The molecular fingerprint of neuroinflammation in COVID-19: A comprehensive discussion on molecular mechanisms of neuroinflammation due to SARS-COV2 antigens

Abstract:

Background and objective: Severe acute respiratory syndrome coronavirus 2 attacks the neural system directly and indirectly via various systems, such as the nasal cavity, olfactory system, and facial nerves. Considering the high energy requirement, lack of antioxidant defenses, and high amounts of metal ions in the brain, oxidative damage is very harmful to the brain. Various neuropathic pain conditions, neurological disorders, and neuropsychiatric complications were reported in Coronavirus disease 2019, prolonged Coronavirus disease 2019, and after Coronavirus disease 2019 immunization. This manuscript offers a distinctive outlook on the interconnectedness between neurology and neuropsychiatry through its meticulous analysis of complications.

Discussion: After recovering from Coronavirus disease 2019, approximately half of the patients reported developing Myalgic Encephalomyelitis/Chronic Fatigue Syndrome. Long Coronavirus disease 2019 imaging reports illustrated the hypometabolism in various parts of the brain, such as olfactory bulbs, limbic/paralimbic domains, the brainstem, and the cerebellum. Ninety imaging and neuropathological studies of Coronavirus disease 2019 have shown evidence of white matter, brainstem, frontotemporal, and oculofrontal lesions. Emotional functions, such as pleasant, long/short-term memory, movement, cognition and cognition in decision-making are controlled by these regions. The neuroinflammation and the mechanisms of defense are well presented in the discussion. The role of microglia activation, Inducible NO synthase, Cyclooxygenases ½, Reactive oxygen species, neurotoxic toxins and pro-inflammatory cytokines, such as Interleukin-1 beta, Interleukin-6 and Tumor Necrosis Factor-alpha are highlighted in neuronal dysfunction and death. Nuclear factor kappa-light-chain-enhancer of activated B cells, Mitogen-activated protein kinase, Activator Protein 1, and Interferon regulatory factors are the main pathways involved in microglia activation in Coronavirus disease 2019 neuroinflammation.

Conclusion: The neurological aspect of Coronavirus disease 2019 should be highlighted. Neurological, psychological, and behavioral aspects of Coronavirus disease 2019, prolonged Coronavirus disease 2019, and Coronavirus disease 2019 vaccines can be the upcoming issues. We need a global awareness where this aspect of the disease should be more considered in health research.

Source: Zayeri ZD, Torabizadeh M, Kargar M, Kazemi H. The molecular fingerprint of neuroinflammation in COVID-19: A comprehensive discussion on molecular mechanisms of neuroinflammation due to SARS-COV2 antigens. Behav Brain Res. 2024 Jan 20;462:114868. doi: 10.1016/j.bbr.2024.114868. Epub ahead of print. PMID: 38246395. https://www.sciencedirect.com/science/article/abs/pii/S016643282400024X

Prevalence and Factors Associated with Long COVID Symptoms among U.S. Adults, 2022

Abstract:

Long COVID and its symptoms have not been examined in different subpopulations of U.S. adults. Using the 2022 BRFSS (n = 445,132), we assessed long COVID and each symptom by sociodemographic characteristics and health-related variables. Multivariable logistic regression was conducted to examine factors associated with long COVID and the individual symptoms. Prevalence differences were conducted to examine differences in long COVID by vaccination status.

Overall, more than one in five adults who ever had COVID-19 reported symptoms consistent with long COVID (21.8%). The most common symptom was tiredness or fatigue (26.2%), followed by difficulty breathing or shortness of breath (18.9%), and loss of taste or smell (17.0%). Long COVID was more common among adults under 65 years, women, American Indian or Alaska Native or other/multi race group, smokers, and people with a disability, depression, overweight or obesity compared to their respective counterparts.

The prevalence of long COVID was higher among unvaccinated adults (25.6%) than vaccinated adults (21.6%) overall, and for 20 of 32 subgroups assessed. These findings underscore the benefits of vaccination, the importance of early treatment, and the need to better inform health care resource allocation and support services for those experiencing long COVID.

Source: Nguyen KH, Bao Y, Mortazavi J, Allen JD, Chocano-Bedoya PO, Corlin L. Prevalence and Factors Associated with Long COVID Symptoms among U.S. Adults, 2022. Vaccines (Basel). 2024 Jan 18;12(1):99. doi: 10.3390/vaccines12010099. PMID: 38250912; PMCID: PMC10820629. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10820629/ (Full text)

Long COVID Diagnostic with Differentiation from Chronic Lyme Disease using Machine Learning and Cytokine Hubs

Abstract:

The absence of a diagnostic for long COVID (LC) or post-acute sequelae of COVID-19 (PASC) has profound implications for research and potential therapeutics. Further, symptom-based identification of patients with long-term COVID-19 lacks the specificity to serve as a diagnostic because of the overlap of symptoms with other chronic inflammatory conditions like chronic Lymedisease (CLD), myalgic encephalomyelitis-chronic fatigue syndrome (ME-CFS), and others. Here, we report a machine-learning approach to long COVID diagnosis using cytokine hubs that are also capable of differentiating long COVID from chronic Lyme.

We constructed three tree-based classifiers: decision tree, random forest, and gradient-boosting machine (GBM) and compared their diagnostic capabilities. A 223 patient dataset was partitioned into training (178 patients) and evaluation (45 patients) sets. The GBM model was selected based on performance (89% Sensitivity and 96% Specificity for LC) with no evidence of overfitting.

We tested the GBM on a random dataset of 124 individuals (106 PASC and 18 Lyme), resulting in high sensitivity (97%) and specificity 90% for LC). A Lyme Index composed of two features ((TNF-alpha +IL-4)/(IFN-gamma + IL-2) and (TNF-alpha *IL-4)/(IFN-gamma + IL-2 + CCL3) was constructed as a confirmatory algorithm to discriminate between LC and CLD.

Source: Bruce Patterson, Jose Guevara-Coto, Javier Mora et al. Long COVID Diagnostic with Differentiation from Chronic Lyme Disease using Machine Learning and Cytokine Hubs, 18 January 2024, PREPRINT (Version 1) available at Research Square [https://doi.org/10.21203/rs.3.rs-3873244/v1] https://www.researchsquare.com/article/rs-3873244/v1 (Full text)

Long Covid

Abstract:

Long COVID, also known as post-acute sequelae of SARS-CoV-2 infection (PASC), refers to a constellation of persistent symptoms and health issues that continue beyond the acute phase of COVID-19. This chapter provides an overview of the pathogenesis, risk factors, manifestations, major findings, and diagnosis and treatment strategies associated with Long COVID.

Hypotheses regarding the pathogenesis of Long COVID are discussed, encompassing various factors such as persistent viral reservoirs, immune dysregulation with or without reactivation of herpesviruses (e.g., Epstein-Barr Virus and human herpesvirus), dysbiosis, autoimmunity triggered by infection, endothelial dysfunction, microvessel blood clotting, and dysfunctional brainstem and/or vagal signaling. The chapter also highlights the risk factors associated with Long COVID and its occurrence in children.

The major findings of Long COVID, including immune dysregulation, vessel and tissue damage, neurological and cognitive pathology, eye symptoms, endocrinal issues, myalgic encephalomyelitis and chronic fatigue syndrome, reproductive system involvement, respiratory and gastrointestinal symptoms, and the chronology of symptoms, are thoroughly explored.

Lastly, the chapter discusses the challenges and current approaches in the diagnosis and treatment of Long COVID, emphasizing the need for multidisciplinary care and individualized management strategies.

Source: Asiya Kamber Zaidi and Puya Dehgani-Mobaraki. Long Covid. Progress in Molecular Biology and Translational Science, Volume 202, 2024, Pages 113-125 https://www.sciencedirect.com/science/article/abs/pii/S1877117323001771

T4 apoptosis in the acute phase of SARS-CoV-2 infection predicts long COVID

Abstract:

Background: As about 10% of patients with COVID-19 present sequelae, it is important to better understand the physiopathology of so-called long COVID.

Method: To this aim, we recruited 29 patients hospitalized for SARS-CoV-2 infection and, by Luminex®, quantified 19 soluble factors in their plasma and in the supernatant of their peripheral blood mononuclear cells, including inflammatory and anti-inflammatory cytokines and chemokines, Th1/Th2/Th17 cytokines, and endothelium activation markers. We also measured their T4, T8 and NK differentiation, activation, exhaustion and senescence, T cell apoptosis, and monocyte subpopulations by flow cytometry. We compared these markers between participants who developed long COVID or not one year later.

Results: None of these markers was predictive for sequelae, except programmed T4 cell death. T4 lymphocytes from participants who later presented long COVID were more apoptotic in culture than those of sequelae-free participants at Month 12 (36.9 ± 14.7 vs. 24.2 ± 9.0%, p = 0.016).

Conclusions: Our observation raises the hypothesis that T4 cell death during the acute phase of SARS-CoV-2 infection might pave the way for long COVID. Mechanistically, T4 lymphopenia might favor phenomena that could cause sequelae, including SARS-CoV-2 persistence, reactivation of other viruses, autoimmunity and immune dysregulation. In this scenario, inhibiting T cell apoptosis, for instance, by caspase inhibitors, could prevent long COVID.

Source: Cezar R, Kundura L, André S, Lozano C, Vincent T, Muller L, Lefrant JY, Roger C, Claret PG, Duvnjak S, Loubet P, Sotto A, Tran TA, Estaquier J, Corbeau P. T4 apoptosis in the acute phase of SARS-CoV-2 infection predicts long COVID. Front Immunol. 2024 Jan 3;14:1335352. doi: 10.3389/fimmu.2023.1335352. PMID: 38235145; PMCID: PMC10791767. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10791767/ (Full text)

Mismatch between subjective and objective dysautonomia

Abstract:

Autonomic symptom questionnaires are frequently used to assess dysautonomia. It is unknown whether subjective dysautonomia obtained from autonomic questionnaires correlates with objective dysautonomia measured by quantitative autonomic testing. The objective of our study was to determine correlations between subjective and objective measures of dysautonomia.

This was a retrospective cross-sectional study conducted at Brigham and Women’s Faulkner Hospital Autonomic Laboratory between 2017 and 2023 evaluating the patients who completed autonomic testing. Analyses included validated autonomic questionnaires [Survey of Autonomic Symptoms (SAS), Composite Autonomic Symptom Score 31 (Compass-31)] and standardized autonomic tests (Valsalva maneuver, deep breathing, sudomotor, and tilt test). The autonomic testing results were graded by a Quantitative scale for grading of cardiovascular reflexes, sudomotor tests and skin biopsies (QASAT), and Composite Autonomic Severity Score (CASS). Autonomic testing, QASAT, CASS, and SAS were obtained in 2627 patients, and Compass-31 in 564 patients.

The correlation was strong between subjective instruments (SAS vs. Compass-31, r = 0.74, p < 0.001) and between objective instruments (QASAT vs. CASS, r = 0.81, p < 0.001). There were no correlations between SAS and QASAT nor between Compass-31 and CASS. There continued to be no correlations between subjective and objective instruments for selected diagnoses (post-acute sequelae of COVID-19, n = 61; postural tachycardia syndrome, 211; peripheral autonomic neuropathy, 463; myalgic encephalomyelitis/chronic fatigue syndrome, 95; preload failure, 120; post-treatment Lyme disease syndrome, 163; hypermobile Ehlers-Danlos syndrome, 213; neurogenic orthostatic hypotension, 86; diabetes type II, 71, mast cell activation syndrome, 172; hereditary alpha tryptasemia, 45).

The lack of correlation between subjective and objective instruments highlights the limitations of the commonly used questionnaires with some patients overestimating and some underestimating true autonomic deficit. The diagnosis-independent subjective–objective mismatch further signifies the unmet need for reliable screening surveys. Patients who overestimate the symptom burden may represent a population with idiosyncratic autonomic-like symptomatology, which needs further study. At this time, the use of autonomic questionnaires as a replacement of autonomic testing cannot be recommended.

Source: Novak, P., Systrom, D., Marciano, S.P. et al. Mismatch between subjective and objective dysautonomia. Sci Rep 14, 2513 (2024). https://doi.org/10.1038/s41598-024-52368-x https://www.nature.com/articles/s41598-024-52368-x (Full text)

Psychometric evaluation of the DePaul Symptom Questionnaire-Short Form (DSQ-SF) among adults with Long COVID, ME/CFS, and healthy controls: A machine learning approach

Abstract:

Long COVID shares a number of clinical features with myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS), including post-exertional malaise, severe fatigue, and neurocognitive deficits. Utilizing validated assessment tools that accurately and efficiently screen for these conditions can facilitate diagnostic and treatment efforts, thereby improving patient outcomes.

In this study, we generated a series of random forest machine learning algorithms to evaluate the psychometric properties of the DePaul Symptom Questionnaire-Short Form (DSQ-SF) in classifying large groups of adults with Long COVID, ME/CFS (without Long COVID), and healthy controls.

We demonstrated that the DSQ-SF can accurately classify these populations with high degrees of sensitivity and specificity. In turn, we identified the particular DSQ-SF symptom items that best distinguish Long COVID from ME/CFS, as well as those that differentiate these illness groups from healthy controls.

Source: McGarrigle WJ, Furst J, Jason LA. Psychometric evaluation of the DePaul Symptom Questionnaire-Short Form (DSQ-SF) among adults with Long COVID, ME/CFS, and healthy controls: A machine learning approach. J Health Psychol. 2024 Jan 28:13591053231223882. doi: 10.1177/13591053231223882. Epub ahead of print. PMID: 38282368. https://pubmed.ncbi.nlm.nih.gov/38282368/

Sleep Issues Amongst People With ME – A Conversation with Professor Dorothy Bruck

by Bronc

Just before Xmas 2010 I was overcome by a bout of Swine Flu. After the holiday, which was a complete blur due to sickness, I went back to work in January feeling very weak. Over the course of the next 8 months, up until my diagnosis of ME, I was afflicted by a bewildering variety of symptoms which caused a great deal of physical and mental suffering. The symptoms which affected me the most in some respects were the unrefreshing sleep and acute insomnia which made me fear that I would lose my job. I was working over 50 hours a week in a very stressful and physically demanding job which I increasingly struggled to keep onto partly due to the lack of sleep/unrefreshing sleep. I noticed a considerable decline in my ability to do some of the basics of my job as I struggled to concentrate and felt increasingly unable to keep up with the very demanding target driven regime at work. Trying to teach a class of 30 teenagers can be hard work at the best of times but when you’re getting 4 hours of unrefreshing sleep it can be a nightmare. Once I received my diagnosis of ME one of the first things I asked my GP for was a course of sleeping tablets to help me overcome the worst of the insomnia.

Since my diagnosis unrefreshing sleep and insomnia have been my constant companions. Sadly, none of the health professionals and scientists I’ve spoken to over the years have been able to offer much insight as to what is causing this and what might help treat it.

There is lack of research into this important aspect of ME. As we all know sleep is the foundation stone of good health for anyone. Those of us who live with dysfunctional sleep all the time it can be very debilitating and have a considerable knock on effect on the other symptoms of our illness.

I recently spoke with Professor Dorothy Bruck about her insights into some of the sleep issues which affect people with ME.

Emeritus Professor Bruck’s main area of research interest and expertise is sleep and sleep health. She has been thinking about, and working with, many aspects of sleep for about 40 years. Professor Bruck has had a long academic career at Victoria University in Melbourne, with particular expertise in sleep/wake behaviour, mental health, chronic fatigue syndrome, waking thresholds and human behaviour in emergencies. She has an international research reputation, with over 120 peer-reviewed full-length publications, $2.5 million in competitive grant income, dozens of invited international and national professional speaking engagements, and numerous awards. Professor Bruck’s research has been regularly featured in the media, including Time Magazine and New Scientist. Apart from her academic work Professor Bruck has worked as a sleep psychologist and most recently she was Chair of the Sleep Health Foundation (Australia). She is now semi-retired and lives in the Far South of Tasmania, Australia.

Q1. How did you get involved in the field of M.E. research?

I have been a sleep researcher since undertaking my Honours degree in 1978, with a particular interest in disorders of excessive daytime sleepiness such as narcolepsy.  In 2010 my teenage son was diagnosed with ME/CFS, which left him bed and recliner bound for about 10 of the next 15 years. Remarkably he has now improved sufficiently to hold a job with flexible hours.  While he was very sick I met ME/CFS clinicians and researchers in Melbourne and we managed to obtain funding for a series of studies focussing on sleep and gut microbes.  We have since published this research with Melinda Jackson and Amy Wallis as the first authors.

Q2. In October 2021 the National Institute for Clinical Excellence in the UK issued a new guideline for the treatment and care of people with M.E. This guideline recognised that for a diagnosis of M.E. to be made people had to suffer from four key symptoms. Unrefreshing sleep or non-restorative sleep is recognised as one of the core symptoms of the illness. The sleep disturbance experienced by pwME can be broken down into two categories: disturbed sleep patterns and unrefreshing sleep. Despite this, there is remarkably little research being conducted into this core symptom of the illness. Amongst the limited studies that have been done into this issue there appears to be no consensus as to what is causing the sleep dysfunction among pwME. How would you explain the sleep dysfunction experienced by pwME?

I think the dichotomy between disturbed sleep patterns and unrefreshing sleep is quite useful, keeping in mind however, that a pwME/CFS may have both.  Neither are unique to ME/CFS.

Disturbed sleep patterns (where the person is unable to sleep when they want to) may arise from co-morbidities with ME/CFS, such as sleep apnea, insomnia and circadian rhythm disorders. Sometimes the latter two disorders may begin with, or be perpetuated by, behavioural changes in sleep/wake behaviours that lead to disturbed sleep.

  • For example, the fatigue associated with ME/CFS may lead to irregular sleep patterns where the person sleeps episodically (i.e. naps) across the 24 hour period and the circadian (24 hour) rhythm becomes confused. The person’s sleep quality suffers because they are no longer getting their main sleep period in a single block at the time the body clock expects it. A different pattern that we may see in ME./CFS is Delayed Sleep Phase Disorder, where the person is very much an ‘evening’ type, going to bed late and getting up late. People who get insufficient outdoor light during the daytime are particularly susceptible to this.  Sometimes their body clock begins to ‘free run’ and each night they may go to bed later than the previous night, so their ‘day’ may be 25 hours instead of 24 hours.
  • Behavioural changes that may precipitate insomnia include decreased sleep drive (or sleep pressure) arising from reduced activity, significant napping during the day, reduced exposure to daytime light, worry at night about the consequences of having ME/CFS, and/or longer time in bed trying to sleep than the actual sleep duration that person may need. For example, due to boredom and/or feelings of fatigue, turning lights off from 9pm to 8am each night (i.e. 11 hours trying to sleep) when the person may only need 8 hours of actual sleep.  Best if lights-out time equals sleep time required.  The research shows quite clearly that treatment with Cognitive Behavioural Therapy for Insomnia can provide significant improvements in people whose sleep has been impaired by such behavioural factors and online programs are available.

On the other hand, disturbed sleep patterns in pwME/CFS may arise, not from behavioural factors, but from factors associated with ME/CFS itself, such as impaired melatonin secretion or other imbalances in the many hormonal or metabolic or neurological factors that we are only now beginning to understand affect sleep patterns.  Such imbalances may, in fact lead to either disturbed sleep patterns or unrefreshing sleep.

Unrefreshing sleep occurs across the population, both in people with a range of clinical conditions and sometimes in people with no diagnosed medical problem.  It is usually described by self-report. It is likely to be a very heterogenous phenomenon. A study by El-Mekkawy Leqaa et al (2022) noted a significant change in delta wave power (deep sleep) in the temporal brain region in those with unrefreshing sleep arising from sleep apnea, compared to controls. In our review of sleep patterns in ME/CFS (Jackson and Bruck, 2012) we concluded that technological advances in the assessment/monitoring of sleep may lead to further understanding of how the micro-structure of sleep may differ between those with self-reported unrefreshing sleep compared to quality sleep.

Q3. Anecdotal evidence from some pwME and a few research studies suggest that the sleep disturbance that people experience can have a significant impact on their cognitive abilities. How prevalent is this? What may be causing the sleep disturbance to impact people’s cognitive function?

Any ongoing sleep disturbance will affect a person’s cognitive abilities. Attention, concentration, memory and reaction time may all be affected in some way depending on (a) their overall health (physical and/or mental) and (b) individual differences in how poor sleep quality affects an individual.  It seems reasonable to think that a pwME/CFS that includes the symptom of brain fog would be affected by the cognitive impairments we associate with poor sleep in an additive way.

Q.4 Is there any evidence that non-restorative sleep is impacting other symptoms which pwME experience such as pain?

I believe that ANY ongoing poor quality sleep, whether it is unrestorative sleep or disturbed sleep will affect a range of ME/CFS symptoms, possibly all.  Pain and brain fog are likely to be particularly affected.

With regard to pain we know that sleep loss increases the experience of pain.  Krause et al (2019) showed that acute sleep deprivation amplifies pain reactivity within the human primary somatosensory cortex, lowers pain thresholds and that ‘even modest nightly changes in sleep quality within an individual determine consequential day-to-day changes in experienced pain’.

Q5. Having a clearer understanding about the pathophysiology of non-restorative sleep in pwME may lead to better treatment options for patients. Are you aware of any clinical trials which are exploring treatment issues for non-restorative sleep in pwME?

Unfortunately not.

Q6. Many people with M.E. report that there is a direct link between the degree of their non-restorative sleep and the depth of the fatigue they experience the next day. What research has been done into this particular issue and what were their findings?

To my knowledge this issue has not yet been investigated in pwME/CFS.  However, cognitive fatigue as measured on a range of working memory tests (Benkirane et al, 2022) found that the main effect of sleep fragmentation was to increase subjectively reported fatigue rather than reduce cognitive test performance.  This study, using healthy participants, highlights the difficulties in objectively measuring fatigue, as many people can rally their mental resources for short-term testing in a research setting.  This may have little to do with how fatigue is experienced in real-life settings.

Q7. What further research is required to investigate the causes of non-restorative sleep and the impact this has on cognitive function, fatigue and pain in pwME?

There are so many unanswered questions.  The first step for any such research is to have a standard definition of non-restorative sleep.  Is it a certain level of sleep fragmentation? Sleep disruption? Lower EEG delta power? Subjective report in the light of an otherwise normal sleep diary?  Is reported non-restorative sleep the same for someone with sleep apnea, vivid dreaming or ME/CFS?

The demographic, laboratory and genetic factors associated with long Covid-19 syndrome: a case–control study

Abstract:

Long Covid-19 syndrome (LCS) manifests with a wide range of clinical symptoms, yet the factors associated with LCS remain poorly understood. The current study aimed to investigate the relationships that demographic characteristics, clinical history, laboratory indicators, and the frequency of HLA-I alleles have with the likelihood of developing LCS.

We extracted the demographic characteristics and clinical histories from the medical records of 88 LCS cases (LCS+ group) and 96 individuals without LCS (LCS− group). Furthermore, we evaluated the clinical symptoms, serum levels of interleukin (IL)-6 and tumor necrosis factor-α, laboratory parameters, and the frequencies of HLA-I alleles.

Following this we used multiple logistic regression to investigate the association these variables had with LCS. Subjects in the LCS+ group were more likely to have experienced severe Covid-19 symptoms and had higher body mass index (BMI), white blood cell, lymphocyte counts, C-reactive protein (CRP), and IL-6 levels than those in the LCS− group (for all: P < 0.05).

Moreover, the frequencies of the HLA-A*11, -B*14, -B*38, -B*50, and -C*07 alleles were higher in the LCS+ group (for all: P < 0.05). After adjusting for the most important variables, the likelihood of suffering from LCS was significantly associated with BMI, CRP, IL-6, the HLA-A*11, and -C*07 alleles, as well as a positive history of severe Covid-19 (for all: P < 0.05).

Our study showed that a history of severe Covid-19 during the acute phase of the disease, the HLA-A*11, and -C*07 alleles, higher BMI, as well as elevated serum CRP and IL-6 levels, were all associated with an increased likelihood of LCS.

Source: Torki, E., Hoseininasab, F., Moradi, M. et al. The demographic, laboratory and genetic factors associated with long Covid-19 syndrome: a case–control study. Clin Exp Med 24, 1 (2024). https://doi.org/10.1007/s10238-023-01256-1 https://link.springer.com/article/10.1007/s10238-023-01256-1 (Full text)

Long COVID in pediatrics-epidemiology, diagnosis, and management

Abstract:

This review summarizes current knowledge on post-acute sequelae of COVID-19 (PASC) and post-COVID-19 condition (PCC) in children and adolescents. A literature review was performed to synthesize information from clinical studies, expert opinions, and guidelines. PASC also termed Long COVID — at any age comprise a plethora of unspecific symptoms present later than 4 weeks after confirmed or probable infection with severe respiratory syndrome corona virus type 2 (SARS-CoV-2), without another medical explanation. PCC in children and adolescents was defined by the WHO as PASC occurring within 3 months of acute coronavirus disease 2019 (COVID-19), lasting at least 2 months, and limiting daily activities.

Pediatric PASC mostly manifest after mild courses of COVID-19 and in the majority of cases remit after few months. However, symptoms can last for more than 1 year and may result in significant disability. Frequent symptoms include fatigue, exertion intolerance, and anxiety. Some patients present with postural tachycardia syndrome (PoTS), and a small number of cases fulfill the clinical criteria of myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS). To date, no diagnostic marker has been established, and differential diagnostics remains challenging. Therapeutic approaches include appropriate self-management as well as the palliation of symptoms by non-pharmaceutical and pharmaceutical strategies.

Conclusion: PASC in pediatrics present with heterogenous severity and duration. A stepped, interdisciplinary, and individualized approach is essential for appropriate clinical management. Current health care structures have to be adapted, and research was extended to meet the medical and psychosocial needs of young people with PASC or similar conditions.

Source: Toepfner N, Brinkmann F, Augustin S, Stojanov S, Behrends U. Long COVID in pediatrics-epidemiology, diagnosis, and management. Eur J Pediatr. 2024 Jan 27. doi: 10.1007/s00431-023-05360-y. Epub ahead of print. PMID: 38279014. https://link.springer.com/article/10.1007/s00431-023-05360-y (Full text available as PDF file)