Absence of Type I Interferon Autoantibodies or Significant Interferon Signature Alterations in Adults With Post-COVID-19 Syndrome

Genetic defects in the interferon (IFN) system or neutralizing autoantibodies against type I IFNs contribute to severe COVID-19. Such autoantibodies were proposed to affect post-COVID-19 syndrome (PCS), possibly causing persistent fatigue for >12 weeks after confirmed SARS-CoV-2 infection. In the current study, we investigated 128 patients with PCS, 21 survivors of severe COVID-19, and 38 individuals who were asymptomatic. We checked for autoantibodies against IFN-α, IFN-β, and IFN-ω. Few patients with PCS had autoantibodies against IFNs but with no neutralizing activity, indicating a limited role of type I IFNs in PCS pathogenesis. In a subset consisting of 28 patients with PCS, we evaluated IFN-stimulated gene activity and showed that it did not correlate with fatigue. In conclusion, impairment of the type I IFN system is unlikely responsible for adult PCS.

Digital Patient Reported Outcome Measures Platform for Post-COVID-19 Condition and Other Long-Term Conditions: User-Centered Development and Technical Description

BACKGROUND

Post-COVID-19 condition (PCC), colloquially known as long COVID, is a multisystem condition characterized by persistent symptoms beyond 4 weeks after the SARS-CoV-2 infection. More than 60 million people with PCC worldwide need prompt assessment, diagnosis, and monitoring, with many requiring specialist help from a multidisciplinary team of health care professionals (HCPs). Consequently, a scalable digital system is required for both people with PCC and HCPs to capture the breadth of symptoms and their impact on health, using patient-reported outcome measures (PROMs) and patient-reported experience measures (PREMs).

OBJECTIVE

We aim to develop and implement a novel PCC digital PROM (DPROM) platform for (1) securely collecting PROM and PREM data from people with PCC, (2) enabling users to monitor symptoms longitudinally and assess response to treatment, (3) generating reports for the electronic health records (EHRs), (4) providing summary reports on PCC services based on national requirements, and (5) facilitating the sharing of relevant data with authorized research teams to accelerate our understanding of this new condition and evaluate new strategies to manage PCC.

METHODS

We (1) undertook requirement analysis with people with PCC, HCPs, and researchers to identify the needs of the DPROM platform and determine its required functionalities; (2) designed and developed a clinically useful web portal for staff and a mobile app for patients, with a web-based alternative app to improve patient and staff choice, limit the risk of digital exclusion, and account for variability across services; (3) determined the PROMs and PREMs that PCC services would prefer to use on the platform; and (4) designed the summary report function that can be generated for each user for the EHR and for reporting to national health authorities.

RESULTS

A DPROM platform to record PCC symptom profile, condition severity, functional disability, and quality of life, based on the C19-YRS (Yorkshire Rehabilitation Scale) and other PROMs and PREMs, was developed. Individual-level medical information and details on the COVID-19 illness can be captured systematically. The platform generates easy-to-understand scores, radar plots and line graphs for people with PCC to self-monitor their condition and for HCPs to assess the natural course of the condition and the response to interventions. Clinics can configure a suite of PROMs and PREMs based on their local and national service and commissioning requirements and support research studies which require large-scale data collection on PROMs. The DPROM platform enables automatic aggregate data analysis for services to undertake service evaluation and cost-effectiveness analysis. The DPROM platform generated summary report can be uploaded to the EHRs of people with PCC.

CONCLUSIONS

A multifunctional DPROM platform to assess, grade, and monitor PCC has been developed. Future research will analyze the system's usability in specialist PCC clinical services and other long-term conditions.

Differences in Clinical Presentation With Long COVID After Community and Hospital Infection and Associations With All-Cause Mortality: English Sentinel Network Database Study

BACKGROUND

Most studies of long COVID (symptoms of COVID-19 infection beyond 4 weeks) have focused on people hospitalized in their initial illness. Long COVID is thought to be underrecorded in UK primary care electronic records.

OBJECTIVE

We sought to determine which symptoms people present to primary care after COVID-19 infection and whether presentation differs in people who were not hospitalized, as well as post-long COVID mortality rates.

METHODS

We used routine data from the nationally representative primary care sentinel cohort of the Oxford-Royal College of General Practitioners Research and Surveillance Centre (N=7,396,702), applying a predefined long COVID phenotype and grouped by whether the index infection occurred in hospital or in the community. We included COVID-19 infection cases from March 1, 2020, to April 1, 2021. We conducted a before-and-after analysis of long COVID symptoms prespecified by the Office of National Statistics, comparing symptoms presented between 1 and 6 months after the index infection matched with the same months 1 year previously. We conducted logistic regression analysis, quoting odds ratios (ORs) with 95% CIs.

RESULTS

In total, 5.63% (416,505/7,396,702) and 1.83% (7623/416,505) of the patients had received a coded diagnosis of COVID-19 infection and diagnosis of, or referral for, long COVID, respectively. People with diagnosis or referral of long COVID had higher odds of presenting the prespecified symptoms after versus before COVID-19 infection (OR 2.66, 95% CI 2.46-2.88, for those with index community infection and OR 2.42, 95% CI 2.03-2.89, for those hospitalized). After an index community infection, patients were more likely to present with nonspecific symptoms (OR 3.44, 95% CI 3.00-3.95; P<.001) compared with after a hospital admission (OR 2.09, 95% CI 1.56-2.80; P<.001). Mental health sequelae were more strongly associated with index hospital infections (OR 2.21, 95% CI 1.64-2.96) than with index community infections (OR 1.36, 95% CI 1.21-1.53; P<.001). People presenting to primary care after hospital infection were more likely to be men (OR 1.43, 95% CI 1.25-1.64; P<.001), more socioeconomically deprived (OR 1.42, 95% CI 1.24-1.63; P<.001), and with higher multimorbidity scores (OR 1.41, 95% CI 1.26-1.57; P<.001) than those presenting after an index community infection. All-cause mortality in people with long COVID was associated with increasing age, male sex (OR 3.32, 95% CI 1.34-9.24; P=.01), and higher multimorbidity score (OR 2.11, 95% CI 1.34-3.29; P<.001). Vaccination was associated with reduced odds of mortality (OR 0.10, 95% CI 0.03-0.35; P<.001).

CONCLUSIONS

The low percentage of people recorded as having long COVID after COVID-19 infection reflects either low prevalence or underrecording. The characteristics and comorbidities of those presenting with long COVID after a community infection are different from those hospitalized. This study provides insights into the presentation of long COVID in primary care and implications for workload.

An mHealth App for Fibromyalgia-like Post-COVID-19 Syndrome: Protocol for the Analysis of User Experience and Clinical Data

Background

Post–COVID-19 syndrome, also referred as “long covid,” describes persisting symptoms after SARS-CoV-2 infection, including myalgia, fatigue, respiratory, or neurological symptoms. Objective symptoms are often lacking, thus resembling a fibromyalgia-like syndrome. Digital therapeutics have shown efficiency in similar chronic disorders such as fibromyalgia, offering specific disease monitoring and interventions such as cognitive behavioral therapy or physical and respiratory exercise guidance.

Objective

This protocol aims to study the requirements and features of a new mobile health (mHealth) app among patients with fibromyalgia-like post–COVID-19 syndrome in a clinical trial.

Methods

We created a web application prototype for the post–COVID-19 syndrome called “POCOS,” as a web-based rehabilitation tool aiming to improve clinical outcomes. Patients without organ damage or ongoing inflammation will be included in the study. App use will be assessed through user experience questionnaires, focus groups, and clinical data analysis. Subsequently, we will analyze cross-sectional and longitudinal clinical data.

Results

The developed mHealth app consists of a clinically adapted app interface with a simplified patient-reported outcome assessment, monitoring of medical interventions, and disease activity as well as web-based instructions for specific physical and respiratory exercises, stress reduction, and lifestyle instructions. The enrollment of participants is expected to be carried out in November 2021.

Conclusions

User experience plays an important role in digital therapeutics and needs to be clinically tested to allow further improvement. We here describe this process for a new app for the treatment of the fibromyalgia-like post–COVID-19 syndrome and discuss the relevance of the potential outcomes such as natural disease course and disease phenotypes.

International Registered Report Identifier (IRRID)

PRR1-10.2196/32193

Evaluation of Novel Concentrated Interdisciplinary Group Rehabilitation for Patients With Chronic Illnesses: Protocol for a Nonrandomized Clinical Intervention Study

BACKGROUND

An aging population with a growing burden of chronic complex illnesses will seriously challenge the public health care system. Consequently, novel and efficacious treatment approaches are highly warranted. Based on our experiences with concentrated treatment formats for other health challenges, we developed a highly concentrated interdisciplinary group rehabilitation approach for chronic illnesses.

OBJECTIVE

We aim to explore the acceptability of the intervention and describe potential changes in functional impairment at follow-up.

METHODS

The cornerstones of the intervention are as follows: (1) prepare the patient for change prior to treatment, (2) focus on health promoting microchoices instead of symptoms, and (3) expect the patient to integrate the changes in everyday living with limited hands-on follow-up. The intervention will be delivered to patients with highly diverse primary symptoms, namely patients with low back pain, post-COVID-19 symptoms, anxiety and depression, and type 2 diabetes.

RESULTS

Recruitment started between August 2020 and January 2021 (according to the illness category). For initial 3-month results, recruitment is expected to be completed by the end of 2021.

CONCLUSIONS

If successful, this study may have a substantial impact on the treatment of low back pain, post-COVID-19 symptoms, anxiety and depression, and type 2 diabetes, which together constitute a major socioeconomic cost. Further, the study may widen the evidence base for the use of the concentrated treatment format in a diverse group of medical conditions.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

DERR1-10.2196/32216.

Insights from myalgic encephalomyelitis/chronic fatigue syndrome may help unravel the pathogenesis of postacute COVID-19 syndrome

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) can cause chronic and acute disease. Postacute sequelae of SARS-CoV-2 infection (PASC) include injury to the lungs, heart, kidneys, and brain that may produce a variety of symptoms. PASC also includes a post-coronavirus disease 2019 (COVID-19) syndrome ('long COVID') with features that can follow other acute infectious diseases and myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS). Here we summarize what is known about the pathogenesis of ME/CFS and of 'acute' COVID-19, and we speculate that the pathogenesis of post-COVID-19 syndrome in some people may be similar to that of ME/CFS. We propose molecular mechanisms that might explain the fatigue and related symptoms in both illnesses, and we suggest a research agenda for both ME/CFS and post-COVID-19 syndrome.