Persistent somatic symptoms are key to individual illness perception at one year after COVID-19

BackgroundSequelae of Coronavirus disease 2019 (COVID-19) were investigated by both patient-initiated and academic initiatives. Patients subjective illness perceptions might differ from physicians clinical assessment results. Herein, we explored factors influencing patients 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.

Distinct smell and taste disorder phenotype of post-acute COVID-19 sequelae

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).

Who is at risk of poor mental health following COVID-19 outpatient management?

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.

A time-resolved proteomic and diagnostic map characterizes COVID-19 disease progression and predicts outcome

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.