Olga I Savushkina, Elena S Muraveva, Irina V Zhitareva, Galina V Nekludova, Malika Kh Mustafina, Sergey N Avdeev
{"title":"预测 COVID-19 肺炎幸存者肺弥散能力受损的情况。","authors":"Olga I Savushkina, Elena S Muraveva, Irina V Zhitareva, Galina V Nekludova, Malika Kh Mustafina, Sergey N Avdeev","doi":"10.21037/jtd-24-1118","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>Patients surviving the coronavirus disease 2019 (COVID-19) are reported to explore pulmonary sequelae. It is challenging to provide pulmonary function tests (PFTs) during the pandemic of this contagious diseases because of the difficulty related to infection control risks. This study aims to identify important predictors of lung diffusion capacity impairment in COVID-19 survivors after hospital discharge.</p><p><strong>Methods: </strong>The retrospective cohort study included 341 patients after COVID-19. The parameters of spirometry, body plethysmography, lung diffusion capacity for carbon monoxide (DLco), and the worst chest computed tomography (CT) scan in the acute phase of COVID-19 (CT<sub>max</sub>, %) were assessed. Multivariable logistic regression analysis for exploring risk factors associated with lung diffusion capacity impairment was used. The receiver operating characteristic (ROC) curve of multivariate observation and the area under the curve (AUC) were used to assess the performance of a model.</p><p><strong>Results: </strong>At the time of the analysis, 64.8% (221/341) patients participated in follow-up visits on 90 days, 23.5% (80/341) on 90-180 days, and 11.7% (40/341) on more than 180 days after the onset of COVID-19 symptoms. The median CT<sub>max</sub> was 50% (50% of the lung area was involved in a pathological process according to a semi-quantitative CT score). Abnormal DLco (<80% of predicted) was recorded in 60.4% cases. The predictors such as age, gender, body mass index (BMI), CT<sub>max</sub>, and the time interval between the COVID-19 symptoms onset and follow-up PFTs were encapsulated in the logistic regression analysis to explore the prediction of reduced DLco. Backward stepwise regression was applied to eliminate insignificant predictors. It was found that CT<sub>max</sub> was important predictor of impaired DLco. AUC value was 0.780 [95% confidential interval (CI): 0.723-0.837, P<0.001]. The sensitivity and specificity in the training group were 80% and 67%, respectively. The odds ratio (OR) showed that CT<sub>max</sub> =45% and more in the acute phase of COVID-19 was significantly associated with reduced DLco during 6 months after COVID-19 (OR 1.21, 95% CI: 1.095-1.334; P<0.05).</p><p><strong>Conclusions: </strong>Pulmonary interstitial damage caused by severe acute respiratory syndrome-related coronavirus 2 (SARS-CoV-2) definitely contributes to reduced DLco after hospital discharge. This indicates that analysis of CT scans during the acute phase of COVID-19 may have prognostic relevance for abnormal DLco.</p>","PeriodicalId":17542,"journal":{"name":"Journal of thoracic disease","volume":"16 11","pages":"7282-7289"},"PeriodicalIF":2.1000,"publicationDate":"2024-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11635270/pdf/","citationCount":"0","resultStr":"{\"title\":\"Prediction of impaired lung diffusion capacity in COVID-19 pneumonia survivors.\",\"authors\":\"Olga I Savushkina, Elena S Muraveva, Irina V Zhitareva, Galina V Nekludova, Malika Kh Mustafina, Sergey N Avdeev\",\"doi\":\"10.21037/jtd-24-1118\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Background: </strong>Patients surviving the coronavirus disease 2019 (COVID-19) are reported to explore pulmonary sequelae. It is challenging to provide pulmonary function tests (PFTs) during the pandemic of this contagious diseases because of the difficulty related to infection control risks. This study aims to identify important predictors of lung diffusion capacity impairment in COVID-19 survivors after hospital discharge.</p><p><strong>Methods: </strong>The retrospective cohort study included 341 patients after COVID-19. The parameters of spirometry, body plethysmography, lung diffusion capacity for carbon monoxide (DLco), and the worst chest computed tomography (CT) scan in the acute phase of COVID-19 (CT<sub>max</sub>, %) were assessed. Multivariable logistic regression analysis for exploring risk factors associated with lung diffusion capacity impairment was used. The receiver operating characteristic (ROC) curve of multivariate observation and the area under the curve (AUC) were used to assess the performance of a model.</p><p><strong>Results: </strong>At the time of the analysis, 64.8% (221/341) patients participated in follow-up visits on 90 days, 23.5% (80/341) on 90-180 days, and 11.7% (40/341) on more than 180 days after the onset of COVID-19 symptoms. The median CT<sub>max</sub> was 50% (50% of the lung area was involved in a pathological process according to a semi-quantitative CT score). Abnormal DLco (<80% of predicted) was recorded in 60.4% cases. The predictors such as age, gender, body mass index (BMI), CT<sub>max</sub>, and the time interval between the COVID-19 symptoms onset and follow-up PFTs were encapsulated in the logistic regression analysis to explore the prediction of reduced DLco. Backward stepwise regression was applied to eliminate insignificant predictors. It was found that CT<sub>max</sub> was important predictor of impaired DLco. AUC value was 0.780 [95% confidential interval (CI): 0.723-0.837, P<0.001]. The sensitivity and specificity in the training group were 80% and 67%, respectively. The odds ratio (OR) showed that CT<sub>max</sub> =45% and more in the acute phase of COVID-19 was significantly associated with reduced DLco during 6 months after COVID-19 (OR 1.21, 95% CI: 1.095-1.334; P<0.05).</p><p><strong>Conclusions: </strong>Pulmonary interstitial damage caused by severe acute respiratory syndrome-related coronavirus 2 (SARS-CoV-2) definitely contributes to reduced DLco after hospital discharge. This indicates that analysis of CT scans during the acute phase of COVID-19 may have prognostic relevance for abnormal DLco.</p>\",\"PeriodicalId\":17542,\"journal\":{\"name\":\"Journal of thoracic disease\",\"volume\":\"16 11\",\"pages\":\"7282-7289\"},\"PeriodicalIF\":2.1000,\"publicationDate\":\"2024-11-30\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11635270/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of thoracic disease\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.21037/jtd-24-1118\",\"RegionNum\":3,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2024/11/18 0:00:00\",\"PubModel\":\"Epub\",\"JCR\":\"Q3\",\"JCRName\":\"RESPIRATORY SYSTEM\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of thoracic disease","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.21037/jtd-24-1118","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2024/11/18 0:00:00","PubModel":"Epub","JCR":"Q3","JCRName":"RESPIRATORY SYSTEM","Score":null,"Total":0}
Prediction of impaired lung diffusion capacity in COVID-19 pneumonia survivors.
Background: Patients surviving the coronavirus disease 2019 (COVID-19) are reported to explore pulmonary sequelae. It is challenging to provide pulmonary function tests (PFTs) during the pandemic of this contagious diseases because of the difficulty related to infection control risks. This study aims to identify important predictors of lung diffusion capacity impairment in COVID-19 survivors after hospital discharge.
Methods: The retrospective cohort study included 341 patients after COVID-19. The parameters of spirometry, body plethysmography, lung diffusion capacity for carbon monoxide (DLco), and the worst chest computed tomography (CT) scan in the acute phase of COVID-19 (CTmax, %) were assessed. Multivariable logistic regression analysis for exploring risk factors associated with lung diffusion capacity impairment was used. The receiver operating characteristic (ROC) curve of multivariate observation and the area under the curve (AUC) were used to assess the performance of a model.
Results: At the time of the analysis, 64.8% (221/341) patients participated in follow-up visits on 90 days, 23.5% (80/341) on 90-180 days, and 11.7% (40/341) on more than 180 days after the onset of COVID-19 symptoms. The median CTmax was 50% (50% of the lung area was involved in a pathological process according to a semi-quantitative CT score). Abnormal DLco (<80% of predicted) was recorded in 60.4% cases. The predictors such as age, gender, body mass index (BMI), CTmax, and the time interval between the COVID-19 symptoms onset and follow-up PFTs were encapsulated in the logistic regression analysis to explore the prediction of reduced DLco. Backward stepwise regression was applied to eliminate insignificant predictors. It was found that CTmax was important predictor of impaired DLco. AUC value was 0.780 [95% confidential interval (CI): 0.723-0.837, P<0.001]. The sensitivity and specificity in the training group were 80% and 67%, respectively. The odds ratio (OR) showed that CTmax =45% and more in the acute phase of COVID-19 was significantly associated with reduced DLco during 6 months after COVID-19 (OR 1.21, 95% CI: 1.095-1.334; P<0.05).
Conclusions: Pulmonary interstitial damage caused by severe acute respiratory syndrome-related coronavirus 2 (SARS-CoV-2) definitely contributes to reduced DLco after hospital discharge. This indicates that analysis of CT scans during the acute phase of COVID-19 may have prognostic relevance for abnormal DLco.
期刊介绍:
The Journal of Thoracic Disease (JTD, J Thorac Dis, pISSN: 2072-1439; eISSN: 2077-6624) was founded in Dec 2009, and indexed in PubMed in Dec 2011 and Science Citation Index SCI in Feb 2013. It is published quarterly (Dec 2009- Dec 2011), bimonthly (Jan 2012 - Dec 2013), monthly (Jan. 2014-) and openly distributed worldwide. JTD received its impact factor of 2.365 for the year 2016. JTD publishes manuscripts that describe new findings and provide current, practical information on the diagnosis and treatment of conditions related to thoracic disease. All the submission and reviewing are conducted electronically so that rapid review is assured.