The long-term effect of COVID-19 infection on lung volumes and respiratory indices among hospitalized patients up to one year after discharging from hospital: a population- based cohort study

The long-term effect of COVID-19 infection on lung volumes and respiratory indices among hospitalized patients up to one year after discharging from hospital: a population- based cohort study | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article The long-term effect of COVID-19 infection on lung volumes and respiratory indices among hospitalized patients up to one year after discharging from hospital: a population- based cohort study Reza vazirinejad, Hassan Ahmadinia, Mohsen Rezaeian, Marziyeh Nazari, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-3908644/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background and purpose As the number of COVID-19 survivors increased, countless people have been affected by the pulmonary consequences of this infection. They are likely to suffer permanent lung damage and long-term pulmonary dysfunction ( 15 ). The present study aimed at investigating the long-term term effect of COVID-19 infection on lung volumes and respiratory indices among hospitalized patients up to one year after discharge from the hospital conducting a population-based cohort study. Materials and Methods This population-based cohort study was conducted by inviting patients with COVID-19 admitted to Afzalipour Hospital in Kerman (a reference hospital during the pandemic in Kerman province, Iran) during September, October, and November 2022, to the present survey. Respondents who agreed to help with the survey were followed for one year, and they were examined in terms of respiratory outcomes on two occasions at eight months and one year after discharge from the hospital. A spirometry test was also performed for the satisfied patients. Demographic information and hospitalization time information were extracted from their hospital records. Data were analyzed using SPSS and R software. Results Out of 1954 hospitalized patients, 500 patients accepted the study invitation. In terms of disease severity, 61 patients (12.2%) were classified as suffering from severe disease and 439 patients (87.8%) were classified as moderate. Cough and shortness of breath during activity were common symptoms that were observed in the first follow-up, although these symptoms were more common in patients with severe disease than in patients with moderate disease (P = 0.012 and P = 0.023, respectively). Despite decreasing patients' breathing problems during the first follow-up, a significant percentage of patients were, still, suffering from these problems 12 months after discharge from the hospital. Among the patients who performed spirometry, 54.9% had low lung volume, 10.8% were classified as obstructive lung patients, and 44.1% were reported as restrictive lung patients. Conclusion COVID-19 causes long-term complications in the lungs that continue for at least one year after the infection. Our results showed that Obstructive complications are more frequent than limiting complications. COVID-19 Respiratory Function Tests Cohort Studies Figures Figure 1 Introduction On March 11, 2020, the World Health Organization declared the Coronavirus as a pandemic ( 1 ) until October 2023, the number of people infected with the Coronavirus in the world has exceeded 696 million people and the number of deaths has exceeded 6,924,281. This disease in Iran has left more than seven million patients and 146 thousand dead ( 2 ). Acute respiratory syndrome of the coronavirus 2 (SARS-CoV-2) causes acute viral respiratory infections, including pneumonia. After the initial infection with SARS-CoV-2 in the upper respiratory tract, the virus continues to multiply in the lower airways and alveolar epithelial cells ( 3 ). Usually, coronaviruses cause an infection in the respiratory ciliated mucus in the throat and nose area, which causes symptoms similar to the common cold. Sometimes, these viruses may cause more serious complications such as exacerbation of asthma, and lung infection (pneumonia) in adults, the elderly, and people with weak immune systems ( 4 ). In a study conducted in China in 2020, approximately 20% of patients with infection require hospitalization and 6% in the intensive care unit requires intensive care and invasive ventilator support. Epidemiological reports showed that 8.2% of all cases had rapid and progressive respiratory failure, similar to acute respiratory distress syndrome (ARDS) ( 3 ). Studies reported that patients may have persistent respiratory disorders for months or even years after discharge ( 7 , 10 , 11 , 15 ), as well as other coronaviruses, have also caused long-term effects, especially in the lungs. 6). Currently, a new topic for research is the investigation of pulmonary function in the survivors of Covid-19( 4 , 8 ). In the initial stage of the COVID-19 pandemic, national and international health authorities refused to perform routine pulmonary function tests ( 10 ). However, after passing the peak of the epidemic, the need to use specialized measures reappeared ( 12 , 13 ). Therefore, most of the national and international scientific institutions modified their initial recommendations and re-introduced pulmonary function tests (PFTs) in routine clinical practice ( 14 ). investigated the distribution of lung volume ( 9 ). According to what was said, since the detection of pulmonary function changes is necessary for the diagnosis and follow-up of patients with respiratory and functional complications caused by COVID-19, we decided to measure the respiratory function of hospitalized patients during the next months. These results help specialist doctors to make decisions about how to change their approach during outpatient visits, considering appropriate measures including respiratory rehabilitation if needed and other necessary plans ( 14 , 16 ). The purpose of this study is to evaluate lung volumes in hospitalized patients with COVID-19, up to one year after discharge from the hospital. Materials and Methods The present research is a population-based cohort study that is prospectively conducted on the survivors of COVID-19 who were discharged from Afzalipur Hospital in Kerman during August, September, and October 2021, after approval by the Research Council of Rafsanjan University of Medical Sciences. The ethics approval was obtained from the University Ethics Committee (the number IR.RUMS.REC.1401.065). Inclusion criteria include ( 1 ) age ≥ 18 years ( 2 ) SARS-CoV-2 infection confirmed by PCR ( 3 ) hospitalization due to COVID-19, Exclusion criteria include having a history of lung diseases such as asthma or lung cancer, a history of lung resection, psychotic disorder, dementia or osteoarthropathy or immobility, unwillingness to continue participating in the study, living in a nursing home or welfare, and death of the patient. The patients who were hospitalized from August to October were invited to help with the study by phone. Respondents were informed about the study objectives and important details were presented to them. Those patients who were willing to participate were requested to fill out and sign the consent form. Respondents were assured that all their information would be kept confidential. These patients were prospectively followed up in one year and their pulmonary function was measured on two occasions in eight months and one year. At the beginning of the data collection process, the demographic information of patients such as age, sex, occupation, and place of residence, as well as the clinical information such as the time of hospitalization, blood oxygen saturation, hospitalization in the ward or ICU, history of smoking and opium use, comorbidities such as hypertension, diabetes, and chronic kidney disease, taking medication such as Remdesivir, use of mechanical ventilation and its duration were obtained retrospectively from their hospital records. According to this information, the patients were divided into two groups of moderate and severe disease severity. The criteria for entering the moderate group were: 1- Presence of respiratory symptoms (including shortness of breath, feeling of pain and pressure in the chest) with or without fever, equal to/more than 38 degrees Celsius 2- Spo2 from 90 to 93, pain and the criteria for entering the severe group were: 1- Rapid progression of respiratory symptoms, especially worsening of shortness of breath, 2- Tachypnea RR > 30), 3- Spo2 less than 90% and pao2/fio2 less than 300 mmHg, 4- Increase in A-a gradient and also increase in involvement more than 50% of the lung in CT scan. In each follow-up, respondents were called by phone, and for those who agreed, the spirometry tests were performed by the experienced staff at the lung specialist's office. Tests of forced vital capacity (FVC), forced expiratory capacity in the first second of exhalation (FEV1), and FEV1/FVC. Also, in each visit, the height and weight of patients were measured to calculate BMI. Oxygen level Blood saturation was also measured for these patients by pulse oximetry device. Other respiratory outcomes such as cough, dyspnea, Exertional dyspnea, chest pain, Exertional dyspnea chest pain, and hemoptysis were also measured. The data were recorded on a researcher-made questionnaire. Furthermore, patients who did not decide to do the spirometry test were asked over the phone about other respiratory outcomes. Finally, after cleaning the collected data and controlling the data by the lung specialist, the data were transferred to SPSS version 26 software and analyzed. Statistical tables and graphs were used for descriptive data reporting, qualitative data was reported as numbers and percentages, and quantitative data was reported as mean and standard deviation. Continuous variables were compared with Student's t-test and categorical variables with χ2. Using McNemar's test, the general respiratory status of patients was examined and compared at 8 and 12 months after discharge. The significance level in all tests was considered equal to 0.05. Lung function tests (Pulmonary function testing) were used to measure lung function, and spirometry, which can be used to measure air flow rate and all lung volumes except FRC-RV, and TLC, was performed ( 17 ). Results During August, September, and October 2021, 1954 patients were admitted to Afzalipour Hospital in Kerman due to COVID-19, 327 patients died in the hospital and 1627 patients were discharged, 1553 patients were over 18 years of age, 1502 were Iranian and 51 Afghan patients were over 18 years old, 783 male patients and 770 female patients. After making phone calls with 1116 discharged patients over 18 years old and explaining the conditions of the study, 500 people agreed to participate in our study. 118 people in the first follow-up and 102 people in the second follow-up did the spirometry test. (Figure No. 1) 223 (44.6%), and 277 (55.4%) patients were male and female respectively. The average age of patients was 52.06 ± 16 years, although patients with severe disease were older than patients with moderate disease severity. (59.8 to 50.98 years) (P < 0.001). Most of the Iranian patients (97.8%) were married (80.6%) and literate (85.8%). The average body mass index of the patients was 26.71 ± 4, that were in the overweight group. The largest group of patients were housewives (47.2 percent). The highest percentage of patients' insurance was related to social security insurance (52.4 percent) (Table No. 1). Table 1 Basic information on hospitalized patients with COVID-19 Variable Variable levels n = 500 Number percent Gender Male 223 44.6 Female 277 55.4 Marital status Single 33 6.6 Married 403 80.6 Widowed 51 10.2 Divorced 13 2.6 education level Illiterate 71 14.2 High school 173 34.6 Diploma 159 31.8 Associate Degree 24 4.8 Bachelor's degree 59 11.8 Master’s degree and higher 14 2.8 Nationality Iranian 489 97.8 Afghan 11 2.2 Job Housewife 236 47.2 Employee 38 7.6 Free 95 19 Student 8 1.6 Retired 58 11.6 Other 65 13 Insurance social security 262 52.4 Health 188 37.6 Armed Forces 10 2 Other layers 28 5.6 does not have insurance 12 2.4 According to Table 2 The proportion of smokers in the severe group who were hospitalized in the ICU (22.9%) was significantly higher than that in the moderate group (10.2%, P = 0.004). The most common comorbidities among respondents was high blood pressure (36.2%). In the severe group, the proportion of patients with Diabetes (31.15%, P < 0.001), kidney (91.4%, P = 0.013), and malignancy (56.6%, P < 0.001) were significantly higher than in the moderate group. Table 2 Frequency distribution of patients based on comorbidities, smoking, and some clinical findings in the moderate and severe groups Variables Variables level Severe group n = 61 Moderate group n = 439 sum (n = 500) P value* number percent number percent number percent comorbidities Heart disease 6 9.84 21 4.78 27 5.4 0.102 Blood pressure 32 52.46 149 33.94 181 36.2 0.005 Diabetes 19 31.15 59 13.44 78 15.6 000 Kidney disease 3 4.92 4 0.91 7 1.4 0.013 Liver disease 0 0 6 1.37 6 1.2 0.358 malignant 4 6.56 3 0.68 7 1.4 000 Immune deficiency 0 0 1 0.23 1 0.2 0.0709 smoking User 14 23.73 45 76.27 59 11.8 0.004 clinical findings Fever 44 72.13 304 69.25 349 69.8 0.664 Cough 31 50.82 202 46.01 233 46.6 0.481 dyspnea 51 83.61 347 79.04 398 79.6 0.407 Receive remdesivir 59 96.72 399 90.89 458 91.6 0.124 Mechanical ventilation 59 96.72 389 88.61 448 89.6 0.052 Abnormal radiological results 41 67.21 287 65.38 328 65.6 0.777 The average duration of hospitalization in respondents was 7.74 ± 6 days, and this average in patients with severe disease (11.3) was significantly longer than this average in patients with moderate disease (7.24) (P < 0.001). The average duration of ventilation in both groups was 4.98 ± 4, and the average duration of ventilation in the severe group (7.63) was significantly longer than the average in the other group (4.61) (P < 0.001). The level of inflammatory factors of patients during hospitalization such as ESR and CRP were not significantly different in the two groups. The average amount of oxygen saturation in both groups was 84.21 ± 6. This average in the severe group (82.72) was significantly less than that in the moderate group (84.50). (P < 0.001) According to Table 3 Eight months after respondents’ discharge from the hospital, 58.8% of patients still had a cough, and the frequency of cough in patients who were admitted to the ICU was significantly higher than that in patients admitted to the ward (P = 0.023). 336 patients (67.2%) had some degree of Dyspnea, but there was no significant difference between the two groups of patients with moderate and severe disease based on this problem. 58.8% of patients had exertional Dyspnea. This problem was significantly more frequent in the patients who were admitted to the ICU (78.7%) than among patients who were admitted to the ward (55.35%) (P = 0.012). Also, 177 patients (35.4%) experienced some degree of chest pain at rest and 161 patients (32.2%) experienced exertional chest pain. Table 3 Comparison of respiratory symptoms between moderate and severe patient groups Symptoms variables Severe Group n = 61 Moderate Group n = 439 Sum (n = 500) P value* number percent number percent number percent Cough Never 21 34 185 42.14 206 41.2 0.023 Rarely 17 28 146 33.26 163 32.6 some 15 25 88 20.05 103 20.6 Much 8 13 20 4.5 28 5.6 dyspnea Never 13 21.31 151 34.40 164 32.8 0.063 Rarely 21 34.43 170 38.72 191 38.2 some 19 31.15 88 20.05 107 21.4 Much 8 13.11 30 6.83 38 7.6 exertional dyspnea Never 13 21.31 193 43.96 206 41.2 0.012 Rarely 22 36.07 125 28.47 147 29.4 some 21 34.43 92 20.96 113 22.6 Much 5 8.20 29 6.6 34 6.8 chest pain Never 24 39.34 299 68.11 323 64.6 0.000 Rarely 20 32.79 95 21.64 115 23 some 14 22.95 41 9.34 55 11 Much 3 4.92 4 0.91 7 1.4 exertional chest pain Never 27 44.26 312 71.07 339 67.8 0.000 Rarely 17 27.87 84 19.13 101 20.2 some 14 22.95 39 8.88 53 10.6 Much 3 4.92 4 0.91 7 1.4 Hemoptysis Never 57 93.44 427 97.27 439 87.8 0.112 Rarely 4 6.56 12 2.73 61 12.2 some 0 0.00 0 0.00 0 0 Much 0 0.00 0 0.00 0 0 In the second follow-up (one year after discharge), the rate of all respiratory symptoms including (cough, Dyspnea, etc.) was significantly decreased compared to the first follow-up, and one year after discharge from the hospital, still 29.6%., 36.6%, 36.4%, 19.4%, and 17.6% of patients had a cough, exertional dyspnea, chest pain, and exertional chest pain, respectively. According to Table 4 In the first follow-up (eight months after discharge): According to FEV1/FVC, 19 patients were classified as obstructive lung diseases (16.1%) and 99 patients were classified as restrictive lung diseases (83.89%). Out of all patients (118 patients), 3 patients (2.5%) in the mild obstruction group and 11 people (9.3%) in the moderate obstruction group and 5 people (4.2%) in the severe obstruction group, 62 people (52.5%) in the mild restrictive group and 4 people (3.4%) in the moderate restrictive group. were placed and 33 people (28%) were normal. In the second follow-up (one year after discharge) According to FEV1/FVC, 11 patients were classified as obstructive lung diseases (10.7%) and 91 patients were classified as restrictive lung diseases (89.2%), out of all patients (102 patients), 1 person (1%) was in the mild obstruction group and 5 people (4.9%) were in the moderate obstruction group, 4 people (3.9%) were in the severe obstruction group, 1 person (1%) was in the very severe obstruction group, and 44 people (43.1%) were in the mild restriction group and 1 person ( 1%) were in the moderate restrictive group and 46 people (45.1%) were normal. Using the McNemar test, the general respiratory condition of the patients at 8 and 12 months after discharge has been examined and compared. Considering the non-significance of this test, it can be concluded that the proportion of obstructive patients 8 months after discharge was in 14 patients (13.72%) and 12 months after discharge in 11 people (10.78%) is almost the same. (P = 0.508) In general, in the first follow-up (eight months after discharge), out of 118 patients who agreed to undergo a spirometry test, 71.9% of the patients had low lung volume, 16% of the patients were among the group of obstructive lung diseases and 55.9% were among the restrictive lung diseases. were classified. In the second follow-up (12 months after discharge), out of 102 patients, spirometry was performed, 54.9% of patients had low lung volume, 10.8% of patients were classified as obstructive lung diseases, and 44.1% as restrictive lung diseases. A significant reduction is observed in both restrictive and Obstructive groups, and the reduction rate in the restrictive group was greater than in the obstructive group. (11.8% reduction in restrictive patients versus 5.8% reduction in obstructive patients) Table 4 Comparison of pulmonary function in 8 and 12 months after discharge from the hospital: 12 months after discharge (n = 102) 8 months after discharge (n = 118) percent number percent number effect FEV1 percent FEV1/FVC 1.0% 1 2.5% 3 mild more than 80 less than 70% Obstructive pulmonary (obstructive) 4.9% 5 9.3% 11 some 50–80 3.9% 4 4.2% 5 intense 30–50 1.0% 1 0 0 very intense less than 30 45.1% 46 28.0% 33 normal more than 80 more than 70% Restrictive pulmonary disease (limited) 43.1% 44 52.5% 62 mild 50–80 1.0% 1 3.4% 4 some 30–50 0 0 0 0 intense less than 30% Discussion After the peak of the COVID-19 pandemic, examining the long-term consequences of post-discharge COVID-19 survivors got a lot of attention, this study is the first cohort study in Iran that evaluates lung volumes and respiratory outcomes in adult patients who are discharged from the hospital after recovering from COVID-19. According to the present study, a significant percentage of people had restrictions in terms of lung function one year after being discharged from the hospital due to COVID-19. In similar studies, the most remarkable finding in one year after discharge is the high proportion of patients with lung damage. COVID-19, respiratory disorder, and a decrease in lung function have been expressed as permanent symptoms ( 20 ). According to previous outbreaks of coronaviruses, such as severe acute respiratory syndrome (SARS) and Middle East respiratory syndrome (MERS), or H7N9 influenza, survivors also suffered from pulmonary dysfunction ( 21 , 22 , 23 ). In the present study, in the first follow-up (eight months after discharge), according to the spirometry results of the patients, more than two-thirds of the patients had lung dysfunction, and restrictive lung diseases accounted for the largest share. In a retrospective study that Eight weeks after hospital discharge, Maurizio Marvisibro conducted a study on 90 patients admitted to the respiratory department of the Istituto Figlie di San Camillo, Cremona (Northern Italy) with SARS-CoV-2 pneumonia. Evidence in favor of early lung fibrosis in 25% of patients was shown ( 24 ) and in another study, in the examination of patients three months after discharge, according to the fibrotic bands that were seen in the CT scan of one-fifth of the patients, it was suggested that some lung injuries may be stable and lead to become stable fibrotic changes in the lung ( 25 ), which can justify the high percentage of patients with dysfunction, especially patients of the restrictive type, in the second follow-up, which was done one year after the disease, 54.8% of pulmonary dysfunction was 17.1% less than the first time, which was more than the reduction in obstructive diseases. During the autopsy of lung tissues from 38 patients who died of COVID-19, pathological changes in the lungs of the patients in the form of diffuse alveolar damage, formation of hyaline membrane, interstitial edema, and type 2 alveolar epithelial cells were identified may be able to justify the results obtained. In other similar studies, a significant percentage of patients had lung function disorders between three and six months after discharge ( 5 , 8 , 15 , 26 ), but the percentage of pulmonary function disorders in our study is significantly higher than this. It was studied that one of the reasons it seems that a significant number of hospitalized patients were workers who previously worked in the steel, iron, copper, and cement industries, which can increase the susceptibility to chronic lung diseases ( 38 ). Also, a study conducted in Kerman in 2013 showed that high occupational exposure to dust particles leads to respiratory symptoms, radiographic abnormalities, and decreased lung function ( 39 ), so many of these patients may have already had lung problems due to occupational exposure. On the other hand, Kerman is one of the desert cities in the southeast of Iran, which faces sandstorms and increased dust in the air during certain seasons of the year ( 40 ). According to a study conducted in Iran between 1990 and 2019, the province (Kerman) had the highest age-standardized mortality rate due to chronic respiratory diseases four times higher than the province (Tehran) and the attributable risk factors that caused the most DALYs, Smoking, Air pollution, and Body Mass Index were high ( 41 ). In our study, 47.2% of patients were housewives, according to a study conducted on rural housewives in Isfahan. Baking bread, weaving carpets, and using fossil fuels were significant risk factors for all lung diseases ( 42 ). Also, in our first follow-up, 67.2% of patients had some degree of Dyspnea, and more than half of the patients had exertional dyspnea, which was higher in severe groups of patients who were hospitalized in the ICU and the second follow-up, the percentage of patients with Dyspnea was reduced by almost half, and exertional dyspnea was almost two-thirds of the first time. In other similar studies, Dyspnea or continuous exertional dyspnea was one of the main complaints of patients with COVID-19 after discharge from the hospital ( 7 , 26 , 28 , 29 , 30 , 31 ). However, in the study of Mattia Bellan and his colleagues, the proportion of patients with Dyspnea and chest pain did not change from 4 months to 12 months of follow-up ( 27 ). Also, patients who recovered from SARS complained of Dyspnea in the early rehabilitation phase ( 32 ). Of course, there is a possibility that Dyspnea in these patients can be caused by lung, heart, and neuromuscular problems, except for the effects of the coronavirus ( 33 , 34 ). In addition, a higher BMI was associated with persistent Dyspnea one year after discharge ( 31 ), and in our study, both groups of patients with severe and moderate disease were overweight. Other studies showed that patients with CT Abnormally had a higher BMI, obese patients were more likely to be infected with severe COVID-19, and a significant proportion of patients with severe disease severity had a BMI of 30 or higher ( 23 , 30 , 31 ). In our study, in both groups of patients with moderate and severe disease severity, high blood pressure was more common than other underlying diseases, and this result was consistent with many studies ( 27 , 30 , 31 , 33 ). Above, it was considered as one of the risk factors for the lasting consequences of COVID-19 ( 27 ). Also, in our study, in the group of patients with severe disease severity, the percentage of people with diabetes, kidney disease, and malignancy was higher than in patients with moderate disease severity, and in other studies, the prevalence of diabetes in the severe group was significantly higher than in the moderate group. ( 26 , 30 , 37 ). Therefore, when treating severe patients, doctors need to keep in mind the control of diabetes in a balanced way along with the treatment of viral infection, so it is necessary to follow up and control diabetes in the management of patients with COVID-19 after discharge ( 26 ). In the current study, patients with more severe diseases were older than patients with moderate disease severity, which was consistent with Qian Wu’s study ( 26 ), in a study conducted in one of Iran's hospitals, it also showed that most of the patients hospitalized due to COVID-19 and Most of the patients with critical conditions were more than or equal to 75 years old ( 35 ) and another study also confirms this fact that older patients are more likely to be affected by the more severe COVID-19 ( 36 ). One of the strong points of this study is the follow-up of two time points after discharge, which allows for comparison over time. This study has several limitations: We didn't have any information about lung function (spirometry test results) before COVID-19, The observed pulmonary dysfunction cannot be directly attributed to COVID-19, It is possible that a large number of patients who agreed to performed the spirometry test were people who had more pulmonary problems before. A significant 4% of the participants did not want to do a spirometry test. Conclusions By summarizing the results of pulmonary function tests by evaluating respiratory symptoms and completing the results, two main patterns of pulmonary involvement after COVID-19 can be distinguished: 1-obstructive pattern and 2-restrictive pattern, which in our study, one year after discharge A significant number of patients had pulmonary dysfunction and it was also seen in this study that obstructive complications are more than restrictive complications, but no significant difference in obstructive and restrictive patterns were observed between the two groups of patients with moderate and severe disease severity. suggestions In this study, during four months (from eight months after discharge to one year after discharge), the process of increasing the volume of the lungs continued, but there was no complete recovery. Therefore, it is better to continue this investigation until the process of increasing the lung volume is stopped. Abbreviations COVID-19 Coronavirus disease 2019 FEV1 Forced expiratory volume in 1 second FVC Forced vital capacity FEV1/FVC Forced expiratory ratio DLCO Diffusing lung capacity for carbon monoxide 6MWT: 6-Minute Walk Test Declarations Acknowledgments The authors would like to express their gratitude to the medical records department of Afzali pour Kerman Hospital, the staff of Dr. Yazdani's office as well as the patients and their families, Dr. Kaveh Rafieipour, Dr.Mozhdeh Nazari and Sajjad Arefi for their cooperation in implementing this project. Author contributions vazirinejad, Ahmadinia, Rezaeian, and Nazari conceived and designed the study. Nazari and Yazdani collected clinical data. Vazirinejad, Ahmadinia, Rezaeian, Nazari, Yazdani, and Doraki analyzed and interpreted the data. Nazari, Vazirinejad, and Ahmadinia, wrote the manuscript. All authors reviewed and approved the final version of the manuscript. Funding This study is supported by Rafsanjan University of Medical Sciences. Data availability Data is provided within the supplementary information file. Ethics approval and consent to participate The studies involving humans were approved by this study is approved by the ethical committee of Rafsanjan University of Medical Sciences with the number of IR.RUMS.REC.1401.065, all the methods were performed in accordance with the relevant guidelines and regulation. The studies were conducted in accordance with the local legislation and institutional requirements. The participants provided their written informed consent to participate in this study. Consent for publication Not applicable. Competing interests The authors declare no competing interests. References Ñamendys-Silva SA. ECMO for ARDS due to COVID-19. 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Tarraso J, Safont B, Carbonell-Asins JA, Fernandez-Fabrellas E, Sancho-Chust JN, Naval E, Amat B, Herrera S, Ros JA, Soler-Cataluña JJ, Rodriguez-Portal JA. Lung function and radiological findings 1 year after COVID-19: a prospective follow-up. Respiratory Research. 2022 Dec;23(1):1-2 Mashhadi M, Sahebozamani M, Daneshjoo A, Adeli SH, Venarji N. Persistent symptoms in recovered patient from COVID-19 and the importance of post-acute rehabilitation: A systematic review. Qom University of Medical Sciences Journal. 2021 Dec 10;15(10):660-73. Ahmed H, Patel K, Greenwood DC, Halpin S, Lewthwaite P, Salawu A, Eyre L, Breen A, Connor RO, Jones A, Sivan M. Long-term clinical outcomes in survivors of severe acute respiratory syndrome (SARS) and Middle East respiratory syndrome coronavirus (MERS) outbreaks after hospitalisation or ICU admission: a systematic review and meta-analysis. Journal of rehabilitation medicine. 2020 May 31;52(5):1-1. Wang Q, Jiang H, Xie Y, Zhang T, Liu S, Wu S, Sun Q, Song S, Wang W, Deng X, Ren L. Long-term clinical prognosis of human infections with avian influenza A (H7N9) viruses in China after hospitalization. EClinicalMedicine. 2020 Mar 1;20:100282. Zhang S, Bai W, Yue J, Qin L, Zhang C, Xu S, Liu X, Ni W, Xie M. Eight months follow-up study on pulmonary function, lung radiographic, and related physiological characteristics in COVID-19 survivors. Scientific reports. 2021 Jul 5;11(1):1-3. Marvisi M, Ferrozzi F, Balzarini L, Mancini C, Ramponi S, Uccelli M. First report on clinical and radiological features of COVID-19 pneumonitis in a Caucasian population: factors predicting fibrotic evolution. International Journal of Infectious Diseases. 2020 Oct 1;99:485-8. George PM, Wells AU, Jenkins RG. Pulmonary fibrosis and COVID-19: the potential role for antifibrotic therapy. The Lancet Respiratory Medicine. 2020 Aug 1;8(8):807-15. Wu Q, Zhong L, Li H, Guo J, Li Y, Hou X, Yang F, Xie Y, Li L, Xing Z. A follow-up study of lung function and chest computed tomography at 6 months after discharge in patients with coronavirus disease 2019. Canadian Respiratory Journal. 2021 Feb 13;2021. Bellan M, Baricich A, Patrucco F, Zeppegno P, Gramaglia C, Balbo PE, Carriero A, Amico CS, Avanzi GC, Barini M, Battaglia M. Long-term sequelae are highly prevalent one year after hospitalization for severe COVID-19. Scientific reports. 2021 Nov 22;11(1):22666. Qin W, Chen S, Zhang Y, Dong F, Zhang Z, Hu B, Zhu Z, Li F, Wang X, Wang Y, Zhen K. Diffusion capacity abnormalities for carbon monoxide in patients with COVID-19 at three-month follow-up. European Respiratory Journal. 2021 Jan 1. Steinbeis F, Thibeault C, Doellinger F, Ring RM, Mittermaier M, Ruwwe-Glösenkamp C, Alius F, Knape P, Meyer HJ, Lippert LJ, Helbig ET. Severity of respiratory failure and computed chest tomography in acute COVID-19 correlates with pulmonary function and respiratory symptoms after infection with SARS-CoV-2: An observational longitudinal study over 12 months. Respiratory Medicine. 2022 Jan 1;191:106709. Zhou F, Tao M, Shang L, Liu Y, Pan G, Jin Y, Wang L, Hu S, Li J, Zhang M, Fu Y. Assessment of sequelae of COVID-19 nearly 1 year after diagnosis. Frontiers in Medicine. 2021 Nov 23;8:717194 Lorent N, Weygaerde YV, Claeys E, Fajardo IG, De Vos N, De Wever W, Salhi B, Gyselinck I, Bosteels C, Lambrecht BN, Everaerts S. Prospective longitudinal evaluation of hospitalised COVID-19 survivors 3 and 12 months after discharge. ERJ open research. 2022 Apr 1;8(2). Chan KS, Zheng JP, Mok YW, Li YM, LIU YN, Chu CM, Ip MS. SARS: prognosis, outcome and sequelae. Respirology. 2003 Nov;8:S36-40. Huang C, Huang L, Wang Y, Li X, Ren L, Gu X, Kang L, Guo L, Liu M, Zhou X, Luo J. 6-month consequences of COVID-19 in patients discharged from hospital: a cohort study. The Lancet. 2021 Jan 16;397(10270):220-32. Nie S, Han S, Ouyang H, Zhang Z. Coronavirus Disease 2019-related dyspnea cases difficult to interpret using chest computed tomography. Respiratory medicine. 2020 Jun 1;167:105951. Mesgarian M, Tarjoman T, Karimloo M, Valizadeh M, Hanifezadeh Z, Ameli O, Alijani M, Farhoodi B, Zangeneh M. Evaluation of clinical, epidemiological and paraclinical characteristics of patients diagnosed with COVID-19 and its relationship with disease severity in Amir Al-Momenin Hospital in Tehran. Medical Science Journal of Islamic Azad Univesity-Tehran Medical Branch. 2022 Mar 10;32(1):64-74. Nikpouraghdam M, Farahani AJ, Alishiri G, Heydari S, Ebrahimnia M, Samadinia H, Sepandi M, Jafari NJ, Izadi M, Qazvini A, Dorostkar R. Epidemiological characteristics of coronavirus disease 2019 (COVID-19) patients in IRAN: A single center study. Journal of Clinical Virology. 2020 Jun 1;127:104378 Hu L, Chen S, Fu Y, Gao Z, Long H, Ren H-W et al. Risk factors associated with clinical outcomes in 323 COVID-19 patients in Wuhan, China. medRxiv; 2020. Khanjani N, Klankash driver l, Mansouri F. Investigating the relationship between open air pollution and death due to respiratory diseases in Kerman2015-2019 . Iranian Specialized Journal of epidemiology. 2013 ;8(3):58-65. Ashrafi-Asgarabad A, Samareh-Fekri M, Ghotbi Ravandi MR. Exposure to particles and respiratory symptoms in stone carvers of Kerman, Iran. Journal of Occupational Health and Epidemiology. 2013 Oct 10;2(4):146-56. . Mansouri F, Khanjani N, Pourmousa R. Forecasting ambient air pollutants by time series models in Kerman, Iran. Journal of School of Public Health and Institute of Public Health Research. 2013 Nov 10;11(2):75-86. Heidari-Foroozan M, Aryan A, Esfahani Z, Shahrbaf MA, Moghaddam SS, Keykhaei M, Ghasemi E, Rashidi MM, Rezaei N, Ghamari SH, Abbasi-Kangevari M. National, subnational and risk attributed burden of chronic respiratory diseases in Iran from 1990 to 2019. Respiratory Research. 2023 Dec;24(1):1-6. Golshan M, Faghihi M, Marandi MM. Indoor women jobs and pulmonary risks in rural areas of Isfahan, Iran, 2000. Respiratory medicine. 2002 Jun 1;96(6):382-8. Additional Declarations No competing interests reported. Supplementary Files 22.pdf Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-3908644","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":272474012,"identity":"d947edc2-d33d-4484-bcd7-4cac94cecbdc","order_by":0,"name":"Reza vazirinejad","email":"","orcid":"","institution":"Rafsanjan University of Medical Sciences","correspondingAuthor":false,"prefix":"","firstName":"Reza","middleName":"","lastName":"vazirinejad","suffix":""},{"id":272474013,"identity":"8ce223d2-b4a5-46fd-ac37-672494967586","order_by":1,"name":"Hassan Ahmadinia","email":"","orcid":"","institution":"Rafsanjan University of Medical Sciences","correspondingAuthor":false,"prefix":"","firstName":"Hassan","middleName":"","lastName":"Ahmadinia","suffix":""},{"id":272474014,"identity":"96e0b2fb-cb3f-4ee9-817c-a42046407c32","order_by":2,"name":"Mohsen Rezaeian","email":"","orcid":"","institution":"Rafsanjan University of Medical Sciences","correspondingAuthor":false,"prefix":"","firstName":"Mohsen","middleName":"","lastName":"Rezaeian","suffix":""},{"id":272474015,"identity":"380b88f9-6883-4c37-a01e-5d28356a6de2","order_by":3,"name":"Marziyeh Nazari","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA/klEQVRIiWNgGAWjYDACZiTGwQ8/bORA7AMPiNTC+FiyJ80YrCWBWAsNeNgOJzaAmPi06LazP2AuqKmTN29nYJOQ4DmcPj/s8EOgLXZyug3YtZgd5jFgnnGMzXDOYaCWAov03I230wyAWpKNzQ7g1MLAzMPGwziDGWyLde7G2QkgLQcSt+HUAnQYzz8Je7AWHjbmdMPZ6R8IaGEwYOZtM0gEagF53zlBXjqHkC08Bod5+xKSZzAzNoIC2XCDdE7BgQQDPH45f/zhY55vdbYz+A8fAEWlvPzs9M0fPlTYyeHSAgJQKcYGMGUA5hrgVo4J5BtIUT0KRsEoGAUjAQAAVLFX4kNFZukAAAAASUVORK5CYII=","orcid":"","institution":"Rafsanjan University of Medical Sciences","correspondingAuthor":true,"prefix":"","firstName":"Marziyeh","middleName":"","lastName":"Nazari","suffix":""},{"id":272474016,"identity":"cbf8ff09-f691-446a-84a1-263ea981a23f","order_by":4,"name":"Rostam Yazdani","email":"","orcid":"","institution":"Kerman University of Medical Sciences","correspondingAuthor":false,"prefix":"","firstName":"Rostam","middleName":"","lastName":"Yazdani","suffix":""},{"id":272474017,"identity":"bbd147b3-af40-458c-bf2a-9383646a69a5","order_by":5,"name":"Nader Doraki","email":"","orcid":"","institution":"Rafsanjan University of Medical Sciences","correspondingAuthor":false,"prefix":"","firstName":"Nader","middleName":"","lastName":"Doraki","suffix":""}],"badges":[],"createdAt":"2024-01-29 10:03:31","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-3908644/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-3908644/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":51084536,"identity":"1791b892-3356-4b0d-8a27-80faaa3c1f03","added_by":"auto","created_at":"2024-02-13 19:47:17","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":164482,"visible":true,"origin":"","legend":"\u003cp\u003eFlow chart of participants\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-3908644/v1/e0a76e662d175de07b14a08f.png"},{"id":52863537,"identity":"d565eaa7-df8f-43de-9c70-b3c3699637d0","added_by":"auto","created_at":"2024-03-18 05:11:14","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":557775,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-3908644/v1/faa8f9b3-20f2-48a0-a51b-460b272f01e4.pdf"},{"id":51084507,"identity":"e758648f-47ec-4af3-9c38-f1bba0c009a2","added_by":"auto","created_at":"2024-02-13 19:47:01","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":2900895,"visible":true,"origin":"","legend":"","description":"","filename":"22.pdf","url":"https://assets-eu.researchsquare.com/files/rs-3908644/v1/ad05fbf1509915fda7449c13.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"The long-term effect of COVID-19 infection on lung volumes and respiratory indices among hospitalized patients up to one year after discharging from hospital: a population- based cohort study","fulltext":[{"header":"Introduction","content":"\u003cp\u003eOn March 11, 2020, the World Health Organization declared the Coronavirus as a pandemic (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e) until October 2023, the number of people infected with the Coronavirus in the world has exceeded 696\u0026nbsp;million people and the number of deaths has exceeded 6,924,281. This disease in Iran has left more than seven million patients and 146 thousand dead (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e). Acute respiratory syndrome of the coronavirus 2 (SARS-CoV-2) causes acute viral respiratory infections, including pneumonia. After the initial infection with SARS-CoV-2 in the upper respiratory tract, the virus continues to multiply in the lower airways and alveolar epithelial cells (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e). Usually, coronaviruses cause an infection in the respiratory ciliated mucus in the throat and nose area, which causes symptoms similar to the common cold. Sometimes, these viruses may cause more serious complications such as exacerbation of asthma, and lung infection (pneumonia) in adults, the elderly, and people with weak immune systems (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e). In a study conducted in China in 2020, approximately 20% of patients with infection require hospitalization and 6% in the intensive care unit requires intensive care and invasive ventilator support. Epidemiological reports showed that 8.2% of all cases had rapid and progressive respiratory failure, similar to acute respiratory distress syndrome (ARDS) (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e). Studies reported that patients may have persistent respiratory disorders for months or even years after discharge (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e), as well as other coronaviruses, have also caused long-term effects, especially in the lungs. 6). Currently, a new topic for research is the investigation of pulmonary function in the survivors of Covid-19(\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIn the initial stage of the COVID-19 pandemic, national and international health authorities refused to perform routine pulmonary function tests (\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e). However, after passing the peak of the epidemic, the need to use specialized measures reappeared (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e). Therefore, most of the national and international scientific institutions modified their initial recommendations and re-introduced pulmonary function tests (PFTs) in routine clinical practice (\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e). investigated the distribution of lung volume (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e). According to what was said, since the detection of pulmonary function changes is necessary for the diagnosis and follow-up of patients with respiratory and functional complications caused by COVID-19, we decided to measure the respiratory function of hospitalized patients during the next months. These results help specialist doctors to make decisions about how to change their approach during outpatient visits, considering appropriate measures including respiratory rehabilitation if needed and other necessary plans (\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e). The purpose of this study is to evaluate lung volumes in hospitalized patients with COVID-19, up to one year after discharge from the hospital.\u003c/p\u003e"},{"header":"Materials and Methods","content":"\u003cp\u003eThe present research is a population-based cohort study that is prospectively conducted on the survivors of COVID-19 who were discharged from Afzalipur Hospital in Kerman during August, September, and October 2021, after approval by the Research Council of Rafsanjan University of Medical Sciences.\u003c/p\u003e \u003cp\u003e The ethics approval was obtained from the University Ethics Committee (the number IR.RUMS.REC.1401.065). Inclusion criteria include (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e) age\u0026thinsp;\u0026ge;\u0026thinsp;18 years (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e) SARS-CoV-2 infection confirmed by PCR (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e) hospitalization due to COVID-19, Exclusion criteria include having a history of lung diseases such as asthma or lung cancer, a history of lung resection, psychotic disorder, dementia or osteoarthropathy or immobility, unwillingness to continue participating in the study, living in a nursing home or welfare, and death of the patient. The patients who were hospitalized from August to October were invited to help with the study by phone. Respondents were informed about the study objectives and important details were presented to them. Those patients who were willing to participate were requested to fill out and sign the consent form. Respondents were assured that all their information would be kept confidential.\u003c/p\u003e \u003cp\u003eThese patients were prospectively followed up in one year and their pulmonary function was measured on two occasions in eight months and one year. At the beginning of the data collection process, the demographic information of patients such as age, sex, occupation, and place of residence, as well as the clinical information such as the time of hospitalization, blood oxygen saturation, hospitalization in the ward or ICU, history of smoking and opium use, comorbidities such as hypertension, diabetes, and chronic kidney disease, taking medication such as Remdesivir, use of mechanical ventilation and its duration were obtained retrospectively from their hospital records. According to this information, the patients were divided into two groups of moderate and severe disease severity. The criteria for entering the moderate group were: 1- Presence of respiratory symptoms (including shortness of breath, feeling of pain and pressure in the chest) with or without fever, equal to/more than 38 degrees Celsius 2- Spo2 from 90 to 93, pain and the criteria for entering the severe group were: 1- Rapid progression of respiratory symptoms, especially worsening of shortness of breath, 2- Tachypnea RR\u0026thinsp;\u0026gt;\u0026thinsp;30), 3- Spo2 less than 90% and pao2/fio2 less than 300 mmHg, 4- Increase in A-a gradient and also increase in involvement more than 50% of the lung in CT scan.\u003c/p\u003e \u003cp\u003e In each follow-up, respondents were called by phone, and for those who agreed, the spirometry tests were performed by the experienced staff at the lung specialist's office. Tests of forced vital capacity (FVC), forced expiratory capacity in the first second of exhalation (FEV1), and FEV1/FVC. Also, in each visit, the height and weight of patients were measured to calculate BMI. Oxygen level Blood saturation was also measured for these patients by pulse oximetry device. Other respiratory outcomes such as cough, dyspnea, Exertional dyspnea, chest pain, Exertional dyspnea chest pain, and hemoptysis were also measured. The data were recorded on a researcher-made questionnaire. Furthermore, patients who did not decide to do the spirometry test were asked over the phone about other respiratory outcomes.\u003c/p\u003e \u003cp\u003eFinally, after cleaning the collected data and controlling the data by the lung specialist, the data were transferred to SPSS version 26 software and analyzed. Statistical tables and graphs were used for descriptive data reporting, qualitative data was reported as numbers and percentages, and quantitative data was reported as mean and standard deviation. Continuous variables were compared with Student's t-test and categorical variables with χ2. Using McNemar's test, the general respiratory status of patients was examined and compared at 8 and 12 months after discharge. The significance level in all tests was considered equal to 0.05.\u003c/p\u003e \u003cp\u003eLung function tests (Pulmonary function testing) were used to measure lung function, and spirometry, which can be used to measure air flow rate and all lung volumes except FRC-RV, and TLC, was performed (\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e).\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003eDuring August, September, and October 2021, 1954 patients were admitted to Afzalipour Hospital in Kerman due to COVID-19, 327 patients died in the hospital and 1627 patients were discharged, 1553 patients were over 18 years of age, 1502 were Iranian and 51 Afghan patients were over 18 years old, 783 male patients and 770 female patients. After making phone calls with 1116 discharged patients over 18 years old and explaining the conditions of the study, 500 people agreed to participate in our study. 118 people in the first follow-up and 102 people in the second follow-up did the spirometry test. (Figure No. 1)\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e223 (44.6%), and 277 (55.4%) patients were male and female respectively. The average age of patients was 52.06\u0026thinsp;\u0026plusmn;\u0026thinsp;16 years, although patients with severe disease were older than patients with moderate disease severity. (59.8 to 50.98 years) (P\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Most of the Iranian patients (97.8%) were married (80.6%) and literate (85.8%). The average body mass index of the patients was 26.71\u0026thinsp;\u0026plusmn;\u0026thinsp;4, that were in the overweight group. The largest group of patients were housewives (47.2 percent). The highest percentage of patients' insurance was related to social security insurance (52.4 percent) (Table No. 1).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eBasic information on hospitalized patients with COVID-19\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eVariable levels\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003en\u0026thinsp;=\u0026thinsp;500\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNumber\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003epercent\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eGender\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e223\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e44.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e277\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e55.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003eMarital status\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSingle\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMarried\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e403\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e80.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eWidowed\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e51\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e10.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDivorced\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"5\" rowspan=\"6\"\u003e \u003cp\u003eeducation level\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eIlliterate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e71\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e14.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHigh school\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e173\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e34.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDiploma\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e159\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e31.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAssociate Degree\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBachelor's degree\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e11.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMaster\u0026rsquo;s degree and higher\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eNationality\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eIranian\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e489\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e97.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAfghan\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"5\" rowspan=\"6\"\u003e \u003cp\u003eJob\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHousewife\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e236\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e47.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eEmployee\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFree\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e95\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e19\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eStudent\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRetired\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e11.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOther\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e13\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003eInsurance\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003esocial security\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e262\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e52.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHealth\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e188\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e37.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eArmed Forces\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOther layers\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003edoes not have insurance\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e\n\u003ch3\u003eAccording to Table 2\u003c/h3\u003e\n\u003cp\u003eThe proportion of smokers in the severe group who were hospitalized in the ICU (22.9%) was significantly higher than that in the moderate group (10.2%, P\u0026thinsp;=\u0026thinsp;0.004). The most common comorbidities among respondents was high blood pressure (36.2%). In the severe group, the proportion of patients with Diabetes (31.15%, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001), kidney (91.4%, P\u0026thinsp;=\u0026thinsp;0.013), and malignancy (56.6%, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001) were significantly higher than in the moderate group.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eFrequency distribution of patients based on comorbidities, smoking, and some clinical findings in the moderate and severe groups\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"9\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eVariables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eVariables level\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003eSevere group n\u0026thinsp;=\u0026thinsp;61\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003eModerate group n\u0026thinsp;=\u0026thinsp;439\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e \u003cp\u003esum (n\u0026thinsp;=\u0026thinsp;500)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eP value*\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003enumber\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003epercent\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003enumber\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003epercent\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003enumber\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003epercent\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"6\" rowspan=\"7\"\u003e \u003cp\u003ecomorbidities\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHeart disease\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e9.84\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e4.78\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e5.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.102\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBlood pressure\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e52.46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e149\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e33.94\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e181\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e36.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.005\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDiabetes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e31.15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e13.44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e78\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e15.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eKidney disease\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4.92\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.91\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e1.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.013\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLiver disease\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1.37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e1.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.358\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003emalignant\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6.56\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.68\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e1.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eImmune deficiency\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.0709\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003esmoking\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eUser\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e23.73\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e76.27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e11.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.004\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"5\" rowspan=\"6\"\u003e \u003cp\u003eclinical findings\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFever\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e72.13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e304\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e69.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e349\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e69.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.664\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCough\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e50.82\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e202\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e46.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e233\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e46.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.481\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003edyspnea\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e51\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e83.61\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e347\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e79.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e398\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e79.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.407\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eReceive\u003c/p\u003e \u003cp\u003eremdesivir\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e96.72\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e399\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e90.89\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e458\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e91.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.124\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMechanical ventilation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e96.72\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e389\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e88.61\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e448\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e89.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.052\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAbnormal radiological results\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e67.21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e287\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e65.38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e328\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e65.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.777\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eThe average duration of hospitalization in respondents was 7.74\u0026thinsp;\u0026plusmn;\u0026thinsp;6 days, and this average in patients with severe disease (11.3) was significantly longer than this average in patients with moderate disease (7.24) (P\u0026thinsp;\u0026lt;\u0026thinsp;0.001). The average duration of ventilation in both groups was 4.98\u0026thinsp;\u0026plusmn;\u0026thinsp;4, and the average duration of ventilation in the severe group (7.63) was significantly longer than the average in the other group (4.61) (P\u0026thinsp;\u0026lt;\u0026thinsp;0.001). The level of inflammatory factors of patients during hospitalization such as ESR and CRP were not significantly different in the two groups. The average amount of oxygen saturation in both groups was 84.21\u0026thinsp;\u0026plusmn;\u0026thinsp;6. This average in the severe group (82.72) was significantly less than that in the moderate group (84.50). (P\u0026thinsp;\u0026lt;\u0026thinsp;0.001)\u003c/p\u003e\n\u003ch3\u003eAccording to Table 3\u003c/h3\u003e\n\u003cp\u003eEight months after respondents\u0026rsquo; discharge from the hospital, 58.8% of patients still had a cough, and the frequency of cough in patients who were admitted to the ICU was significantly higher than that in patients admitted to the ward (P\u0026thinsp;=\u0026thinsp;0.023). 336 patients (67.2%) had some degree of Dyspnea, but there was no significant difference between the two groups of patients with moderate and severe disease based on this problem. 58.8% of patients had exertional Dyspnea. This problem was significantly more frequent in the patients who were admitted to the ICU (78.7%) than among patients who were admitted to the ward (55.35%) (P\u0026thinsp;=\u0026thinsp;0.012). Also, 177 patients (35.4%) experienced some degree of chest pain at rest and 161 patients (32.2%) experienced exertional chest pain.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eComparison of respiratory symptoms between moderate and severe patient groups\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"9\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eSymptoms\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003evariables\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003eSevere Group n\u0026thinsp;=\u0026thinsp;61\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003eModerate Group n\u0026thinsp;=\u0026thinsp;439\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e \u003cp\u003eSum (n\u0026thinsp;=\u0026thinsp;500)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eP value*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003enumber\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003epercent\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003enumber\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003epercent\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003enumber\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003epercent\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003eCough\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNever\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e185\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e42.14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e206\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e41.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e0.023\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRarely\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e146\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e33.26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e163\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e32.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003esome\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e88\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e20.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e103\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e20.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMuch\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e5.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003edyspnea\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNever\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e21.31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e151\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e34.40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e164\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e32.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e0.063\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRarely\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e34.43\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e170\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e38.72\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e191\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e38.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003esome\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e31.15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e88\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e20.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e107\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e21.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMuch\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e13.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e6.83\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e7.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003eexertional dyspnea\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNever\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e21.31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e193\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e43.96\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e206\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e41.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e0.012\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRarely\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e36.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e125\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e28.47\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e147\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e29.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003esome\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e34.43\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e92\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e20.96\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e113\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e22.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMuch\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e8.20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e6.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e6.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e\u003csub\u003echest pain\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNever\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003csub\u003e24\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003csub\u003e39.34\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003csub\u003e299\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003csub\u003e68.11\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003csub\u003e323\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003csub\u003e64.6\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRarely\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003csub\u003e20\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003csub\u003e32.79\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003csub\u003e95\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003csub\u003e21.64\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003csub\u003e115\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003csub\u003e23\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003esome\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003csub\u003e14\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003csub\u003e22.95\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003csub\u003e41\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003csub\u003e9.34\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003csub\u003e55\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003csub\u003e11\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMuch\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003csub\u003e3\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003csub\u003e4.92\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003csub\u003e4\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003csub\u003e0.91\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003csub\u003e7\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003csub\u003e1.4\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003eexertional chest pain\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNever\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003csub\u003e27\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003csub\u003e44.26\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003csub\u003e312\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003csub\u003e71.07\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003csub\u003e339\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003csub\u003e67.8\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRarely\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e27.87\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e84\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e19.13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e101\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e20.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003esome\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e22.95\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e8.88\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e10.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMuch\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4.92\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.91\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003eHemoptysis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNever\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e93.44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e427\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e97.27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e439\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e87.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e0.112\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRarely\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6.56\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.73\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e61\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e12.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003esome\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMuch\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eIn the second follow-up (one year after discharge), the rate of all respiratory symptoms including (cough, Dyspnea, etc.) was significantly decreased compared to the first follow-up, and one year after discharge from the hospital, still 29.6%., 36.6%, 36.4%, 19.4%, and 17.6% of patients had a cough, exertional dyspnea, chest pain, and exertional chest pain, respectively.\u003c/p\u003e\n\u003ch3\u003eAccording to Table 4\u003c/h3\u003e\n\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003eIn the first follow-up (eight months after discharge):\u003c/h2\u003e \u003cp\u003eAccording to FEV1/FVC, 19 patients were classified as obstructive lung diseases (16.1%) and 99 patients were classified as restrictive lung diseases (83.89%). Out of all patients (118 patients), 3 patients (2.5%) in the mild obstruction group and 11 people (9.3%) in the moderate obstruction group and 5 people (4.2%) in the severe obstruction group, 62 people (52.5%) in the mild restrictive group and 4 people (3.4%) in the moderate restrictive group. were placed and 33 people (28%) were normal.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eIn the second follow-up (one year after discharge)\u003c/h2\u003e \u003cp\u003eAccording to FEV1/FVC, 11 patients were classified as obstructive lung diseases (10.7%) and 91 patients were classified as restrictive lung diseases (89.2%), out of all patients (102 patients), 1 person (1%) was in the mild obstruction group and 5 people (4.9%) were in the moderate obstruction group, 4 people (3.9%) were in the severe obstruction group, 1 person (1%) was in the very severe obstruction group, and 44 people (43.1%) were in the mild restriction group and 1 person ( 1%) were in the moderate restrictive group and 46 people (45.1%) were normal.\u003c/p\u003e \u003cp\u003eUsing the McNemar test, the general respiratory condition of the patients at 8 and 12 months after discharge has been examined and compared. Considering the non-significance of this test, it can be concluded that the proportion of obstructive patients 8 months after discharge was in 14 patients (13.72%) and 12 months after discharge in 11 people (10.78%) is almost the same. (P\u0026thinsp;=\u0026thinsp;0.508)\u003c/p\u003e \u003cp\u003eIn general, in the first follow-up (eight months after discharge), out of 118 patients who agreed to undergo a spirometry test, 71.9% of the patients had low lung volume, 16% of the patients were among the group of obstructive lung diseases and 55.9% were among the restrictive lung diseases. were classified. In the second follow-up (12 months after discharge), out of 102 patients, spirometry was performed, 54.9% of patients had low lung volume, 10.8% of patients were classified as obstructive lung diseases, and 44.1% as restrictive lung diseases. A significant reduction is observed in both restrictive and Obstructive groups, and the reduction rate in the restrictive group was greater than in the obstructive group. (11.8% reduction in restrictive patients versus 5.8% reduction in obstructive patients)\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eComparison of pulmonary function in 8 and 12 months after discharge from the hospital:\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"8\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003e12 months after discharge\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;102)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e8 months after discharge\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;118)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003epercent\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003enumber\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003epercent\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003enumber\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eeffect\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eFEV1 percent\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eFEV1/FVC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1.0%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.5%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003emild\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003emore than 80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003eless than 70%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003eObstructive pulmonary\u003c/p\u003e \u003cp\u003e(obstructive)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e4.9%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9.3%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003esome\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e50\u0026ndash;80\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3.9%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.2%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eintense\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e30\u0026ndash;50\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1.0%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003every intense\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eless than 30\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e45.1%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e28.0%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003enormal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003emore than 80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003emore than 70%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003eRestrictive pulmonary disease\u003c/p\u003e \u003cp\u003e(limited)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e43.1%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e52.5%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003emild\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e50\u0026ndash;80\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1.0%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.4%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003esome\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e30\u0026ndash;50\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eintense\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eless than 30%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eAfter the peak of the COVID-19 pandemic, examining the long-term consequences of post-discharge COVID-19 survivors got a lot of attention, this study is the first cohort study in Iran that evaluates lung volumes and respiratory outcomes in adult patients who are discharged from the hospital after recovering from COVID-19. According to the present study, a significant percentage of people had restrictions in terms of lung function one year after being discharged from the hospital due to COVID-19. In similar studies, the most remarkable finding in one year after discharge is the high proportion of patients with lung damage. COVID-19, respiratory disorder, and a decrease in lung function have been expressed as permanent symptoms (\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e). According to previous outbreaks of coronaviruses, such as severe acute respiratory syndrome (SARS) and Middle East respiratory syndrome (MERS), or H7N9 influenza, survivors also suffered from pulmonary dysfunction (\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIn the present study, in the first follow-up (eight months after discharge), according to the spirometry results of the patients, more than two-thirds of the patients had lung dysfunction, and restrictive lung diseases accounted for the largest share. In a retrospective study that Eight weeks after hospital discharge, Maurizio Marvisibro conducted a study on 90 patients admitted to the respiratory department of the Istituto Figlie di San Camillo, Cremona (Northern Italy) with SARS-CoV-2 pneumonia. Evidence in favor of early lung fibrosis in 25% of patients was shown (\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e) and in another study, in the examination of patients three months after discharge, according to the fibrotic bands that were seen in the CT scan of one-fifth of the patients, it was suggested that some lung injuries may be stable and lead to become stable fibrotic changes in the lung (\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e), which can justify the high percentage of patients with dysfunction, especially patients of the restrictive type, in the second follow-up, which was done one year after the disease, 54.8% of pulmonary dysfunction was 17.1% less than the first time, which was more than the reduction in obstructive diseases. During the autopsy of lung tissues from 38 patients who died of COVID-19, pathological changes in the lungs of the patients in the form of diffuse alveolar damage, formation of hyaline membrane, interstitial edema, and type 2 alveolar epithelial cells were identified may be able to justify the results obtained. In other similar studies, a significant percentage of patients had lung function disorders between three and six months after discharge (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e), but the percentage of pulmonary function disorders in our study is significantly higher than this. It was studied that one of the reasons it seems that a significant number of hospitalized patients were workers who previously worked in the steel, iron, copper, and cement industries, which can increase the susceptibility to chronic lung diseases (\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e). Also, a study conducted in Kerman in 2013 showed that high occupational exposure to dust particles leads to respiratory symptoms, radiographic abnormalities, and decreased lung function (\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e), so many of these patients may have already had lung problems due to occupational exposure. On the other hand, Kerman is one of the desert cities in the southeast of Iran, which faces sandstorms and increased dust in the air during certain seasons of the year (\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e). According to a study conducted in Iran between 1990 and 2019, the province (Kerman) had the highest age-standardized mortality rate due to chronic respiratory diseases four times higher than the province (Tehran) and the attributable risk factors that caused the most DALYs, Smoking, Air pollution, and Body Mass Index were high (\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e). In our study, 47.2% of patients were housewives, according to a study conducted on rural housewives in Isfahan. Baking bread, weaving carpets, and using fossil fuels were significant risk factors for all lung diseases (\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eAlso, in our first follow-up, 67.2% of patients had some degree of Dyspnea, and more than half of the patients had exertional dyspnea, which was higher in severe groups of patients who were hospitalized in the ICU and the second follow-up, the percentage of patients with Dyspnea was reduced by almost half, and exertional dyspnea was almost two-thirds of the first time. In other similar studies, Dyspnea or continuous exertional dyspnea was one of the main complaints of patients with COVID-19 after discharge from the hospital (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e, \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e, \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e, \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e). However, in the study of Mattia Bellan and his colleagues, the proportion of patients with Dyspnea and chest pain did not change from 4 months to 12 months of follow-up (\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e). Also, patients who recovered from SARS complained of Dyspnea in the early rehabilitation phase (\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e). Of course, there is a possibility that Dyspnea in these patients can be caused by lung, heart, and neuromuscular problems, except for the effects of the coronavirus (\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e, \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIn addition, a higher BMI was associated with persistent Dyspnea one year after discharge (\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e), and in our study, both groups of patients with severe and moderate disease were overweight. Other studies showed that patients with CT Abnormally had a higher BMI, obese patients were more likely to be infected with severe COVID-19, and a significant proportion of patients with severe disease severity had a BMI of 30 or higher (\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e, \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e, \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e). In our study, in both groups of patients with moderate and severe disease severity, high blood pressure was more common than other underlying diseases, and this result was consistent with many studies (\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e, \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e, \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e, \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e). Above, it was considered as one of the risk factors for the lasting consequences of COVID-19 (\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e). Also, in our study, in the group of patients with severe disease severity, the percentage of people with diabetes, kidney disease, and malignancy was higher than in patients with moderate disease severity, and in other studies, the prevalence of diabetes in the severe group was significantly higher than in the moderate group. (\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e, \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e, \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e). Therefore, when treating severe patients, doctors need to keep in mind the control of diabetes in a balanced way along with the treatment of viral infection, so it is necessary to follow up and control diabetes in the management of patients with COVID-19 after discharge (\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIn the current study, patients with more severe diseases were older than patients with moderate disease severity, which was consistent with Qian Wu\u0026rsquo;s study (\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e), in a study conducted in one of Iran's hospitals, it also showed that most of the patients hospitalized due to COVID-19 and Most of the patients with critical conditions were more than or equal to 75 years old (\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e) and another study also confirms this fact that older patients are more likely to be affected by the more severe COVID-19 (\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eOne of the strong points of this study is the follow-up of two time points after discharge, which allows for comparison over time.\u003c/p\u003e \u003cp\u003eThis study has several limitations:\u003c/p\u003e \u003cp\u003eWe didn't have any information about lung function (spirometry test results) before COVID-19, The observed pulmonary dysfunction cannot be directly attributed to COVID-19, It is possible that a large number of patients who agreed to performed the spirometry test were people who had more pulmonary problems before. A significant 4% of the participants did not want to do a spirometry test.\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eBy summarizing the results of pulmonary function tests by evaluating respiratory symptoms and completing the results, two main patterns of pulmonary involvement after COVID-19 can be distinguished: 1-obstructive pattern and 2-restrictive pattern, which in our study, one year after discharge A significant number of patients had pulmonary dysfunction and it was also seen in this study that obstructive complications are more than restrictive complications, but no significant difference in obstructive and restrictive patterns were observed between the two groups of patients with moderate and severe disease severity.\u003c/p\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003esuggestions\u003c/h2\u003e \u003cp\u003eIn this study, during four months (from eight months after discharge to one year after discharge), the process of increasing the volume of the lungs continued, but there was no complete recovery. Therefore, it is better to continue this investigation until the process of increasing the lung volume is stopped.\u003c/p\u003e \u003c/div\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eCOVID-19 Coronavirus disease 2019\u003c/p\u003e\n\u003cp\u003eFEV1 Forced expiratory volume in 1 second\u003c/p\u003e\n\u003cp\u003eFVC Forced vital capacity\u003c/p\u003e\n\u003cp\u003eFEV1/FVC Forced expiratory ratio\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eDLCO Diffusing lung capacity for carbon monoxide\u003c/p\u003e\n\u003cp\u003e6MWT: 6-Minute Walk Test\u003c/p\u003e\n\u003cp\u003e\u003cspan dir=\"RTL\"\u003e\u0026nbsp;\u003c/span\u003e\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgments\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors would like to express their gratitude to the medical records department of Afzali pour Kerman Hospital, the staff of Dr. Yazdani\u0026apos;s office as well as the patients and their families, Dr. Kaveh Rafieipour, Dr.Mozhdeh Nazari and Sajjad Arefi for their cooperation in implementing this project.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003evazirinejad, Ahmadinia, Rezaeian, and Nazari\u003cspan dir=\"RTL\"\u003e\u0026nbsp;\u003c/span\u003econceived and designed the study. Nazari\u003cspan dir=\"RTL\"\u003e\u0026nbsp;\u003c/span\u003eand Yazdani collected clinical data. Vazirinejad, Ahmadinia, Rezaeian, Nazari, Yazdani, and Doraki analyzed and interpreted the data. Nazari, Vazirinejad, and Ahmadinia, wrote the manuscript. All authors reviewed and approved the final version of the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study is supported by Rafsanjan University of Medical Sciences.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eData is provided within the supplementary information file.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe studies involving humans were approved by this study is approved by the ethical committee of \u0026nbsp;Rafsanjan University of Medical Sciences with the number of IR.RUMS.REC.1401.065, all the methods were performed in accordance with the relevant guidelines and regulation. The studies were conducted in accordance with the local legislation and institutional requirements. The participants provided their written informed consent to participate in this study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no competing interests.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003e\u0026Ntilde;amendys-Silva SA. ECMO for ARDS due to COVID-19. Heart \u0026amp; Lung: The Journal of Cardiopulmonary and Acute Care. 2020 Jul 1;49(4):348-9\u003cspan dir=\"RTL\"\u003e.\u003c/span\u003e\u003c/li\u003e\n\u003cli\u003ewebda.behdasht.gov.ir\u003c/li\u003e\n\u003cli\u003eWiersinga WJ, Rhodes A, Cheng AC, Peacock SJ, Prescott HC. Pathophysiology, transmission, diagnosis, and treatment of coronavirus disease 2019 (COVID-19): a review. Jama. 2020 Aug 25;324(8):782-93.\u003c/li\u003e\n\u003cli\u003eBoseley S, Devlin H, Belam M. 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Eight months follow-up study on pulmonary function, lung radiographic, and related physiological characteristics in COVID-19 survivors. Scientific reports. 2021 Jul 5;11(1):1-3.\u003c/li\u003e\n\u003cli\u003eMarvisi M, Ferrozzi F, Balzarini L, Mancini C, Ramponi S, Uccelli M. First report on clinical and radiological features of COVID-19 pneumonitis in a Caucasian population: factors predicting fibrotic evolution. International Journal of Infectious Diseases. 2020 Oct 1;99:485-8.\u003c/li\u003e\n\u003cli\u003eGeorge PM, Wells AU, Jenkins RG. Pulmonary fibrosis and COVID-19: the potential role for antifibrotic therapy. The Lancet Respiratory Medicine. 2020 Aug 1;8(8):807-15.\u003c/li\u003e\n\u003cli\u003eWu Q, Zhong L, Li H, Guo J, Li Y, Hou X, Yang F, Xie Y, Li L, Xing Z. A follow-up study of lung function and chest computed tomography at 6 months after discharge in patients with coronavirus disease 2019. 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National, subnational and risk attributed burden of chronic respiratory diseases in Iran from 1990 to 2019. Respiratory Research. 2023 Dec;24(1):1-6.\u003c/li\u003e\n\u003cli\u003eGolshan M, Faghihi M, Marandi MM. Indoor women jobs and pulmonary risks in rural areas of Isfahan, Iran, 2000. Respiratory medicine. 2002 Jun 1;96(6):382-8.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"COVID-19, Respiratory Function Tests, Cohort Studies","lastPublishedDoi":"10.21203/rs.3.rs-3908644/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-3908644/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground and purpose\u003c/h2\u003e \u003cp\u003eAs the number of COVID-19 survivors increased, countless people have been affected by the pulmonary consequences of this infection. They are likely to suffer permanent lung damage and long-term pulmonary dysfunction (\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e). The present study aimed at investigating the long-term term effect of COVID-19 infection on lung volumes and respiratory indices among hospitalized patients up to one year after discharge from the hospital conducting a population-based cohort study.\u003c/p\u003e\u003ch2\u003eMaterials and Methods\u003c/h2\u003e \u003cp\u003eThis population-based cohort study was conducted by inviting patients with COVID-19 admitted to Afzalipour Hospital in Kerman (a reference hospital during the pandemic in Kerman province, Iran) during September, October, and November 2022, to the present survey. Respondents who agreed to help with the survey were followed for one year, and they were examined in terms of respiratory outcomes on two occasions at eight months and one year after discharge from the hospital. A spirometry test was also performed for the satisfied patients. Demographic information and hospitalization time information were extracted from their hospital records. Data were analyzed using SPSS and R software.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eOut of 1954 hospitalized patients, 500 patients accepted the study invitation. In terms of disease severity, 61 patients (12.2%) were classified as suffering from severe disease and 439 patients (87.8%) were classified as moderate. Cough and shortness of breath during activity were common symptoms that were observed in the first follow-up, although these symptoms were more common in patients with severe disease than in patients with moderate disease (P\u0026thinsp;=\u0026thinsp;0.012 and P\u0026thinsp;=\u0026thinsp;0.023, respectively). Despite decreasing patients' breathing problems during the first follow-up, a significant percentage of patients were, still, suffering from these problems 12 months after discharge from the hospital. Among the patients who performed spirometry, 54.9% had low lung volume, 10.8% were classified as obstructive lung patients, and 44.1% were reported as restrictive lung patients.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eCOVID-19 causes long-term complications in the lungs that continue for at least one year after the infection. Our results showed that Obstructive complications are more frequent than limiting complications.\u003c/p\u003e","manuscriptTitle":"The long-term effect of COVID-19 infection on lung volumes and respiratory indices among hospitalized patients up to one year after discharging from hospital: a population- based cohort study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-02-13 19:46:05","doi":"10.21203/rs.3.rs-3908644/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"2f4a6814-8548-41e0-8343-71a3bfe7b2b0","owner":[],"postedDate":"February 13th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2024-03-18T05:03:02+00:00","versionOfRecord":[],"versionCreatedAt":"2024-02-13 19:46:05","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-3908644","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-3908644","identity":"rs-3908644","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}