Persistent somatic symptoms are key to individual illness perception at one year after COVID-19 in a cross-sectional analysis of a prospective cohort study

Objective Subjective illness perception (IP) can differ from physician's clinical assessment results. Herein, we explored patient's IP during coronavirus disease 2019 (COVID-19) recovery. Methods Participants of the prospective observation CovILD study (ClinicalTrials.gov: NCT04416100) with persistent somatic symptoms or cardiopulmonary findings one year after COVID-19 were analyzed (n = 74). Explanatory variables included demographic and comorbidity, COVID-19 course and one-year follow-up data of persistent somatic symptoms, physical performance, lung function testing, chest computed tomography and trans-thoracic echocardiography. Factors affecting IP (Brief Illness Perception Questionnaire) one year after COVID-19 were identified by regularized modeling and unsupervised clustering. Results In modeling, 33% of overall IP variance (R2) was attributed to fatigue intensity, reduced physical performance and persistent somatic symptom count. Overall IP was largely independent of lung and heart findings revealed by imaging and function testing. In clustering, persistent somatic symptom count (Kruskal-Wallis test: η2 = 0.31, p < .001), fatigue (η2 = 0.34, p < .001), diminished physical performance (χ2 test, Cramer V effect size statistic: V = 0.51, p < .001), dyspnea (V = 0.37, p = .006), hair loss (V = 0.57, p < .001) and sleep problems (V = 0.36, p = .008) were strongly associated with the concern, emotional representation, complaints, disease timeline and consequences IP dimensions. Conclusion Persistent somatic symptoms rather than abnormalities in cardiopulmonary testing influence IP one year after COVID-19. Modifying IP represents a promising innovative approach to treatment of post-COVID-19 condition. Besides COVID-19 severity, individual IP should guide rehabilitation and psychological therapy decisions.

Persistent somatic symptoms are key to individual illness perception at one year after COVID-19 in a cross-sectional analysis of a prospective cohort study.

OBJECTIVE: Subjective illness perception (IP) can differ from physician's clinical assessment results. Herein, we explored patient's IP during coronavirus disease 2019 (COVID-19) recovery. METHODS: Participants of the prospective observation CovILD study (ClinicalTrials.gov: NCT04416100) with persistent somatic symptoms or cardiopulmonary findings one year after COVID-19 were analyzed (n = 74). Explanatory variables included demographic and comorbidity, COVID-19 course and one-year follow-up data of persistent somatic symptoms, physical performance, lung function testing, chest computed tomography and trans-thoracic echocardiography. Factors affecting IP (Brief Illness Perception Questionnaire) one year after COVID-19 were identified by regularized modeling and unsupervised clustering. RESULTS: In modeling, 33% of overall IP variance (R2) was attributed to fatigue intensity, reduced physical performance and persistent somatic symptom count. Overall IP was largely independent of lung and heart findings revealed by imaging and function testing. In clustering, persistent somatic symptom count (Kruskal-Wallis test: η2 = 0.31, p < .001), fatigue (η2 = 0.34, p < .001), diminished physical performance (χ2 test, Cramer V effect size statistic: V = 0.51, p < .001), dyspnea (V = 0.37, p = .006), hair loss (V = 0.57, p < .001) and sleep problems (V = 0.36, p = .008) were strongly associated with the concern, emotional representation, complaints, disease timeline and consequences IP dimensions. CONCLUSION: Persistent somatic symptoms rather than abnormalities in cardiopulmonary testing influence IP one year after COVID-19. Modifying IP represents a promising innovative approach to treatment of post-COVID-19 condition. Besides COVID-19 severity, individual IP should guide rehabilitation and psychological therapy decisions.

Interferon-gamma Mediated Metabolic Pathways in Hospitalized Patients During Acute and Reconvalescent COVID-19.

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.

COVID-19 and its continuing burden after 12†months: a longitudinal observational prospective multicentre trial.

Background: Recovery trajectories from coronavirus disease 2019 (COVID-19) call for longitudinal investigation. We aimed to characterise the kinetics and status of clinical, cardiopulmonary and mental health recovery up to 1 year following COVID-19. Methods: Clinical evaluation, lung function testing (LFT), chest computed tomography (CT) and transthoracic echocardiography were conducted at 2, 3, 6 and 12 months after disease onset. Submaximal exercise capacity, mental health status and quality of life were assessed at 12 months. Recovery kinetics and patterns were investigated by mixed-effect logistic modelling, correlation and clustering analyses. Risk of persistent symptoms and cardiopulmonary abnormalities at the 1-year follow-up were modelled by logistic regression. Findings: Out of 145 CovILD study participants, 108 (74.5%) completed the 1-year follow-up (median age 56.5 years; 59.3% male; 24% intensive care unit patients). Comorbidities were present in 75% (n=81). Key outcome measures plateaued after 180 days. At 12 months, persistent symptoms were found in 65% of participants; 33% suffered from LFT impairment; 51% showed CT abnormalities; and 63% had low-grade diastolic dysfunction. Main risk factors for cardiopulmonary impairment included pro-inflammatory and immunological biomarkers at early visits. In addition, we deciphered three recovery clusters separating almost complete recovery from patients with post-acute inflammatory profile and an enrichment in cardiopulmonary residuals from a female-dominated post-COVID-19 syndrome with reduced mental health status. Conclusion: 1 year after COVID-19, the burden of persistent symptoms, impaired lung function, radiological abnormalities remains high in our study population. Yet, three recovery trajectories are emerging, ranging from almost complete recovery to post-COVID-19 syndrome with impaired mental health.

A proteomic survival predictor for COVID-19 patients in intensive care.

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. Additional tools are also needed to monitor treatment, including experimental therapies in clinical trials. Comprehensively capturing human 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 showed limited performance in predicting the COVID-19 outcome. Instead, the quantification of 321 plasma protein groups at 349 timepoints in 50 critically ill patients receiving invasive mechanical ventilation revealed 14 proteins that showed trajectories different between survivors and non-survivors. A predictor trained on proteomic measurements obtained at the first time point at maximum treatment level (i.e. WHO grade 7), which was weeks before the outcome, achieved accurate classification of survivors (AUROC 0.81). We tested the established predictor on an independent validation cohort (AUROC 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 plasma proteomics can give rise to prognostic predictors substantially outperforming current prognostic markers in intensive care.

Pulmonary recovery from COVID-19 in patients with metabolic diseases: a longitudinal prospective cohort study.

The severity of coronavirus disease 2019 (COVID-19) is related to the presence of comorbidities including metabolic diseases. We herein present data from the longitudinal prospective CovILD trial, and investigate the recovery from COVID-19 in individuals with dysglycemia and dyslipidemia. A total of 145 COVID-19 patients were prospectively followed and a comprehensive clinical, laboratory and imaging assessment was performed at 60, 100, 180, and 360 days after the onset of COVID-19. The severity of acute COVID-19 and outcome at early post-acute follow-up were significantly related to the presence of dysglycemia and dyslipidemia. Still, at long-term follow-up, metabolic disorders were not associated with an adverse pulmonary outcome, as reflected by a good recovery of structural lung abnormalities in both, patients with and without metabolic diseases. To conclude, dyslipidemia and dysglycemia are associated with a more severe course of acute COVID-19 as well as delayed early recovery but do not impair long-term pulmonary recovery.

Markers of Infection-Mediated Cardiac Damage in Influenza and COVID-19.

INTRODUCTION: Influenza and the coronavirus disease 2019 (COVID-19) are two potentially severe viral infections causing significant morbidity and mortality. The causative viruses, influenza A/B and the severe acute respiratory syndrome coronavirus 2 (SARS-CoV2) can cause both pulmonary and extra-pulmonary disease, including cardiovascular involvement. The objective of this study was to determine the levels of cardiac biomarkers in hospitalized patients infected with influenza or COVID-19 and their correlation with secondary outcomes. METHODS: We performed a retrospective comparative analysis of cardiac biomarkers in patients hospitalized at our department with influenza or COVID-19 by measuring high-sensitivity troponin-T (hs-TnT) and creatinine kinase (CK) in plasma. Secondary outcomes were intensive care unit (ICU) admission and all-cause in-hospital mortality. RESULTS: We analyzed the data of 250 influenza patients and 366 COVID-19 patients. 58.6% of patients with influenza and 46.2% of patients with COVID-19 presented with increased hs-TnT levels. Patients of both groups with increased hs-TnT levels were significantly more likely to require ICU treatment or to die during their hospital stay. Compared with COVID-19, cardiac biomarkers were significantly higher in patients affected by influenza of all age groups, regardless of pre-existing cardiovascular disease. In patients aged under 65 years, no significant difference in ICU admission and mortality was detected between influenza and COVID-19, whereas significantly more COVID-19 patients 65 years or older died or required intensive care treatment. CONCLUSIONS: Our study shows that increased cardiac biomarkers are associated with higher mortality and ICU admission in both, influenza and SARS-CoV-2-infected patients. Cardiac biomarkers are higher in the influenza cohort; however, this does not translate into worse outcomes when compared with the COVID-19 cohort.

Phenotyping of Acute and Persistent Coronavirus Disease 2019 Features in the Outpatient Setting: Exploratory Analysis of an International Cross-sectional Online Survey.

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.

The Impact of Iron Dyshomeostasis and Anaemia on Long-Term Pulmonary Recovery and Persisting Symptom Burden after COVID-19: A Prospective Observational Cohort Study.

Coronavirus disease 2019 (COVID-19) is frequently associated with iron dyshomeostasis. The latter is related to acute disease severity and COVID-19 convalescence. We herein describe iron dyshomeostasis at COVID-19 follow-up and its association with long-term pulmonary and symptomatic recovery. The prospective, multicentre, observational cohort study "Development of Interstitial Lung Disease (ILD) in Patients With Severe SARS-CoV-2 Infection (CovILD)" encompasses serial extensive clinical, laboratory, functional and imaging evaluations at 60, 100, 180 and 360 days after COVID-19 onset. We included 108 individuals with mild-to-critical acute COVID-19, whereas 75% presented with severe acute disease. At 60 days post-COVID-19 follow-up, hyperferritinaemia (35% of patients), iron deficiency (24% of the cohort) and anaemia (9% of the patients) were frequently found. Anaemia of inflammation (AI) was the predominant feature at early post-acute follow-up, whereas the anaemia phenotype shifted towards iron deficiency anaemia (IDA) and combinations of IDA and AI until the 360 days follow-up. The prevalence of anaemia significantly decreased over time, but iron dyshomeostasis remained a frequent finding throughout the study. Neither iron dyshomeostasis nor anaemia were related to persisting structural lung impairment, but both were associated with impaired stress resilience at long-term COVID-19 follow-up. To conclude, iron dyshomeostasis and anaemia are frequent findings after COVID-19 and may contribute to its long-term symptomatic outcome.

Who Is at Risk of Poor Mental Health Following Coronavirus Disease-19 Outpatient Management?

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].

Chest CT of Lung Injury 1 Year after COVID-19 Pneumonia: The CovILD Study.

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.

Quantity of IgG response to SARS-CoV-2 spike glycoprotein predicts pulmonary recovery from 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.

Investigating phenotypes of pulmonary COVID-19 recovery: A longitudinal observational prospective multicenter trial.

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.

Neurological outcome and quality of life 3 months after COVID-19: A prospective observational cohort study.

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 < 0.001). At follow-up, cognitive deficits were apparent in 23%, and QoL was impaired in 31%. Assessment of mental health revealed symptoms of depression, anxiety, and posttraumatic stress disorders in 11%, 25%, and 11%, respectively. CONCLUSIONS: Despite recovery from the acute infection, neurological symptoms were prevalent at the 3-month follow-up. Above all, smelling disorders were persistent in a large proportion of patients.

Factors associated with impaired quality of life three months after being diagnosed with COVID-19.

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.

A time-resolved proteomic and prognostic map of COVID-19.

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.

Beneficial effects of multi-disciplinary rehabilitation in postacute COVID-19: an observational cohort study.

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.

Clinical validation of the Siemens quantitative SARS-CoV-2 spike IgG assay (sCOVG) reveals improved sensitivity and a good correlation with virus neutralization titers.

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<0.0001). S1-RBD antibody levels showed a good correlation with virus neutralization titers (r=0.843; p<0.0001) and an overall qualitative agreement of 98.5%. Finally, median S1-RBD IgG levels increase with age and were significantly higher in hospitalized COVID-19 patients (median levels general ward: 25.7 U/mL; intensive care: 59.5 U/mL) than in outpatients (3.8 U/mL; p<0.0001). 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.

Evaluation of four commercial, fully automated SARS-CoV-2 antibody tests suggests a revision of the Siemens SARS-CoV-2 IgG assay.

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.