BackgroundThe COVID-19 pandemic has strained healthcare systems and how best to address post-COVID health needs is uncertain. Here we describe the post-COVID symptoms of 675 patients followed up using a virtual review pathway, stratified by severity of acute COVID infection. MethodsCOVID-19 survivors completed an online/telephone questionnaire of symptoms after 12+ weeks and a chest radiograph. Dependent on findings at virtual review, patients were provided information leaflets, attended for investigations and/or were reviewed face-to-face. Outcomes were compared between patients following high-risk and low-risk admissions for COVID pneumonia, and community referrals. ResultsPatients reviewed after hospitalisation for COVID pneumonia had a median of two ongoing physical health symptoms post-COVID. The most common was fatigue (50.3% of highrisk patients). Symptom burden did not vary significantly by severity of hospitalised COVID pneumonia but was highest in community referrals. Symptoms suggestive of depression, anxiety and post-traumatic stress disorder were common (depression occurred in 24.9% of high-risk patients). Asynchronous virtual review facilitated triage of patients at highest need of face-to-face review. ConclusionMany patients continue to have a significant burden of post-COVID symptoms irrespective of severity of initial pneumonia. How best to assess and manage long COVID will be of major importance over the next few years.

IntroductionLong COVID-19 is a distressing, disabling and heterogeneous syndrome often causing severe functional impairment. Predominant symptoms include fatigue, cognitive impairment (‘brain fog’), breathlessness and anxiety or depression. These symptoms are amenable to rehabilitation delivered by skilled healthcare professionals, but COVID-19 has put severe strain on healthcare systems. This study aims to explore whether digitally enabled, remotely supported rehabilitation for people with long COVID-19 can enable healthcare systems to provide high quality care to large numbers of patients within the available resources. Specific objectives are to (1) develop and refine a digital health intervention (DHI) that supports patient assessment, monitoring and remote rehabilitation; (2) develop implementation models that support sustainable deployment at scale; (3) evaluate the impact of the DHI on recovery trajectories and (4) identify and mitigate health inequalities due to the digital divide.Methods and analysisMixed-methods, theoretically informed, single-arm prospective study, combining methods drawn from engineering/computer science with those from biomedicine. There are four work packages (WP), one for each objective. WP1 focuses on identifying user requirements and iteratively developing the intervention to meet them; WP2 combines qualitative data from users with learning from implementation science and normalisation process theory, to promote adoption, scale-up, spread and sustainability of the intervention; WP3 uses quantitative demographic, clinical and resource use data collected by the DHI to determine illness trajectories and how these are affected by use of the DHI; while WP4 focuses on identifying and mitigating health inequalities and overarches the other three WPs.Ethics and disseminationEthical approval obtained from East Midlands – Derby Research Ethics Committee (reference 288199). Our dissemination strategy targets three audiences: (1) Policy makers, Health service managers and clinicians responsible for delivering long COVID-19 services; (2) patients and the public; (3) academics.Trial registration numberResearch Registry number: researchregistry6173.

Patients undergoing face-to-face review in a post-COVID clinic were assessed by a respiratory physician and specialist respiratory physiotherapist. Assessment included a Dyspnoea-12 (D12) questionnaire to assess breathlessness, physiotherapist assessment of breathing pattern including manual assessment of respiratory motion, and BPAT assessment. The sensitivity and specificity of BPAT for diagnosis of BPD in post-COVID patients was assessed. ResultsBPAT had a sensitivity of 89.5% and specificity of 78.3% for diagnosing BPD in post-COVID breathlessness. Patients with a BPAT score above the diagnostic cut-off had higher levels of breathlessness than those with lower BPAT scores (D12 score mean average 19.4 vs 13.2). ConclusionBPAT has high sensitivity and moderate specificity for BPD in patients with long COVID. This would support its use as a screening test in clinic, and as a diagnostic tool for large cohort studies.

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