Associations of dyspnea symptoms with lung function in patients with COVID-19 in the acute period

doi:10.21203/rs.3.rs-3752634/v1

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Associations of dyspnea symptoms with lung function in patients with COVID-19 in the acute period

https://doi.org/10.21203/rs.3.rs-3752634/v1

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Background

Currently, the main prevalent strain of severe acute respiratory syndrome coronavirus 2 (SARS‑CoV‑2) is Omicron, which shows elevated viral load and spread ability, bringing new challenges to pandemic prevention and control.

Objective

To examine the associations of dyspnea symptoms with lung function in coronavirus disease-19 (COVID-19) patients during the acute period.

Methods

This study included COVID-19 cases diagnosed by real-time PCR (RT-PCR). These patients were divided into the dyspnea and non-dyspnea groups based on whether they had dyspnea symptoms at the time of admission.

Results

A total of 29 patients with pulmonary function tests (PFTs) were included in this study. Of all patients, 17.24% (5/29) had severe COVID-19, while the remaining cases were mild or moderate. Lung function was normal, with forced vital capacity (FVC) ≥ 80%, forced expiratory volume in 1 second (FEV1)/FVC ≥ 0.92, and diffusing capacity for carbon monoxide (DLCO) ≥ 80% in 96.55% (28/29), 79.31% (23/29), and 72.41% (21/29) of patients, respectively. Computer tomography (CT) findings were normal in 10.34% (3/29) of patients.

Conclusions

Multivariate analysis showed that lung function and chest CT parameters are not independently associated with dyspnea persistence in acute COVID-19 patients.

COVID-19

lung function

pulmonary function tests (PFTs)

dyspnea

chest CT

Since its outbreak, the infection known as coronavirus disease-19 (COVID-19), whose causative agent is the 2019 novel coronavirus (2019-nCoV) or severe acute respiratory syndrome coronavirus 2 (SARS‑CoV‑2), has expanded quickly to become a pandemic. To date, COVID-19 has affected humans for approximately three years. Currently, COVID-19 is considered a category B infection, with control measures for category A infections switched to category B infection control based on the Law of the People's Republic of China on the Prevention and Treatment of Infectious Diseases, and individuals with COVID-19 are no longer submitted to quarantine restrictions. The World Health Organization (WHO) determined that COVID-19 is no longer a public health emergency of worldwide significance on May 5, 2023^[1].

A typical symptom of COVID-19 infection is dyspnea. Pathological analysis of autopsy specimens from a COVID-19 patient revealed bilateral diffuse alveolar damage with cellular fibromyxoid exudates, interstitial mononuclear inflammatory infiltrates, pneumocyte desquamation, lung edema, and hyaline membrane generation in lung tissue^[2]. These findings suggested acute respiratory distress syndrome in this individual, which resulted in dyspnea and impaired lung function. Pulmonary function is a general term for ventilation of the respiratory system. The diagnosis, differential diagnosis, disease severity assessment, treatment efficacy assessment, and follow-up of respiratory disorders all rely heavily on pulmonary function tests (PFTs)^[3]. Previous studies assessing post-COVID-19 cases reported that the dyspnea symptoms could last 3 to 6 months, and even 2 years after infection in patients with COVID-19, with impaired diffusion ability detected by lung function testing^[4][5][6][7]. Because of the viral nature of the infection, limited research has been performed to assess lung function in acute COVID-19 cases.

The COVID-19 prevalence in China has dramatically increased with the implementation of class B infection control. We discovered an intriguing phenomenon in the clinic, with some COVID-19 patients still experiencing dyspnea, although PFTs show no overt abnormalities involving lung volume, diffusion capacity, ventilation ability, or small airway injury. Moreover, the nucleic acid test was negative, and lung CT imaging showed improvement. Whether this indicates that the development of dyspnea symptoms does not reflect lung function impairment is unknown. To date, most studies that analyze the underlying causes and influencing factors of dyspnea in COVID-19 patients have focused on the recovery process or long-term follow-up. The results showed that COVID-19 patients may develop residual respiratory impairment after hospitalization^[5], with the most important lung function parameter affected being diffusion capacity^[4][6]. In this study, COVID-19 patients following the onset of unblocking management were retrospectively evaluated. Their clinical characteristics, laboratory data, PFT findings and lung imaging features were investigated to determine potential correlations between dyspnea symptoms and lung function in COVID-19 cases in the acute phase.

2.1 Study population

A retrospective analysis of patients hospitalized for the diagnosis of COVID-19 in the First Affiliated Hospital of Zhengzhou University from January 18, 2023, to May 31, 2023, was performed. Inclusion criteria were as follows: (1) diagnosis by reverse transcription polymerase chain reaction (RT‒PCR) assessment of throat swab specimens; (2) chest CT examination within 3 days of admission; (3) PFTs performed after the nucleic acid test turned negative. The exclusion criteria were as follows: (1) basic respiratory diseases; (2) COVID-19 cases classified as critical according to current guidelines^[8]. Acute COVID-19 was defined as 4 weeks after the onset of the first symptoms^[9]. In total, 29 cases were included and assigned to the dyspnea and non-dyspnea groups considering whether they complained of dyspnea at admission (Fig. 1).

2.2 Pulmonary Function Tests

Spirometry, diffusion capacity and lung volume were measured using an Ultima PF™ Pulmonary Function System (Medical Graphics, UK) or an Easy One Pro® (ndd Medical Technologies, Switzerland). The normal ranges of FVC, FEV₁, and DLCO were %predicted ≥ 80%, versus 80%≤%predicted ≤ 120% for TLC and RV^[9][10][11]. FEV₁/FVC %predicted ≥ 92% was normal^[12][13]. The measured values for FVC, FEV₁, FEV₁/FVC, DLCO and DLCO/VA all within the respective normal ranges reflected normal lung function^[14]. If the measured values of some parameters were slightly beyond the normal ranges, basic normal lung function was considered.

Lung function data were interpreted according to Chinese experts’ consensus on the standardization of adult lung function diagnosis^[15]: FEV₁/FVC %predicted < 92% (obstructive pattern) or FVC %predicted < 80% (restrictive pattern), ventilation dysfunction; DLCO %predicted or DLCO/VA %predicted < 80%, diffuse dysfunction; at least two of FEF_{25% −75%}, FEF₅₀ and FEF₇₅ decreased to less than 80% of the respective normal predicted values, small airway dysfunction.

2.3 CT Imaging

All chest CT scans were carried out on a SOMATOM Definition Flash (Siemens Healthineers, Germany) or IQon Spectral CT (Philips Healthcare) with the following parameters: tube voltage, 120 kV; tube current, 200–600 mA; iterative reconstruction; rotation time, 0.5 s; section thickness, 5 mm; pitch, 1.0; and matrix, 512×512. In this study, two chest radiologists (blinded to clinical data) independently reviewed the obtained CT images and resolved differences through consensual discussion, including the range of lesions in each lobe and the type of lesions, and provided scores according to the following scoring methods and standards.

2.3.1 Scoring method and step range scoring: The compromised lung volume was quantified using the InferRead CT Lung system (InferVision, Beijing, China). The system can automatically identify and segment inflammatory lesions in the lung lobe and determine the number of affected lung lobes and the degree of lung involvement (Fig. 2-E). The accuracy of the automatically segmented lesions was reviewed by the above two radiologists, and chest images were scored by the visual severity score (VSS) method^[16] based on quantitative parameters collected on the InferRead CT Lung system. The whole lung was divided into 5 regions according to the anatomy of the lobe: (1) 0, normal lung tissue; (2) 1, lesions accounting for 1–25%; (3) 2, lesions accounting for 25–50%; (4) 3, lesions accounting for 50–75%; (5) 4, lesions accounting for 75–100%.

2.3.2 Scoring method and lesion type score: Two radiologists independently interpreted chest CT images, collected CT signs and CT semi-quantitative visual scores, and differences were resolved by consensual discussion. The CT findings were described with the international standard terminology defined by the Fleischner Society Glossary and previous studies of viral pneumonia^{[17][18][19][20]}. The description terms included ground-glass opacity (GGO), consolidation, pulmonary fibrosis and reticulation. Scores were as follows: 0, no abnormal density in the lung; 1, GGO (Fig. 2-A); 2, consolidation (Fig. 2-B); 3, pulmonary fibrosis (Fig. 2-C); 4, reticulation (Fig. 2-D).

2.3.3 Comprehensive score: This score was defined as the lung region range score × lesion type score. The comprehensive score of the right lung was (composite score of right upper lung + composite score of right middle lung + composite score of right lower lung)/3; that of the left lung was (left upper lung comprehensive score + left lower lung comprehensive score)/2. The whole lung’s composite score was right lung composite score + left lung composite score.

2.4 Statistical analysis

Count data are presented as n (%). Normally distributed continuous variables are presented as the mean ± SD, and those with skewed distributions are presented as interquartile ranges (IQRs, medians (P₂₅, P₇₅)). The independent t test, Fisher’s exact test and chi-square test were carried out where appropriate for the comparison of the dyspnea and non-dyspnea groups. A multivariate logistic regression model was employed to determine risk factors for dyspnea. Statistical analyses utilized SPSS 25.0 (SPSS, USA). P < 0.05 was considered to indicate statistical significance.

3.1 Clinical characteristics A total of 29 subjects, including 16 (55.17%) females and 13 (44.83%) males, were included in the study, of whom 72.41% (21/29) had never smoked. On admission, 20 patients had basic diseases, of which the top three were hypertension (8/29), coronary heart disease (6/29), cerebrovascular disease and diabetes (5/29). The participants were aged 64.69 ± 13.34 years (32 to 86 years). The length of hospitalization in the 29 patients was 7.83 ± 3.43 days. For disease severity, there were 3 (10.34%) mild, 26 (89.66%) moderate and 5 (17.24%) severe cases. The dyspnea group had increased age and longer hospital stay in comparison with the non-dyspnea group, although the differences were not statistically significant (both P > 0.05). The sex distribution and disease severity were similar in both groups (P > 0.05). The clinicodemographic features are shown in Table 1.

Table 1

Baseline patient characteristics
Characteristic	Total(n = 29)	Dyspnea	Non-dyspnea	P-Value
Age, mean ± SD	64.69 ± 13.34	66.05 ± 13.94	60.43 ± 11.06	0.34
Male/Female, n (%)	13(44.83)/16༈55.17༉	10(34.48)/12(41.38)	3(10.34)/4(13.79)	1.00
BMI, mean ± SD	24.97 ± 3.55	24.83 ± 3.51	25.39 ± 3.95	0.72
Alcohol, n (%)	8(27.59)	5(17.24)	3(10.34)	0.36
Smoking, n (%)	8(27.59)	5(17.24)	3(10.34)	0.36
Underlying disease, n (%)
Hypertension	8(27.59)	7(24.14)	1(3.45)	0.64
Diabetes	5(17.24)	5(17.24)	0	0.30
Cardiovascular disease	6(20.69)	5(17.24)	1(3.45)	1.00
Cerebrovascular disease	5(17.24)	4(13.79)	1(3.45)	1.00
Liver disease	1(3.45)	1(3.45)	0	1.00
Kidney disease	1(3.45)	1(3.45)	0	1.00
None	9(31.03)
Disease severity, n (%)
Mild	3(10.34)	2(6.90)	1(3.45)	0.39
Moderate	26(89.66)	15(51.72)	6(20.69)
Severe	5(17.24)	5(17.24)	0
Hospitalization (day), mean ± SD	7.83 ± 3.43	8.14 ± 3.83	6.86 ± 1.46	0.40

3.2 Laboratory indicators On admission, WBC counts were 7.20 ± 3.70, with 6 and 7 cases showing levels lower and higher than normal, respectively. The mean lymphocyte count (Lym) was 0.91 (0.69, 1.33), with 9 cases showing values lower than normal. C-reactive protein (CRP) levels were elevated in the dyspnea group compared with the non-dyspnea group, while procalcitonin (PCT) levels were lower, and the differences were not statistically significant (P > 0.05) (Table 2).

Table 2

Laboratory findings for hospitalized patients with COVID-19
Laboratory index		Dyspnoea	Non-dyspnoea	P-Value
WBC, mean ± SD	7.20 ± 3.70	7.02 ± 3.35	7.78 ± 4.90	0.64
Lymphocyte, IQR	0.91(0.69,1.33)	0.92(0.70, 1.39)	0.81(0.60, 1.15)	0.60
Eosinophil count, IQR	0.02(0.01,0.05)	0.02(0.01, 0.043)	0.01(0.01, 0.10)	0.98
PCT(ug/L), IQR	0.074(0.044,0.141)	0.063(0.043, 0.147)	0.094(0.058, 0.146)	0.33
CRP(mg/L), IQR	20.21(2.74, 65.99)	17.62(2.46, 52.43)	53.00(8.49, 115.89)	0.20
Pulmonary function tests (PFTs), mean ± SD
Spirometry
FVC %predicted	99.93 ± 13.64	99.53 ± 15.10	101.19 ± 8.21	0.79
FVC %predicted＜80%, n(%)	1 (3.45)	1 (3.45)	0	1.00
FEV₁%predicted	98.20 ± 14.68	98.40 ± 16.28	97.59 ± 8.86	0.90
FEV₁/FVC %predicted	97.22 ± 7.42	97.57 ± 7.22	96.13 ± 8.52	0.66
FEV₁/FVC %predicted＜92%, n(%)	6 (20.69)	4 (13.79)	2 (6.90)	0.61
TLC %predicted	90.40 ± 10.50	88.61 ± 10.06	96.03 ± 10.57	0.11
RV %predicted	85.74 ± 16.96	83.37 ± 14.79	93.19 ± 22.16	0.19
Diffusion capacity
DLCO %predicted	84.89 ± 13.24	84.45 ± 14.31	86.27 ± 9.93	0.76
DLCO %predicted＜80%, n(%)	9 (31.03)	8 (27.59)	1 (3.45)	0.38
DLCO/VA %predicted	99.47 ± 14.12	100.67 ± 13.04	95.67 ± 17.68	0.42
DLCO/VA %predicted＜80%, n(%)	2 (6.90)	1 (3.45)	1 (3.45)	0.43
Small airway functions
FEF₅₀%predicted	84.00 ± 29.79	82.32 ± 27.39	89.27 ± 38.37	0.60
FEF₇₅%predicted	82.38 ± 29.54	80.50 ± 28.14	88.29 ± 35.31	0.55
FEF_{25 − 75}%predicted, IQR	73.30 (62.65, 78.30)	74.70(63.13, 78.90)	67.60(59.40, 74.30)	0.47
Pulmonary dysfunction, n (%)
Ventilation dysfunction	7(24.14)	5 (17.24)	2 (6.90)	1.00
Diffuse dysfunction	9(31.03)	8 (27.59)	1 (3.45)	0.38
Small airway dysfunction	21(72.41)	16 (55.17)	5 (17.24)	1.00
Basically normal, n (%)	7(24.14)

3.3 Pulmonary function Overall, 29 patients had normal lung function, with FVC %predicted of 99.93 ± 13.64 (> 80%), FEV₁%predicted of 98.20 ± 14.68 (> 80%), FEV₁/FVC %predicted of 97.22 ± 7.42 (> 92%), DLCO %predicted of 84.89 ± 13.24 (> 80%) and DLCO/VA %predicted of 99.47 ± 14.12 (> 80%). The patients with pulmonary dysfunction included 7 (24.14%) with ventilation dysfunction, 9 (31.03%) with diffuse dysfunction and 21 (72.41%) with small airway dysfunction cases. There were more patients with pulmonary dysfunction in the dyspnea group, but statistical significance was not reached (P > 0.05). Table 2

3.4 Lung CT findings Three patients showed no pneumonia on chest CT at admission. Meanwhile, 17 (58.62%) had GGO (with no consolidation), 3 (10.34%) had consolidation or consolidation combined with GGO, and 6 (20.39%) showed the main CT signs of fibrosis and reticulation. The mean lung CT visual score was higher in the dyspnea group versus the non-dyspnea group, with 2.17 (0.88, 3.21) vs 1.17 (0.33, 2.00) (Table 3). Of the 18 patients who underwent lung CT examination before discharge, 6 had significant absorption of shadows (Fig. 3).

Table 3

Radiographic findings on thin-section CT scans of 29 patients with COVID-19 at admission
Lesions	Dyspnea (n)	Non-dyspnea (n)	P-Value
No abnormal density shadow	2	1	0.19
GGO	10	6
Consolidation	3	0
Fibrosis or reticulation	7	0
Visual score(IQR)	2.17(0.88, 3.33)	1.17(0.33, 2.00)	0.06

Figure 3 Totally 14 of 18 patients (11 with no CT scans before leaving the hospital) showed improvement in pulmonary CT.

3.5 Dyspnea versus non-dyspnea analysis Age, sex, BMI, WBC, lymphocyte count, PCT, and CRP were similar in the dyspnea (experimental) and non-dyspnea (control) groups (all P > 0.05). Lung function and CT vision scores were also comparable in both groups (both P > 0.05) (Fig. 4).

With the continuous understanding of COVID-19, it has been determined that many patients infected with the novel coronavirus have different degrees of symptoms in different disease periods. A meta-analysis^[21] showed that dyspnea, chest pain and cough are the most common respiratory symptoms after COVID-19 infection, with 22.9–53.0% of patients still having dyspnea 2 months after infection^[22]. In this study, a retrospective analysis was conducted of individuals who had negative nucleic acid conversion and even reached the criteria for clinical recovery, comprehensively assessing general clinical data, lung function indexes and lung CT images.

In terms of clinical baseline data, age was slightly higher in the dyspnea cases versus the non-dyspnea group, but statistical significance was not achieved (P > 0.05), indicating that age is not a risk factor for dyspnea persistence. In addition, there were no significant differences in hospitalization duration or disease severity between the dyspnea and non-dyspnea groups. In contrast, Yin X et al.^[23] found that the longer the hospital stay and the more severe the clinical classification, the higher the risk of dyspnea. This discrepancy may be explained by the distinct evaluation times. The patients selected by YIN et al. were infected by the Delta variant that was epidemic in 2020, while the patients included in the present study were infected by the variant strain Omicron that has been prevalent since December 2022. In terms of laboratory findings, the biomarkers of COVID-19 include CRP, LYM and NLR^[24][25]. These indicators can be used as predictors of prognosis in critically ill patients^[26]. In this study, CRP, PCT and WBC were slightly reduced in dyspnea cases versus the non-dyspnea group, but the differences were not statistically significant (all P > 0.05).

A meta-analysis^[27] showed altered diffusion capacity, restrictive pattern and obstructive pattern in 39%, 15% and 7% of COVID-19 cases post-infection, respectively, corroborating previous findings^[28][29][30]. In this study, altered diffusion capacity, ventilation dysfunction and small airway dysfunction at discharge were found in 31,03%, 24.14% and 72.41% of patients, respectively, and showed no statistically significant differences between the two groups. Relevant imaging studies have found that some patients have imaging abnormalities at 3 months after infection accompanied by abnormal lung function. As an important examination tool for lung diseases, CT accurately reveals the nature and scope of lung lesions, with a critical role in severity and treatment efficacy evaluations in COVID-19 patients^[20]. In this study, the VVS method and CT quantitative parameter score were combined to analyze lung CT scans. As shown above, the main CT sign in COVID-19 infected patients was GGO, which was consistent with previous studies^[31][32]. Most patients still showed residual disease in the lungs on CT images after they were discharged from the hospital. Studies have shown that the absorption of lesions mainly occurs after discharge and is more obvious in the first 3 months^[33].

A long-term follow-up study^[34] found that quantitative CT parameters related to lesion volume are highly accurate in predicting persistent dyspnea in discharged COVID-19 cases, with survivors developing dyspnea showing enhanced reticulation, which might be the factor causing dyspnea. Guinto E et al.^[35] suggested that the prevalence of imaging abnormalities is related to the proportion of patients with dyspnea. Cortés-Telles A et al.^[36] suggested that individuals with persistent dyspnea have an elevated number of abnormalities in comparison with well-matched non-dyspnea cases, including enhanced restriction on spirometry, decreased DLCO and suppressed functional capacity. The present study found no factors that affect dyspnea recovery in patients, among the examined laboratory indexes, lung function or lung CT signs and visual scores. In addition to temporal and spatial differences, we believe that the following factors can also explain the inconsistency between this study and previous reports. On the one hand, as the Omicron strain continues to mutate, its virulence also changes. In addition, milder symptoms are detected after infection by Omicron compared with previous strains. Shuai et al.^[37], Trunfio et al.^[38] reported that compared with the WT variant, Omicron variants are less pathogenic, have lower replication efficiency in vivo, and induce relatively lower levels of cell damage in infected cells. The cases examined in this study were all diagnosed after 2022, when Omicron was considered a variant of concern by the WHO^[39]. On the other hand, patients became ill after widespread vaccination, which is a key strategy to prevent broad viral infection and reduce morbidity and mortality. Furthermore, we consider that the persistence of dyspnea symptoms is related to mental factors; in other words, some dyspnea symptoms in these cases may be due to anxiety. Previous studies have shown that COVID-19 has increased the incidence of severe depression worldwide by 27.6%^[40]. Although the toxicity of mutant strains has decreased for most individuals, COVID-19 remains a major public health issue. Current evidence indicates that breathing difficulties are a multidimensional subjective feeling; difficulty in breathing generally results in a state of fear, anxiety, etc., in patients^[41].

This study had some limitations. First of all, due to the lack of baseline PFT data, it was impossible to compare pre-disease PFT data with post-disease values. Secondly, all cases in this study were Chinese individuals from a single institution; additionally, the sample size was small, and we did not classify cases according to disease severity and the number of vaccinations, indicating potential selection bias. Finally, this study only analyzed a short disease course from hospitalization to discharge, and the long-term dynamic changes of lung function still need further investigation.

In summary, the above findings suggest that in the third year of the COVID-19 pandemic, the emergence of dyspnea symptoms with COVID-19 infection in the acute phase and pulmonary impairment are not associated. Dyspnea is considered to be caused by viral mutations. Discharge does not mean the end of the disease course, and the disease status of many COVID-19 cases may continue for a long time after discharge^[42], especially the impaired respiratory function, which is often accompanied by dyspnea^[43]. Therefore, it is of great clinical significance to identify factors and mechanisms associated with COVID-19 sequelae. In future studies, regular follow-up of patients is needed to comprehensively determine the changes in the condition, allowing patients to recover as soon as possible and achieve the goal of recovery.

Ethics declarations

Ethics approval and consent to participate

This study was approved by the Ethics Committee of the First Affiliated Hospital of Zhengzhou University (approval number 2020-KY-0928-005). Written informed consent was obtained from the patients.

Consent for publication

Not applicable.

Funding

No funding.

Availability of data and materials

The data used to support the findings of this study are available from the corresponding author upon request.

Author Contribution

LW and LZ: Conceptualization, Methodology, Writing – original draft，MZ and NL: Formal Analysis, Investigation, Writing – original draft, LC: Investigation, Writing – review & editing, ZL and PW: Methodology, Writing – review & editing. All authors reviewed the manuscript.

Burki, T. 2023. WHO ends the COVID-19 public health emergency. The Lancet. Respiratory Medicine, 11(7): 588.
Z. Xu, L. Shi, Y. Wang et al., Pathological findings of COVID-19 associated with acute respiratory distress syndrome, The Lancet Respiratory Medicine, vol. 8, no. 4, pp. 420–422, 2020.
Chinse Medical Association, Chinese Medical Journals Publishing House, Chinese Society of General Practice, Pulmonary Function Group of Chinese Thoracic Society, Editorial Board of Chinese Journal of General Practitioners of Chinese Medical Association, Expert Group of Guidelines for Primary Care of Respiratory System Disease. Guideline for pulmonary function tests (PFTs) in primary care (2018). [J]. Chin J Gen Pract, 2019,18(6): 511-518. doi: 10.3760/cma.j.issn.1671-7368.2019.06.003
Torres-Castro R, Vasconcello-Castillo L, Alsina-Restoy X, et al. Respiratory function in patients post-infection by COVID-19: a systematic review and meta-analysis. Pulmonology. 2021;27(4):328-337. doi:10.1016/j.pulmoe.2020.10.013
Lombardi F, Calabrese A, Iovene B, et al. Residual respiratory impairment after COVID-19 pneumonia. BMC Pulm Med. 2021;21(1):241.
Blanco JR, Cobos-Ceballos MJ, Navarro F, et al. Pulmonary long-term consequences of COVID-19 infections after hospital discharge. Clin Microbiol Infect. 2021;27(6):892-896. doi:10.1016/j.cmi.2021.02.019
Yang X, Hou C, Shen Y, et al. Two-Year Health Outcomes in Hospitalized COVID-19 Survivors in China. JAMA Netw Open. 2022;5(9):e2231790. Published 2022 Sep 1. doi:10.1001/jamanetworkopen.2022.31790
National Health Commission of the People's Republic of China. Diagnosis and Treatment Protocol for Novel Coronavirus Infection (Trial Version 10)[EB/OL]. 2023;
Nalbandian A, Sehgal K, Gupta A, et al. Post-acute COVID-19 syndrome. Nat Med. 2021;27(4):601-615. doi:10.1038/s41591-021-01283-z
Zhu L. Clincal Pulmonary Function. [M]. Version 2. Bei Jing: People’s Medical Publishing House. 2014
Pulmonary Function Group of Chinese Thoracic Society. Lung Function Inspection Guide (Part II) - Lung Quantitative Examination[J]. Chinese Journal of Tuberculosis and Respiratory Diseases. 2014; 37(7):481-486. DOI: 10.3760/cma.j.issn.1001-0939.2014.07.001.
Zhu L. Disputes and responses to lung function diagnosis. [J]. Chin J Tuberc Respir Dis, 2015,38(6): 405-407. DOI: 10.3760/cma.j.issn.1001-0939.2015.06.003
Pulmonary Function Group of Chinese Thoracic Society. Lung Function Inspection Guide-Lung Capacity Test. [J]. Chinese Journal of Tuberculosis and Respiratory Diseases. 2015; 38(4): 255-260. DOI:10.3760/cma.j.issn.1001-0939.2015.04.005
Kociánová J. Spirometrie - základní vyšetření funkce plic [Spirometry - basic examination of the lung function]. Vnitr Lek. 2018;63(11):889-894.
Zhu L, Chen RC. Chinese experts’ consensus on the standardization of adult lung function diagnosis. Journal of Clinical Pulmonary Medicine. 2022,27(7):973-981. DOI:10.3969/j.issn.1009-6663.2022.07.001.
Bernheim A, Mei X, Huang M, et al. Chest CT findings in coronavirus disease－19 (COVID－19): relationship to duration of infection[J]. Radiology, 2020, 295:200463. DOI:10.1148/radiol.2020200463
FRANQUET T. Imaging of pulmonary viral pneumonia[J]. Radiology, 2011, 260 (1): 18-39.
KOO H J, LIM S, CHOE J, et al. Radiographic and CT Features of Viral Pneumonia[J]. Radiographics, 2018, 38 (3): 719-739.
HANSELL D M, BANKIER A A, MACMAHON H, et al. Fleischner Society: glossary of terms for thoracic imaging[J]. Radiology, 2008, 246 (3): 697-722.
AKL E A, BLAZIC I, YAACOUB S, et al. Use of Chest Imaging in the Diagnosis and Management of COVID-19: A WHO Rapid Advice Guide[J]. Radiology, 2021, 298 (2): E63-E69.
CARES-MARAMBIO K, MONTENEGRO-JIMéNEZ Y, TORRES-CASTRO R, et al. Prevalence of potential respiratory symptoms in survivors of hospital admission after coronavirus disease 2019 (COVID-19): a systematic review and meta-analysis［J］.Chron Respir Dis, 2021, 18: 14799731211002240.
CARFì A, BERNABEI R, LANDI F. Persistent symptoms in patients after acute COVID-19［J］. Jama, 2020, 324(6): 603-605.
Yin X, Xi X, Min X, et al. Long-term chest CT follow-up in COVID-19 Survivors: 102-361 days after onset [published correction appears in Ann Transl Med. 2022 May;10(9):532]. Ann Transl Med. 2021;9(15):1231. doi:10.21037/atm-21-1438.
Battaglini D, Lopes-Pacheco M, Castro-Faria-Neto HC, Pelosi P, Rocco PRM. Laboratory Biomarkers for Diagnosis and Prognosis in COVID-19. Front Immunol. 2022;13:857573. doi:10.3389/fimmu.2022.857573.
Karimi A, Shobeiri P, Kulasinghe A, Rezaei N. Novel Systemic Inflammation Markers to Predict COVID-19 Prognosis. Front Immunol. 2021;12:741061. doi:10.3389/fimmu.2021.741061.
CHE Xiao, WANG Lexiao, ZHAO Lei, HUANG Rui, XU Zhe, WANG Fusheng. Clinical characteristics and prognostic factors of severe COVID-19[J]. ACADEMIC JOURNAL OF CHINESE PLA MEDICAL SCHOOL, 2023, 44(2): 101-107. doi: 10.3969/j.issn.2095-5227.2023.02.001
Torres-Castro R, Vasconcello-Castillo L, Alsina-Restoy X, et al. Respiratory function in patients post-infection by COVID-19: a systematic review and meta-analysis. Pulmonology. 2021;27(4):328-337. doi:10.1016/j.pulmoe.2020.10.013
Mo X, Jian W, Su Z, Chen M, Peng H, Peng P, et al. Abnormal pulmonary function in COVID-19 patients at time of hospital discharge. Eur Respir J. 2020;55:2001217.
Frija-Masson J, Debray MP, Gilbert M, Lescure FX, Travert F, Borie R, et al. Functional characteristics of patients with SARSCoV-2 pneumonia at 30 days post infection. Eur Respir J. 2020:2001754.
Huang Y, Tan C, Wu J, Chen M, Wang Z, Luo L, et al. Impact of coronavirus disease 2019 on pulmonary function in early convalescence phase. Respir Res. 2020;21:163.
Y. Wang, C. Dong, Y. Hu, C. Li, Q. Ren, X. Zhang, H. Shi, M. Zhou, Temporal changes of CT findings in 90 patients with COVID-19 pneumonia: a longitudinal study, Radiology, 296 (2) (2020) E55–E64.
F. Pan, T. Ye, P. Sun, S. Gui, B. Liang, L. Li, D. Zheng, J. Wang, R.L. Hesketh, L. Yang, C. Zheng, Time course of lung changes at chest CT during recovery from coronavirus disease 2019 (COVID-19), Radiology, 295 (3) (2020) 715–721.
LIU M, LV F, HUANG Y, et al. Follow-Up Study of the Chest CT Characteristics of COVID-19 Survivors Seven Months After Recovery[J]. Frontiers in Medicine, 2021, 8 (2296-858X (Print)): 636298.
YIN X, MIN X, NAN Y, et al. Assessment of the Severity of Coronavirus Disease: Quantitative Computed Tomography Parameters versus Semiquantitative Visual Score[J]. Korean Journal of Radiology, 2020, 21 (8): 998-1006.
Guinto E, Gerayeli FV, Eddy RL, Lee H, Milne S, Sin DD. Post-COVID-19 dyspnoea and pulmonary imaging: a systematic review and meta-analysis. Eur Respir Rev. 2023;32(169):220253. doi:10.1183/16000617.0253-2022
Cortés-Telles A, López-Romero S, Figueroa-Hurtado E, et al. Pulmonary function and functional capacity in COVID-19 survivors with persistent dyspnoea. Respir Physiol Neurobiol. 2021;288:103644. doi:10.1016/j.resp.2021.103644
Shuai H, Chan JF, Hu B, et al. Attenuated replication and pathogenicity of SARS-CoV-2 B.1.1.529 Omicron. Nature. 2022;603(7902):693-699. doi:10.1038/s41586-022-04442-5
Trunfio M, Portesani F, Vicinanza S, et al. Real-life Evidence of Lower Lung Virulence in COVID-19 Inpatients Infected with SARS-CoV-2 Omicron Variant Compared to Wild-Type and Delta SARS-CoV-2 Pneumonia. Lung. 2022;200(5):573-577. doi:10.1007/s00408-022-00566-7.
World Health Organization. Classifi cation of Omicron (Ｂ.1.1.529):SARS-CoV-2 variant of concern[OL]. (2021-11-26)[2022-02-10].
Santomauro D F, Mantilla Herrera A M, Shadid J, et al. Global prevalence and burden of depressive and anxiety disorders in 204 countries and territories in 2020 due to the COVID-19 pandemic[J]. The Lancet,2021,398(10312):1700-1712.
Ibrahim AA, Akindele MO, Kaka B, Bello B. Translation, cross-cultural adaptation, and psychometric properties of the Hausa version of the Fear-Avoidance Beliefs Questionnaire in patients with low back pain. Scand J Pain. 2019;19(1):83-92. doi:10.1515/sjpain-2018-0303
SHAW B, DASKAREH M, GHOLAMREZANEZHAD A. The lingering manifestations of COVID-19 during and after convalescence: update on long-term pulmonary consequences of coronavirus disease 2019 (COVID-19)[J]. Radiologia Medica, 2021, 126 (1): 40-46.
YU M, LIU Y, XU D, et al. Prediction of the Development of Pulmonary Fibrosis Using Serial Thin-Section CT and Clinical Features in Patients Discharged after Treatment for COVID-19 Pneumonia[J]. Korean Journal of Radiology, 2020, 21 (6): 746-755.

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Associations of dyspnea symptoms with lung function in patients with COVID-19 in the acute period

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Abstract

Background

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Methods

Results

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1. Introduction

2. Methods

2.1 Study population

2.2 Pulmonary Function Tests

2.3 CT Imaging

2.4 Statistical analysis

3. Results

4. Discussion

Conclusions

Declarations

References

Additional Declarations

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