory impairment after COVID-19 pneumonia.

Francesco Lombardi1,2, Angelo Calabrese1,2, Bruno Iovene1, Chiara Pierandrei2, Marialessia Lerede2, Francesco Varone1, Luca Richeldi1,2, Giacomo Sgalla3.   

Abstract

INTRODUCTION: The novel coronavirus SARS-Cov-2 can infect the respiratory tract causing a spectrum of disease varying from mild to fatal pneumonia, and known as COVID-19. Ongoing clinical research is assessing the potential for long-term respiratory sequelae in these patients. We assessed the respiratory function in a cohort of patients after recovering from SARS-Cov-2 infection, stratified according to PaO2/FiO2 (p/F) values.
METHOD: Approximately one month after hospital discharge, 86 COVID-19 patients underwent physical examination, arterial blood gas (ABG) analysis, pulmonary function tests (PFTs), and six-minute walk test (6MWT). Patients were also asked to quantify the severity of dyspnoea and cough before, during, and after hospitalization using a visual analogic scale (VAS). Seventy-six subjects with ABG during hospitalization were stratified in three groups according to their worst p/F values: above 300 (n = 38), between 200 and 300 (n = 30) and below 200 (n = 20).
RESULTS: On PFTs, lung volumes were overall preserved yet, mean percent predicted residual volume was slightly reduced (74.8 ± 18.1%). Percent predicted diffusing capacity for carbon monoxide (DLCO) was also mildly reduced (77.2 ± 16.5%). Patients reported residual breathlessness at the time of the visit (VAS 19.8, p < 0.001). Patients with p/F below 200 during hospitalization had lower percent predicted forced vital capacity (p = 0.005), lower percent predicted total lung capacity (p = 0.012), lower DLCO (p < 0.001) and shorter 6MWT distance (p = 0.004) than patients with higher p/F.
CONCLUSION: Approximately one month after hospital discharge, patients with COVID-19 can have residual respiratory impairment, including lower exercise tolerance. The extent of this impairment seems to correlate with the severity of respiratory failure during hospitalization.
© 2021. The Author(s).

Entities:  

Keywords:  6MWT; ABG; COVID; PFT; cough; dyspnoea

Mesh:

Substances:

Year:  2021        PMID: 34273962      PMCID: PMC8286033          DOI: 10.1186/s12890-021-01594-4

Source DB:  PubMed          Journal:  BMC Pulm Med        ISSN: 1471-2466            Impact factor:   3.317


Introduction

In December 2019, a novel coronavirus (SARS-CoV-2) able to infect the respiratory tract in humans emerged in Wuhan (China), causing a disease known as COVID-19. A possible complication of SARS-CoV-2 infection is a severe acute respiratory syndrome (SARS) due to interstitial pneumonia [1]. On March 11, 2020, the WHO declared COVID-19 a global pandemic. As of June, 2021 more than 175 million people have been infected by SARS-CoV-2 worldwide and 3.8 have died [2]. Several studies reported a range of clinical and laboratory features among hospitalized COVID-19 patients, including increased levels of inflammatory markers [3]. The frequency of respiratory and functional impairment after COVID-19 is still debated but several studies found reduced lung volumes, reduced diffusing capacity of the lung for carbon monoxide (DLCO) and reduced exercise tolerance following hospital discharge [4-7]. A comprehensive follow-up strategy for COVID-19 patients after clinical recovery has been advocated [8]. We performed a study to investigate the prevalence of respiratory impairment in a cohort of COVID-19 patients after hospital discharge and to determine the relationship between the severity of pulmonary involvement during hospitalization and the extent of residual clinical and functional abnormalities.

Material and methods

Study population and subgroups

In the post-COVID-19 outpatient program at Fondazione Policlinico Universitario “A. Gemelli” IRCCS, Rome (Italy), a multidisciplinary team evaluates patients after hospital discharge. Patients presenting between April 22nd and May 27th, 2020 were invited to participate in the study. Inclusion criteria were: previous hospitalization for COVID-19; radiological evidence of interstitial pneumonia at the time of hospital admission; nasopharyngeal swab negative for SARS-Cov-2 in the 48–72 h before study enrolment. Based on arterial blood gas (ABG) analysis values during hospitalizzation, three subgroups were defined using the worst PaO2/FiO2 value (p/F): mild (p/F ≥ 300), moderate (≤ 200 p/F < 300), and severe (p/F < 200). Such values, derived from the Berlin Criteria for ARDS, have been used in clinical practice to stratify severity of respiratory failure [9]. Written informed consent was obtained from each participant. The study protocol was approved by the Institutional Review Board of the Università Cattolica del Sacro Cuore (Rome, Italy) (approval number 0024185/20). Clinical evaluations, exams, and procedures were performed in accordance with the Declaration of Helsinki.

Study design and assessments

In this cross-sectional study, all patients underwent physical examination, resting ABG, pulmonary function tests (PFT) with DLCO, and 6MWT at the time of the study visit. ABG was analyzed using the ABL90FLEX radiometer (A. de Mori Spa Milano, Italy). The Biomedin Spirometer (software Baires version 5.1 revision 3, Biomedin SRL, Padova, Italy) was used to perform PFT and DLCO with the single breath-hold method (software Baires version 5.1 revision 3, Biomedin SRL, Padova, Italy). Lung function tests were performed according to current international guidelines [10, 11]. The 6MWT was used to assess the sub-maximal level of functional capacity. After 6 min of rest, the patient was instructed to walk along a 50 m corridor as fast as possible for 6 min wearing a finger/forehead pulse oximeter (Nonin 3100 Wristox pulse oximeter with nVISION software; Nonin Medical Inc, Plymouth, MN, USA) to record percutaneous oxygen saturation (SpO2) and heart rate (HR). At the end of the 6 min (or before, if the patient was unable to walk any further for fatigue, dyspnoea, or chest pain, or if saturation dropped below 80%) the distance covered was recorded and the patient was invited to sit and rest for 6 min. A drop in oxygen saturation ≥ 4% from baseline was considered to be clinically relevant During the study visit, a visual analog scale (VAS) score was used to measure the levels of dyspnoea and cough. Using a 100 mm linear scale, where 0 mm represents absence and 100 mm represents the worst dyspnoea and cough, patients were asked to report the levels of these two symptoms at the onset of the disease (i.e. immediately before hospital admission), during hospitalization, and at the moment of the study visit [12]. Retrospective data collected for this study included chest imaging findings, pharmacological treatments, p/F values, the type of respiratory support, and duration of hospitalization.

Statistical analysis

Descriptive statistics such as means with standard deviations or medians with interquartile ranges were used for continuous variables after checking for normal distribution of data. Frequencies or percentages were used to describe categorical variables. Dyspnea and cough VAS scores collected from the same patient were compared using analysis of variance (ANOVA) for repeated measures. Between-group comparisons of demographics and clinical data were performed using one-way analysis of covariance (ANCOVA) for continuous variables and the chi-square test for categorical variables. Estimated means of physiological variables across study groups were reported after adjustment by age, included as covariate in the ANCOVA model due to a significant age difference between study groups. P-values less than 0.05 were considered statistically significant. SPSS (version 24, IBM, New York, NY, USA) was used to perform statistical analyses.

Results

Characteristics of the study population

One hundred and fifty-seven patients included in the post-Covid follow-up program were screened for inclusion in the study. Twenty-six patients were excluded due to positivity at the nasopharyngeal SARS-Cov-2 swab; eighteen patients were excluded due to lack of radiological evidence of COVID-19 pneumonia at the time of hospitalization; twenty-seven patients were excluded because they had not been hospitalized (discharged from the Emergency Department). Eighty-six patients were included in the analyses. The characteristics of the study population are reported in Table 1. Study visit occurred 35 (SD: ± 21) days after hospital discharge. At the time of hospital admission, chest imaging (i.e., chest X-ray or chest CT scan) revealed bilateral ground-glass opacities (GGO) with or without consolidations in 70 patients (81%). Sixteen patients (19%) had unilateral lung involvement. During hospitalization, 56 (65%) patients required supplemental oxygen and 15 patients (17%) were admitted to the intensive care unit.
Table 1

Characteristics of patients during the hospitalization for Covid-19

Available observationsN = 87
Age, years58 (13)
Male, n (%)58 (67)
BMI (kg/m2)26.7 (4.4)
p/F worst76281 (150)*
Hospitalization time (days)8613 (10)*
Day from discharge (days)8535 (21)*
Smoking history, n (%)85
 Never smoker33 (39)
 Smoker4 (5)
 Former smoker48 (56)
Pulmonary disease history, n (%)86
 COPD3 (4)
 Asthma9 (11)
Radiology (chest XR or CT), n (%)86
 Chest CT performed51 (59)
 Unilateral involvement16 (19)
 Bilateral involvement70 (81)
Antiviral therapy, n (%)86
 Lopinavir/Ritonavir37 (43)
 Darunavir/Ritonavir53 (62)
Anti-IL-6, n (%)8631 (36)
Enoxaparin, n (%)8642 (49)
Azithromycin, n (%)8641 (48)
Hydroxychloroquine, n (%)8681 (94)
Corticosteroids, n (%)866 (7)
Respiratory support, n (%)86
 Ventimask56 (65)
 HFNC9 (11)
 NIV or CPAP13 (15)
 Orotracheal Intubation6 (7)
ICU admission, n (%)8615 (17)
FVC83
 Litres3.9 (1.1)
 % predicted104.6 (18.5)
FEV-183
 Litres3.1 (0.9)
 % predicted102.8 (16.0)
FEV-1/FVC83
 % predicted79.6 (5.8)
TLC82
 Litres5.7 (1.3)
 % predicted89.6 (14.6)
DLco83
 Litres21.2 (6.8)
 % predicted77.2 (16.5)
RV82
 Litres1.58 (0.47)*
 % predicted74.8 (18.1)
RC/TLC82
 Ratio30 (10)*
 % predicted79.0 (13.0)
ABG84
 pO2 (mmHg)91.4 (8.0)
 pCO2 (mmHg)38.8 (3.1)
 pH7.42 (0.02)*
 d(A-a) (mmHg)13.0 (7.5)
6MWT82
 SpO2 basal97 (2)*
 SpO2 nadir95 (4)*
 Meters500 (88)*

Categorical data are presented as counts (%). Continuous data are presented as means with standard deviation (SD) or medians with interquartile range (IQR) for non-normally distributed variables (indicated with *). BMI: Body Mass Index; ICU: Intensive Care Unit; COPD: Chronic Obstructive Pulmonary Disease; IL-6: Interleukin; HFNC: High Flow Nasal Cannula; NIV: Non-Invasive Ventilation; CPAP: Continue Positive Airway Pressure

Characteristics of patients during the hospitalization for Covid-19 Categorical data are presented as counts (%). Continuous data are presented as means with standard deviation (SD) or medians with interquartile range (IQR) for non-normally distributed variables (indicated with *). BMI: Body Mass Index; ICU: Intensive Care Unit; COPD: Chronic Obstructive Pulmonary Disease; IL-6: Interleukin; HFNC: High Flow Nasal Cannula; NIV: Non-Invasive Ventilation; CPAP: Continue Positive Airway Pressure Pulmonary function testing (Fig. 1) showed overall preserved lung volumes, with mean percent predicted total lung capacity (TLC) of 89.6% (± 14.6%) and mean percent predicted forced vital capacity (FVC) of 104.6% (± 18.5%). Mean percent predicted forced expiratory volume in one second (FEV1) was 102.8% (± 16.0%). Mean percent predicted residual volume (RV) was the only respiratory volume reduced under the 5th percentile (74.8 ± 18.1%). Percent predicted DLco was also mildly reduced (77.2 ± 16.5%).
Fig. 1

Overall cohort pulmonay function tests. Total Lung Capacity (TLC), Forced Vital Capacity (FVC), Forced Expiratory Volume in the first second (FEV-1), Residual Volume (RV) Diffusion Lung capacity for carbon monoxide (DLco)

Overall cohort pulmonay function tests. Total Lung Capacity (TLC), Forced Vital Capacity (FVC), Forced Expiratory Volume in the first second (FEV-1), Residual Volume (RV) Diffusion Lung capacity for carbon monoxide (DLco) Mean partial pressure of oxygen (pO2) was 91.4 mmHg (± 8.0) and mean alveolar-arterial oxygen gradient (d(A-a)) was 13.0 mmHg (± 7.5). Approximately one month after hospital discharge, patients reported more dyspnoea than pre-admission values (VAS score estimated mean difference: 15.3 mm; p < 0.001) (Fig. 2; Table 2).
Fig. 2

Overall cohort trends of the VAS scores for dyspnoea and cough before hospitalization, during hospitalization, and at follow-up

Table 2

Dyspnoea and cough in overall population in three-time points: before hospitalization, during the hospitalization, and at study visit-time; VAS: Visual Analogic Scale

Before hospitalizationDuring Covid-19 hospitalizationVisit-timep value
Dyspnoea VAS4.5 (1.3)47.4 (3.2) °#19.8 (2.1) # < 0.001
Cough VAS2.9 (1.2)31.8 (3.1) °#5.5 (1.3) < 0.001

Data are reported as estimated means (Standard Error) after adjustment for age used as covariate in the ANOVA model. ° p value < 0.05 vs “before hospitalization”. # p value < 0.05 vs “visit-time”

Overall cohort trends of the VAS scores for dyspnoea and cough before hospitalization, during hospitalization, and at follow-up Dyspnoea and cough in overall population in three-time points: before hospitalization, during the hospitalization, and at study visit-time; VAS: Visual Analogic Scale Data are reported as estimated means (Standard Error) after adjustment for age used as covariate in the ANOVA model. ° p value < 0.05 vs “before hospitalization”. # p value < 0.05 vs “visit-time”

Comparison of study groups by p/F ratio

Most patients (n = 76, 88%) had an ABG performed during the hospitalization and were therefore included in this analysis. Among excluded patients, 8 patients had no ABG and 2 patients had an ABG performed with unknown oxygen inhaled fraction. Gender, smoking status and comorbidities were not different across groups. Six patients (21%) in the mild hypoxemia group had a history of asthma. Patients in the severe hypoxemia group were older (63.1 years, p = 0.014 vs other groups), had a longer hospitalization time (23.0 days, p < 0.001 vs other groups) and were treated with anti-IL-6 drugs and enoxaparin more frequently (respectively 81% and 95%, p < 0.001 vs other groups). Lung volumes were generally lower in the severe hypoxemia group, including lower percent of predicted FVC (p = 0.005), lower percent of predicted FEV1 (p = 0.009) and lower percent of predicted TLC (p = 0.012) (Table 3). In the severe hypoxemia group mean percent predicted TLC was 80.4% (± 3.1), indicating a residual restrictive impairment after 35 days from hospital discharge. DLco was also more reduced (64.9 ± 3.2% predicted) in the severe hypoxemia group than in the other two groups (p < 0.001).
Table 3

Characteristics of patients stratified by p/F during hospitalization

N available observationsp/F ≥ 300 (N = 28)p/F < 300 ≥ 200 (n = 27)p/F < 200 (n = 21)p value
Age (years)7652.3 (14.0)59.2 (12.2)63.1 (11.9)0.014
Sex760.618
 Male19 (68)17 (63)16 (76)
 Female9 (32)10 (37)5 (24)
BMI (Kg/m2)7525.7 (5.1)27.3 (3.9)28.0 (4.3)0.181
p/F worst76349.0 (55.8)*276.0 (54.0)*135.0 (92.5)* < 0.001
Hospitalization time (days)769.5 (6.0)*13.0 (9.0)*23.0 (14.0)* < 0.001
ICU admission760 (0)1 (4)13 (62) < 0.001
Smoking history750.595
 Never smoker10 (36)9 (33)10 (50)
 Smoker1 (3)2 (8)0 (0)
 Former smoker17 (61)16 (59)10 (50)
Pulmonary disease history
 COPD760 (0)2 (7)0 (0)0.155
 Asthma766 (21)1 (4)0 (0)0.017
Chest CT performed7615 (54)17 (63)13 (62)0.745
Radiology (chest XR or CT)760.001
 Unilateral involvement11 (39)3 (11)0 (0)
 Bilateral involvement17 (61)24 (89)21 (100)
Antiviral therapy
 Lopinavir/Ritonavir7512 (43)9 (35)13 (62)0.165
 Darunavir/Ritonavir7614 (50)19 (70)13 (62)0.300
Anti IL-6762 (7)10 (37)17 (81) < 0.001
Enoxaparin768 (29)11 (41)20 (95) < 0.001
Azithromycin7512 (43)13 (50)12 (57)0.611
Hydroxychloroquine7627 (96)25 (93)21 (100)0.422
Corticosteroids740 (0)3 (11)2 (11)0.195
Respiratory support
 Ventimask768 (28)25 (93)21 (100) < 0.001
 HFNC750 (0)1 (4)8 (38) < 0.001
 NIV or CPAP750 (0)0 (0)11 (52) < 0.001
 Orotracheal Intubation680 (0)0 (0)5 (25)0.002
FVC§73
 Litres4.23 (0.18)3.77 (0.18)3.68 (0.21)0.099
 % predicted119.6 (3.3)104.5 (3.4)92.0 (3.9)°0.005
FEV1§73
 Litres3.36 (0.14)3.00 (0.14)2.98 (0.16)0.110
 % predicted107.8 (3.0)103.0 (3.1)92.6 (3.6)°0.009
FEV1/FVC§73
 %80.0 (1.0)79.3 (1.0)81.1 (1.2)0.536
TLC§72
 Litres5.95 (0.23)5.53 (0.24)5.31 (0.26)0.191
 % predicted92.6 (2.7)90.7 (2.8)80.4 (3.1)° #0.012
DLCO§73
 Litres23.23 (0.97)21.05 (1.00)18.69 (1.15)°0.017
 % predicted82.7 (2.7)80.6 (2.8)64.9 (3.2)° # < 0.001
RV§72
 Litres1.58 (0.48)*1.58 (0.44)*1.48 (0.71)*0.362
 % predicted77.6 (3.6)73.8 (3.8)70.8 (4.2)0.498
ABG§74
 pO2 (mmHg)93.3 (1.6)92.7 (1.5)87.8 (1.8)0.053
 pCO2 (mmHg)39.2 (0.6)38.3 (0.6)38.9 (0.7)0.467
 pH7.41 (0.03)*7.41 (0.04)*7.42 (0.03)*0.995
 d(A-a) (mmHg)10.1 (1.4)12.3 (1.3)16.6 (1.6)°0.011
6MWT§72
 SpO2 basal98.0 (1.0)*97.0 (2.0)*97.0 (2.0)*0.121
 SpO2 nadir96.5 (3.0)*95.0 (3.0)*94.0 (4.0)*°0.005
 Meters560 (130)*500 (95)*°480 (140)*°0.004
Dyspnoea VAS (mm)§
 Before753.5 (2.1)6.1 (2.1)1.5 (2.5)0.359
 During7544.1 (5.4)45.1 (5.5)60.0 (6.4)0.128
 Follow-up7514.1 (3.5)22.5 (3.6)25.9 (4.1)0.077
Cough VAS (mm)§
 Before750.4 (1.3)4.8 (1.4)1.1 (1.6)0.055
 During7537.0 (5.8)35.1 (5.9)31.5 (6.9)0.830
 Follow-up752.9 (2.3)8.8 (2.3)7.7 (2.7)0.171

Data are presented as counts (%) or means (SD) or medians with interquartile range (IQR) for non-normally distributed variables (indicated with *). BMI: Body Mass Index; ICU: Intensive Care Unit; COPD: Chronic Obstructive Pulmonary Disease; IL-6: Interleukin; HFNC: High Flow Nasal Cannula; NIV: Non-Invasive Ventilation; CPAP: Continue Positive Airway Pressure; VAS: Visual Analogic Scale. §Pulmonary Function, ABG, 6MWT parameters, Dyspnoea Visual Anlogic Scale (VAS) and Cough VAS are reported as estimated means (Standard Error) after adjustment for age used as covariate in the ANOVA model. °p value < 0.05 versus p/F ≥ 300 group. # p value < 0.05 versus p/F < 300 ≥ 200 group

Characteristics of patients stratified by p/F during hospitalization Data are presented as counts (%) or means (SD) or medians with interquartile range (IQR) for non-normally distributed variables (indicated with *). BMI: Body Mass Index; ICU: Intensive Care Unit; COPD: Chronic Obstructive Pulmonary Disease; IL-6: Interleukin; HFNC: High Flow Nasal Cannula; NIV: Non-Invasive Ventilation; CPAP: Continue Positive Airway Pressure; VAS: Visual Analogic Scale. §Pulmonary Function, ABG, 6MWT parameters, Dyspnoea Visual Anlogic Scale (VAS) and Cough VAS are reported as estimated means (Standard Error) after adjustment for age used as covariate in the ANOVA model. °p value < 0.05 versus p/F ≥ 300 group. # p value < 0.05 versus p/F < 300 ≥ 200 group As expected, the alveolar-arterial oxygen gradient increased progressively across study groups, ranging from 10.1 mmHg (± 1.4) in the mild hypoxemia group to 16.6 mmHg (± 1.6) in the severe hypoxemia group (p = 0.011). Compared to patients in the severe hypoxemia group, patients in the mild hypoxemia group demonstrated greater exercise tolerance (+ 80.0 m in 6MWD; p = 0.004) and higher nadir in SpO2 (+ 2.5%; p = 0.005). Dyspnoea and cough levels at the time of study visit were similar across groups.

Discussion

The findings of this study suggest that respiratory abnormalities persist over time in COVID-19 patients who experienced a more severe form of disease during hospitalization. Several studies already reported a reduction in lung volumes and DLco levels as well as reduced exercise tolerance following hospital discharge [4-7]. Our study expands these findings in a larger Italian cohort. To our knowledge, this is the first study establishing the relationships between the severity of acute respiratory failure (as measured by the p/F ratio) and a wide range of blood gas and physiological parameters. We identified a persistence of dyspnoea in the overall study population, a finding consistent with a study by Wong and coworkers, which reported dyspnoea in half of 78 COVID-19 patients after hospital discharge [13]. In order to explore the impact of disease severity on residual respiratory abnormalities, patients were stratified into three groups, according to levels of respiratory failure during hospitalization. No significant differences were observed regarding therapies, except for enoxaparin and anti-IL-6 drugs, administered more frequently in the severe group. The limited use of corticosteroids was likely due to the fact that evidence for dexamethasone use appeared towards the end of study completion [14]. We cannot exclude that a more extensive use of corticosteroids would have changed our findings. Patients with mild and moderate disease had normal lung volumes. In contrast, a mild reduction in RV was found in the severe hypoxemia group. Whether this finding results by altered lung compliance in this group [15] remain to be determined. Moreover, TLC was at the lower limit of normal in the severe group: this finding suggests a link between severity of COVID-19 pneumonia and reduction in lung volumes. Whether such abnormalities were due to the presence of fibrotic sequelae after acute interstitial pneumonia could not be determined, since our cohort did not undergo a chest CT scan at the time of the study visit. Moreover, we identified normal DLco values in the mild and the moderate hypoxemia groups and reduced values in the severe hypoxemia group. This could reflect the degree of microvascular and epithelial damage, likely to be more consistent in the severe cases [16]. Patients recovering from ARDS from any cause may have persistent functional impairment one year after hospital discharge [17]. Therefore, these findings might not be COVID-19-specific. Our study had several limitations. CT imaging was not available at the time of study visit: as such, the relationships between functional impairment and residual fibrotic changes remain unknown. The follow-up time in this study is short, and further studies are warranted to clarify whether respiratory abnormalities persist in the longer term. The use of p/F ratio to classify COVID-19 severity is not ideal as it may not be reliable in non-intubated patients [18]. Finally, the levels of dyspnoea and cough before and during hospitalization were collected at the time of the follow-up clinical evaluation: they may therefore not measure accurately the severity of symptoms at those timepoints.

Conclusion

Severe COVID-19 pneumonia may result in respiratory abnormalities and a reduction in exercise tolerance, which can be present at least one month after hospital discharge. Moreover, a low p/F ratio during the acute phase of the infection seems to correlate with a residual reduction of lung volumes, and residual reduction in DLCO. Further follow up is required to determine the degree of pulmonary and exercise impairment following hospitalization for COVID-19 pneumonia.
  16 in total

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Authors:  N Macintyre; R O Crapo; G Viegi; D C Johnson; C P M van der Grinten; V Brusasco; F Burgos; R Casaburi; A Coates; P Enright; P Gustafsson; J Hankinson; R Jensen; R McKay; M R Miller; D Navajas; O F Pedersen; R Pellegrino; J Wanger
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2.  Standardisation of spirometry.

Authors:  M R Miller; J Hankinson; V Brusasco; F Burgos; R Casaburi; A Coates; R Crapo; P Enright; C P M van der Grinten; P Gustafsson; R Jensen; D C Johnson; N MacIntyre; R McKay; D Navajas; O F Pedersen; R Pellegrino; G Viegi; J Wanger
Journal:  Eur Respir J       Date:  2005-08       Impact factor: 16.671

3.  Validity of the numeric rating scale as a measure of dyspnea.

Authors:  A G Gift; G Narsavage
Journal:  Am J Crit Care       Date:  1998-05       Impact factor: 2.228

4.  One-year outcomes in survivors of the acute respiratory distress syndrome.

Authors:  Margaret S Herridge; Angela M Cheung; Catherine M Tansey; Andrea Matte-Martyn; Natalia Diaz-Granados; Fatma Al-Saidi; Andrew B Cooper; Cameron B Guest; C David Mazer; Sangeeta Mehta; Thomas E Stewart; Aiala Barr; Deborah Cook; Arthur S Slutsky
Journal:  N Engl J Med       Date:  2003-02-20       Impact factor: 91.245

5.  Acute respiratory distress syndrome: the Berlin Definition.

Authors:  V Marco Ranieri; Gordon D Rubenfeld; B Taylor Thompson; Niall D Ferguson; Ellen Caldwell; Eddy Fan; Luigi Camporota; Arthur S Slutsky
Journal:  JAMA       Date:  2012-06-20       Impact factor: 56.272

6.  Impact of coronavirus disease 2019 on pulmonary function in early convalescence phase.

Authors:  Yiying Huang; Cuiyan Tan; Jian Wu; Meizhu Chen; Zhenguo Wang; Liyun Luo; Xiaorong Zhou; Xinran Liu; Xiaoling Huang; Shican Yuan; Chaolin Chen; Fen Gao; Jin Huang; Hong Shan; Jing Liu
Journal:  Respir Res       Date:  2020-06-29

7.  P aO2 /F IO2 ratio: the mismeasure of oxygenation in COVID-19.

Authors:  Martin J Tobin; Amal Jubran; Franco Laghi
Journal:  Eur Respir J       Date:  2021-03-25       Impact factor: 16.671

Review 8.  Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2): An Update.

Authors:  Mahendra Pal; Gemechu Berhanu; Chaltu Desalegn; Venkataramana Kandi
Journal:  Cureus       Date:  2020-03-26

9.  COVID-19 pneumonia: different respiratory treatments for different phenotypes?

Authors:  Luciano Gattinoni; Davide Chiumello; Pietro Caironi; Mattia Busana; Federica Romitti; Luca Brazzi; Luigi Camporota
Journal:  Intensive Care Med       Date:  2020-04-14       Impact factor: 17.440

10.  Dexamethasone in Hospitalized Patients with Covid-19.

Authors:  Peter Horby; Wei Shen Lim; Jonathan R Emberson; Marion Mafham; Jennifer L Bell; Louise Linsell; Natalie Staplin; Christopher Brightling; Andrew Ustianowski; Einas Elmahi; Benjamin Prudon; Christopher Green; Timothy Felton; David Chadwick; Kanchan Rege; Christopher Fegan; Lucy C Chappell; Saul N Faust; Thomas Jaki; Katie Jeffery; Alan Montgomery; Kathryn Rowan; Edmund Juszczak; J Kenneth Baillie; Richard Haynes; Martin J Landray
Journal:  N Engl J Med       Date:  2020-07-17       Impact factor: 91.245

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1.  Detection of residual pulmonary alterations with lung ultrasound and effects on postoperative pulmonary complications for patients with asymptomatic SARS-CoV-2 infection undergoing surgeries.

Authors:  Susana González-Suárez; Antonio Barbara Ferreras; Melissa Caicedo Toro; Macarena Aznar de Legarra
Journal:  BMC Anesthesiol       Date:  2022-06-16       Impact factor: 2.376

Review 2.  Pulmonary function test and computed tomography features during follow-up after SARS, MERS and COVID-19: a systematic review and meta-analysis.

Authors:  Christopher C Huntley; Ketan Patel; Shahnoor-E-Salam Bil Bushra; Farah Mobeen; Michael N Armitage; Anita Pye; Chloe B Knight; Alyaa Mostafa; Marie Kershaw; Aishah Z Mughal; Emily McKemey; Alice M Turner; P Sherwood Burge; Gareth I Walters
Journal:  ERJ Open Res       Date:  2022-05-30

3.  Multi-organ assessment in mainly non-hospitalized individuals after SARS-CoV-2 infection: The Hamburg City Health Study COVID programme.

Authors:  Elina Larissa Petersen; Alina Goßling; Gerhard Adam; Martin Aepfelbacher; Christian-Alexander Behrendt; Ersin Cavus; Bastian Cheng; Nicole Fischer; Jürgen Gallinat; Simone Kühn; Christian Gerloff; Uwe Koch-Gromus; Martin Härter; Uta Hanning; Tobias B Huber; Stefan Kluge; Johannes K Knobloch; Piotr Kuta; Christian Schmidt-Lauber; Marc Lütgehetmann; Christina Magnussen; Carola Mayer; Kai Muellerleile; Julia Münch; Felix Leonard Nägele; Marvin Petersen; Thomas Renné; Katharina Alina Riedl; David Leander Rimmele; Ines Schäfer; Holger Schulz; Enver Tahir; Benjamin Waschki; Jan-Per Wenzel; Tanja Zeller; Andreas Ziegler; Götz Thomalla; Raphael Twerenbold; Stefan Blankenberg
Journal:  Eur Heart J       Date:  2022-03-14       Impact factor: 29.983

4.  Effects of SARS-CoV-2 Infection on Pulmonary Function Tests and Exercise Tolerance.

Authors:  Josuel Ora; Bartolomeo Zerillo; Patrizia De Marco; Gian Marco Manzetti; Ilaria De Guido; Luigino Calzetta; Paola Rogliani
Journal:  J Clin Med       Date:  2022-08-23       Impact factor: 4.964

5.  Relation of Pulmonary Diffusing Capacity Decline to HRCT and VQ SPECT/CT Findings at Early Follow-Up after COVID-19: A Prospective Cohort Study (The SECURe Study).

Authors:  Terese L Katzenstein; Jan Christensen; Thomas Kromann Lund; Anna Kalhauge; Frederikke Rönsholt; Daria Podlekareva; Elisabeth Arndal; Ronan M G Berg; Thora Wesenberg Helt; Anne-Mette Lebech; Jann Mortensen
Journal:  J Clin Med       Date:  2022-09-26       Impact factor: 4.964

6.  Lung-function trajectories in COVID-19 survivors after discharge: A two-year longitudinal cohort study.

Authors:  Hui Zhang; Xia Li; Lixue Huang; Xiaoyin Gu; Yimin Wang; Min Liu; Zhibo Liu; Xueyang Zhang; Zhenxing Yu; Yeming Wang; Chaolin Huang; Bin Cao
Journal:  EClinicalMedicine       Date:  2022-09-28

7.  Parenchymal lung abnormalities following hospitalisation for COVID-19 and viral pneumonitis: a systematic review and meta-analysis.

Authors:  Laura Fabbri; Samuel Moss; Fasihul A Khan; Wenjie Chi; Jun Xia; Karen Robinson; Alan Robert Smyth; Gisli Jenkins; Iain Stewart
Journal:  Thorax       Date:  2022-03-25       Impact factor: 9.139

  7 in total

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