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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

After COVID-19, patients have reported various complaints such as fatigue, neurological symptoms, and insomnia. Immune-mediated changes in amino acid metabolism might contribute to the development of these symptoms. Patients who had had acute, PCR-confirmed COVID-19 infection about 60 days earlier were recruited within the scope of the prospective CovILD study. We determined the inflammatory parameters and alterations in tryptophan and phenylalanine metabolism in 142 patients cross-sectionally. Symptom persistence (pain, gastrointestinal symptoms, anosmia, sleep disturbance, and neurological symptoms) and patients’ physical levels of functioning were recorded. Symptoms improved in many patients after acute COVID-19 (n = 73, 51.4%). Still, a high percentage of patients had complaints, and women were affected more often. In many patients, ongoing immune activation (as indicated by high neopterin and CRP concentrations) and enhanced tryptophan catabolism were found. A higher phenylalanine to tyrosine ratio (Phe/Tyr) was found in women with a lower level of functioning. Patients who reported improvements in pain had lower Phe/Tyr ratios, while patients with improved gastrointestinal symptoms presented with higher tryptophan and kynurenine values. Our results suggest that women have persistent symptoms after COVID-19 more often than men. In addition, the physical level of functioning and the improvements in certain symptoms appear to be associated with immune-mediated changes in amino acid metabolism.

Background Long COVID, defined as the presence of coronavirus disease 2019 (COVID-19) symptoms ≥28 days after clinical onset, is an emerging challenge to healthcare systems. The objective of the current study was to explore recovery phenotypes in nonhospitalized individuals with COVID-19. 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 were collected on demographics, comorbid conditions, COVID-19 symptoms, and recovery in adult outpatients. Phenotypes of acute COVID-19, postacute sequelae, and risk of protracted recovery were explored using semi-supervised clustering and multiparameter least absolute shrinkage and selection operator (LASSO) modeling. Results Participants in the study cohorts were predominantly working age (median age [interquartile range], 43 [31–53] years] for TY and 45 [35–55] years] for STY) and female (65.1% in TY and 68.3% in STY). Nearly half (47.6% in TY and 49.3% in STY) reported symptom persistence beyond 28 days. Two acute COVID-19 phenotypes were discerned: the nonspecific infection phenotype and the multiorgan phenotype (MOP). Acute MOP symptoms encompassing multiple neurological, cardiopulmonary, gastrointestinal, and dermatological symptoms were linked to elevated risk of protracted recovery. The major subset of individuals with long COVID (49.3% in TY; 55.6% in STY) displayed no persistent hyposmia or hypogeusia but high counts of postacute MOP symptoms and poor self-reported physical recovery. Conclusions The results of our 2-cohort analysis delineated phenotypic diversity of acute and postacute COVID-19 manifestations in home-isolated patients, which must be considered in predicting protracted convalescence and allocating medical resources.

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.

BackgroundSequelae of Coronavirus disease 2019 (COVID-19) were investigated by both patient-initiated and academic initiatives. Patient’s subjective illness perceptions might differ from physician’s clinical assessment results. Herein, we explored factors influencing patient’s perception during COVID-19 recovery.MethodsParticipants of the prospective observation CovILD study with persistent somatic symptoms or cardiopulmonary findings at the clinical follow-up one year after COVID-19 were analyzed (n = 74). Explanatory variables included baseline demographic and comorbidity data, COVID-19 course and one-year follow-up data of persistent somatic symptoms, physical performance, lung function testing (LFT), chest computed tomography (CT) and trans-thoracic echocardiography (TTE). Factors affecting illness perception (Brief Illness Perception Questionnaire, BIPQ) were identified by penalized multi-parameter regression and unsupervised clustering.ResultsIn modeling, 47% of overall illness perception variance at one year after COVID-19 was attributed to fatigue intensity, reduced physical performance, hair loss and baseline respiratory comorbidity. Overall illness perception was independent of LFT results, pulmonary lesions in CT or heart abnormality in TTE. As identified by clustering, persistent somatic symptom count, fatigue, diminished physical performance, dyspnea, hair loss and sleep problems at the one-year follow-up and severe acute COVID-19 were associated with the BIPQ domains of concern, emotional representation, complaints, disease timeline and consequences.ConclusionPersistent somatic symptoms rather than clinical assessment results, revealing lung and heart abnormalities, impact on severity and quality of illness perception at one year after COVID-19 and may foster unhelpful coping mechanisms. Besides COVID-19 severity, individual illness perception should be taken into account when allocating rehabilitation and psychological therapy resources.Study registrationClinicalTrials.gov: NCT04416100.

Background Triggers of acute exacerbations of chronic obstructive pulmonary disease (AECOPD) are diverse, potentially including airborne pollutants. Objectives To analyze whether daily air pollution levels correlate with AECOPD frequency. Methods In this retrospective pilot-study, AECOPD frequency was recorded between 2010 and 2016 at the University Hospital of Innsbruck's emergency department and correlated with daily air quality parameters. Data was compared to pulmonary embolism (PE) frequency, a disease not directly involving the airways. Results In total, 669 AECOPD and 857 PE events were registered. Days with AECOPD revealed significantly higher concentrations of CO and SO2, whereas days with PE displayed an elevation of NO. Higher frequencies of AECOPD during winter months correlated with higher CO and SO2 levels, disclosing a seasonal trend, while no such pattern was observed for PE. Conclusion Air pollution is linked to AECOPD frequency, however, prospective studies are needed to confirm this possible, underrecognized trigger of AECOPD.

BackgroundOlfactory dysfunction (OD) often accompanies acute coronavirus disease 2019 (COVID-19) and its sequelae. Herein, we investigated OD during COVID-19 recovery in the context of other symptoms, quality of life, physical and mental health.MethodsSymptom recovery patterns were analyzed in a bi-national, ambulatory COVID-19 survey (n = 906, ≥ 90 days follow-up) and a multi-center observational cross-sectional cohort of ambulatory and hospitalized individuals (n = 108, 360 days follow-up) with multi-dimensional scaling, association rule mining and partitioning around medoids clustering.ResultsBoth in the ambulatory collective (72%, n = 655/906) and the cross-sectional ambulatory and hospitalized cohort (41%, n = 44/108) self-reported OD was frequent during acute COVID-19, displayed a slow recovery pace (ambulatory: 28 days, cross-sectional: 90 days median recovery time) and commonly co-occurred with taste disorders. In the ambulatory collective, a predominantly young, female, comorbidity-free group of convalescents with persistent OD and taste disorder (>90 days) was identified. This post-acute smell and taste disorder phenotype was characterized by a low frequency of other leading post-acute symptoms including fatigue, respiratory and neurocognitive complaints. Despite a protracted smell and taste dysfunction, this subset had high ratings of physical performance, mental health, and quality of life.ConclusionOur results underline the clinical heterogeneity of post-acute COVID-19 sequelae calling for tailored management strategies. The persistent smell and taste disorder phenotype may represent a distinct COVID-19 recovery pathway characterized by a good recovery of other COVID-19 related symptoms.Study registrationClinicalTrials.gov: NCT04661462 (ambulatory collective), NCT04416100 (cross-sectional cohort).

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

Background: Current evidence suggests an increased prevalence of iron deficiency (ID) and anemia in chronic obstructive pulmonary disease (COPD). ID and subsequent anemia can be due to iron losses via bleeding resulting in absolute ID or inflammation-driven retention of iron within macrophages resulting in functional ID and anemia of inflammation. Methods: This is a retrospective analysis of 204 non-exacerbated COPD patients in outpatient care. Current definitions of absolute and functional ID were applied to determine the prevalence of ID and to analyze associations to disease severity in terms of lung function parameters and clinical symptoms. Results: The studied cohort of COPD patients demonstrated a high prevalence of ID, ranging from 30 to 40% during the observation time. At the initial presentation, absolute or functional ID was found in 9.3% to 12.3% of COPD individuals, whereas combined forms of absolute and functional ID were most prevalent (25.9% of all individuals). The prevalence of ID increased during longitudinal follow-up (37 ± 15 months), and especially combined forms of ID were significantly related to anemia. Anemia prevalence ranged between 14.2% and 20.8% during the observation period and anemia was associated with lower FEV1, DLCOc, and CRP elevation. Accordingly, ID was associated with decreased FEV1, DLCOc, and an elevation in CRP. Conclusion: ID is common in COPD patients, but a uniform definition for accurate diagnosis does not exist. Prevalence of functional ID and anemia increased during follow-up. The associations of ID and anemia with reduced functional lung capacity and elevated inflammation may reflect a more severe COPD phenotype.

Anaemia is a highly prevalent condition, which negatively impacts on patients’ cardiovascular performance and quality of life. Anaemia is mainly caused by disturbances of iron homeostasis. While absolute iron deficiency mostly as a consequence of chronic blood loss or insufficient dietary iron absorption results in the emergence of iron deficiency anaemia, inflammation-driven iron retention in innate immune cells and blockade of iron absorption leads to the development of anaemia of chronic disease. Both, iron deficiency and anaemia have been linked to the clinical course of pulmonary hypertension. Various mechanistic links between iron homeostasis, anaemia, and pulmonary hypertension have been described and current treatment guidelines suggest regular iron status assessment and the implementation of iron supplementation strategies in these patients. The pathophysiology, diagnostic assessment as well as current and future treatment options concerning iron deficiency with or without anaemia in individuals suffering from pulmonary hypertension are discussed within this review.

Seasonal influenza is an important cause of morbidity and mortality worldwide and cardiac injuries are dangerous complications of influenza infection. Cardiac troponins are established biomarkers of myocardial damage.The aim of the study was to assess high sensitive Troponin-T (hsTnT) serum levels as a surrogate parameter of cardiac involvement in influenza patients.Cross-sectional analysis of 264 patients with laboratory-confirmed influenza virus infection. Routine laboratory parameters, hsTNT, and the history of cardiovascular disease were included in the analysis. Assessed prognostic endpoints were inpatient therapy requirement, death 30 days after hospitalization and acute cardiac events (ACE) defined as myocardial ischemia, heart failure or new arrhythmia requiring therapy.Eighty-four patients (31.8%) had increased hsTnT at the initial presentation and twenty patients (7.6%) experienced ACE. Patients with ACE had higher hsTnT (p 0.01) and CRP (p = 0.04) serum levels compared to patients who did not experience ACE. A binary logistic regression model to predict ACE revealed hsTnT (p 0.01) and CRP (p = 0.01) to significantly influence the odds for ACE. A hsTnT cut-off of 46,4 ng/l was identified as having the best discriminative potential to identify patients with ACE (sensitivity = 0.7, specificity = 0.8).To date, this is the largest available analysis of the specific cardiac marker hsTnT in patients with influenza. A slight elevation of hsTnT is a common feature of patients with influenza, however increased hsTnT also highlights a higher risk for cardiac complications and fatal outcome.

Background: Fatigue, sleep disturbance, and neurological symptoms during and after COVID-19 are common and might be associated with inflammation-induced changes in tryptophan (Trp) and phenylalanine (Phe) metabolism. Aim: This pilot study investigated interferon gamma inducible biochemical pathways (namely Trp catabolism, neopterin, tyrosine [Tyr], and nitrite formation) during acute COVID-19 and reconvalescence. Patients and methods: Thirty one patients with moderate to severe COVID-19 admitted to the University Hospital of Innsbruck in early 2020 (March-May) were followed up. Neurotransmitter precursors Trp, Phe, Tyr as well as kynurenine (Kyn), neopterin, nitrite, and routine laboratory parameters were analyzed during acute infection and at a follow-up (FU) 60 days thereafter. Clinical symptoms of patients (neurological symptoms, fatigue, sleep disturbance) were recorded and associations with concentrations of laboratory parameters investigated. Results and conclusion: Almost half of the patients suffered from neurological symptoms (48.4%), the majority of patients experienced sleep difficulties (56.7%) during acute COVID-19. Fatigue was present in nearly all patients. C-reactive protein (CRP), interleukin-6 (IL-6), neopterin, Kyn, Phe concentrations were significantly increased, and Trp levels depleted during acute COVID-19. Patients with sleep impairment and neurological symptoms during acute illness presented with increased CRP and IL-6 concentrations, Trp levels were lower in patients with sleep disturbance. In general, inflammatory markers declined during reconvalescence. A high percentage of patients suffered from persistent symptoms at FU (neurological symptoms: 17.2%, fatigue: 51.7%, sleeping disturbance: 34.5%) and had higher CRP concentrations. Nitrite and Phe levels were lower in patients with sleeping difficulties at FU and Kyn/Trp ratio, as indicator of IDO activity, was significantly lower in patients with neurological symptoms compared to patients without them at FU. In summary, inflammation induced alterations of amino acid metabolism might be related to acute and persisting symptoms of COVID-19.

BACKGROUNDLong COVID, defined as presence of COVID-19 related symptoms 28 days or more after the onset of acute SARS-CoV-2 infection, is an emerging challenge to healthcare systems. The objective of this study was to phenotype recovery trajectories of non-hospitalized COVID-19 individuals.METHODSWe performed an international, multi-center, exploratory online survey study on demographics, comorbidities, COVID-19 symptoms and recovery status of non-hospitalized SARS-CoV-2 infected adults (Austria: n=1157), and Italy: n= 893).RESULTSWorking age subjects (Austria median: 43 yrs (IQR: 31 – 53), Italy: 45 yrs (IQR: 35 – 55)) and females (65.1% and 68.3%) predominated the study cohorts. Course of acute COVID-19 was characterized by a high symptom burden (median 13 (IQR: 9 – 18) and 13 (7 – 18) out of 44 features queried), a 47.6 – 49.3% rate of symptom persistence beyond 28 days and 20.9 – 31.9% relapse rate. By cluster analysis, two acute symptom phenotypes could be discerned: the non-specific infection phenotype and the multi-organ phenotype (MOP), the latter encompassing multiple neurological, cardiopulmonary, gastrointestinal and dermatological features. Clustering of long COVID subjects yielded three distinct subgroups, with a subset of 48.7 – 55 % long COVID individuals particularly affected by post-acute MOP symptoms. The number and presence of specific acute MOP symptoms and pre-existing multi-morbidity was linked to elevated risk of long COVID.CONCLUSIONThe consistent findings of two independent cohorts further delineate patterns of acute and post-acute COVID-19 and emphasize the importance of symptom phenotyping of home-isolated COVID-19 patients to predict protracted convalescence and to allocate medical resources.Key PointsQuestionWhich acute symptom patterns of acute COVID-19 are associated with prolonged symptom persistence, symptom relapse or physical performance impairment?FindingsIn this multicenter international comparative survey study on non-hospitalized SARS- CoV-2 infected adults (Austria: n = 1157, Italy: n = 893) we identified distinct and reproducible phenotypes of acute and persistent features. Acute multi-organ symptoms including neurological and cardiopulmonary manifestations are linked to elevated risk of long COVID.MeaningThese findings suggest to employ symptom phenotyping of home-isolated COVID-19 patients to predict protracted convalescence and to allocate medical resources.

BackgroundCOVID-19 convalescents are at risk of developing a de novo mental health disorder or of worsening of a pre-existing one. The objectives of our study was to phenotype individuals at highest risk of mental health disorders among COVID-19 outpatients.MethodsWe conducted a binational online survey study with adult non-hospitalized COVID-19 convalescents (Austria/AT: n=1157, Italy/IT: n= 893). Primary endpoints were positive screening for depression and anxiety (PHQ-4, Patient Health Questionnaire) and self-perceived overall mental health and quality of life rated with 4 point Likert scales. Psychosocial stress was surveyed with a modified PHQ stress module. Associations of the mental health with socio-demographic variables, COVID-19 course and recovery data were assessed by multi-parameter random forest and serial univariable modeling. Mental disorder risk subsets were defined by self-organizing map and hierarchical clustering algorithms. The survey analyses are publicly available (https://im2-ibk.shinyapps.io/mental_health_dashboard/).ResultsIn the study cohorts, 4.6 (IT)/6% (AT) of participants reported depression and/or anxiety before to infection. 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 overall mental health (AT: 21.8%, IT: 24.1%) or quality of life (AT: 20.3%, IT: 25.9%) as fair or poor. In both study collectives, psychosocial stress, high numbers of acute and persistent COVID-19 complaints and the presence of acute neurocognitive symptoms (impaired concentration, confusion, forgetfulness) were the strongest correlates of deteriorating mental health and poor quality of life. In clustering analysis, these variables defined a ‘high risk’ subset with particularly high propensity of post-COVID-19 mental health impairment and decreased quality of life. Pre-existing depression or anxiety was associated with an increased symptom burden during acute COVID-19 and recovery.ConclusionOur 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 COVID-19 patients who may benefit from early psychological and psychiatric intervention.Trial registrationClinicalTrials.gov: NCT04661462.

COVID-19 is highly variable in its clinical presentation, ranging from asymptomatic infection to severe organ damage and death. We characterized the time-dependent progression of the disease in 139 COVID-19 inpatients by measuring 86 accredited diagnostic parameters, such as blood cell counts and enzyme activities, as well as untargeted plasma proteomes at 687 sampling points. We report an initial spike in a systemic inflammatory response, which is gradually alleviated and followed by a protein signature indicative of tissue repair, metabolic reconstitution, and immunomodulation. We identify prognostic marker signatures for devising risk-adapted treatment strategies and use machine learning to classify therapeutic needs. We show that the machine learning models based on the proteome are transferable to an independent cohort. Our study presents a map linking routinely used clinical diagnostic parameters to plasma proteomes and their dynamics in an infectious disease., Graphical abstract, Demichev, Tober-Lau et al., present a time-resolved molecular map of the COVID-19, measuring plasma proteomes of patients with COVID-19 along with an extensive panel of clinical diagnostic parameters at 687-time points. They describe the specificity and dynamics, as well as the predictive and prognostic power of the molecular signatures in COVID-19.

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.

Global healthcare systems are challenged by the COVID-19 pandemic. There is a need to optimize allocation of treatment and resources in intensive care, as clinically established risk assessments such as SOFA and APACHE II scores show only limited performance for predicting the survival of severely ill COVID-19 patients. Comprehensively capturing the host physiology, we speculated that proteomics in combination with new data-driven analysis strategies could produce a new generation of prognostic discriminators. We studied two independent cohorts of patients with severe COVID-19 who required intensive care and invasive mechanical ventilation. SOFA score, Charlson comorbidity index and APACHE II score were poor predictors of survival. Plasma proteomics instead identified 14 proteins that showed concentration trajectories different between survivors and non-survivors. A proteomic predictor trained on single samples obtained at the first time point at maximum treatment level (i.e. WHO grade 7) and weeks before the outcome, achieved accurate classification of survivors in an exploratory (AUROC 0.81) as well as in the independent validation cohort (AUROC of 1.0). The majority of proteins with high relevance in the prediction model belong to the coagulation system and complement cascade. Our study demonstrates that predictors derived from plasma protein levels have the potential to substantially outperform current prognostic markers in intensive care.Trial registrationGerman Clinical Trials Register DRKS00021688

BackgroundCOVID-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 questionTo 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 methodsA 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.ResultsAt 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.InterpretationSeverity 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 RegistrationClinicalTrials.gov: NCT04416100

BACKGROUND: The Coronavirus Disease 2019 (COVID-19) pandemic increases the demand for postacute care in patients after a severe disease course. Various long-term sequelae are expected and rehabilitation medicine is challenged to support physical and cognitive recovery. AIM: We aimed to explore the dysfunctions and outcome of COVID-19 survivors after early postacute rehabilitation. DESIGN: Observational cohort study. METHODS: This study evaluated the postacute sequelae of patients hospitalized for SARS-CoV-2 infection and analyzed rehabilitative outcomes of a subgroup of patients included in the prospective observational multicenter CovILD study. RESULTS: A total of 23 subjects discharged after severe to critical COVID-19 infection underwent an individualized, multiprofessional rehabilitation. At the start of postacute rehabilitation, impairment of pulmonary function (87%), symptoms related to postintensive care syndrome, and neuropsychological dysfunction (85%) were frequently found, whereas cardiac function appeared to be largely unaffected. Of interest, multi-disciplinary rehabilitation resulted in a significant improvement in lung function, as reflected by an increase of forced vital capacity (P=0.007) and forced expiratory volume in one second (P=0.014), total lung capacity (P=0.003), and diffusion capacity for carbon monoxide (P=0.002). Accordingly, physical performance status significantly improved as reflected by a mean increase of six-minute walking distance by 176 (SD±137) meters. Contrarily, a considerable proportion of patients still had limited diffusion capacity (83%) or neurological symptoms including peripheral neuropathy at the end of rehabilitation. CONCLUSIONS: Individuals discharged after a severe course of COVID-19 frequently present with persisting physical and cognitive dysfunctions after hospital discharge. Those patients significantly benefit from multi-disciplinary inpatient rehabilitation. CLINICAL REHABILITATION IMPACT: Our data demonstrated the highly promising effects of early postacute rehabilitation in survivors of severe or critical COVID-19. This findings urge further prospective evaluations and may impact future treatment and rehabilitation strategies.

Background Seasonal influenza is an important cause of morbidity and mortality worldwide. Immune activation after stimulation with interferon‐gamma leads to increased production of neopterin but also results in increased tryptophan catabolism through indoleamine 2,3‐dioxygenase (IDO). Our pilot study determined neopterin serum levels and IDO activity in patients with influenza infection and investigated whether neopterin is linked to clinical outcome parameters (mortality ≤30 days, acute cardiac events (ACE) length of hospitalization, ICU admission). Methods Neopterin concentrations were analyzed in serum samples of 40 patients with a confirmed diagnosis of influenza infection and in‐hospital treatment for >24 hours. Data were compared to values of 100 healthy blood donors and 48 age‐matched pneumonia patients. In a subgroup of 14 patients, tryptophan and kynurenine concentrations, as well as kynurenine‐to‐tryptophan ratio, were analyzed. Results In all influenza patients, neopterin concentrations were increased and significantly higher compared to those determined in patients with pneumonia and healthy controls. Positive correlations between the duration of hospitalization and neopterin were found. Significantly higher levels of kynurenine, kynurenine‐to‐tryptophan ratio, and lower levels of tryptophan were seen in influenza patients compared to healthy controls. Conclusions Neopterin seems to be related to the course of the disease and could be a valuable biomarker to identify patients at an elevated risk of a worsened outcome; however, further prospective validation studies are needed to support the here presented preliminary results.

Bacteremia is a major clinical challenge requiring early treatment. Metabolic alterations occur during bacteremia, and accordingly plasma concentrations of lipoproteins LDL-C and HDL-C are substantially changed. We questioned whether bacteremia with Gram-negative versus Gram-positive bacteria causes contrasting changes of lipoprotein levels in order to differentiate between the 2-g stain types and if there is a relation with outcome parameters namely ICU-admission, 30-day mortality, duration of hospitalization. This is a retrospective dual-center cross-sectional study, including 258 patients with bacteremia. Plasma lipid levels were analyzed within 48 h to positive blood culture. Upon admission, HDL-C, LDL-C, and total cholesterol (p = 0.99) in plasma did not significantly differ between patients with Gram-negative and Gram-positive bacteremia, while significantly higher triglyceride concentrations were found in Gram-negative bacteremia (p

ObjectivesSevere Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) infections cause Coronavirus Disease 2019 (COVID-19) and induce a specific antibody response. Serological assays detecting IgG against the receptor binding domain (RBD) of the spike (S) protein are useful to monitor the immune response after infection or vaccination. The objective of our study was to evaluate the clinical performance of the Siemens SARS-CoV-2 IgG (sCOVG) assay.MethodsSensitivity and specificity of the Siemens sCOVG test were evaluated on 178 patients with SARS-CoV-2-infection and 160 pre-pandemic samples in comparison with its predecessor test COV2G. Furthermore, correlation with virus neutralization titers was investigated on 134 samples of convalescent COVID-19 patients.ResultsSpecificity of the sCOVG test was 99.4% and sensitivity was 90.5% (COV2G assay 78.7%; pConclusionsPerformance characteristics of the sCOVG assay have been improved compared to the predecessor test COV2G. Quantitative SARS-CoV-2 S1-RBD IgG levels could be used as a surrogate for virus neutralization capacity. Further harmonization of antibody quantification might assist to monitor the humoral immune response after COVID-19 disease or vaccination.

Objectives Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections cause coronavirus disease 2019 (COVID-19) and induce a specific antibody response. Serological assays detecting IgG against the receptor binding domain (RBD) of the spike (S) protein are useful to monitor the immune response after infection or vaccination. The objective of our study was to evaluate the clinical performance of the Siemens SARS-CoV-2 IgG (sCOVG) assay. Methods Sensitivity and specificity of the Siemens sCOVG test were evaluated on 178 patients with SARS-CoV-2-infection and 160 pre-pandemic samples in comparison with its predecessor test COV2G. Furthermore, correlation with virus neutralization titers was investigated on 134 samples of convalescent COVID-19 patients. Results Specificity of the sCOVG test was 99.4% and sensitivity was 90.5% (COV2G assay 78.7%; p Conclusions Performance characteristics of the sCOVG assay have been improved compared to the predecessor test COV2G. Quantitative SARS-CoV-2 S1-RBD IgG levels could be used as a surrogate for virus neutralization capacity. Further harmonization of antibody quantification might assist to monitor the humoral immune response after COVID-19 disease or vaccination.

Background and purpose To assess neurological manifestations and health‐related quality of life (QoL) 3 months after COVID‐19. Methods In this prospective, multicenter, observational cohort study we systematically evaluated neurological signs and diseases by detailed neurological examination and a predefined test battery assessing smelling disorders (16‐item Sniffin Sticks test), cognitive deficits (Montreal Cognitive Assessment), QoL (36‐item Short Form), and mental health (Hospital Anxiety and Depression Scale, Posttraumatic Stress Disorder Checklist–5) 3 months after disease onset. Results Of 135 consecutive COVID‐19 patients, 31 (23%) required intensive care unit (ICU) care (severe), 72 (53%) were admitted to the regular ward (moderate), and 32 (24%) underwent outpatient care (mild) during acute disease. At the 3‐month follow‐up, 20 patients (15%) presented with one or more neurological syndromes that were not evident before COVID‐19. These included polyneuro/myopathy (n = 17, 13%) with one patient presenting with Guillain‐Barré syndrome, mild encephalopathy (n = 2, 2%), parkinsonism (n = 1, 1%), orthostatic hypotension (n = 1, 1%), and ischemic stroke (n = 1, 1%). Objective testing revealed hyposmia/anosmia in 57/127 (45%) patients at the 3‐month follow‐up. Self‐reported hyposmia/anosmia was lower (17%) at 3 months, however, improved when compared to the acute disease phase (44%; p, Three months after COVID‐19, 20/135 patients (15%) presented with one or more neurological syndromes that were not evident before disease onset. Objective testing revealed hyposmia/anosmia in 45% of patients at the 3‐month follow‐up in comparison to 17% who reported hyposmia/anosmia. Cognitive deficits were apparent in 23%, quality of life was impaired in 31%, depression was found in 11%, anxiety in 25% and posttraumatic stress disorders in 11%.

Objectives Serological tests detect antibodies against Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) in the ongoing coronavirus disease-19 (COVID-19) pandemic. Independent external clinical validation of performance characteristics is of paramount importance. Methods Four fully automated assays, Roche Elecsys Anti-SARS-CoV-2, Abbott SARS-CoV-2 IgG, Siemens SARS-CoV-2 total (COV2T) and SARS-CoV-2 IgG (COV2G) were evaluated using 350 pre-pandemic samples and 700 samples from 245 COVID-19 patients (158 hospitalized, 87 outpatients). Results All tests showed very high diagnostic specificity. Sensitivities in samples collected at least 14 days after disease onset were slightly lower than manufacturers’ claims for Roche (93.0%), Abbott (90.8%), and Siemens COV2T (90.3%), and distinctly lower for Siemens COV2G (78.8%). Concordantly negative results were enriched for immunocompromised patients. ROC curve analyses suggest a lowering of the cut-off index for the Siemens COV2G assay. Finally, the combination of two anti-SARS-CoV-2 antibody assays is feasible when considering borderline reactive results. Conclusions Thorough on-site evaluation of commercially available serologic tests for detection of antibodies against SARS-CoV-2 remains imperative for laboratories. The potentially impaired sensitivity of the Siemens COV2G necessitates a switch to the company’s newly filed SARS-CoV-2 IgG assay for follow-up studies. A combination of tests could be considered in clinical practice.

COVID-19 is highly variable in its clinical presentation, ranging from asymptomatic infection to severe organ damage and death. There is an urgent need for predictive markers that can guide clinical decision-making, inform about the effect of experimental therapies, and point to novel therapeutic targets. Here, we characterize the time-dependent progression of COVID-19 through different stages of the disease, by measuring 86 accredited diagnostic parameters and plasma proteomes at 687 sampling points, in a cohort of 139 patients during hospitalization. We report that the time-resolved patient molecular phenotypes reflect an initial spike in the systemic inflammatory response, which is gradually alleviated and followed by a protein signature indicative of tissue repair, metabolic reconstitution and immunomodulation. Further, we show that the early host response is predictive for the disease trajectory and gives rise to proteomic and diagnostic marker signatures that classify the need for supplemental oxygen therapy and mechanical ventilation, and that predict the time to recovery of mildly ill patients. In severely ill patients, the molecular phenotype of the early host response predicts survival, in two independent cohorts and weeks before outcome. We also identify age-specific molecular response to COVID-19, which involves increased inflammation and lipoprotein dysregulation in older patients. Our study provides a deep and time resolved molecular characterization of COVID-19 disease progression, and reports biomarkers for risk-adapted treatment strategies and molecular disease monitoring. Our study demonstrates accurate prognosis of COVID-19 outcome from proteomic signatures recorded weeks earlier.

Background Severe coronavirus disease 2019 (COVID-19) is frequently associated with hyperinflammation and hyperferritinemia. The latter is related to increased mortality in COVID-19. Still, it is not clear if iron dysmetabolism is mechanistically linked to COVID-19 pathobiology. Methods We herein present data from the ongoing prospective, multicentre, observational CovILD cohort study (ClinicalTrials.gov number, NCT04416100), which systematically follows up patients after COVID-19. 109 participants were evaluated 60 days after onset of first COVID-19 symptoms including clinical examination, chest computed tomography and laboratory testing. Results We investigated subjects with mild to critical COVID-19, of which the majority received hospital treatment. 60 days after disease onset, 30% of subjects still presented with iron deficiency and 9% had anemia, mostly categorized as anemia of inflammation. Anemic patients had increased levels of inflammation markers such as interleukin-6 and C-reactive protein and survived a more severe course of COVID-19. Hyperferritinemia was still present in 38% of all individuals and was more frequent in subjects with preceding severe or critical COVID-19. Analysis of the mRNA expression of peripheral blood mononuclear cells demonstrated a correlation of increased ferritin and cytokine mRNA expression in these patients. Finally, persisting hyperferritinemia was significantly associated with severe lung pathologies in computed tomography scans and a decreased performance status as compared to patients without hyperferritinemia. Discussion Alterations of iron homeostasis can persist for at least two months after the onset of COVID-19 and are closely associated with non-resolving lung pathologies and impaired physical performance. Determination of serum iron parameters may thus be a easy to access measure to monitor the resolution of COVID-19. Trial registration ClinicalTrials.gov number: NCT04416100.

Background Cardiovascular diseases are arguably the most important comorbidity in patients with COPD. Despite an increased prevalence of coronary artery disease (CAD) in COPD patients, there are no dedicated diagnostic recommendations. Objectives We investigated whether COPD patients receive adequate primary evaluation of CAD despite overlapping symptoms. Methods In total, 302 patients with COPD who underwent invasive coronary angiography (ICA) were retrospectively matched (for age, body mass index and cardiovascular risk factors) with 302 patients without functional lung diseases. Quality and onset of symptoms prior to ICA were documented, and individual patients’ pretest probabilities according to European Society of Cardiology (ESC) guidelines were calculated. Endpoints were delay of ICA referral after symptom onset and clinical outcome, defined as subsequent revascularisation. Results Mean delay between symptom onset and ICA was 19.9±22.0 months in COPD patients compared to 8.3±12.7 months in the control group (p70% stenosis) was 35.3%; the revascularisation rate increased with higher pretest probability for the control group but decreased for patients with COPD GOLD 1–4. Conclusion Patients with COPD are insufficiently evaluated for CAD due to overlapping symptoms. Current CAD risk scores for stable chest pain appear inappropriate for patients with COPD., Coronary artery disease evaluation is delayed in COPD patients compared to patients without obstructive lung disease. Due to overlapping symptoms, pretest probabilities of current stable angina models do not fit patients with COPD. https://bit.ly/318RkNz