Incidence and affecting factors of pulmonary diffusing capacity impairment with COVID-19 survivors 18 months after discharge in Wuhan, China.
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ABSTRACT:
SUBMITTER: Xu B
PROVIDER: S-EPMC8710135 | biostudies-literature | 2022 Feb
REPOSITORIES: biostudies-literature
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Incidence and affecting factors of pulmonary diffusing capacity impairment with COVID-19 survivors 18 months after discharge in Wuhan, China.
Xu Bo B Ma Fu-Qiang FQ He Cong C Wu Zi-Qi ZQ Fan Cun-Yu CY Mao He-Rong HR Zhang Ji-Xian JX Yang Min M Hu Zuo-Wei ZW
The Journal of infection 20211225 2
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Project description:BackgroundSome COVID-19 survivors present lung function abnormalities during follow-up, particularly reduced carbon monoxide lung diffusing capacity (DLCO). To investigate risk factors and underlying pathophysiology, we compared the clinical characteristics and levels of circulating pulmonary epithelial and endothelial markers in COVID-19 survivors with normal or reduced DLCO 6 months after discharge.MethodsProspective, observational study. Clinical characteristics during hospitalization, and spirometry, DLCO and plasma levels of epithelial (surfactant protein (SP) A (SP-A), SP-D, Club cell secretory protein-16 (CC16) and secretory leukocyte protease inhibitor (SLPI)), and endothelial (soluble intercellular adhesion molecule 1 (sICAM-1), soluble E-selectin and Angiopoietin-2) 6 months after hospital discharge were determined in 215 COVID-19 survivors.ResultsDLCO was < 80% ref. in 125 (58%) of patients, who were older, more frequently smokers, had hypertension, suffered more severe COVID-19 during hospitalization and refer persistent dyspnoea 6 months after discharge. Multivariate regression analysis showed that age ≥ 60 years and severity score of the acute episode ≥ 6 were independent risk factors of reduced DLCO 6 months after discharge. Levels of epithelial (SP-A, SP-D and SLPI) and endothelial (sICAM-1 and angiopoietin-2) markers were higher in patients with reduced DLCO, particularly in those with DLCO ≤ 50% ref. Circulating SP-A levels were associated with the occurrence of acute respiratory distress syndrome (ARDS), organizing pneumonia and pulmonary embolisms during hospitalization.ConclusionsReduced DLCO is common in COVID-19 survivors 6 months after hospital discharge, especially in those older than 60 years with very severe acute disease. In these individuals, elevated levels of epithelial and endothelial markers suggest persistent lung damage.
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Project description:IntroductionThe COVID-19 patients in the convalescent stage noticeably have pulmonary diffusing capacity impairment (PDCI). The pulmonary diffusing capacity is a frequently-used indicator of the COVID-19 survivors' prognosis of pulmonary function, but the current studies focusing on prediction of the pulmonary diffusing capacity of these people are limited. The aim of this study was to develop and validate a machine learning (ML) model for predicting PDCI in the COVID-19 patients using routinely available clinical data, thus assisting the clinical diagnosis.MethodsCollected from a follow-up study from August to September 2021 of 221 hospitalized survivors of COVID-19 18 months after discharge from Wuhan, including the demographic characteristics and clinical examination, the data in this study were randomly separated into a training (80%) data set and a validation (20%) data set. Six popular machine learning models were developed to predict the pulmonary diffusing capacity of patients infected with COVID-19 in the recovery stage. The performance indicators of the model included area under the curve (AUC), Accuracy, Recall, Precision, Positive Predictive Value(PPV), Negative Predictive Value (NPV) and F1. The model with the optimum performance was defined as the optimal model, which was further employed in the interpretability analysis. The MAHAKIL method was utilized to balance the data and optimize the balance of sample distribution, while the RFECV method for feature selection was utilized to select combined features more favorable to machine learning.ResultsA total of 221 COVID-19 survivors were recruited in this study after discharge from hospitals in Wuhan. Of these participants, 117 (52.94%) were female, with a median age of 58.2 years (standard deviation (SD) = 12). After feature selection, 31 of the 37 clinical factors were finally selected for use in constructing the model. Among the six tested ML models, the best performance was accomplished in the XGBoost model, with an AUC of 0.755 and an accuracy of 78.01% after experimental verification. The SHAPELY Additive explanations (SHAP) summary analysis exhibited that hemoglobin (Hb), maximal voluntary ventilation (MVV), severity of illness, platelet (PLT), Uric Acid (UA) and blood urea nitrogen (BUN) were the top six most important factors affecting the XGBoost model decision-making.ConclusionThe XGBoost model reported here showed a good prognostic prediction ability for PDCI of COVID-19 survivors during the recovery period. Among the interpretation methods based on the importance of SHAP values, Hb and MVV contributed the most to the prediction of PDCI outcomes of COVID-19 survivors in the recovery period.
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Project description:Coronavirus disease 2019 (COVID-19) has gained prominence as a global pandemic. Studies have suggested that systemic alterations persist in a considerable proportion of COVID-19 patients after hospital discharge. We used proteomic and metabolomic approaches to analyze plasma samples obtained from 30 healthy subjects and 54 COVID-19 survivors 6 months after discharge from the hospital, including 30 non-severe and 24 severe patients. Through this analysis, we identified 1019 proteins and 1091 metabolites. The differentially expressed proteins and metabolites were then subjected to Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis. Among the patients evaluated, 41% of COVID-19 survivors reported at least one clinical symptom and 26.5% showed lung imaging abnormalities at 6 months after discharge. Plasma proteomics and metabolomics analysis showed that COVID-19 survivors differed from healthy control subjects in terms of the extracellular matrix, immune response, and hemostasis pathways. COVID-19 survivors also exhibited abnormal lipid metabolism, disordered immune response, and changes in pulmonary fibrosis-related proteins. COVID-19 survivors show persistent proteomic and metabolomic abnormalities 6 months after discharge from the hospital. Hence, the recovery period for COVID-19 survivors may be longer.
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Project description:Long-term outcome data of coronavirus disease 2019 (COVID-19) survivors are needed to understand their recovery trajectory and additional care needs. A prospective observational multicentre cohort study was carried out of adults hospitalised with COVID-19 from March through May 2020. Workup at 3 and 12 months following admission consisted of clinical review, pulmonary function testing, 6-min walk distance (6MWD), muscle strength, chest computed tomography (CT) and quality of life questionnaires. We evaluated factors correlating with recovery by linear mixed effects modelling. Of 695 patients admitted, 299 and 226 returned at 3 and 12 months, respectively (median age 59 years, 69% male, 31% severe disease). About half and a third of the patients reported fatigue, dyspnoea and/or cognitive impairment at 3 and 12 months, respectively. Reduced 6MWD and quadriceps strength were present in 20% and 60% at 3 months versus 7% and 30% at 12 months. A high anxiety score and body mass index correlated with poor functional recovery. At 3 months, diffusing capacity for carbon monoxide (DLCO) and total lung capacity were below the lower limit of normal in 35% and 18%, decreasing to 21% and 16% at 12 months; predictors of poor DLCO recovery were female sex, pre-existing lung disease, smoking and disease severity. Chest CT improved over time; 10% presented non-progressive fibrotic changes at 1 year. Many COVID-19 survivors, especially those with severe disease, experienced limitations at 3 months. At 1 year, the majority showed improvement to almost complete recovery. To identify additional care or rehabilitation needs, we recommend a timely multidisciplinary follow-up visit following COVID-19 admission.
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Project description:BackgroundThe Post-COVID-19 Functional Status (PCFS) scale is a validated tool used to measure the functional status of patients discharged from the hospital.ObjectivesTo describe the functional limitations of hospitalized COVID-19 patients at the time of discharge and two months afterward, and to identify risk factors associated with functional impairment.DesignRetrospective study.MethodsA total of 540 patients were included in this monocentric study. The functional status assessment using the PCFS scale and ventilatory needs were recorded at discharge and two months later. Univariate and multivariate analyses were performed in order to identify the risk factors of a high PCFS score.ResultsTwo months after discharge, the PCFS grade was 0 in 60,6% of the survivors, 1 in 24.5%, 2 in 6.9%, 3 in 2.8%, and 4 in 5.3%. The identified risk factors of a high PCFS scale were: age, arterial hypertension, diabetes mellitus, immunosuppression, cardiovascular disease, high need for oxygen and high News2 score at admission, a high percentage of ground glass at chest CT scan performed at admission or during follow-up, elevated leukocytes, neutrophils, LDH, D-dimers, procalcitonin, and serum creatinine levels. During the hospital stay, treatment with steroids, tocilizumab, longer duration of hospitalization, ICU admission and prolonged stay, and the occurrence of thromboembolic or hemorrhagic events were also significantly associated with a higher PCFS. Multivariate analysis identified that only age and a high News2 score at admission were independent risk factors of a low PCFS score.ConclusionMultiple risk factors for a higher PCFS score were identified, but only age and a high News2 score at admission were found to be independent risk factors.
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Project description:BackgroundThe significant morbidity caused by COVID-19 necessitates further understanding of long-term recovery. Our aim was to evaluate long-term lung function, exercise capacity, and radiological findings in patients after critical COVID-19.MethodsPatients who received treatment in ICU for COVID-19 between March 2020 and January 2021 underwent pulmonary function tests, a 6MWD and CXR 6 months after hospital discharge.ResultsA restrictive ventilatory defect was found in 35% (23/65) and an impaired diffusing capacity in 52% (32/62) at 6 months. The 6-minute walk distance was reduced in 33% (18/55), and 7% (4/55) of the patients had reduced exercise capacity. Chest X-ray was abnormal in 78% (52/67) at 6 months after hospital discharge.ConclusionA significant number of patients had persisting lung function impairment and radiological abnormalities at 6 months after critical COVID-19. Reduced exercise capacity was rare.
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