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Respiratory Muscle Dysfunction and Associated Risk Factors Following COVID-19-Related Hospitalisation

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12 December 2024

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12 December 2024

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Preprints on COVID-19 and SARS-CoV-2
Abstract
Background: Studies have highlighted long-term respiratory muscle dysfunction in COVID-19 survivors, although the underlying risk factors remain unclear. This single-center study assessed respiratory muscle function and individual associated factors at follow-up in patients hospitalised with COVID-19 and related acute respiratory failure. Methods: Data were collected for consecutive patients, aged ≥18 years, at the post-COVID outpatient service of Hospital Policlinico in Modena (Italy) in the time frame of 3 to 6 months after discharge. Data were analysed using single and multiple logistic regression model. Correlation between MIP/MEP, hand-grip values and lung function were further explored. Results: Out of 223 patients (mean age 67 years, 69% male) 121 (54.3%) exhibited MIP or MEP dysfunction which was found to be associated with use of non-invasive ventilation (OR=1.93 [1.08–3.52], p=0.03) and female gender (OR=1.96 [1.1–3.57], p=0.03) as indipendent risk factors. A positive correlation was observed between MIP dysfunction and hand-grip strength (p=0.03 and 0.01), whereas both MIP and MEP were significantly associated with FEV1, FVC, TLC, and DLCO. Conclusions: Respiratory muscle dysfunction is consistently prevalent and parallels peripheral muscle weakness and lung fuction level in patients at follow up after severe COVID-19. The need for non-invasive ventilation during the acute phase and female gender might represent risk factors. MIP/MEP assessment should be recommended to observe respiratory muscle dysfunction in severe post-COVID survivors.
Keywords: 
post-COVID
;  
Maximal Inspiratory Pressure (MIP)
;  
Maximal Expiratory Pressure (MEP)
;  
Hand-Grip Strength
;  
Lung function
;  
Non-invasive ventilation
Subject: 
Public Health and Healthcare  -   Public Health and Health Services

1. Introduction

The Coronavirus disease 2019 (COVID-19) pandemic was declared on March 11, 2020 from the World Health Organization (WHO) and had an unprecedented impact on global health in terms of morbidity and mortality. Beyond 7,065,880 deaths confirmed in September 2024,[1] it is known that the symptoms of COVID-19 can range from asymptomatic to life threatening.[2] People experience a wide range of symptoms including fever, dry cough, shortness of breath, muscle pain, and fatigue, although most infections are not severe and people are able to recover at home without hospital treatment. Where the novel Coronavirus causes severe illness, the commonest clinical presentation is bilateral pneumonia leading to hypoxemia with acute respiratory failure. Individuals getting moderate to severe respiratory failure require hospital admission with need of respiratory support, such as oxygen therapy and/or non-invasive ventilation (NIV).
A significant proportion of patients post COVID-19, particularly those with severe acute disease, may experience persistent symptoms with poor quality of life following recovery from the viral infection. Increasing evidence of post-COVID long-term effects following hospitalisation has been reported in literature. Clusters of symptoms including dyspnea, fatigue, muscle pain, and sleep disturbances have been frequently described and indicated new disability.[3,4]
Considering that SARS-CoV-2 is a virus spreading to multiple organs other than lungs, it has been proposed that the COVID-related cytokine storm may cause dysfunction to the respiratory muscles (RM), especially the diaphragm.[5,6] On the other hand, critical illness myopathy is associated with prolonged mechanical ventilation and patient immobilisation that are risk factors for complications such as peripheral muscle weakness and RM dysfunction.[7,8] Skeletal muscle is one of the most involved organs in COVID-19. Myalgia and fatigue are the third most reported symptoms (after fever and cough) in people with symptomatic infection.[9]
The relationship between COVID-19 and changes in RM and the resulting functional implications have not been yet completely understood in individuals without pre-existing conditions associated with RM dysfunction. In this study, we aimed to explore: 1) long-term RM function in patients previously hospitalised for COVID-19; 2) factors associated with RM dysfunction, and association of MIP/MEP levels with the follow up variables.

2. Materials and Methods

Study Design

We established a post-COVID follow up service at the Outpatient Department of Hospital Policlinico in Modena (Italy), for patients admitted with COVID-19 since the first wave of the pandemic. The primary setting that provided patient assessment was a multidisciplinary referral centre for post-Acute COVID syndrome at the Infectious Disease Unit and secondly, at the Respiratory Unit. We aimed to follow up all patients in-person after discharge and collected data also to identify people presenting with any persistent symptom. This study is an observational single-centre cohort study that has been designed and carried out in those patients who attended the service solely 3 to 6 (three-to-six) months after discharge. All visits were conducted into an optimal time window.

Participants

All consecutive patients referred to the post-COVID service between June 2020 and October 2021, aged ≥18 years, with a minimum 7-day length of hospital stay, were systematically included. Exclusion criteria were pre-admission diagnosis of chronic conditions potentially affecting RM function such as asthma, COPD, ILD, coronary artery disease and/or chronic heart failure, cardiomyopathies, and neuromuscular diseases. Nursing home residents were excluded due to difficulty of attending follow up appointments. Patients not able to perform lung function test and hand-grip test were also excluded.

Procedures

At the follow up visit, patients had spirometry with diffusing capacity for carbon monoxide (DLCO), [10,11] measurement of Maximal Inspiratory Pressure (MIP) and Maximal Expiratory Pressure (MEP), [12,13] hand-grip test, [14] and modified Medical Research Council (mMRC) dyspnea scale.[15]

Variables and Outcomes

Variables

Variables collected at follow up included: age; sex; smoking status (never, previous, or current); pre-admission Body Mass Index (BMI); respiratory support (Non-Invasive Ventilation (NIV); high-flow nasal cannula (HFNC) oxygen therapy; intubation); use of Dexamethasone; use of any other systemic corticosteroid; use of Tocilizumab; O2 at discharge; length of stay in hospital (LOS) and in Intensive Care Unit (ICU); time from discharge to follow up; pulmonary function parameters, DLCO, MIP and MEP; skeletal muscle strength of the hand; and dyspnea scale. Data collection was completed by patient clinical records (case notes and electronic records) and drug prescription charts. All data entered into a specific database.

Outcomes

The primary aim was to explore the prevalence of Maximal Inspiratory Pressure (MIP) and Maximal Expiratory Pressure (MEP) dysfunction in COVID-19 survivors, according to the age-adjusted lower threshold from Lista-Paz 2023.[13] The secondary outcomes were: 1) MIP/MEP dysfunction related risk factors; 2) association of MIP/MEP levels with the follow up variables. The peripheral muscle dysfunction was defined as reduction in dominant hand grip strength under 25th percentile (age- and sex-adjusted value).[14] The lung volume reduction was defined either as restrictive pattern (TLC <90% of predicted value) or reduced lung diffusion capacity (DLco <80% of predicted value). A self-reported symptom of dyspnea according to mMRC scale score ≥ 1 indicated the presence of breathlessness.[15] Outcomes were assessed up to last data entry using systems of prospective follow-up and electronic health records.

Data Analysis

A priori sample size calculation on the primary outcome was based on the reported prevalence of MIP/MEP dysfunction among critically ill patients ranging 50-80%. 16-18] Assuming α = 0.05 and power of 85 and a margin of error of 5%, a sample size of 223 patients was suitable for assessing the primary outcome. Data were displayed as median and interquartile range (IQR) for continuous variables and numbers and percentages for dichotomous variables. Continuous variables were compared by Student’s t-test or Mann-Whitney test as appropriate. Categorical variables were expressed as numbers and percentages (%) and compared by χ2 test or Fisher’s exact test across the groups. The association with MIP/MEP dysfunction was analysed using a univariate single logistic regression model and a multiple logistic regression model to explore independent associations for selected variables. Sensitivity analysis was used to examine the correlation between the values of MIP and MEP (expressed as % of predicted values) and hand-grip values and pulmonary function parameters (namely TLC, FEV1, FVC and DLCO). Pearson’s R or Spearman correlation coefficient were used as appropriate. Statistical analysis was performed using SPSS package ver.25.0 (IBM Corp., Armonk-NY, USA) and GraphPad Prism version 8.0 (GraphPad Software, Inc., La Jolla, Ca, USA) unless otherwise indicated.

3. Results

Between June 2020 and October 2021, 719 participants with COVID-19 were assessed at the follow up service. Of these, 496 were excluded based on the study criteria, missing data and follow up time not ranging within 3-6 months. The study included 223 patients. The time from discharge to follow up was 4 ±1.1 months (mean±SD). Demographic and clinical variables are shown in Table 1. Overall, the mean age was 67 years with a greater proportion of men (69%). The mean BMI was 30. On admission, conventional oxygen therapy (COT) was used in 24%, HFNC oxygen therapy in 27%, NIV in 33%. Intubation rate was 16% (36/223). Missing data accounted for less than 3% of the dataset.
Table 1. Sample characteristics and hospital admission factors of patients attending follow up by MIP/MEP dysfunction.
Table 1. Sample characteristics and hospital admission factors of patients attending follow up by MIP/MEP dysfunction.
Overall n = 223 (100) MIP/MEP abnormal values *
n=121 (54.2)		 MIP/MEP normal values *
n=102 (45.8)		 p value
Demographics
Age, years [IQR] 67 (57 – 75) 67 (59 – 74) 65 (55 – 75) 0.11
Male gender, no. [%] 153 (68.6) 76 (62.8) 77 (75.5) 0.04
Ethnicity
Caucasian, n [%] 218 (97.8) 118 (97.5) 100 (98) 0.99
Black, n [%] 4 (1.8) 2 (1.7) 2 (2) 0.99
Asian, n [%] 1 (0.4) 1 (0.8) 0 (0) 0.99
Smoking history
Current smoker, no. [%] 2 (0.9) 1 (0.8) 1 (1) 0.99
Former smoker, no. [%] 88 (39.5) 51 (42.1) 37 (36.2) 0.41
Non-smoker, no. [%] 133 (59.6) 69 (57) 64 (62.7) 0.41
BMI (pre-admission), median [IQR] 30 (27 – 34) 30 (27 – 34) 30 (27 – 34) 0.64
BMI >30, no. [%] 121 (54.3) 68 (56.2) 53 (52) 0.21
Outcomes
LOS, days [IQR] 14 (10 – 21) 15 (11 – 23.5) 13 (9 – 19.3) 0.14
Respiratory support
HFNC, no. [%] 60 (26.9) 32 (26.4) 28 (27.5) 0.88
NIV, no. [%] 74 (33.2) 48 (39.7) 26 (25.5) 0.03
Intubation/MV, no. [%] 36 (16.1) 21 (17.4) 15 (14.7) 0.72
Use of Tocilizumab 150 (67.3) 79 (65.3) 71 (69.6) 0.47
Use of Dexamethasone 67 (30) 37 (16.6) 30 (13.4) 0.88
Use of other corticosteroids (oral/IV) 134 (60.1) 73 (60.3) 61 (59.8) 0.99
O2 at discharge, no. [%] 32 (14.3) 19 (15.7) 13 (12.75) 0.57
Follow up
Dyspnea grade (mMRC), median [IQR] 0 (0 – 1) 0 (0 – 1) 0 (0 – 1) 0.09
Dyspnea as mMRC ≥ 1, no. [%] 67 (30) 39 (32.2) 28 (27.5) 0.46
FEV1/FVC, % [IQR] 82 (78 – 85.7) 81.8 (78.7 – 86.3) 82.1 (78.1 – 85.1) 0.78
TLC, %pred [IQR] 105 (94 – 116) 101 (91.5 – 113) 107.5 (96.8 – 117) 0.06
TLC <90%pred, no. [%] 38 (17) 27 (22.3) 11 (10.8) 0.03
DLCO, %pred [IQR] 77 (67 – 87) 75 (64.5 – 86) 79.5 (68 – 92.3) 0.02
DLCO <80%pred, no. [%] 128 (57.4) 77 (63.6) 51 (50.5) 0.06
MIP, %pred [IQR] 84 (66 – 104) 68 (58 – 73) 102 (90 – 120) <0.0001
MEP, %pred [IQR] 82 (62 – 93) 65 (54 – 72) 96 (88 – 101) <0.0001
Reduced strength in dominant hand, no. [%] 60 (26.9) 40 (33.1) 20 (19.6) 0.034
Reduced strength in right hand, no. [%] 68 (30.5) 46 (38) 22 (21.6) 0.01
Reduced strength in left hand, no. [%] 77 (34.5) 46 (38) 31 (30.4) 0.26
Abbreviations: BMI, body mass index; LOS, Length of stay; mMRC, modified Medical Research Council; FEV1, Forced Expiratory Volume in 1 Second; FVC, Forced Vital Capacity; TLC, Total Lung Capacity; DLCO, Diffusing capacity of the Lungs for Carbon monoxide; MIP, Maximal Inspiratory Pressure; MEP, Maximal Expiratory Pressure *Lista-Paz A et al. Arch Bronconeumol 2023; 59(12):813-820. [13].

3.1.1. Prevalence of MIP/MEP Dysfunction and Related Risk Factors

Reduction in MIP or MEP was found in 54.2% of patients (Table 1). In the multiple logistic regression model, MIP or MEP dysfunction showed positive association with use of NIV (p = 0.03) and female gender (p = 0.03) (Table 2).
Table 2. Raw and independent association between clinical variables and MIP/MEP dysfunction at follow-up according to Lista-Paz A et al 2023.[13].
Table 2. Raw and independent association between clinical variables and MIP/MEP dysfunction at follow-up according to Lista-Paz A et al 2023.[13].
Univariable Multivariable
Parameter OR 95% Confidence Interval p value OR 95% Confidence Interval p value
Age 1.02 0.99 – 1.04 0.12
Female sex 0.54 0.3 – 0.98 0.04 0.51 0.28 – 0.91 0.03*
Smoking status (active/former) 1.19 0.91 – 1.55 0.20
BMI 1.01 0.96 – 1.07 0.64
BMI ≥ 30 kg/m2 1.19 0.7 – 2 0.53
Hospital length of stay 1.01 0.99 – 1.03 0.15
HFNC 0.95 0.52 – 1.93 0.87
NIV 1.79 1.01 – 3.22 0.04 1.93 1.08 – 3.52 0.03*
Intubation/MV 1.22 0.59 – 2.54 0.59
Use of Dexamethasone 1.06 0.59 – 1.6 0.85
Use of other corticosteroids 1.02 0.6 – 1.75 0.94
Use of Tocilizumab 0.82 0.47 -1.44 0.49
Association is shown through odds ratio (OR) and 95%CI. Abbreviations: OR, odds ratio; IQR, InterQuartile Range; HFNC, high-flow nasal cannula oxygen therapy; NIV, non-invasive ventilation; MV, mechanical ventilation; BMI, body mass index.

3.1.2. Correlation Between MIP/MEP, Peripheral Muscle Function, Lung Function, and Dyspnea

Reduction in dominant hand grip strength (in kg) was observed in 27% of patients (Table 1). Using the Pearson correlation coefficient test, right and left hand grip strength was associated with MIP dysfunction (p = 0.03 and 0.01, respectively) (Figure 1). None of the patients showed obstructive pattern on spirometry (FEV1/FVC <0.7). Restrictive pattern (TLC <90% pred) was observed in 17% of patients and reduced lung diffusing capacity (DLCO <80% pred) was found in 57.4% (128 participants). All patients presenting restrictive pattern on spirometry showed reduction in DLCO. MIP and MEP were significantly correlated with lung function level (Figure 2) and DLCO (Figure 3). mMRC ≥ 1 grade was reported in 67/223 patients (30%) (Table 1), and no association was found with RM dysfunction.
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Figure 1. Correlation between MIP/MEP and hand-grip strength.
Figure 1. Correlation between MIP/MEP and hand-grip strength.
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Figure 2. Correlation between MIP/MEP and FEV1 and FVC values.
Figure 2. Correlation between MIP/MEP and FEV1 and FVC values.
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Figure 3. Correlation between MIP/MEP and TLC and DLCO values.
Figure 3. Correlation between MIP/MEP and TLC and DLCO values.
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4. Discussion

In this cohort study of 223 patients hospitalised with severe COVID-19, we found MIP or MEP dysfunction in 54.2% of participants at follow-up ranging from 3 to 6 months, excluding those with pre-existing pulmonary, cardiac, and neuromuscular comorbidities.
The study adds to evidence base evaluating RM function in COVID-19 survivors.[19,20,21] One previous study found a reduction of MIP and MEP in 49.1% and 22.8% respectively among slightly younger patients at 1 month from hospital discharge,[19] and no correlation was observed with use of corticosteroids or severe COVID. That population was characterised by 30% of severe cases without underlying pulmonary and cardiovascular disease. Correspondingly, we also did not find any association with glucocorticoid therapy and/or illness severity or intubation. Another study demonstrated greater decrease of MIP (27%) than MEP at the same timepoint in patients who presented higher intubation rate (40%) and pre-admission lung disease (29%).[20] A multicentric study showed MIP reduction even 30 months following hospitalisation for severe COVID-19 in younger patients, after excluding chronic diseases that lead to RM dysfunction.[21] Whilst the authors did not report data on intubation or mechanical ventilation, these findings were associated with prolonged hospital stay and age. Our findings are consistent with previous data on medium- and long-term outcomes regarding RM dysfunction in individuals exposed to severe COVID-19 but without underlying RM-affecting diseases.
As MIP has a strong relationship with strength of the diaphragm that is the major inspiratory muscle, a few studies also included diaphragm ultrasound measurements following ICU admission due to COVID-19. One study, considering inspiratory muscle normal thresold level as MIP > 70% predicted, confirmed that mechanically ventilated COVID-19 survivors had overall dysfunction at 3 (48%) and 6 (24%) months but not any specific diaphragm dysfunction.[8] Contrastingly, one complex study demonstratred a diaphragm dysfunction in 80% of patients not requiring mechanical ventilation, at 15 months.[22] Another study showed a significant reduction in diaphragm contractility in COVID-19 survivors.[23] The persistence of MIP reduction in our population highlights the substantial impact of severe COVID-19 on inspiratory muscle function, even in the absence of prolonged mechanical ventilation or other established contributors to RM impairment.
This impairment is likely to be linked to a combination of factors, including systemic inflammation, microvascular damage, and critical illness myopathy. Additionally, mechanisms such as ventilator-induced diaphragm dysfunction and oxidative stress may further impair contractility and strength. Unlike MEP, MIP appears particularly vulnerable due to the diaphragm’s central role in respiration and its heightened sensitivity to systemic and illness-related factors.
We also found that MIP/MEP dysfunction was associated with the use of NIV as an independent risk factor. Prolonged NIV use may contribute to diaphragmatic deconditioning, promoting long-term impairment as a result. Interestingly, the number of patients with reduced MIP or MEP exceeded those requiring NIV (33%) or intubation (16%). Whilst ICU admission and mechanical ventilation, which can lead to critical illness myopathy,[8,24] may explain RM dysfunction in some severe COVID-19 cases, the persistence of MIP reduction in non-hospitalised patients or those requiring no respiratory support, as observed in our study, requires further investigation. Evidence on RM dysfunction in survivors, regardless of mechanical ventilation status, remains inconclusive. Factors such as ageing and its associated decline in respiratory muscle performance may also play a role.[25]
In our study, mechanical ventilation was not associated with RM dysfunction, whereas NIV was—a difference that may be attributed to survivorship bias. Many intubated patients did not survive, excluding the most severe cases from follow-up analysis, whereas in contrast NIV patients, unless under therapeutic ceiling, were more likely to survive and be included. This overrepresentation of NIV patients amplifies its apparent statistical association with RM dysfunction, underscoring the need for cautious interpretation of these findings.
We also found that female gender was an independent risk factor for reduced MIP or MEP. This finding is in line with recent literature showing that females had a marked reduction in MIP,[21] even in women not admitted to hospital for COVID at 5 months following discharge.[26] Although the role of gender shoud be further clarified, Hennigs et al [26] and Steinbeis et al [27] demonstrated that all patients with RM dysfunction were also symptomatic at follow up. RM reduction was associated with dyspnea and fatigue after 3-8 months, irrespective of hospitalisation, admission to ICU, or need for oxigen.[27] Nonetheless, when we assessed breathlessness, the prevalence of mMRC score ≥1 (as clinically symptom presence) was 30% and not to be related to RM dysfunction. These findings of dyspnea are consistent with literature on large populations of post-COVID patients, showing a prevalence ranging from 20% to 43% in the time frame of 2-8 months follow up.[28,29,30,31,32]
We also found that hand-grip strength was lower in 27% of patients, similarly to the study of Johnsen et al. (28%) who reported a prevalence of 28% at 3 months, regardless of hospitalisation, though a higher prevalence among admitted patients (32%).[33] In contrast, Godoy et al. observed only 14% of reduced hand-grip strength at 4 months,[34] while Hussain et al. reported a prevalence of 24% among ICU-admitted patients after 1 year.[35] Unlike these studies, our cohort excluded patients with relevant comorbidities. Although we cannot confirm normal hand-grip strength prior to hospitalisation, the observed changes in peripheral muscle strength were likely due to to SARS-CoV-2 infection. In addition, both right and left hand-grip strength were associated with MIP dysfunction in our cohort, suggesting a relationship between peripheral and respiratory muscle function. Whilst the lack of association between MEP and skeletal muscle strength might seem controversial, our findings highlight that peripheral muscle function and RM function are related each other, which is in line with data reporting parallel dysfunction in older healthy individuals.[36] In addition, one previous study showed that both older age and obesity were linked to low muscle quality index - including hand-grip strength as a component - and concomitant reduction of MIP/MEP at 3 months after admission for COVID-19.[37] These data further support the interrelationship between peripheral and respiratory muscle dysfunction in post-COVID.
We also found a mild reduction in DLCO in 57% of patients. This was expected as a potential residual lung damage following extensively acute lung involvement. Our findings are in line with previous studies. A systematic review confirmed that reduced DLCO was the most frequent residual functional abnormality with a prevalence of 39% at 6 months after recovery.[38] One study showed a higher prevalence of DLCO reduction (76.5%) in 30-day follow up,[19] whereas another reported comparable rates to our findings in patients treated with HFNC, NIV or intubation at 6 months. In contrast, a lower prevalence (29%) was found in patients requiring only COT.[31] We also observed that DLCO was reduced in patients showing restrictive pattern on spirometry (17%), in line with literature data.[27] Additionally, MIP/MEP values were globally associated with the lung function parameters (FEV1, FVC, TLC, and DLCO) at follow up. However, the impact of these findings in people without chronic diseases potentially affecting pulmonary function remains poorly understood. Generally, published research in COVID-19 survivors showed that DLCO is the most accurate respiratory functional parameter,[19,27,31,38,39,40] which should be monitored in post-COVID population.
It is worth noting that our study is single-centre. The population included is reflective of the wider post-COVID populations during the first waves of the pandemic [2,41] but might not reflect those of different contexts.
Further limitations of note were that we did not collect imaging data examining extension of lung abnormalities such as chest CT that could explore the relationship with functional data, and real-time diaphragm ultrasound in patients with MIP dysfunction. Nonetheless, excluding patients with pre-existing respiratory/cardiac or neuromuscular diseases helped to better evaluate the impact of the viral pneumonia on RM function, lung function, and dyspnea in absence of potential confounding factors.

5. Conclusions

The study assessed RM strength in COVID-19 survivors and showed that most people had RM dysfunction at follow up. Whilst the direct effect of SARS-CoV-2 on RM needs further research, these findings support the introduction of MIP/MEP measurement as screening for RM dysfunction at post-COVID follow up, regardless of symptoms, and consideration of RM training [42] in patients identified as having moderate to severe dysfunction.[25,43]

Author Contributions

Alessia Verduri: Conceptualisation; Data curation; Methodology; Investigation; Supervision; Writing – original draft; Writing – review and editing. Roberto Tonelli: Formal analysis; Method-ology; Software; Validation; Writing – review and editing. Pierluigi Donatelli: Data curation; Writing – review and editing. Jonathan Hewitt: Methodology; Supervision; Writing – review and editing. Giovanni Guaraldi: Writing – review and editing. Jovana Milić: Writing – review and editing. Valentina Ruggieri: Project administration; Writing – review & editing. Cristina Mussini: Writing – review and editing. Enrico Clini: Methodology; Supervision; Validation; Writing – review and editing. Bianca Beghé: Methodology; Supervision; Writing – review and editing. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Institutional Review Board Statement

Ethical review and approval were waived for this study due to the retrospective anonymised data analysis.

Informed Consent Statement

Not applicable.

Data Availability Statement

The dataset used and analysed during the study is available from the corresponding author on reasonable request and with ethical permission.

Acknowledgements

The Authors thank Ms. Elisabetta Adami for lung function and MIP/MEP measurements.

Conflicts of Interest

The authors declare no conflicts of interest.

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