Association of circulating biomarkers with illness severity measures differentiates myalgic encephalomyelitis/chronic fatigue syndrome and post-COVID-19 condition: a prospective pilot cohort study.

BACKGROUND: Accumulating evidence suggests that autonomic dysfunction and persistent systemic inflammation are common clinical features in myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) and long COVID. However, there is limited knowledge regarding their potential association with circulating biomarkers and illness severity in these conditions. METHODS: This single-site, prospective, cross-sectional, pilot cohort study aimed to distinguish between the two patient populations by using self-reported outcome measures and circulating biomarkers of endothelial function and systemic inflammation status. Thirty-one individuals with ME/CFS, 23 individuals with long COVID, and 31 matched sedentary healthy controls were included. All study participants underwent non-invasive cardiovascular hemodynamic challenge testing (10 min NASA lean test) for assessment of orthostatic intolerance. Regression analysis was used to examine associations between outcome measures and circulating biomarkers in the study participants. Classification across groups was based on principal component and discriminant analyses. RESULTS: Four ME/CFS patients (13%), 1 with long COVID (4%), and 1 healthy control (3%) presented postural orthostatic tachycardia syndrome (POTS) using the 10-min NASA lean test. Compared with matched healthy controls, ME/CFS and long COVID subjects showed higher levels of ET-1 (p < 0.05) and VCAM-1 (p < 0.001), and lower levels of nitrites (NOx assessed as NO2- + NO3-) (p < 0.01). ME/CFS patients also showed higher levels of serpin E1 (PAI-1) and E-selectin than did both long COVID and matched control subjects (p < 0.01 in all cases). Long COVID patients had lower TSP-1 levels than did ME/CFS patients and matched sedentary healthy controls (p < 0.001). As for inflammation biomarkers, both long COVID and ME/CFS subjects had higher levels of TNF-α than did matched healthy controls (p < 0.01 in both comparisons). Compared with controls, ME/CFS patients had higher levels of IL-1ß (p < 0.001), IL-4 (p < 0.001), IL-6 (p < 0.01), IL-10 (p < 0.001), IP-10 (p < 0.05), and leptin (p < 0.001). Principal component analysis supported differentiation between groups based on self-reported outcome measures and biomarkers of endothelial function and inflammatory status in the study population. CONCLUSIONS: Our findings revealed that combining biomarkers of endothelial dysfunction and inflammation with outcome measures differentiate ME/CFS and Long COVID using robust discriminant analysis of principal components. Further research is needed to provide a more comprehensive characterization of these underlying pathomechanisms, which could be promising targets for therapeutic and preventive strategies in these conditions.

Development of an expert system for the classification of myalgic encephalomyelitis/chronic fatigue syndrome.

Myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) is a severe condition with an uncertain origin and a dismal prognosis. There is presently no precise diagnostic test for ME/CFS, and the diagnosis is determined primarily by the presence of certain symptoms. The current study presents an explainable artificial intelligence (XAI) integrated machine learning (ML) framework that identifies and classifies potential metabolic biomarkers of ME/CFS. Metabolomic data from blood samples from 19 controls and 32 ME/CFS patients, all female, who were between age and body mass index (BMI) frequency-matched groups, were used to develop the XAI-based model. The dataset contained 832 metabolites, and after feature selection, the model was developed using only 50 metabolites, meaning less medical knowledge is required, thus reducing diagnostic costs and improving prognostic time. The computational method was developed using six different ML algorithms before and after feature selection. The final classification model was explained using the XAI approach, SHAP. The best-performing classification model (XGBoost) achieved an area under the receiver operating characteristic curve (AUCROC) value of 98.85%. SHAP results showed that decreased levels of alpha-CEHC sulfate, hypoxanthine, and phenylacetylglutamine, as well as increased levels of N-delta-acetylornithine and oleoyl-linoloyl-glycerol (18:1/18:2)[2], increased the risk of ME/CFS. Besides the robustness of the methodology used, the results showed that the combination of ML and XAI could explain the biomarker prediction of ME/CFS and provided a first step toward establishing prognostic models for ME/CFS.

Research progress in the treatment of chronic fatigue syndrome through interventions targeting the hypothalamus-pituitary-adrenal axis.

Chronic fatigue syndrome (CFS) causes great harm to individuals and society. Elucidating the pathogenesis of CFS and developing safe and effective treatments are urgently needed. This paper reviews the functional changes in the hypothalamus-pituitary-adrenal (HPA) axis in patients with CFS and the associated neuroendocrine mechanisms. Despite some controversy, the current mainstream research evidence indicates that CFS patients have mild hypocortisolism, weakened daily variation in cortisol, a weakened response to the HPA axis, and an increase in negative feedback of the HPA axis. The relationship between dysfunction of the HPA axis and the typical symptoms of CFS are discussed, and the current treatment methods are reviewed.

Mitochondrial dysfunction in long COVID: mechanisms, consequences, and potential therapeutic approaches.

The COVID-19 pandemic, caused by the SARS-CoV-2 virus, has introduced the medical community to the phenomenon of long COVID, a condition characterized by persistent symptoms following the resolution of the acute phase of infection. Among the myriad of symptoms reported by long COVID sufferers, chronic fatigue, cognitive disturbances, and exercise intolerance are predominant, suggesting systemic alterations beyond the initial viral pathology. Emerging evidence has pointed to mitochondrial dysfunction as a potential underpinning mechanism contributing to the persistence and diversity of long COVID symptoms. This review aims to synthesize current findings related to mitochondrial dysfunction in long COVID, exploring its implications for cellular energy deficits, oxidative stress, immune dysregulation, metabolic disturbances, and endothelial dysfunction. Through a comprehensive analysis of the literature, we highlight the significance of mitochondrial health in the pathophysiology of long COVID, drawing parallels with similar clinical syndromes linked to post-infectious states in other diseases where mitochondrial impairment has been implicated. We discuss potential therapeutic strategies targeting mitochondrial function, including pharmacological interventions, lifestyle modifications, exercise, and dietary approaches, and emphasize the need for further research and collaborative efforts to advance our understanding and management of long COVID. This review underscores the critical role of mitochondrial dysfunction in long COVID and calls for a multidisciplinary approach to address the gaps in our knowledge and treatment options for those affected by this condition.

Sijunzi decoction, a classical Chinese herbal formula, improves fatigue symptoms with changes in gut microbiota in chronic fatigue syndrome: A randomized, double-blind, placebo-controlled, multi-center clinical trial.

BACKGROUD: Chronic fatigue syndrome (CFS) severely impact patients' quality of life and lacks well-acknowledged drug therapy. Sijunzi decoction (SJZD), a classical Chinese herbal formula, has been widely used for spleen deficiency syndrome like fatigue in China. However, there is a lack of evidence on the efficacy of SJZD in treating CFS. PURPOSE: To evaluate the efficacy and safety of SJZD for CFS. STUDY DESIGN: A multi-center, double-blinded, randomized controlled trial. METHODS: Participants with definite diagnoses of CFS and spleen deficiency syndrome were randomly assigned in 1:1 ratio to receive SJZD or placebo granules for 2 months. The primary outcome was the change of Chalder fatigue questionnaire (CFQ) scoring after treatment. Other outcomes included changes in short form-36 physical function (SF36-PF) score, spleen deficiency scale score, Euroqol Questionnaire-Visual Analogue Scale (ED-VAS) score, and clinical global impression (CGI) evaluating by corresponding questionnaires. Fecal metagenome sequencing was conducted to explore the potential mechanism of SJZD effect. RESULTS: From June 2020 to July 2021, 105 of 127 participants completed the study at four hospitals in China. After a 2-month treatment, intention-to-treat (ITT) analysis found participants who received SJZD had larger reduction than placebo control (mean change 6.65 [standard deviation (SD) 6.11] points vs. 5.31 [SD 5.19] points; difference 1.34, 95 % confidence interval [CI] -0.65 to 3.33). Per-protocol (PP) analysis reported confirmative results with a significant difference between SJZD and placebo groups (2.24, 95 % CI 0.10 to 4.39). SJZD also significantly improved overall health status compared with placebo in per-protocol population (p = 0.009). No significant difference was found between groups in changes of SF36-PF, spleen deficiency scale scoring, and CGI. Fecal metagenome sequencing and correlation analyses indicated that the beneficial effect of SJZD may be related to the abundance change of Pediococcus acidilactici. No serious adverse event or abnormal laboratory test was found during the whole study. CONCLUSION: Our results indicated that SJZD can improve fatigue symptom and overall health status in patients with CFS under good medication adherence. Potential therapeutic effects may be related to the regulation of gut microbiota. Large-scale trials with longer intervention period are encouraged to further support SJZD's application. CLINICAL TRIAL REGISTRATION: (ID, ISRCTN23930966, URL = https://www.isrctn.com/ISRCTN23930966).

Psychological flexibility in somatic symptom and related disorders: A case control study.

A key diagnostic criterion of Somatic Symptom and related Disorders (SSD) comprises significant distress and excessive time-and-energy consuming thoughts, feelings, and behavior pertaining to somatic symptoms. This diagnostic criterion is lacking in central sensitivity syndromes (CSS), such as fibromyalgia, irritable bowel syndrome, and chronic fatigue syndrome. This strong emphasis on disturbed psychological processing of somatic symptoms, suggests that psychological flexibility is low in SDD. Psychological flexibility is defined as the ability to approach difficult or challenging internal states (thoughts, emotions, and bodily sensations) in a non-judgmental, mindful way, and being committed to pursue one's values. To clarify the potential significance of psychological flexibility in SSD, we examined its levels in 154 people referred to specialized treatment for SDD, as compared to reference groups from the general population encompassing 597 people with CSS and 1422 people without SSD or CSS (controls). Mean levels of psychological flexibility (adjusted for demographic covariates) were lowest for SSD and highest for controls (F = 154.5, p < 0.001, pη2 = 0.13). Percentages of people with low psychological flexibility (<0.8 SD below the mean of controls) were: SSD 74%, CSS 42%, controls 21%. In SSD, higher psychological flexibility was associated with better mental health (ß = 0.56, p < 0.001), but interaction analysis rejected that psychological flexibility preserved health when having more severe somatic symptoms (ß ≤ 0.08, p ≥ 0.10). The results indicate that lower psychological flexibility is a prevalent problem in SSD that is associated with lower mental health. This suggests that it is worthwhile to take account of psychological flexibility in SSD in screening, monitoring, and therapy.

Reactivation of herpesvirus type 6 and IgA/IgM-mediated responses to activin-A underpin long COVID, including affective symptoms and chronic fatigue syndrome.

BACKGROUND: Persistent infection with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), reactivation of dormant viruses, and immune-oxidative responses are involved in long COVID. OBJECTIVES: To investigate whether long COVID and depressive, anxiety, and chronic fatigue syndrome (CFS) symptoms are associated with IgA/IgM/IgG to SARS-CoV-2, human herpesvirus type 6 (HHV-6), Epstein-Barr Virus (EBV), and immune-oxidative biomarkers. METHODS: We examined 90 long COVID patients and ninety healthy controls. We measured serum IgA/IgM/IgG against HHV-6 and EBV and their deoxyuridine 5'-triphosphate nucleotidohydrolase (duTPase), SARS-CoV-2, and activin-A, C-reactive protein (CRP), advanced oxidation protein products (AOPP), and insulin resistance (HOMA2-IR). RESULTS: Long COVID patients showed significant elevations in IgG/IgM-SARS-CoV-2, IgG/IgM-HHV-6, and HHV-6-duTPase, IgA/IgM-activin-A, CRP, AOPP, and HOMA2-IR. Neural network analysis yielded a highly significant predictive accuracy of 80.6% for the long COVID diagnosis (sensitivity: 78.9%, specificity: 81.8%, area under the ROC curve = 0.876); the topmost predictors were as follows: IGA-activin-A, IgG-HHV-6, IgM-HHV-6-duTPase, IgG-SARS-CoV-2, and IgM-HHV-6 (all positively) and a factor extracted from all IgA levels to all viral antigens (inversely). The top 5 predictors of affective symptoms due to long COVID were IgM-HHV-6-duTPase, IgG-HHV-6, CRP, education, IgA-activin-A (predictive accuracy of r = 0.636). The top 5 predictors of CFS due to long COVID were in descending order: CRP, IgG-HHV-6-duTPase, IgM-activin-A, IgM-SARS-CoV-2, and IgA-activin-A (predictive accuracy: r = 0.709). CONCLUSION: Reactivation of HHV-6, SARS-CoV-2 persistence, and autoimmune reactions to activin-A combined with activated immune-oxidative pathways play a major role in the pathophysiology of long COVID as well as the severity of its affective symptoms and CFS.

Time-dependent complexity characterisation of activity patterns in patients with Chronic Fatigue Syndrome.

BACKGROUND: Chronic Fatigue Syndrome patients suffer from symptoms that cannot be explained by a single underlying biological cause. It is sometimes claimed that these symptoms are a manifestation of a disrupted autonomic nervous system. Prior works studying this claim from the complex adaptive systems perspective, have observed a lower average complexity of physical activity patterns in chronic fatigue syndrome patients compared to healthy controls. To further study the robustness of such methods, we investigate the within-patient changes in complexity of activity over time. Furthermore, we explore how these changes might be related to changes in patient functioning. METHODS: We propose an extension of the allometric aggregation method, which characterises the complexity of a physiological signal by quantifying the evolution of its fractal dimension. We use it to investigate the temporal variations in within-patient complexity. To this end, physical activity patterns of 7 patients diagnosed with chronic fatigue syndrome were recorded over a period of 3 weeks. These recordings are accompanied by physicians' judgements in terms of the patients' weekly functioning. RESULTS: We report significant within-patient variations in complexity over time. The obtained metrics are shown to depend on the range of timescales for which these are evaluated. We were unable to establish a consistent link between complexity and functioning on a week-by-week basis for the majority of the patients. CONCLUSIONS: The considerable within-patient variations of the fractal dimension across scales and time force us to question the utility of previous studies that characterise long-term activity signals using a single static complexity metric. The complexity of a Chronic Fatigue Syndrome patient's physical activity signal does not suffice to characterise their high-level functioning over time and has limited potential as an objective monitoring metric by itself.

Efficacy of supervised immersive virtual reality-based training for the treatment of chronic fatigue in post-COVID syndrome: study protocol for a double-blind randomized controlled trial (IFATICO Trial).

BACKGROUND: The treatment of persistent fatigue after COVID-19 infection is complex. On the one hand, it involves maintaining a sufficient level of physical and mental activity to counteract possible degenerative processes of the body and nervous system. On the other hand, physical and mental activities can also lead to worsening of symptoms. Therefore, the challenge in treating Post-COVID fatigue is to stimulate the body and central nervous system in a way that stimulates growth and improvement, but does not overtax individual physical and mental limits. Special training programs try to take these characteristics into account, but often reach their limits. A promising approach is offered by new fitness technologies based on immersive virtual realities that stimulate both body and brain while minimizing physical and psychological stress. The aim of this study is to investigate the efficacy of supervised immersive Virtual Reality (VR)-based activity training compared to conventional activity training for patients with Post-COVID-associated fatigue. METHODS: In a single centre, individually randomised, prospective, double-blind two-arm exploratory superiority trial with parallel group design, N = 100 patients with persistent fatigue after COVID-19 infection will be recruited. The intervention includes a supervised immersive neuromuscular training (12 sessions of 30 min over 6 weeks) based on a novel VR-exercise device. We will systematically compare the effects of this intervention on Post-COVID-associated fatigue with a supervised conventional activation program of comparable scope without an immersive environment. The primary outcome is the difference between groups in absolute change in the mean fatigue symptom severity measured on the Fatigue Severity Scale (FSS) from baseline to posttreatment assessment. Posttreatment assessment in both groups will be conducted by blinded outcome assessors. At three and six months afterwards, patients are sent self-report questionnaires for follow up. The main analysis will be based on the intention-to-treat principle. DISCUSSION: To the best of our knowledge, this is the first exploratory study on a supervised immersive neuromuscular training for the treatment of persistent fatigue after COVID-19 infection. TRIAL REGISTRATION: German register for clinical studies (ID: DRKS00032059) Prospectively registered on June 16th 2023. URL of trial registration.

Different subtypes of chronic fatigue in childhood cancer survivors: A DCCSS LATER study.

INTRODUCTION: The aim of the current study was to investigate whether subtypes of chronic fatigue (CF) can be identified in childhood cancer survivors (CCS), and if so, to determine the characteristics of participants with a specific subtype. METHODS: Participants were included from the nationwide DCCSS LATER cohort. The Checklist Individual Strength (CIS) was completed to assess fatigue. Participants with CF (scored ≥35 on the fatigue severity subscale and indicated to suffer from fatigue for ≥6 months) were divided into subgroups using two-step cluster analysis based on the CIS concentration, motivation, and physical activity subscales. Differences between groups on demographics, psychosocial, lifestyle, and treatment-related variables were determined using ANOVA and chi-square analyses (univariable) and multinomial regression analysis (multivariable). RESULTS: A total of 1910 participants participated in the current study (n = 450 with CF; n = 1460 without CF). Three CF subgroups were identified: Subgroup 1 (n = 133, 29% of participants) had CF with problems in physical activity; Subgroup 2 (n = 111, 25% of participants) had CF with difficulty concentrating; and Subgroup 3 (n = 206, 46% of participants) had multi-dimensional CF. Compared to Subgroup 1, Subgroup 2 more often reported sleep problems, limitations in social functioning, and less often have more than two comorbidities. Subgroup 3 more often reported depression, sleep problems, a lower self-esteem, and limitations in social functioning and a lower educational level compared to Subgroup 1. CONCLUSION: Different subgroups of CCS with CF can be identified based on fatigue dimensions physical activity, motivation and concentration. Results suggest that different intervention strategies, tailored for each subgroup, might be beneficial.

Personalized Management of Fatigue in Individuals With Myalgic Encephalomyelitis/Chronic Fatigue Syndrome and Long COVID Using a Smart Digital mHealth Solution: Protocol for a Participatory Design Approach.

BACKGROUND: Fatigue is the most common symptom in myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) and long COVID, impacting patients' quality of life; however, there is currently a lack of evidence-based context-aware tools for fatigue self-management in these populations. OBJECTIVE: This study aimed to (1) address fatigue in ME/CFS and long COVID through the development of digital mobile health solutions for self-management, (2) predict perceived fatigue severity using real-time data, and (3) assess the feasibility and potential benefits of personalized digital mobile health solutions. METHODS: The MyFatigue project adopts a patient-centered approach within the participatory health informatics domain. Patient representatives will be actively involved in decision-making processes. This study combines inductive and deductive research approaches, using qualitative studies to generate new knowledge and quantitative methods to test hypotheses regarding the relationship between factors like physical activity, sleep behaviors, and perceived fatigue in ME/CFS and long COVID. Co-design methods will be used to develop a personalized digital solution for fatigue self-management based on the generated knowledge. Finally, a pilot study will evaluate the feasibility, acceptance, and potential benefits of the digital health solution. RESULTS: The MyFatigue project opened to enrollment in November 2023. Initial results are expected to be published by the end of 2024. CONCLUSIONS: This study protocol holds the potential to expand understanding, create personalized self-management approaches, engage stakeholders, and ultimately improve the well-being of individuals with ME/CFS and long COVID. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): PRR1-10.2196/50157.

Machine learning algorithms for detection of visuomotor neural control differences in individuals with PASC and ME.

The COVID-19 pandemic has affected millions worldwide, giving rise to long-term symptoms known as post-acute sequelae of SARS-CoV-2 (PASC) infection, colloquially referred to as long COVID. With an increasing number of people experiencing these symptoms, early intervention is crucial. In this study, we introduce a novel method to detect the likelihood of PASC or Myalgic Encephalomyelitis (ME) using a wearable four-channel headband that collects Electroencephalogram (EEG) data. The raw EEG signals are processed using Continuous Wavelet Transform (CWT) to form a spectrogram-like matrix, which serves as input for various machine learning and deep learning models. We employ models such as CONVLSTM (Convolutional Long Short-Term Memory), CNN-LSTM, and Bi-LSTM (Bidirectional Long short-term memory). Additionally, we test the dataset on traditional machine learning models for comparative analysis. Our results show that the best-performing model, CNN-LSTM, achieved an accuracy of 83%. In addition to the original spectrogram data, we generated synthetic spectrograms using Wasserstein Generative Adversarial Networks (WGANs) to augment our dataset. These synthetic spectrograms contributed to the training phase, addressing challenges such as limited data volume and patient privacy. Impressively, the model trained on synthetic data achieved an average accuracy of 93%, significantly outperforming the original model. These results demonstrate the feasibility and effectiveness of our proposed method in detecting the effects of PASC and ME, paving the way for early identification and management of the condition. The proposed approach holds significant potential for various practical applications, particularly in the clinical domain. It can be utilized for evaluating the current condition of individuals with PASC or ME, and monitoring the recovery process of those with PASC, or the efficacy of any interventions in the PASC and ME populations. By implementing this technique, healthcare professionals can facilitate more effective management of chronic PASC or ME effects, ensuring timely intervention and improving the quality of life for those experiencing these conditions.

Impaired Hand Grip Strength Correlates with Greater Disability and Symptom Severity in Post-COVID Myalgic Encephalomyelitis/Chronic Fatigue Syndrome.

Background: Post-COVID syndrome (PCS) encompasses a diverse array of symptoms persisting beyond 3 months after acute SARS-CoV-2 infection, with mental as well as physical fatigue being the most frequent manifestations. Methods: In 144 female patients with PCS, hand grip strength (HGS) parameters were assessed as an objective measure of muscle fatigue, with 78 meeting the Canadian Consensus Criteria for postinfectious myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS). The severity of disability and key symptoms was evaluated using self-reported questionnaires. Results: Patients with ME/CFS exhibited heightened overall symptom severity, including lower physical function (p < 0.001), a greater degree of disability (p < 0.001), more severe fatigue (p < 0.001), postexertional malaise (p < 0.001), and autonomic dysfunction (p = 0.004) compared to other patients with PCS. While HGS was impaired similarly in all patients with PCS and exhibited a significant correlation with physical function across the entire patient group, HGS of patients with ME/CFS uniquely demonstrated associations with key symptoms. Conclusions: Thus, impaired HGS serves as an objective marker of physical function in patients with PCS. Only in patients meeting ME/CFS criteria is impaired HGS also associated with the severity of hallmark symptoms. This suggests a common mechanism for muscle fatigue and other symptoms in the ME/CFS subtype, distinct from that in other types of PCS.

Long COVID: Long-Term Impact of SARS-CoV2.

Four years post-pandemic, SARS-CoV-2 continues to affect many lives across the globe. An estimated 65 million people suffer from long COVID, a term used to encapsulate the post-acute sequelae of SARS-CoV-2 infections that affect multiple organ systems. Known symptoms include chronic fatigue syndrome, brain fog, cardiovascular issues, autoimmunity, dysautonomia, and clotting due to inflammation. Herein, we review long COVID symptoms, the proposed theories behind the pathology, diagnostics, treatments, and the clinical trials underway to explore treatments for viral persistence, autonomic and cognitive dysfunctions, sleep disturbances, fatigue, and exercise intolerance.

Heterogeneity in Measures of Illness among Patients with Myalgic Encephalomyelitis/Chronic Fatigue Syndrome Is Not Explained by Clinical Practice: A Study in Seven U.S. Specialty Clinics.

Background: One of the goals of the Multi-site Clinical Assessment of Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (MCAM) study was to evaluate whether clinicians experienced in diagnosing and caring for patients with myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) recognized the same clinical entity. Methods: We enrolled participants from seven specialty clinics in the United States. We used baseline data (n = 465) on standardized questions measuring general clinical characteristics, functional impairment, post-exertional malaise, fatigue, sleep, neurocognitive/autonomic symptoms, pain, and other symptoms to evaluate whether patient characteristics differed by clinic. Results: We found few statistically significant and no clinically significant differences between clinics in their patients' standardized measures of ME/CFS symptoms and function. Strikingly, patients in each clinic sample and overall showed a wide distribution in all scores and measures. Conclusions: Illness heterogeneity may be an inherent feature of ME/CFS. Presenting research data in scatter plots or histograms will help clarify the challenge. Relying on case-control study designs without subgrouping or stratification of ME/CFS illness characteristics may limit the reproducibility of research findings and could obscure underlying mechanisms.

'The world was going through what we go through everyday': The experiences of women with myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) living with their partners during the COVID-19 lockdown in the United Kingdom.

OBJECTIVES: Myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) is a long-term debilitating illness characterised by profound and persistent fatigue (JAMA: The Journal of the American Medical Association, 313, 2015, 1101). The current study aims to explore the experiences of women with ME/CFS living with their partners during the COVID-19 pandemic in the United Kingdom. DESIGN: The study adopted a qualitative design comprising semi-structured interviews with participants. Interviews were analysed using thematic analysis (TA). METHODS: Participants were women with ME/CFS (n = 21) recruited through ME/CFS support groups in the United Kingdom. All participants were in romantic relationships and lived with their partners. RESULTS: Data were organised into three themes: (1) lockdown disrupting routine, (2) reducing difference and (3) fear of getting COVID-19. People with ME/CFS found that lockdown disrupted their well-established routines. Although routines were disrupted by partners and increased working-from-home practices, participants found having partners at home helpful. People with ME/CFS believed that the changes induced by the pandemic reduced the differences between themselves and the outside world which, prior to lockdown, had felt prominent. They were fearful of getting COVID-19 as they believed this would make their ME/CFS worse. This meant that for people with ME/CFS, the lifting of the lockdown restrictions was an anxiety-provoking time, hence impacting symptoms. People with ME/CFS continued to adhere to government guidelines after national restrictions were eased. CONCLUSIONS: This study outlines the experiences of women with ME/CFS during COVID-19, alongside the long-term impact this has had due to the changes that the pandemic imposed. These findings may have implications for those with long COVID.

Management of severe ME/CFS in children and young people in the UK: a British Paediatric Surveillance Unit study.

OBJECTIVE: Severe myalgic encephalomyelitis or chronic fatigue syndrome (ME/CFS) in children and young people (CYP) is a little-understood condition which significantly impacts education, development and quality of life. We used data from a population-wide surveillance study to explore the screening investigation, referral and management of suspected cases of paediatric severe ME/CFS. METHODS: A British Paediatric Surveillance Unit (BPSU) study reported cases of CYP with suspected severe ME/CFS between February 2018 and February 2019. Paediatricians reporting cases to BPSU and allied healthcare professionals in two large specialist paediatric ME/CFS centres were invited to complete questionnaires for CYP meeting the surveillance case definition. The study focused primarily on CYP with confirmed severe ME/CFS and the extent to which their care met NICE (The National Institute for Health and Care Excellence) recommendations but also considered separately those with probable or possible severe ME/CFS. RESULTS: This study includes a total of 92 CYP with suspected severe ME/CFS; 33 meeting criteria for severe ME/CFS and an additional 59 classified as probable or possible severe ME/CFS. For 16 possible cases, incomplete investigation to exclude alternative diagnoses prevented confirmation of a severe ME/CFS diagnosis. Only 21 of 33 (64%) confirmed severe ME/CFS cases had been referred to specialist services. The management provided varied considerably between patients and four received nothing at all. Of the management provided, the most frequent approaches were medication (67%), activity management (61%) and physiotherapy (61%). Domiciliary assessments and support, and social services referrals were received by 12% and 6% of confirmed severe cases. Similar proportions of management approaches were seen in probable/possible severe ME/CFS. CONCLUSION: Full investigation is frequently incomplete in CYP with suspected severe ME/CFS and recommendations for referral and management are poorly implemented, in particular the needs of CYP who are unable to leave their home might be poorly met.

Clinical evidence of the link between gut microbiome and myalgic encephalomyelitis/chronic fatigue syndrome: a retrospective review.

Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS) is a heterogeneous disorder with elusive causes, but most likely because of clinical and other biological factors. As a vital environmental factor, the gut microbiome is increasingly emphasized in various refractory diseases including ME/CFS. The present study is aimed to enhance our understanding of the relationship between the gut microbiome and ME/CFS through data analysis of various clinical studies. We conducted a literature search in four databases (PubMed, Cochrane Library, Web of Science, and Google Scholar) until May 31, 2023. Our analysis encompassed 11 clinical studies with 553 ME/CFS patients and 480 healthy controls. A comparative analysis of meta data revealed a significant decrease in α-diversity and a noticeable change in ß-diversity in the gut microbiome of ME/CFS patients compared to healthy controls. The notable ratio of Firmicutes and Bacteroides was 2.3 times decreased, and also, there was a significant reduction in the production of microbial metabolites such as acetate, butyrate, isobutyrate, and some amino acids (alanine, serine, and hypoxanthine) observed in ME/CFS patients. The lack of comparison under similar conditions with various standardized analytical methods has impeded the optimal calculation of results in ME/CFS patients and healthy controls. This review provides a comprehensive overview of the recent advancements in understanding the role of the gut microbiome in ME/CFS patients. Additionally, we have also discussed the potentials of using microbiome-related interventions and associated challenges to alleviate ME/CFS.

Burnout, Compassion Fatigue, and the Long Haul of Caring for Long COVID.

The current landscape of clinician burnout is prompting the need for our health care system to revise its approach toward complex conditions such as long coronavirus disease (COVID), myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS), and other postinfectious fatiguing illnesses (PIFIs). We discuss our efforts here at Family Health Center of San Diego (FHCSD) to help share insight and glean perspective from clinicians who have participated in our Centers for Disease Control and Prevention (CDC)-funded 3-year continuing professional development initiative. The Long COVID and Fatiguing Illness Recovery Program uses multidisciplinary team-based case consultation and peer-to-peer sharing of emerging best and promising practices (ie, teleECHO [Extension for Community Healthcare Outcomes]) to support the management of complex cases associated with long COVID, ME/CFS, and other PIFIs. We believe that this perspective captures a key moment in the trajectory of postpandemic clinician burnout and prompts further reflection and action from the health care system to improve clinician- and patient-level outcomes related to the care of patients with postinfectious fatiguing illnesses.