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1.
Eur J Immunol ; 52(8): 1285-1296, 2022 Aug.
Article in English | MEDLINE | ID: covidwho-1819355

ABSTRACT

Severe coronavirus disease 19 (COVID-19) manifests with systemic immediate proinflammatory innate immune activation and altered iron turnover. Iron homeostasis, differentiation, and function of myeloid leukocytes are interconnected. Therefore, we characterized the cellularity, surface marker expression, and iron transporter phenotype of neutrophils and monocyte subsets in COVID-19 patients within 72 h from hospital admission, and analyzed how these parameters relate to infection severity. Between March and November 2020, blood leukocyte samples from hospitalized COVID-19 patients (n = 48) and healthy individuals (n = 7) were analyzed by flow cytometry enabling comparative analysis of 40 features. Inflammation-driven neutrophil expansion, depletion of CD16+ nonclassical monocytes, and changes in surface expression of neutrophil and monocyte CD64 and CD86 were associated with COVID-19 severity. By unsupervised self-organizing map clustering, four patterns of innate myeloid response were identified and linked to varying levels of systemic inflammation, altered cellular iron trafficking and the severity of disease. These alterations of the myeloid leukocyte compartment during acute COVID-19 may be hallmarks of inefficient viral control and immune hyperactivation and may help at risk prediction and treatment optimization.


Subject(s)
COVID-19 , Monocytes , Humans , Inflammation , Inpatients , Iron/metabolism , Phenotype
3.
Front Med (Lausanne) ; 9: 792881, 2022.
Article in English | MEDLINE | ID: covidwho-1775691

ABSTRACT

Background: Coronavirus Disease-19 (COVID-19) convalescents are at risk of developing a de novo mental health disorder or worsening of a pre-existing one. COVID-19 outpatients have been less well characterized than their hospitalized counterparts. The objectives of our study were to identify indicators for poor mental health following COVID-19 outpatient management and to identify high-risk individuals. Methods: We conducted a binational online survey study with adult non-hospitalized COVID-19 convalescents (Austria/AT: n = 1,157, Italy/IT: n = 893). Primary endpoints were positive screening for depression and anxiety (Patient Health Questionnaire; PHQ-4) and self-perceived overall mental health (OMH) and quality of life (QoL) rated with 4 point Likert scales. Psychosocial stress was surveyed with a modified PHQ stress module. Associations of the mental health and QoL with socio-demographic, COVID-19 course, and recovery variables were assessed by multi-parameter Random Forest and Poisson modeling. Mental health risk subsets were defined by self-organizing maps (SOMs) and hierarchical clustering algorithms. The survey analyses are publicly available (https://im2-ibk.shinyapps.io/mental_health_dashboard/). Results: Depression and/or anxiety before infection was reported by 4.6% (IT)/6% (AT) of participants. At a median of 79 days (AT)/96 days (IT) post-COVID-19 onset, 12.4% (AT)/19.3% (IT) of subjects were screened positive for anxiety and 17.3% (AT)/23.2% (IT) for depression. Over one-fifth of the respondents rated their OMH (AT: 21.8%, IT: 24.1%) or QoL (AT: 20.3%, IT: 25.9%) as fair or poor. Psychosocial stress, physical performance loss, high numbers of acute and sub-acute COVID-19 complaints, and the presence of acute and sub-acute neurocognitive symptoms (impaired concentration, confusion, and forgetfulness) were the strongest correlates of deteriorating mental health and poor QoL. In clustering analysis, these variables defined subsets with a particularly high propensity of post-COVID-19 mental health impairment and decreased QoL. Pre-existing depression or anxiety (DA) was associated with an increased symptom burden during acute COVID-19 and recovery. Conclusion: Our study revealed a bidirectional relationship between COVID-19 symptoms and mental health. We put forward specific acute symptoms of the disease as "red flags" of mental health deterioration, which should prompt general practitioners to identify non-hospitalized COVID-19 patients who may benefit from early psychological and psychiatric intervention. Clinical Trial Registration: [ClinicalTrials.gov], identifier [NCT04661462].

4.
Radiology ; 304(2): 462-470, 2022 Aug.
Article in English | MEDLINE | ID: covidwho-1765163

ABSTRACT

Background The long-term pulmonary sequelae of COVID-19 is not well known. Purpose To characterize patterns and rates of improvement of chest CT abnormalities 1 year after COVID-19 pneumonia. Materials and Methods This was a secondary analysis of a prospective, multicenter observational cohort study conducted from April 29 to August 12, 2020, to assess pulmonary abnormalities at chest CT approximately 2, 3, and 6 months and 1 year after onset of COVID-19 symptoms. Pulmonary findings were graded for each lung lobe using a qualitative CT severity score (CTSS) ranging from 0 (normal) to 25 (all lobes involved). The association of demographic and clinical factors with CT abnormalities after 1 year was assessed with logistic regression. The rate of change of the CTSS at follow-up CT was investigated by using the Friedmann test. Results Of 142 enrolled participants, 91 underwent a 1-year follow-up CT examination and were included in the analysis (mean age, 59 years ± 13 [SD]; 35 women [38%]). In 49 of 91 (54%) participants, CT abnormalities were observed: 31 of 91 (34%) participants showed subtle subpleural reticulation, ground-glass opacities, or both, and 18 of 91 (20%) participants had extensive ground-glass opacities, reticulations, bronchial dilation, microcystic changes, or a combination thereof. At multivariable analysis, age of more than 60 years (odds ratio [OR], 5.8; 95% CI: 1.7, 24; P = .009), critical COVID-19 severity (OR, 29; 95% CI: 4.8, 280; P < .001), and male sex (OR, 8.9; 95% CI: 2.6, 36; P < .001) were associated with persistent CT abnormalities at 1-year follow-up. Reduction of CTSS was observed in participants at subsequent follow-up CT (P < .001); during the study period, 49% (69 of 142) of participants had complete resolution of CT abnormalities. Thirty-one of 49 (63%) participants with CT abnormalities showed no further improvement after 6 months. Conclusion Long-term CT abnormalities were common 1 year after COVID-19 pneumonia. © RSNA, 2022 Online supplemental material is available for this article. See also the editorial by Leung in this issue.


Subject(s)
COVID-19 , Lung Injury , COVID-19/diagnostic imaging , Female , Humans , Lung/diagnostic imaging , Male , Middle Aged , Prospective Studies , SARS-CoV-2 , Tomography, X-Ray Computed/methods
5.
Sci Rep ; 12(1): 3677, 2022 03 07.
Article in English | MEDLINE | ID: covidwho-1730313

ABSTRACT

The CovILD study is a prospective, multicenter, observational cohort study to systematically follow up patients after coronavirus disease-2019 (COVID-19). We extensively evaluated 145 COVID-19 patients at 3 follow-up visits scheduled for 60, 100, and 180 days after initial confirmed diagnosis based on typical symptoms and a positive reverse transcription-polymerase chain reaction (RT-PCR) for severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2). We employed comprehensive pulmonary function and laboratory tests, including serum concentrations of IgG against the viral spike (S) glycoprotein, and compared the results to clinical data and chest computed tomography (CT). We found that at the 60 day follow-up, 131 of 145 (90.3%) participants displayed S-specific serum IgG levels above the cut-off threshold. Notably, the highly elevated IgG levels against S glycoprotein positively correlated with biomarkers of immune activation and negatively correlated with pulmonary function and the extent of pulmonary CT abnormalities. Based on the association between serum S glycoprotein-specific IgG and clinical outcome, we generated an S-specific IgG-based recovery score that, when applied in the early convalescent phase, accurately predicted delayed pulmonary recovery after COVID-19. Therefore, we propose that S-specific IgG levels serve as a useful immunological surrogate marker for identifying at-risk individuals with persistent pulmonary injury who may require intensive follow-up care after COVID-19.


Subject(s)
COVID-19/immunology , Immunoglobulin G/immunology , Lung/pathology , Spike Glycoprotein, Coronavirus/immunology , COVID-19/pathology , Female , Humans , Male , Middle Aged , Patient Acuity , Prospective Studies , Respiratory Function Tests , Reverse Transcriptase Polymerase Chain Reaction
6.
Elife ; 112022 02 08.
Article in English | MEDLINE | ID: covidwho-1675184

ABSTRACT

Background: The optimal procedures to prevent, identify, monitor, and treat long-term pulmonary sequelae of COVID-19 are elusive. Here, we characterized the kinetics of respiratory and symptom recovery following COVID-19. Methods: We conducted a longitudinal, multicenter observational study in ambulatory and hospitalized COVID-19 patients recruited in early 2020 (n = 145). Pulmonary computed tomography (CT) and lung function (LF) readouts, symptom prevalence, and clinical and laboratory parameters were collected during acute COVID-19 and at 60, 100, and 180 days follow-up visits. Recovery kinetics and risk factors were investigated by logistic regression. Classification of clinical features and participants was accomplished by unsupervised and semi-supervised multiparameter clustering and machine learning. Results: At the 6-month follow-up, 49% of participants reported persistent symptoms. The frequency of structural lung CT abnormalities ranged from 18% in the mild outpatient cases to 76% in the intensive care unit (ICU) convalescents. Prevalence of impaired LF ranged from 14% in the mild outpatient cases to 50% in the ICU survivors. Incomplete radiological lung recovery was associated with increased anti-S1/S2 antibody titer, IL-6, and CRP levels at the early follow-up. We demonstrated that the risk of perturbed pulmonary recovery could be robustly estimated at early follow-up by clustering and machine learning classifiers employing solely non-CT and non-LF parameters. Conclusions: The severity of acute COVID-19 and protracted systemic inflammation is strongly linked to persistent structural and functional lung abnormality. Automated screening of multiparameter health record data may assist in the prediction of incomplete pulmonary recovery and optimize COVID-19 follow-up management. Funding: The State of Tyrol (GZ 71934), Boehringer Ingelheim/Investigator initiated study (IIS 1199-0424). Clinical trial number: ClinicalTrials.gov: NCT04416100.


Subject(s)
COVID-19/therapy , Lung Diseases/epidemiology , Lung Diseases/physiopathology , Adult , Aged , COVID-19/epidemiology , COVID-19/rehabilitation , Female , Follow-Up Studies , Humans , Intensive Care Units , Logistic Models , Longitudinal Studies , Lung Diseases/diagnosis , Male , Middle Aged , Phenotype , Prospective Studies , Risk Factors , SARS-CoV-2 , Tomography, X-Ray Computed/methods
7.
2021.
Preprint in English | Other preprints | ID: ppcovidwho-296047

ABSTRACT

Background COVID-19 is associated with long-term pulmonary symptoms and may result in chronic pulmonary impairment. The optimal procedures to prevent, identify, monitor, and treat these pulmonary sequelae are elusive. Research question To characterize the kinetics of pulmonary recovery, risk factors and constellations of clinical features linked to persisting radiological lung findings after COVID-19. Study design and methods A longitudinal, prospective, multicenter, observational cohort study including COVID-19 patients (n = 108). Longitudinal pulmonary imaging and functional readouts, symptom prevalence, clinical and laboratory parameters were collected during acute COVID-19 and at 60-, 100- and 180-days follow-up visits. Recovery kinetics and risk factors were investigated by logistic regression. Classification of clinical features and study participants was accomplished by k-means clustering, the k-nearest neighbors (kNN), and naive Bayes algorithms. Results At the six-month follow-up, 51.9% of participants reported persistent symptoms with physical performance impairment (27.8%) and dyspnea (24.1%) being the most frequent. Structural lung abnormalities were still present in 45.4% of the collective, ranging from 12% in the outpatients to 78% in the subjects treated at the ICU during acute infection. The strongest risk factors of persisting lung findings were elevated interleukin-6 (IL6) and C-reactive protein (CRP) during recovery and hospitalization during acute COVID-19. Clustering analysis revealed association of the lung lesions with increased anti-S1/S2 antibody, IL6, CRP, and D-dimer levels at the early follow-up suggesting non-resolving inflammation as a mechanism of the perturbed recovery. Finally, we demonstrate the robustness of risk class assignment and prediction of individual risk of delayed lung recovery employing clustering and machine learning algorithms. Interpretation Severity of acute infection, and systemic inflammation is strongly linked to persistent post-COVID-19 lung abnormality. Automated screening of multi-parameter health record data may assist the identification of patients at risk of delayed pulmonary recovery and optimize COVID-19 follow-up management. Clinical Trial Registration ClinicalTrials.gov: NCT04416100

8.
Clin Infect Dis ; 2021 Nov 26.
Article in English | MEDLINE | ID: covidwho-1545917

ABSTRACT

BACKGROUND: Long COVID, defined as presence of COVID-19 symptoms 28 days or more after clinical onset, is an emerging challenge to healthcare systems. The objective of this study was to explore recovery phenotypes in non-hospitalized COVID-19 individuals. METHODS: A dual cohort, online survey study was conducted between September 2020 and July 2021 in the neighboring European regions Tyrol (TY, Austria, n = 1157) and South Tyrol (STY, Italy, n = 893). Data on demographics, comorbidities, COVID-19 symptoms and recovery adult outpatients were collected. Phenotypes of acute COVID-19, post-acute sequelae and risk of protracted recovery were explored by semi-supervised clustering and multi-parameter LASSO modeling. RESULTS: Working age subjects (TY: 43 yrs (IQR: 31 - 53), STY: 45 yrs (IQR: 35 - 55)) and females (TY: 65.1%, STY: 68.3%) predominated the study cohorts. Nearly half of the participants (TY: 47.6%, STY: 49.3%) reported symptom persistence beyond 28 days. Two acute COVID-19 phenotypes were discerned: the non-specific infection phenotype and the multi-organ phenotype (MOP). Acute MOP symptoms encompassing multiple neurological, cardiopulmonary, gastrointestinal and dermatological complaints were linked to elevated risk of protracted recovery. The major subset of long COVID individuals (TY: 49.3%, STY: 55.6%) displayed no persistent hyposmia or hypogeusia but high counts of post-acute MOP symptoms and poor self-reported physical recovery. CONCLUSION: The results of our two-cohort analysis delineated phenotypic diversity of acute and post-acute COVID-19 manifestations in home-isolated patients which needs to be considered for predicting protracted convalescence and allocation of medical resources.

9.
Qual Life Res ; 31(5): 1401-1414, 2022 May.
Article in English | MEDLINE | ID: covidwho-1439744

ABSTRACT

PURPOSE: To assess patient characteristics associated with health-related quality of life (HR-QoL) and its mental and physical subcategories 3 months after diagnosis with COVID-19. METHODS: In this prospective multicentre cohort study, HR-QoL was assessed in 90 patients using the SF-36 questionnaire (36-item Short Form Health Survey), which consists of 8 health domains that can be divided into a mental and physical health component. Mental health symptoms including anxiety, depression, and post-traumatic stress disorders were evaluated using the Hospital Anxiety and Depression Scale (HADS) and Post-traumatic Stress Disorder Checklist-5 (PCL-5) 3 months after COVID-19. Using descriptive statistics and multivariable regression analysis, we identified factors associated with impaired HR-QoL 3 months after COVID-19 diagnosis. RESULTS: Patients were 55 years of age (IQR, 49-63; 39% women) and were classified as severe (23%), moderate (57%), or mild (20%) according to acute disease severity. HR-QoL was impaired in 28/90 patients (31%). Younger age [per year, adjOR (95%CI) 0.94 (0.88-1.00), p = 0.049], longer hospitalization [per day, adjOR (95%CI) 1.07 (1.01-1.13), p = 0.015], impaired sleep [adjOR (95%CI) 5.54 (1.2-25.61), p = 0.028], and anxiety [adjOR (95%CI) 15.67 (3.03-80.99), p = 0.001) were independently associated with impaired HR-QoL. Twenty-nine percent (n = 26) scored below the normal range on the mental health component of the SF-36 and independent associations emerged for anxiety, depression, and self-reported numbness. Impairments in the physical health component of the SF-36 were reported by 12 (13%) patients and linked to hypogeusia and fatigue. CONCLUSION: Every third patient reported a reduction in HR-QoL 3 months after COVID-19 diagnosis and impairments were more prominent in mental than physical well-being.


Subject(s)
COVID-19 , Anxiety/epidemiology , COVID-19/epidemiology , COVID-19 Testing , Cohort Studies , Depression/epidemiology , Depression/psychology , Female , Humans , Male , Prospective Studies , Quality of Life/psychology
10.
Front Physiol ; 12: 688946, 2021.
Article in English | MEDLINE | ID: covidwho-1348532

ABSTRACT

In this review, we discuss spatiotemporal kinetics and inflammatory signatures of innate immune cells specifically found in response to SARS-CoV-2 compared to influenza virus infection. Importantly, we cover the current understanding on the mechanisms by which SARS-CoV-2 may fail to engage a coordinated type I response and instead may lead to exaggerated inflammation and death. This knowledge is central for the understanding of available data on specialized pro-resolving lipid mediators in severe SARS-CoV-2 infection pointing toward inhibited E-series resolvin synthesis in severe cases. By investigating a publicly available RNA-seq database of bronchoalveolar lavage cells from patients affected by COVID-19, we moreover offer insights into the regulation of key enzymes involved in lipid mediator synthesis, critically complementing the current knowledge about the mediator lipidome in severely affected patients. This review finally discusses different potential approaches to sustain the synthesis of 3-PUFA-derived pro-resolving lipid mediators, including resolvins and lipoxins, which may critically aid in the prevention of acute lung injury and death from COVID-19.

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