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.
UNASSIGNED: RR2-10.1101/2023.07.27.23293272.

UNASSIGNED: 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.
UNASSIGNED: 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.
UNASSIGNED: 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).
UNASSIGNED: 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.
UNASSIGNED: 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.

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.

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.

OBJECTIVE: 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.

UNASSIGNED: SARS-CoV-2 pandemic still poses a significant burden on global health and economy, especially for symptoms persisting beyond the acute disease. COVID-19 manifests with various degrees of severity and the identification of early biomarkers capable of stratifying patient based on risk of progression could allow tailored treatments.
UNASSIGNED: We longitudinally analyzed 67 patients, classified according to a WHO ordinal scale as having Mild, Moderate, or Severe COVID-19. Peripheral blood samples were prospectively collected at hospital admission and during a 6-month follow-up after discharge. Several subsets and markers of the innate and adaptive immunity were monitored as putative factors associated with COVID-19 symptoms.
UNASSIGNED: More than 50 immunological parameters were associated with disease severity. A decision tree including the main clinical, laboratory, and biological variables at admission identified low NK-cell precursors and CD14+CD91+ monocytes, and high CD8+ Effector Memory T cell frequencies as the most robust immunological correlates of COVID-19 severity and reduced survival. Moreover, low regulatory B-cell frequency at one month was associated with the susceptibility to develop long COVID at six months, likely due to their immunomodulatory ability.
UNASSIGNED: These results highlight the profound perturbation of the immune response during COVID-19. The evaluation of specific innate and adaptive immune-cell subsets allows to distinguish between different acute and persistent COVID-19 symptoms.

BACKGROUND: Omicron variant impacts populations with its rapid contagiousness, and part of patients suffered from persistent symptoms termed as long COVID. The molecular and immune mechanisms of this currently dominant global variant leading to long COVID remain unclear, due to long COVID heterogeneity across populations.
METHODS: We recruited 66 participants in total, 22 out of 66 were healthy control without COVID-19 infection history, and 22 complaining about long COVID symptoms 6 months after first infection of Omicron, referred as long COVID (LC) Group. The left ones were defined as non-long COVID (NLC) Group. We profiled them via plasma neutralizing antibody titer, SARS-CoV-2 viral load, transcriptomic and proteomics screening, and machine learning.
RESULTS: No serum residual SARS-CoV-2 was observed in the participants 6 months post COVID-19 infection. No significant difference in neutralizing antibody titers was found between the long COVID (LC) Group and the non-long COVID (NLC) Group. Transcriptomic and proteomic profiling allow the stratification of long COVID into neutrophil function upregulated (NU-LC) and downregulated types (ND-LC). The NU-LC, identifiable through a refined set of 5 blood gene markers (ABCA13, CEACAM6, CRISP3, CTSG and BPI), displays evidence of relatively higher neutrophil counts and function of degranulation than the ND-LC at 6 months after infection, while recovered at 12 months post COVID-19.
CONCLUSIONS: The transcriptomic and proteomic profiling revealed heterogeneity among long COVID patients. We discovered a subgroup of long COVID population characterized by neutrophil activation, which might associate with the development of psychiatric symptoms and indicate a higher inflammatory state. Meanwhile, a cluster of 5 genes was manually curated as the most potent discriminators of NU-LC from long COVID population. This study can serve as a foundational exploration of the heterogeneity in the pathogenesis of long COVID and assist in therapeutic targeting and detailed epidemiological investigation of long COVID.

The global impact of coronavirus disease 2019 (COVID-19) marked by numerous pandemic peaks is attributed to its high variability and infectious nature, transforming it into a persistent global public health concern. With hundreds of millions of cases reported globally, the illness is caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Despite its initial classification as an acute respiratory illness, recent evidence indicates that lingering effects on various bodily systems, such as cardiovascular, pulmonary, nervous, gastrointestinal (GI), and musculoskeletal, may endure well beyond the acute phase. These persistent manifestations following COVID-19, commonly known as long COVID, have the potential to affect individuals across the entire range of illness severity, with a tendency to be more prevalent in mild to moderate cases. At present, there are no established criteria for diagnosing long COVID. Nonetheless, it is conceptualized as a multi-organ disorder encompassing a diverse array of clinical manifestations. The most common, persistent, and debilitating symptoms of long COVID may be neurological, known as neurological complications of post-acute sequelae of COVID-19 (NC-PASC). More than one-third of individuals with a prior SARS-CoV-2 infection show involvement of both the central nervous system (CNS) and peripheral nervous system (PNS), as evidenced by an approximately threefold higher incidence of neurological symptoms in observational studies. The persistent neurological symptoms of long COVID encompass fatigue, headache, cognitive decline, \"brain fog\", dysautonomia, neuropsychiatric issues, loss of smell (anosmia), loss of taste (ageusia), and peripheral nerve problems (peripheral neuropathy). Reported pathogenic mechanisms encompass viral persistence and neuro-invasion by SARS-CoV-2, neuroinflammation, autoimmunity, coagulopathy, and endotheliopathy. Raising awareness of potential complications is crucial for preventing and alleviating the long-term effects of long COVID and enhancing the prognosis for affected patients. This review explores the hypothetical pathophysiological mechanisms and pathways of NC-PASC with a sole aim to increase awareness about this crippling disease.

Long COVID, often following SARS-CoV-2 infection, may stem from sustained inflammation, overlapping with autoimmune diseases like sarcoidosis. Though specific treatments lack, this link could shape future diagnostic and therapeutic methods.

BACKGROUND: Cognitive impairment can be caused by infections with various pathogens, including SARS-CoV-2. Research has yet to determine the true incidence and course of cognitive impairment in older adults following COVID-19. Furthermore, research has theorised that COVID-19 is associated with dementia progression and diagnosis but this association has yet to be fully described.
METHODS: A systematic review was registered in Prospero and conducted on the databases PubMed, Embase, Ovid, CENTRAL and Cochrane Library. Studies reporting cognitive impairment and dementia outcomes in post-acute and post-COVID-19 patients aged ≥65 years, and which included control data, were included in this review.
RESULTS: 15,124 articles were identified by the search strategy. After eliminating duplicate titles and completing title, abstracts and full-text review, 18 studies were included comprising of 412,957 patients with COVID-19 (46.63% male) and 411,929 patients without COVID-19 (46.59% male). The overall mean Montreal Cognitive Assessment (MoCA) score in COVID-19 patients was 23.34 out of 30 (95% CI [22.24, 24.43]). indicating cognitive impairment. The overall proportion of patients identified as having new onset cognitive impairment was 65% (95% CI [44, 81]). Subgroup analyses indicated that time since infection significantly improves overall MoCA score and reduces proportion of patients with cognitive impairment.
CONCLUSIONS: This study indicates that cognitive impairment may be an important sequela of COVID-19. Further research with adequate sample sizes is warranted regarding COVID-19\'s association with new-onset dementia and dementia progression, and the effect of repeat infections. There is a need for development of diagnostic and management protocols for COVID-19 patients with cognitive impairment.