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Background Self-rated health (SRH) is widely recognized as a clinically significant predictor of subsequent mortality risk. Although COVID-19 may impair SRH, this relationship has not been extensively examined. The present study aimed to examine the correlation between habitual sleep duration, changes in sleep duration after infection, and SRH in subjects who have experienced SARS-CoV-2 infection. Methods Participants from 16 countries participated in the International COVID Sleep Study-II (ICOSS-II) online survey in 2021. A total of 10,794 of these participants were included in the analysis, including 1,509 COVID-19 individuals (who reported that they had tested positive for COVID-19). SRH was evaluated using a 0-100 linear visual analog scale. Habitual sleep durations of < 6 h and > 9 h were defined as short and long habitual sleep duration, respectively. Changes in habitual sleep duration after infection of ≤ -2 h and ≥ 1 h were defined as decreased or increased, respectively. Results Participants with COVID-19 had lower SRH scores than non-infected participants, and those with more severe COVID-19 had a tendency towards even lower SRH scores. In a multivariate regression analysis of participants who had experienced COVID-19, both decreased and increased habitual sleep duration after infection were significantly associated with lower SRH after controlling for sleep quality ( β = − 0.056 and − 0.058, respectively, both p < 0.05); however, associations between current short or long habitual sleep duration and SRH were negligible. Multinomial logistic regression analysis showed that decreased habitual sleep duration was significantly related to increased fatigue (odds ratio [OR] = 1.824, p < 0.01), shortness of breath (OR = 1.725, p < 0.05), diarrhea/nausea/vomiting (OR = 2.636, p < 0.01), and hallucinations (OR = 5.091, p < 0.05), while increased habitual sleep duration was significantly related to increased fatigue (OR = 1.900, p < 0.01). Conclusions Changes in habitual sleep duration following SARS-CoV-2 infection were associated with lower SRH. Decreased or increased habitual sleep duration might have a bidirectional relation with post-COVID-19 symptoms. Further research is needed to better understand the mechanisms underlying these relationships for in order to improve SRH in individuals with COVID-19.

Abstract Study Objectives Obstructive sleep apnea (OSA) has been associated with more severe acute coronavirus disease-2019 (COVID-19) outcomes. We assessed OSA as a potential risk factor for Post-Acute Sequelae of SARS-CoV-2 (PASC). Methods We assessed the impact of preexisting OSA on the risk for probable PASC in adults and children using electronic health record data from multiple research networks. Three research networks within the REsearching COVID to Enhance Recovery initiative (PCORnet Adult, PCORnet Pediatric, and the National COVID Cohort Collaborative [N3C]) employed a harmonized analytic approach to examine the risk of probable PASC in COVID-19-positive patients with and without a diagnosis of OSA prior to pandemic onset. Unadjusted odds ratios (ORs) were calculated as well as ORs adjusted for age group, sex, race/ethnicity, hospitalization status, obesity, and preexisting comorbidities. Results Across networks, the unadjusted OR for probable PASC associated with a preexisting OSA diagnosis in adults and children ranged from 1.41 to 3.93. Adjusted analyses found an attenuated association that remained significant among adults only. Multiple sensitivity analyses with expanded inclusion criteria and covariates yielded results consistent with the primary analysis. Conclusions Adults with preexisting OSA were found to have significantly elevated odds of probable PASC. This finding was consistent across data sources, approaches for identifying COVID-19-positive patients, and definitions of PASC. Patients with OSA may be at elevated risk for PASC after SARS-CoV-2 infection and should be monitored for post-acute sequelae. Graphical Abstract

While there are many postulates for the etiology of post-viral chronic fatigue and other symptomatology, little is known. We draw on our past experience of these syndromes to devise means which can expose the primary players of this malady in terms of a panoply participating biomolecules and the state of the stool microbiome. Using databases established from a large dataset of patients at risk of colorectal cancer who were followed longitudinally over 3 decades, and a smaller database dedicated to building a Long PASC cohort (Post-Acute Sequelae of COVID-19), we were able to ascertain factors that predisposed patients to (and resulted in) significant changes in various biomarkers, i.e., the stool microbiome and serum cytokine levels, which we verified by collecting stool and serum samples. There were significant changes in the stool microbiome with an inversion from the usual Bacillota and Bacteroidota species. Serum cytokines showed significant differences in MIP-1β versus TARC (CC chemokine ligand 17) in patients with either PASC or COVID-19 (p < 0.02); IL10 versus IL-12p70a (p < 0.02); IL-1b versus IL-6 (p < 0.01); MCP1 versus TARC (p < 0.03); IL-8 versus TARC (p < 0.002); and Eotaxin3 versus TARC (p < 0.004) in PASC. Some changes were seen solely in COVID-19, including MDC versus MIP-1α (p < 0.01); TNF-α versus IL-1-β (p < 0.06); MCP4 versus TARC (p < 0.0001). We also show correlates with chronic fatigue where an etiology was not identified. These findings in patients with positive criteria for PASC show profound changes in the microbiome and serum cytokine expression. Patients with chronic fatigue without clear viral etiologies also have common associations, including a history of tonsillectomy, which evokes a likely immune etiology.

Background The aim of our study was to determine whether the application of machine learning could predict PASC by using diagnoses from primary care and prescribed medication 1 year prior to PASC diagnosis. Methods This population-based case–control study included subjects aged 18–65 years from Sweden. Stochastic gradient boosting was used to develop a predictive model using diagnoses received in primary care, hospitalization due to acute COVID- 19, and prescribed medication. The variables with normalized relative influence (NRI) ≥ 1% showed were considered predictive. Odds ratios of marginal effects (OR ME ) were calculated. Results The study included 47,568 PASC cases and controls. More females ( n  = 5113) than males ( n  = 2815) were diagnosed with PASC. Key predictive factors identified in both sexes included prior hospitalization due to acute COVID- 19 (NRI 16.1%, OR ME 18.8 for females; NRI 41.7%, OR ME 31.6 for males), malaise and fatigue (NRI 14.5%, OR ME 4.6 for females; NRI 11.5%, OR ME 7.9 for males), and post-viral and related fatigue syndromes (NRI 10.1%, OR ME 21.1 for females; NRI 6.4%, OR ME 28.4 for males). Conclusions Machine learning can predict PASC based on previous diagnoses and medications. Use of this AI method could support diagnostics of PASC in primary care and provide insight into PASC etiology.

SARS‐CoV‐2 infection and the resultant COVID‐19 pneumonia cause significant damage to the airway and lung epithelium. This damage manifests as mucus hypersecretion, pulmonary inflammation and fibrosis, which often lead to long‐term complications collectively referred to as long COVID or post‐acute sequelae of COVID‐19 (PASC). The airway epithelium, as the first line of defence against respiratory pathogens, depends on airway basal stem cells (BSCs) for regeneration. Alterations in BSCs are associated with impaired epithelial repair and may contribute to the respiratory complications observed in PASC. Given the critical role of BSCs in maintaining epithelial integrity, understanding their alterations in COVID‐19 is essential for developing effective therapeutic strategies. This study investigates the intrinsic properties of BSCs derived from COVID‐19 patients and evaluates the modulatory effects of mesenchymal stem cells (MSCs). Through a combination of functional assessments and transcriptomic profiling, we identified key phenotypic and molecular deviations in COVID‐19 patient‐derived BSCs, including goblet cell hyperplasia, inflammation and fibrosis, which may underlie their contribution to PASC. Notably, MSC co‐culture significantly mitigated these adverse effects, potentially through modulation of the interferon signalling pathway. This is the first study to isolate BSCs from COVID‐19 patients in the Chinese population and establish a COVID‐19 BSC‐based xenograft model. Our findings reveal critical insights into the role of BSCs in epithelial repair and their inflammatory alterations in COVID‐19 pathology, with potential relevance to PASC and virus‐induced respiratory sequelae. Additionally, our study highlights MSC‐based therapies as a promising strategy to address respiratory sequelae and persistent symptoms. Airway basal stem cells derived from COVID‐19 patients demonstrated pronounced goblet cell hyperplasia, inflammatory responses and tendencies toward fibrosis. Co‐culture with mesenchymal stem cells (MSCs) notably reduced these pathological changes, likely due to MSCs' regulatory effects on the interferon signalling pathway.

Introduction Many patients report neuropsychiatric symptoms after SARS‐CoV‐2 infection. Data on prevalence of post‐COVID‐19 condition (PCC) vary due to the lack of specific diagnostic criteria, the report of unspecific symptoms, and reliable biomarkers. Methods PCC patients seen in a neurological outpatient department were followed for up to 18 months. Neurological examination, SARS‐CoV‐2 antibodies, Epstein–Barr virus antibodies, and cortisol levels as possible biomarkers, questionnaires to evaluate neuropsychiatric symptoms and somatization (Patient Health Questionnaires D [PHQ‐D]), cognition deficits (Montreal Cognitive Assessment [MoCA]), sleep disorders (ISS, Epworth Sleepiness Scale [ESS]), and fatigue (FSS) were included. Results A total of 175 consecutive patients (78% females, median age 42 years) were seen between May 2021 and February 2023. Fatigue, subjective stress intolerance, and subjective cognitive deficits were the most common symptoms. Specific scores were positive for fatigue, insomnia, and sleepiness and were present in 95%, 62.1%, and 44.0%, respectively. Cognitive deficits were found in 2.3%. Signs of somatization were identified in 61%, who also had an average of two symptoms more than patients without somatization. Overall, 28% had a psychiatric disorder, including depression and anxiety. At the second visit (n = 92), fatigue (67.3%) and insomnia (45.5%) had decreased. At visit three (n = 43), symptom load had decreased in 76.8%; overall, 51.2% of patients were symptom‐free. Biomarker testing did not confirm an anti‐EBV response. SARS‐CoV‐2‐specific immune reactions increased over time, and cortisol levels were within the physiological range. Conclusion Despite high initial symptom load, 76.8% improved over time. The prevalence of somatization and psychiatric disorders was high. Our data do not confirm the role of previously suggested biomarkers in PCC patients. Numerous patients report neuropsychiatric symptoms following SARS‐CoV‐2 infection, with fatigue, stress intolerance, and cognitive deficits being predominant. In a cohort of 175 patients, 61% exhibited somatization, frequently accompanied by higher symptom load. Questionnaire assessments and self‐reported symptom load showed a reduction in symptoms over time for the majority of patients. Biomarker testing did not support Epstein–Barr virus involvement, and cortisol levels remained within the normal range.

Post‐acute sequelae of SARS‐CoV‐2 (PASC or “long COVID”) and chronic fatigue syndrome/myalgic encephalitis (CFS/ME) share symptoms such as exertional dyspnea. We used exercise oxygen pathway analysis, comprising six parameters of oxygen transport and utilization, to identify limiting mechanisms in both conditions. Invasive cardiopulmonary exercise testing was performed on 15 PASC patients, 11 CFS/ME patients, and 11 controls. We evaluated the contributions of alveolar ventilation (V̇a), lung diffusion capacity (DL ), cardiac output (Q̇), skeletal muscle diffusion capacity (DM ), hemoglobin (Hb), and mitochondrial oxidative phosphorylation (Vmax) to peak oxygen consumption (V̇O2peak). To simulate targeted interventions, each variable was sequentially normalized to assess its impact on V̇O2peak. V̇O2peak was significantly reduced in both PASC and CFS/ME compared to controls. Skeletal muscle O2 diffusion (DM ) was the most impaired parameter in both patient groups (p = 0.01). Correcting DM alone improved V̇O2 by 66% in PASC (p = 0.008) and 34.7% in CFS/ME (p = 0.06), suggesting a dominant role for peripheral O2 extraction in exercise limitation. Impaired skeletal muscle oxygen diffusion (DM ) is a shared mechanism of exercise intolerance in PASC and CFS/ME and may represent a therapeutic target. However, our findings are limited by small sample size.

Aim This pilot examined the effect of online peer support on mental health problems among individuals with post‐acute sequelae of COVID‐2019 (PASC). Methods A single‐arm pre‐post design of online peer‐support design consisting of eight sessions of 1 h per week with three to six participants and two facilitators per group was performed. Participants were recruited from online communities, social media, and medical clinics for the PASC between May and August 2023. The degrees of depression, anxiety, loneliness, social withdrawal, and self‐esteem were measured pre‐ and post‐intervention. Participants' statements during the sessions were analyzed using thematic analyses. Results Of the 18 participants, three dropped out of the interventions, and 17 (including two participants who dropped out) completed the pre‐ and post‐intervention questionnaires. Depression severity significantly decreased in the paired t‐test and linear mixed model. The following interactions were extracted: conveying the same feelings, dealing with difficulties, showing empathy, enhancing the atmosphere, and adapting to suit health conditions. Impressions extracted from participating in the interventions included feelings of emotional support, a sense of bonding, changes in perspective, changes in behaviors or new actions through participation, inadequacy during sessions, and adverse effects associated with participation. Conclusion Online peer support may be helpful in treating depression in individuals with PASC. This pre‐post study investigated the effects of an online peer‐support group on mental health in individuals with post‐acute sequelae of COVID‐19. Of 18 participants, 17 completed both the pre‐ and post‐intervention questionnaires, and 15 remained until the end of intervention program, which included 8 weekly 1‐h sessions. Repeated t‐test showed a significant decrease in depression severity from pre‐ to post‐intervention under both intention to treat and per protocol analyses.

The present study provides a brief survey, based on a search of the US National Institutes of Health dataset Clinicaltrials.gov, of clinical trials for interventions that could prevent, mitigate or cure Long COVID, a syndrome of increasing concern to patients and their physicians, as the acute phase years of the main pandemic recede and some patients remain afflicted by the failure of the disease signs to completely abate. The disease is pleomorphic in its presentations and severity, with the consequence that there is no one generally accepted approach to treatment, and clinical trial design can be a challenge. At time of writing, there is no approved therapeutic intervention or combination of interventions for Long COVID. Over the last 3 years, there have been several reviews of the state-of-play in relation to therapies for long COVID; however, this is a rapidly moving field and the intention of this brief article is to provide a succinct update on a subset of potential interventional therapies that are currently undergoing clinical trial. There are at least 82 unique active agents in development, and they are characterised by diverse mechanisms of action; however, the emergency approach that was employed during the COVID-19 pandemic is not being replicated for development of treatments for Long COVID.

Post‐COVID conditions, also known as post‐acute sequelae of SARS‐CoV‐2 (PASC), refer to the persistence of symptoms in COVID‐19 long‐haulers. Various manifestations of post‐COVID conditions are general symptoms and/or manifestations of damage in multiple organs. Besides, SARS‐CoV‐2 can involve the gastrointestinal tract, resulting in sequelae such as diarrhea, abdominal pain, nausea, anorexia, vomiting, constipation, abdominal distension, acid reflux, and/or gastrointestinal bleeding. Previous investigations point to SARS‐CoV‐2 entry into enterocytes enhances by the angiotensin‐converting enzyme 2 (ACE2) receptors. Interestingly, ACE2 receptors are abundantly expressed in the gut, implying infection with SARS‐CoV‐2 might occur through this route as well as in the respiratory tract. According to mounting evidence, SARS‐CoV‐2 RNA has been identified in fecal specimens of patients with COVID‐19 during and beyond the acute phase. In addition, studies have shown gut microbiome composition is altered in patients with PASC, hence, another putative mechanism linked to gastrointestinal symptoms is gut dysbiosis. The presence of the gut‐lung axis in COVID‐19 might have major implications for disease pathogenesis and treatment. This review discussed the prevalence of gastrointestinal symptoms and pathophysiology underlying possible infection of the gut in patients with PASC. Also, SARS‐COV‐2 induced NLRP3 inflammasome‐dependent inflammatory pathways are briefly addressed. The gastrointestinal symptoms associated with post coronavirus disease (COVID) conditions could stem from disruptions in the gut‐lung axis caused by infection with severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2). The present review article aims to shed light on this subject matter with an emphasis on NLRP3‐mediated inflammation in COVID‐19.