Exploring the prevalence and chest CT predictors of Long COVID in children: a comprehensive study from Shanghai and Linyi.

Introduction: COVID-19 constitutes a pandemic of significant detriment to human health. This study aimed to investigate the prevalence of Long COVID following SARS-CoV-2 infection, analyze the potential predictors of chest CT for the development of Long COVID in children. Methods: A cohort of children who visited the respiratory outpatient clinics at Shanghai Children's Medical Center or Linyi Maternal and Child Health Care Hospital from December 2022 to February 2023 and underwent chest CT scans within 1 week was followed up. Data on clinical characteristics, Long COVID symptoms, and chest CT manifestations were collected and analyzed. Multivariate logistic regression models and decision tree models were employed to identify factors associated with Long COVID. Results: A total of 416 children were included in the study. Among 277 children who completed the follow-up, the prevalence of Long COVID was 23.1%. Chronic cough, fatigue, brain fog, and post-exertional malaise were the most commonly reported symptoms. In the decision tree model for Long COVID, the presence of increased vascular markings, the absence of normal CT findings, and younger age were identified as predictors associated with a higher likelihood of developing Long COVID in children. However, no significant correlation was found between chest CT abnormality and the occurrence of Long COVID. Discussion: Long COVID in children presents a complex challenge with a significant prevalence rate of 23.1%. Chest CT scans of children post-SARS-CoV-2 infection, identified as abnormal with increased vascular markings, indicate a higher risk of developing Long COVID.

Cytokine Profile in Patients with Postacute Sequelae of COVID-19.

The enduring impact of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and its disease manifestation, COVID-19, on public health remains significant. Postacute sequelae of SARS-CoV-2 infection (PASC) affect a considerable number of patients, impairing their quality of life. While the role of the cytokine storm in acute COVID-19 is well established, its contribution to the pathophysiology of PASC is not fully understood. This study aimed to analyze the cytokine profile of patients with PASC following in vitro stimulation of Toll-like receptor (TLR) pathways, comparing them with a healthy control group. From October 2020 till March 2021, Brugmann University Hospital's clinical research unit included patients with PASC in the study. Whole blood samples were collected from 50 patients and 25 healthy volunteers. After in vitro stimulation under five different conditions, cytokine levels were measured using a multiplex method. Significantly decreased cytokine levels were observed in patients with PASC compared with healthy volunteers, particularly after TLR4 (interleukin [IL]-1α, IL-1ß, IL-2, IL-10, interferon (IFN)α, IFNγ, IFNω, and tumor necrosis factor (TNF)α) and TLR7/8 (IL-1α, IL-1ß, IFNα, IFNω, IFNγ, and TNFα) pathway stimulation. Principal component analysis identified two distinct clusters, suggesting a likely dysregulation of immunity involving TLR4 and TLR7/8 pathways in patients with PASC. Our study suggests that TLR4 and TLR7/8 pathways play a role in the pathophysiology of PASC. Continuous basal activation of immunity could explain the high basal concentrations of cytokines described in these patients and the decreased amplitude of response of these signaling pathways following specific stimulation.

Risk factors for long COVID syndrome in postmenopausal women with previously reported diagnosis of COVID-19.

PURPOSE: Long COVID-19 syndrome occurs in 10-20 % of people after a confirmed/probable SARS-COV-2 infection; new symptoms begin within three months of COVID-19 diagnosis and last > 8 weeks. Little is known about risk factors for long COVID, particularly in older people who are at greater risk of COVID complications. METHODS: Data are from Women's Health Initiative (WHI) postmenopausal women who completed COVID surveys that included questions on whether they had ever been diagnosed with COVID and length and nature of symptoms. Long COVID was classified using standard consensus criteria. Using WHI demographic and health data collected at study enrollment (1993-98) through the present day, machine learning identified the top 20 risk factors for long COVID. These variables were tested in logistic regression models. RESULTS: Of n = 37,280 survey respondents, 1237 (mean age = 83 years) reported a positive COVID-19 test and 425 (30 %) reported long COVID. Symptoms included an array of neurological, cardio-pulmonary, musculoskeletal, and general fatigue, and malaise symptoms. Long COVID risk factors included weight loss, physical and mobility limitations, and specific heath conditions (e.g., history of heart valve procedure, rheumatoid arthritis). CONCLUSIONS: Knowledge of risk factors for long COVID may be the first step in understanding the etiology of this complex disease.

A practical framework for Long COVID treatment in primary care.

Long COVID is a complex, multisystem illness with a poorly understood pathophysiology, absence of specific diagnostic tests or criteria, or evidence-based treatments. With over 200 identified symptoms and approximately 10% of COVID-19 cases resulting in Long COVID, it is a challenge to provide comprehensive treatment at a scale commensurate with the illness burden. The diverse manifestations of Long COVID, encompassing numerous medical specialties, typically place primary care providers (PCPs) at the forefront of management, navigating an evolving landscape of research and lack of evidence-based guidelines. This paper presents a pragmatic, structured framework for Long COVID management in primary care, integrating current knowledge and best practices. The approach is individualized, addressing Long COVID's broad symptomatology through a four-step framework. The first step focuses on energy management strategies, emphasizing the prevention of post-exertional malaise, a cardinal feature of Long COVID. The second step, intentional rehabilitation, employs carefully titrated multidisciplinary modalities to address physical, cognitive, and emotional domains. The third step utilizes symptomatic management through both pharmacological and non-pharmacological interventions, targeting debilitating symptoms like fatigue, insomnia, and chronic pain. The fourth step outlines an approach to trialing experimental, targeted therapies that may impact Long COVID's underlying pathophysiology. These treatments, while experimental and lacking quality evidence in Long COVID, may be available off-label on an individual basis following a thorough risk-benefit discussion. This stepwise framework can equip PCPs to effectively address the most common and disabling symptoms of Long COVID, individualize care, and remain attuned to the evolving scientific understanding of the condition.

Understanding post-hospitalised patients' experiences of long-COVID - the PELCO study.

Despite significant advances in long COVID research, many aspects of the condition remain unknown. There is a persisting need for further research to improve the management of long COVID symptoms. This study aimed to explore the experiences and psychological needs of patients who were previously hospitalised with COVID-19, and who subsequently developed long COVID symptoms. Twelve patients with long COVID were interviewed between October 2021 and June 2022. Transcripts were analysed thematically. An overarching theme of 'Existential Crisis' was developed, incorporating three interconnecting sub-themes: 'Facing Psychological Threat', 'Seeking Legitimisation' and 'Forging a Path Through Uncertainty'. Findings suggest that the psychological impact of emergency hospitalisation for COVID-19 can be severe, particularly for those with ongoing long COVID symptoms, and that early psychological intervention should be available. Our findings also suggest the importance of further planning for future pandemics to ensure the presence of patient advocates during hospitalisation at points of critical decision-making.

Biological factors associated with long COVID and comparative analysis of SARS-CoV-2 spike protein variants: a retrospective study in Thailand.

Background: Post-acute COVID-19 syndrome (long COVID) refers to the persistence of COVID-19 symptoms or exceptional symptoms following recovery. Even without conferring fatality, it represents a significant global public health burden. Despite many reports on long COVID, the prevalence and data on associated biological factors remain unclear and limited. This research aimed to determine the prevalence of long COVID during the two distinct epidemic periods in Thailand, due to the Delta and Omicron variants of SARS-CoV-2, and to investigate the biological factors associated with long COVID. In addition, the spike protein amino acid sequences of the Delta and Omicron variants were compared to determine the frequency of mutations and their potential biological implications. Methods: A retrospective cross-sectional study was established to recruit confirmed COVID-19 participants at Maharat Nakhon Ratchasima Hospital who had recovered for at least three months and were infected between June 2021 and August 2022. The demographic data and long COVID experience were collected via telephone interview. The biological factors were analyzed through binary logistic regression. The datasets of the SARS-CoV-2 spike protein amino acid sequence of the Delta and Omicron variants in Thailand were retrieved from GIDSAID to determine mutation frequencies and to identify possible roles of the mutations based on published data. Results: Data was collected from a total of 247 participants comprising 106 and 141 participants of the Delta and Omicron epidemic periods, respectively. Apart from the COVID-19 severity and health status, the baseline participant data of the two time periods were remarkably similar. The prevalence of long COVID observed in the Omicron period was higher than in the Delta period (74.5% vs. 66.0%). The biological factors associated with long COVID were epidemic variant, age, treatment with symptomatic medicines, and vaccination status. When the spike protein sequence data of the two variants were compared, it was observed that the Omicron variant exhibited a greater quantity of amino acid changes in its receptor-binding domain (RBD) and receptor-binding motif (RBM). The critical changes of the Omicron variant within these regions had a significant function in enhancing virus transmissibility and host immune response resistance. Conclusion: This study revealed informative data associated with long COVID in Thailand. More attention should be given to long COVID caused by unique virus variants and other biological factors to prepare a healthcare management strategy for COVID-19 patients after recovery.

Challenges in Daily Computerized Assessment of Cognitive Functions of Post-COVID Patients.

While it would be quite helpful to learn more about the daily fluctuations of fatigue and cognitive impairments of post-COVID patients, their condition can make investigating these especially challenging. By discussing these issues with post-COVID patients and clinical practitioners, we identified six challenges that specifically apply to daily computerized assessment of cognitive functions of post-COVID patients. We proposed solutions for each of the challenges which can be summarized as offering a carefully planned and flexible study design to participants and monitoring their well-being throughout the assessments. We argue that when the proposed precautions are taken, it is feasible to conduct a study that will generate valuable insights into the trajectories of (cognitive) post-COVID symptoms.

Cerebral blood flow alterations and host genetic association in individuals with long COVID: A transcriptomic-neuroimaging study.

Neuroimaging studies have indicated that altered cerebral blood flow (CBF) was associated with the long-term symptoms of postacute sequelae of SARS-CoV-2 infection (PASC), also known as "long COVID". COVID-19 and long COVID were found to be strongly associated with host gene expression. Nevertheless, the relationships between altered CBF, clinical symptoms, and gene expression in the central nervous system (CNS) remain unclear in individuals with long COVID. This study aimed to explore the genetic mechanisms of CBF abnormalities in individuals with long COVID by transcriptomic-neuroimaging spatial association. Lower CBF in the left frontal-temporal gyrus was associated with higher fatigue and worse cognition in individuals with long COVID. This CBF pattern was spatially associated with the expression of 2,178 genes, which were enriched in the molecular functions and biological pathways of COVID-19. Our study suggested that lower CBF is associated with persistent clinical symptoms in long COVID individuals, possibly as a consequence of the complex interactions among multiple COVID-19-related genes, which contributes to our understanding of the impact of adverse CNS outcomes and the trajectory of development to long COVID.

Neuropsychology practice guidance for the neuropsychiatric aspects of Long COVID.

Objective: The coronavirus disease-2019 (COVID-19) pandemic, caused by severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), has had a profound global impact on individual health and well-being in adults and children. While most fully recover from COVID-19, a relatively large subgroup continues to experience persistent physical, cognitive, and emotional/behavioral symptoms beyond the initial infection period. The World Health Organization has termed this phenomenon "Post-COVID-19 Condition" (PCC), better known as "Long COVID." Due to the cognitive and psychosocial symptoms, neuropsychologists often assess and recommend treatment for individuals with Long COVID. However, guidance for neuropsychologists' involvement in clinical care, policy-making, and research has not yet been developed. The authors of this manuscript convened to address this critical gap and develop guidance for clinical neuropsychologists working with patients presenting with Long COVID. Method: Authors include pediatric and adult neuropsychologists with expertise in Long COVID and behavioral health. All authors have been engaged in clinical and research efforts examining the impact of COVID-19. Authors summarized the literature-to-date pertinent to the neuropsychiatric sequelae of Long COVID and developed guidance for neuropsychologists working with individuals with Long COVID. Conclusions: Research findings regarding neuropsychiatric symptoms associated with Long COVID are mixed and limited by methodological differences. As they practice and conduct research, neuropsychologists should remain mindful of the evolving and tenuous nature of the literature.

A Practical Approach to Tailor the Term Long COVID for Diagnostics, Therapy and Epidemiological Research for Improved Long COVID Patient Care.

The term long COVID (LC) effectively describes the broad long-term disease burden of severe acute respiratory syndrome coronavirus type 2 (SARS-CoV-2) infections, encompassing individual suffering and significant socioeconomic impacts. However, its general use hampers precise epidemiological research, diagnostics and therapeutic strategies. Misinterpretations occur, for example, when population surveys are compared to studies using health record data, because both refer to these data as LC. This also emphasizes the need for different terminology. The National Institute for Health and Care Excellence (NICE) rapid guideline differentiates ongoing symptomatic COVID-19 from post-COVID conditions, yet real-world observations challenge these two subgroup definitions. We propose refining the term LC into three subgroups: ongoing symptomatic COVID-19, SARS-CoV-2 induced or exacerbated diseases and post-acute COVID condition. This stratification aids targeted diagnostics, treatment and epidemiological research. Subgroup-specific documentation using the International Classification of Diseases, Tenth Revision (ICD-10) codes ensures accurate tracking and understanding of long-term effects. The subgroup of post-acute COVID condition again includes various symptoms, syndromes and diseases like post-exertional malaise (PEM), dysautonomia or cognitive dysfunctions. In this regard, differentiation, especially considering PEM, is crucial for effective diagnostics and treatment.

Baseline Characteristics in the Remote Diet Intervention to REduce long-COVID Symptoms Trial (ReDIRECT).

Background: The persistence of symptoms for ≥12 weeks after a COVID-19 infection is known as Long COVID (LC), a condition with unclear pathophysiology and no proven treatments to date. Living with obesity is a risk factor for LC and has symptoms which may overlap with and aggravate LC. Methods: ReDIRECT is a remotely delivered trial assessing whether weight management can reduce LC symptoms. We recruited people with LC and BMI >27kg/m 2. The intervention was delivered remotely by dietitians, with online data collection (medical and dietary history, COVID-19 infection and vaccination, body composition, LC history/symptoms, blood pressure, quality of life, sociodemographic data). Participants self-selected the dominant LC symptoms they most wanted to improve from the intervention. Results: Participants (n=234) in England (64%) and Scotland (30%) were mainly women (85%) of white ethnicity (90%), with 13% living in the 20% most deprived areas, a mean age of 46 (SD10) years, and median BMI of 35kg/m 2 (IQR 32-40). Before starting the study, 30% reported more than one COVID-19 infection (82% confirmed with one or more positive tests). LC Diagnosis was mainly by GPs (71%), other healthcare professionals (9%), or self-diagnosed (21%). The median total number of symptoms was 6 (IQR 4-8). Self-selected dominant LC symptoms included fatigue (54%), breathlessness (16%), pain (12%), anxiety/depression (1%) and "other" (17%). At baseline, 82% were taking medication, 57% reported 1+ other medical conditions. Quality of life was poor; 20% were on long-term sick leave or reduced working hours. Most (92%) reported having gained weight since contracting COVID-19 (median weight change +11.5 kg, range -11.5 to +45.3 kg). Conclusions: Symptoms linked to LC and overweight are diverse and complex. Remote trial delivery enabled rapid recruitment across the UK yet certain groups (e.g. men and those from ethnic minority groups) were under-represented. Trial registration: ISRCTN registry ( ISRCTN12595520, 25/11/2021).

Long COVID (LC, symptoms lasting 12 weeks or more after a COVID-19 infection) is a poorly understood condition, with no proven treatments. Living with obesity increases the risk of developing LC; symptoms of obesity overlap and aggravate those of LC. The ReDIRECT study tests, in people living with both LC and overweight, whether weight management can reduce LC symptoms. The study involves total diet replacement (with porridge, soups and shakes) for 12 weeks and is delivered remotely, with dietitian support via internet and/or phone. Researchers collected all data via online forms (medical and diet history, COVID-19 infection and vaccination, weight, height, LC history and symptoms, blood pressure, quality of life, and other demographic data). Each participant selected the LC symptom they most wanted to see improve. Participants (n=234) lived across the UK, were mainly women (85%) of white ethnicity (90%), with 13% living in the 20% most deprived areas. Their average age was 46 years old with an average body mass index (BMI) of 35kg/m ². Diagnosis of LC was mainly by GPs (71%), other healthcare professionals (9%), or self-diagnosed (21%). Participants reported on average 6 symptoms each, identifying fatigue (54%), breathlessness (16%), pain (12%), anxiety/depression (1%) and "other" (17%) as the symptom they would most like to see improve. At the start of the study, most (82%) were taking medication, half (57%) reported 1+ other medical conditions. Quality of life was poor, and 20% were on long-term sick leave or reduced working hours. Most (92%) reported gaining weight since contracting COVID-19, on average +11.5 kg. The baseline characteristics of ReDIRECT study participants show that symptoms linked to LC and overweight are diverse and complex. The study being "remote" means that recruitment was rapid and across the UK, yet certain groups (e.g. men and those from ethnic minority groups) were under-represented.

Predicting Long COVID in the National COVID Cohort Collaborative Using Super Learner: Cohort Study.

BACKGROUND: Postacute sequelae of COVID-19 (PASC), also known as long COVID, is a broad grouping of a range of long-term symptoms following acute COVID-19. These symptoms can occur across a range of biological systems, leading to challenges in determining risk factors for PASC and the causal etiology of this disorder. An understanding of characteristics that are predictive of future PASC is valuable, as this can inform the identification of high-risk individuals and future preventative efforts. However, current knowledge regarding PASC risk factors is limited. OBJECTIVE: Using a sample of 55,257 patients (at a ratio of 1 patient with PASC to 4 matched controls) from the National COVID Cohort Collaborative, as part of the National Institutes of Health Long COVID Computational Challenge, we sought to predict individual risk of PASC diagnosis from a curated set of clinically informed covariates. The National COVID Cohort Collaborative includes electronic health records for more than 22 million patients from 84 sites across the United States. METHODS: We predicted individual PASC status, given covariate information, using Super Learner (an ensemble machine learning algorithm also known as stacking) to learn the optimal combination of gradient boosting and random forest algorithms to maximize the area under the receiver operator curve. We evaluated variable importance (Shapley values) based on 3 levels: individual features, temporal windows, and clinical domains. We externally validated these findings using a holdout set of randomly selected study sites. RESULTS: We were able to predict individual PASC diagnoses accurately (area under the curve 0.874). The individual features of the length of observation period, number of health care interactions during acute COVID-19, and viral lower respiratory infection were the most predictive of subsequent PASC diagnosis. Temporally, we found that baseline characteristics were the most predictive of future PASC diagnosis, compared with characteristics immediately before, during, or after acute COVID-19. We found that the clinical domains of health care use, demographics or anthropometry, and respiratory factors were the most predictive of PASC diagnosis. CONCLUSIONS: The methods outlined here provide an open-source, applied example of using Super Learner to predict PASC status using electronic health record data, which can be replicated across a variety of settings. Across individual predictors and clinical domains, we consistently found that factors related to health care use were the strongest predictors of PASC diagnosis. This indicates that any observational studies using PASC diagnosis as a primary outcome must rigorously account for heterogeneous health care use. Our temporal findings support the hypothesis that clinicians may be able to accurately assess the risk of PASC in patients before acute COVID-19 diagnosis, which could improve early interventions and preventive care. Our findings also highlight the importance of respiratory characteristics in PASC risk assessment. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): RR2-10.1101/2023.07.27.23293272.

Systemic oxidative stress associates with the development of post-COVID-19 syndrome in non-hospitalized individuals.

BACKGROUND: Post-COVID-19 syndrome (PCS) remains a major health issue worldwide, while its pathophysiology is still poorly understood. Systemic oxidative stress (OS) may be involved in PCS, which is reflected by lower circulating free thiols (R-SH, sulfhydryl groups), as they are receptive to rapid oxidation by reactive species. This study aimed to investigate the longitudinal dynamics of serum R-SH after SARS-CoV-2 infection and its association with the development of PCS in individuals with mild COVID-19. METHODS: Baseline serum R-SH concentrations were measured and compared between 135 non-hospitalized COVID-19 subjects and 82 healthy controls (HC). In COVID-19 subjects, serum R-SH concentrations were longitudinally measured during the acute disease phase (up to 3 weeks) and at 3, 6, and 12 months of follow-up, and their associations with relevant clinical parameters were investigated, including the development of PCS. RESULTS: Baseline albumin-adjusted serum R-SH were significantly reduced in non-hospitalized COVID-19 subjects as compared to HC (p = 0.041), reflecting systemic OS. In mild COVID-19 subjects, trajectories of albumin-adjusted serum R-SH levels over a course of 12 months were longitudinally associated with the future presence of PCS 18 months after initial infection (b = -9.48, p = 0.023). CONCLUSION: Non-hospitalized individuals with COVID-19 show evidence of systemic oxidative stress, which is longitudinally associated with the development of PCS. Our results provide a rationale for future studies to further investigate the value of R-SH as a monitoring biomarker and a potential therapeutic target in the development of PCS.

A description of the development of an innovative multi-component long COVID treatment program based on central sensitization with preliminary patient satisfaction data.

OBJECTIVE: Estimates of the prevalence of Long COVID in the United States or worldwide are imprecise, but millions of people are thought to be affected. No effective treatment exists for the often devastating symptoms of Long COVID. Central Sensitization has been postulated as a causal/explanatory mechanism for developing Long COVID. No treatment to date has targeted Central Sensitization. The present cross-sectional study describes the first 140 patients treated in a multi-component treatment program that targets Central Sensitization to reduce symptom burden, improve functioning, and lower the psychological distress observed in these patients. METHODS: 140 patients diagnosed with Long COVID after an extensive medical evaluation were assessed for function, depression, and pain catastrophizing using questionnaires and patient satisfaction measures after completion of a 16-h Cognitive Behavioral Therapy treatment program focused on Central Sensitization. RESULTS: Upon admission, patients diagnosed with Long COVID were significantly impaired in their ability to function due to their symptoms. Further, 70% of the patients were depressed. Pain catastrophizing was observed in up to 20% of patients. CONCLUSION: Patient satisfaction measures were high for the sample at the end of the treatment program suggesting that a multicomponent treatment program targeting Central Sensitization is acceptable to patients. Further research is needed to explore the effectiveness and durability of this treatment approach.

Short-term intermittent hypoxia exposure for dyspnea and fatigue in post-acute sequelae of COVID-19: A randomized controlled study.

BACKGROUND: Post-acute sequelae of COVID-19 (PASC) is incurring a huge health and economic burden worldwide. There is currently no effective treatment or recommended drug for PASC. METHODS: This prospective randomized controlled study was conducted in a hospital in China. The effect of intermittent hypoxia exposure (IHE; 5-min hypoxia alternating with 5-min normal air, repeated five times) on dyspnea and fatigue was investigated in patients meeting the NICE definition of PASC. Patients were computationally randomized to receive normoxia exposure (NE) and routine therapy or IHE and routine therapy. Six-minute walk distance (6MWD) and spirometry were tested before and after the interventions; the Borg Dyspnea Scale (Borg) and the modified Medical Research Council Dyspnea Scale (mMRC) were used to assess dyspnea; and the Fatigue Assessment Scale (FAS) and the Chalder Fatigue Scale-11 (CFQ-11) were used to assess fatigue. The study was registered in the Chinese Clinical Trial Registry (ChiCTR2300070565). FINDINGS: Ninety-five participants (33 males and 62 females) were recruited between March 1, 2023 and December 30, 2023. Forty-seven patients in the IHE group received 10.0 (9.0, 15.0) days of IHE, and 48 patients in NE group received 10.0 (8.0, 12.0) days of NE. 6MWD, forced vital capacity (FVC), FVC %pred, forced expiratory volume in 1 s (FEV1), FEV1 %pred, tidal volume (VT), and dyspnea and fatigue scales markedly improved after IHE (p < 0.05), and improvements were greater than in the NE group (all p < 0.05). Furthermore, participants in IHE group had better subjective improvements in dyspnea and fatigue than those in the NE group (p < 0.05). Compared with <10 days of IHE, ≥10 days of IHE had a greater impact on 6MWD, FVC, FEV1, FEV1 %pred, VT, FAS, and CFQ-11. No severe adverse events were reported. INTERPRETATION: IHE improved spirometry and 6MWD and relieved dyspnea and fatigue in PASC patients. Larger prospective studies are now needed to verify these findings.

Prevalence, risk factors and characterisation of individuals with long COVID using Electronic Health Records in over 1.5 million COVID cases in England.

OBJECTIVES: This study examines clinically confirmed long-COVID symptoms and diagnosis among individuals with COVID in England, aiming to understand prevalence and associated risk factors using electronic health records. To further understand long COVID, the study also explored differences in risks and symptom profiles in three subgroups: hospitalised, non-hospitalised, and untreated COVID cases. METHODS: A population-based longitudinal cohort study was conducted using data from 1,554,040 individuals with confirmed SARS-CoV-2 infection via Clinical Practice Research Datalink. Descriptive statistics explored the prevalence of long COVID symptoms 12 weeks post-infection, and Cox regression models analysed the associated risk factors. Sensitivity analysis was conducted to test the impact of right-censoring data. RESULTS: During an average 400-day follow-up, 7.4% of individuals with COVID had at least one long-COVID symptom after acute phase, yet only 0.5% had long-COVID diagnostic codes. The most common long-COVID symptoms included cough (17.7%), back pain (15.2%), stomach-ache (11.2%), headache (11.1%), and sore throat (10.0%). The same trend was observed in all three subgroups. Risk factors associated with long-COVID symptoms were female sex, non-white ethnicity, obesity, and pre-existing medical conditions like anxiety, depression, type II diabetes, and somatic symptom disorders. CONCLUSIONS: This study is the first to investigate the prevalence and risk factors of clinically confirmed long-COVID in the general population. The findings could help clinicians identify higher risk individuals for timely intervention and allow decision-makers to more efficiently allocate resources for managing long-COVID.

Designing and optimizing clinical trials for long COVID.

Long COVID is a debilitating, multisystemic illness following a SARS-CoV-2 infection whose duration may be indefinite. Over four years into the pandemic, little knowledge has been generated from clinical trials. We analyzed the information available on ClinicalTrials.gov, and found that the rigor and focus of trials vary widely, and that the majority test non-pharmacological interventions with insufficient evidence. We highlight promising trials underway, and encourage the proliferation of clinical trials for treating Long COVID and other infection-associated chronic conditions and illnesses (IACCIs). We recommend several guidelines for Long COVID trials: First, pharmaceutical trials with potentially curative, primary interventions should be prioritized, and both drug repurposing and new drug development should be pursued. Second, study designs should be both rigorous and accessible, e.g., triple-blinded randomized trials that can be conducted remotely, without participants needing to leave their homes. Third, studies should have multiple illness comparator cohorts for IACCIs such as myalgic encephalomyelitis (ME/CFS) and dysautonomia, and screen for the full spectrum of symptomatology and pathologies of these illnesses. Fourth, studies should consider inclusion/exclusion criteria with an eye towards equity and breadth of representation, including participants of all races, ethnicities, and genders most impacted by COVID-19, and including all levels of illness severity. Fifth, involving patient-researchers in all aspects of studies brings immensely valuable perspectives that will increase the impact of trials. We also encourage the development of efficient clinical trial designs including methods to study several therapies in parallel.

Adult outpatients with long COVID infected with SARS-CoV-2 Omicron variant. Part 1: Oral microbiota alterations.

BACKGROUND: Many individuals experience long COVID after SARS-CoV-2 infection. As microbiota can influence health, it may change with COVID-19. This study investigated differences in oral microbiota between COVID-19 patients with and without long COVID. METHODS: Based on a prospective follow-up investigation, this nested case-control study evaluated the differences in oral microbiota in individuals with and without long COVID (Symptomatic and Asymptomatic groups), which were assessed by 16S rRNA sequencing on tongue coating samples. A predictive model was established using machine learning based on specific differential microbial communities. RESULTS: One-hundred-and-eight patients were included (n=54 Symptomatic group). The Symptomatic group had higher Alpha diversity indices (observed_otus, Chao1, Shannon, and Simpson indices), differences in microbial composition (Beta diversity), and microbial dysbiosis with increased diversity and relative abundance of pathogenic bacteria. Marker bacteria (c__Campylobacterota, o__Coriobacteriales, o__Pseudomonadales, and o__Campylobacterales) were associated with long COVID by linear discriminant analysis effect size and receiver operating characteristic curves (AUC 0.821). CONCLUSION: There were distinct variations in oral microbiota between COVID-19 patients with and without long COVID. Changes in oral microbiota may indicate long COVID.

Prevalence of infection and reinfection among healthcare workers in a hospital of Northern China between BA.5/BF. 7 and XBB.1.5 wave.

BACKGROUND: Healthcare workers (HCWs) play a crucial role as frontline responders during the COVID-19 pandemic. This study aimed to analyze the epidemiological characteristics of the first SARS-CoV-2 infection and reinfection associated with the emergence of Omicron variant in HCWs. METHODS: We enrolled 760 HCWs who received 2-4 vaccination doses of COVID-19 and followed by BA.5/BF.7 and/or XBB.1.5 breakthrough infections between December 2022 and July 2023. Serum sample from each individual were collected approximately 1,3 and 6 months after last exposure. IgM, IgG and Total antibodies against SARS-CoV-2 were measured by chemiluminescent immunoassay. Meanwhile, we created an Enterprise WeChat link for HCWs to self-report SARS-CoV-2 infections, symptoms and post COVID-19 conditions. RESULTS: Our study revealed that the reinfection rate among HCWs reached 26.1%. The main symptoms were fever (91.2% vs. 60.1%), cough (78.8% vs. 58.0%), and sore throat (75.4% vs. 59.6%) during infection and reinfection in Omicron BA.5/BF.7 and XBB.1.5 wave, and the interval for reinfection ranged from 91 to 210 days (median 152 days). Fatigue (23.6%), memory loss (18.8%) and coughing (18.6%) were the most prevalent long COVID symptoms in HCWs, with a higher prevalence among female HCWs. CONCLUSIONS: HCWs reinfection with SARS-CoV-2 causes milder symptoms, but high reinfection rate and short intervals. Enhancing prevention strategies, protection and training is crucial to mitigating HCW infection risk and improving health services.