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.

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.

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.

Ad hoc Setup of an Online Mental Health Self-Help Program During the COVID-19 Pandemic: Description of the Development and Implementation Processes and Analysis of Its Users' and Usage Profiles.

Background: The COVID-19 pandemic hit Austria in March 2020. This led to a considerable reduction in outpatient psychiatric therapies. People with mental disorders as well as with newly emerging mental health issues found themselves with very limited treatment options. Within only a few days our hospital set up an online mental health self-help program which went online in its first version on the first day of the lockdown in Austria. The process of this development and implementation process alongside with the user's and usage data for the program are presented here. Methods: A small core team initiated the development of the program on a low-budget basis and using mostly freely available digital resources. The program had to be free of costs for its users and easy to navigate. Each self-help module contains a text description of the topic, a self-rating questionnaire and several psychoeducational 2-5 min videos. These videos explain, e.g., interactions of mental stress and the immune system or the vicious circle of anxiety. Additional videos provide easy to learn techniques like breathing and relaxation exercises. Results: We illustrate the implementation of this program following the replicating effective program (REP) model. We provide a detailed description of the implementation process starting from a simple website to a smartphone-based application with registered user area and instantaneous reporting of self-rating questionnaire results to users. The described process could be used as a model for the setup of similar programs in a very short time. As an indicator of acceptance, we report 46,100 unique video views and 3,937 completed questionnaires in the first year of use. The most accessed videos were those on anxiety, relaxation and resilience. Analysis of the sociodemographic user data indicate that they were mostly young (< 45 years; 59.7%), females (77.5%) and previously mentally healthy individuals (74.5%). An example of the collected psychometric questionnaire data over time is given. Conclusion: We show that it is possible to set up an online mental health self-help program ad hoc and without extensive prior planning, which enabled us to dynamically respond to a new situation. We are now planning on keeping the program active for a longer period of time to supplement and expand traditional treatment settings also outside the COVID-19 pandemic.

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].

6-month SARS-CoV-2 antibody persistency in a Tyrolian COVID-19 cohort.

BACKGROUND: As coronavirus disease 2019 caused by severe acute respiratory syndrome coronavirus 2 evolved only recently, the persistency of the anti-viral antibody response remains to be determined. METHODS: We prospectively followed 29 coronavirus disease 2019 cases, mean age 44 ± 13.2 years. Except for one participant with a pre-existing diagnosis of rheumatoid arthritis, all other participants were previously healthy. We determined anti-viral binding antibodies at 2-10 weeks, 3 months, and 6 months after disease onset as well as neutralizing antibodies at 6 months. Two binding antibody assays were used, targeting the S1 subunit of the spike protein, and the receptor binding domain. RESULTS: All participants fully recovered spontaneously except for one who had persisting hyposmia. Antibodies to the receptor binding domain persisted for 6 months in all cases with a slight increase of titers, whereas antibodies to S1 dropped below the cut-off point in 2 participants and showed a minimal decrease on average, mainly at month 3 of follow-up in males; however, neutralizing antibodies were detected in all samples at 6 months of follow-up. CONCLUSION: There is a stable and persisting antibody response against acute respiratory syndrome coronavirus 2 at 6 months after infection. Neutralizing antibodies confirm virus specificity. As the number of coronavirus disease 2019 convalescent cases is increasing sharply, antibody testing should be implemented to identify immunized individuals. This information can be helpful in various settings of professional and private life.