Long COVID exhibits clinically distinct phenotypes at 3-6 months post-SARS-CoV-2 infection: results from the P4O2 consortium

BACKGROUND

Four months after SARS-CoV-2 infection, 22%-50% of COVID-19 patients still experience complaints. Long COVID is a heterogeneous disease and finding subtypes could aid in optimising and developing treatment for the individual patient.

METHODS

Data were collected from 95 patients in the P4O2 COVID-19 cohort at 3-6 months after infection. Unsupervised hierarchical clustering was performed on patient characteristics, characteristics from acute SARS-CoV-2 infection, long COVID symptom data, lung function and questionnaires describing the impact and severity of long COVID. To assess robustness, partitioning around medoids was used as alternative clustering.

RESULTS

Three distinct clusters of patients with long COVID were revealed. Cluster 1 (44%) represented predominantly female patients (93%) with pre-existing asthma and suffered from a median of four symptom categories, including fatigue and respiratory and neurological symptoms. They showed a milder SARS-CoV-2 infection. Cluster 2 (38%) consisted of predominantly male patients (83%) with cardiovascular disease (CVD) and suffered from a median of three symptom categories, most commonly respiratory and neurological symptoms. This cluster also showed a significantly lower forced expiratory volume within 1 s and diffusion capacity of the lung for carbon monoxide. Cluster 3 (18%) was predominantly male (88%) with pre-existing CVD and diabetes. This cluster showed the mildest long COVID, and suffered from symptoms in a median of one symptom category.

CONCLUSIONS

Long COVID patients can be clustered into three distinct phenotypes based on their clinical presentation and easily obtainable information. These clusters show distinction in patient characteristics, lung function, long COVID severity and acute SARS-CoV-2 infection severity. This clustering can help in selecting the most beneficial monitoring and/or treatment strategies for patients suffering from long COVID. Follow-up research is needed to reveal the underlying molecular mechanisms implicated in the different phenotypes and determine the efficacy of treatment.

Pulmonary function 3-6 months after acute COVID-19: A systematic review and multicentre cohort study

Aims

To describe pulmonary function 3-6 months following acute COVID-19, to evaluate potential predictors of decreased pulmonary function and to review literature for the effect of COVID-19 on pulmonary function.

Materials and methods

A systematic review and cohort study were conducted. Within the P4O2 COVID-19 cohort, 95 patients aged 40-65 years were recruited from outpatient post-COVID-19 clinics in five Dutch hospitals between May 2021-September 2022. At 3-6 months post COVID-19, medical records data and biological samples were collected and questionnaires were administered. In addition, pulmonary function tests (PFTs), including spirometry and transfer factor, were performed. To identify factors associated with PFTs, linear regression analyses were conducted, adjusted for covariates.

Results

In PFTs (n = 90), mean ± SD % of predicted was 89.7 ± 18.2 for forced vital capacity (FVC) and 79.8 ± 20.0 for transfer factor for carbon monoxide (DLCO). FVC was

Conclusion

A low DLCO 3-6 months following acute COVID-19 was observed more often than a low FVC, both in the P4O2 COVID-19 study and the literature review.

Collapse

Key Words

• Long COVID
• Post COVID-19
• Pulmonary function
• Transfer factor for carbon monoxide

Collapse

MESH Headings Collapse

Grants Collapse

Affiliation(s)

Merel E.B. Cornelissen Department of Pulmonary Medicine, Amsterdam UMC, University of Amsterdam, 1105, AZ Amsterdam, the Netherlands Amsterdam Institute for Infection and Immunity, Amsterdam, the Netherlands Amsterdam Public Health, Amsterdam, the Netherlands
Asabi Leliveld Department of Pulmonary Medicine, Amsterdam UMC, University of Amsterdam, 1105, AZ Amsterdam, the Netherlands Amsterdam Institute for Infection and Immunity, Amsterdam, the Netherlands Amsterdam Public Health, Amsterdam, the Netherlands
Nadia Baalbaki Department of Pulmonary Medicine, Amsterdam UMC, University of Amsterdam, 1105, AZ Amsterdam, the Netherlands Amsterdam Institute for Infection and Immunity, Amsterdam, the Netherlands Amsterdam Public Health, Amsterdam, the Netherlands
Debbie Gach Department of Respiratory Medicine, NUTRIM School of Nutrition and Translational Research in Metabolism, Maastricht University Medical Centre+, Maastricht, the Netherlands School of Nutrition and Translational Research in Metabolism, Faculty of Health, Medicine and Life Sciences, Maastricht University, the Netherlands
Ivo van der Lee Department of Pulmonology, Spaarne Hospital, the Netherlands
Esther J. Nossent Department of Pulmonary Medicine, Amsterdam UMC, University of Amsterdam, 1105, AZ Amsterdam, the Netherlands
Lizan D. Bloemsma Department of Pulmonary Medicine, Amsterdam UMC, University of Amsterdam, 1105, AZ Amsterdam, the Netherlands Amsterdam Institute for Infection and Immunity, Amsterdam, the Netherlands Amsterdam Public Health, Amsterdam, the Netherlands
Anke H. Maitland-van der Zee Department of Pulmonary Medicine, Amsterdam UMC, University of Amsterdam, 1105, AZ Amsterdam, the Netherlands Amsterdam Institute for Infection and Immunity, Amsterdam, the Netherlands Amsterdam Public Health, Amsterdam, the Netherlands

Collapse

Fatigue and symptom-based clusters in post COVID-19 patients: a multicentre, prospective, observational cohort study

BACKGROUND

In the Netherlands, the prevalence of post COVID-19 condition is estimated at 12.7% at 90-150 days after SARS-CoV-2 infection. This study aimed to determine the occurrence of fatigue and other symptoms, to assess how many patients meet the Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS) criteria, to identify symptom-based clusters within the P4O2 COVID-19 cohort and to compare these clusters with clusters in a ME/CFS cohort.

METHODS

In this multicentre, prospective, observational cohort in the Netherlands, 95 post COVID-19 patients aged 40-65 years were included. Data collection at 3-6 months after infection included demographics, medical history, questionnaires, and a medical examination. Follow-up assessments occurred 9-12 months later, where the same data were collected. Fatigue was determined with the Fatigue Severity Scale (FSS), a score of ≥ 4 means moderate to high fatigue. The frequency and severity of other symptoms and the percentage of patients that meet the ME/CFS criteria were assessed using the DePaul Symptom Questionnaire-2 (DSQ-2). A self-organizing map was used to visualize the clustering of patients based on severity and frequency of 79 symptoms. In a previous study, 337 Dutch ME/CFS patients were clustered based on their symptom scores. The symptom scores of post COVID-19 patients were applied to these clusters to examine whether the same or different clusters were found.

RESULTS

According to the FSS, fatigue was reported by 75.9% of the patients at 3-6 months after infection and by 57.1% of the patients 9-12 months later. Post-exertional malaise, sleep disturbances, pain, and neurocognitive symptoms were also frequently reported, according to the DSQ-2. Over half of the patients (52.7%) met the Fukuda criteria for ME/CFS, while fewer patients met other ME/CFS definitions. Clustering revealed specific symptom patterns and showed that post COVID-19 patients occurred in 11 of the clusters that have been observed in the ME/CFS cohort, where 2 clusters had > 10 patients.

CONCLUSIONS

This study shows persistent fatigue and diverse symptomatology in post COVID-19 patients, up to 12-18 months after SARS-CoV-2 infection. Clustering showed that post COVID-19 patients occurred in 11 of the clusters that have been observed in the ME/CFS cohort.

Precision Medicine for More Oxygen (P4O2)-Study Design and First Results of the Long COVID-19 Extension

Introduction: The coronavirus disease 2019 (COVID-19) pandemic has led to the death of almost 7 million people, however, with a cumulative incidence of 0.76 billion, most people survive COVID-19. Several studies indicate that the acute phase of COVID-19 may be followed by persistent symptoms including fatigue, dyspnea, headache, musculoskeletal symptoms, and pulmonary functional-and radiological abnormalities. However, the impact of COVID-19 on long-term health outcomes remains to be elucidated. Aims: The Precision Medicine for more Oxygen (P4O2) consortium COVID-19 extension aims to identify long COVID patients that are at risk for developing chronic lung disease and furthermore, to identify treatable traits and innovative personalized therapeutic strategies for prevention and treatment. This study aims to describe the study design and first results of the P4O2 COVID-19 cohort. Methods: The P4O2 COVID-19 study is a prospective multicenter cohort study that includes nested personalized counseling intervention trial. Patients, aged 40-65 years, were recruited from outpatient post-COVID clinics from five hospitals in The Netherlands. During study visits at 3-6 and 12-18 months post-COVID-19, data from medical records, pulmonary function tests, chest computed tomography scans and biological samples were collected and questionnaires were administered. Furthermore, exposome data was collected at the patient's home and state-of-the-art imaging techniques as well as multi-omics analyses will be performed on collected data. Results: 95 long COVID patients were enrolled between May 2021 and September 2022. The current study showed persistence of clinical symptoms and signs of pulmonary function test/radiological abnormalities in post-COVID patients at 3-6 months post-COVID. The most commonly reported symptoms included respiratory symptoms (78.9%), neurological symptoms (68.4%) and fatigue (67.4%). Female sex and infection with the Delta, compared with the Beta, SARS-CoV-2 variant were significantly associated with more persisting symptom categories. Conclusions: The P4O2 COVID-19 study contributes to our understanding of the long-term health impacts of COVID-19. Furthermore, P4O2 COVID-19 can lead to the identification of different phenotypes of long COVID patients, for example those that are at risk for developing chronic lung disease. Understanding the mechanisms behind the different phenotypes and identifying these patients at an early stage can help to develop and optimize prevention and treatment strategies.

Pharmacokinetics and pharmacodynamics of imatinib for optimal drug repurposing from cancer to COVID-19

INTRODUCTION

In the randomized double-blind placebo-controlled CounterCOVID study, oral imatinib treatment conferred a positive clinical outcome and a signal for reduced mortality in COVID-19 patients. High concentrations of alpha-1 acid glycoprotein (AAG) were observed in these patients and were associated with increased total imatinib concentrations.

AIMS

This post-hoc study aimed to compare the difference in exposure following oral imatinib administration in COVID-19 patients to cancer patients and assess assocations between pharmacokinetic (PK) parameters and pharmacodynamic (PD) outcomes of imatinib in COVID-19 patients. We hypothesize that a relatively higher drug exposure of imatinib in severe COVID-19 patients leads to improved pharmacodynamic outcome parameters.

METHODS

648 total concentration plasma samples obtained from 168 COVID-19 patients were compared to 475 samples of 105 cancer patients, using an AAG-binding model. Total trough concentration at steady state (Ct_trough) and total average area under the concentration-time curve (AUCt_ave) were associated with ratio between partial oxygen pressure and fraction of inspired oxygen (P/F), WHO ordinal scale (WHO-score) and liberation of oxygen supplementation (O₂lib). Linear regression, linear mixed effects models and time-to-event analysis were adjusted for possible confounders.

RESULTS

AUCt_ave and Ct_trough were respectively 2.21-fold (95%CI 2.07-2.37) and 1.53-fold (95%CI 1.44-1.63) lower for cancer compared to COVID-19 patients. Ct_trough, not AUCt_ave, associated significantly with P/F (β=-19,64; p-value=0.014) and O₂lib (HR 0.78; p-value= 0.032), after adjusting for sex, age, neutrophil-lymphocyte ratio, dexamethasone concomitant treatment, AAG and baseline P/F-and WHO-score. Ct_trough, but not AUCt_ave associated significantly with WHO-score. These results suggest an inverse relationship between PK-parameters, Ct_trough and AUCt_ave, and PD outcomes.

CONCLUSION

COVID-19 patients exhibit higher total imatinib exposure compared to cancer patients, attributed to differences in plasma protein concentrations. Higher imatinib exposure in COVID-19 patients did not associate with improved clinical outcomes. Ct_trough and AUCt_ave inversely associated with some PD-outcomes, which may be biased by disease course, variability in metabolic rate and protein binding. Therefore, additional PKPD analyses into unbound imatinib and its main metabolite may better explain exposure-response.