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OBJECTIVES: This study aimed to explore the 1-year temporal change in prevalence, variety, and potential risk factors of long COVID symptoms, and to further predict the prognostic trends of long COVID. METHODS: We searched electronic databases for related studies published from January 2020 to February 2022, and conducted one group meta-analysis and locally weighted regression explore the monthly temporal change in the prevalence of each long COVID symptom in 1-year follow-up period. RESULTS: A total of 137 studies were included in meta-analysis, including 134,093 participants. The temporal change of any long COVID symptom showed a steep decrease initially (from 92% at acute phase to 55% at 1-month follow-up), followed by stabilization at approximately 50% during 1-year follow-up. Six months or more after the acute phase, the odds ratio (OR) of population characteristic factors increased, such as female gender (from 1.62 to 1.82), while the OR value of acute phase-related factors (severe/critical and hospitalization) decreased. As for specific symptoms, about two-thirds of the symptoms did not significantly reduce during the 1-year follow-up, and the neuropsychiatric symptoms showed a higher long-term prevalence (approximately 25%) and longer persistence than physical-symptoms. CONCLUSIONS: The temporal changes in the prevalence and characteristics speculate that long COVID may persist longer than expected. In particular, we should pay more attention to neuropsychiatric symptoms and other symptoms for which there is no significant downward trend in prevalence. The influence of acute phase-related factors for long COVID gradually decreases over time, while the influence of population characteristic-related gradually increases.
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As the number of COVID-19 cases increases, the long-COVID symptoms become the focus of clinical attention. Based on the statistical analysis of long-COVID symptoms in European and Chinese populations, this study proposes the path module correlation coefficient, which can estimate the correlation between two modules in a network, to evaluate the correlation between SARS-CoV-2 infection and long-COVID symptoms, providing a theoretical support for analyzing the frequency of long-COVID symptoms in European and Chinese populations. The path module correlation coefficients between specific COVID-19-related genes in the European and Chinese populations and genes that may induce long-COVID symptoms were calculated. The results showed that the path module correlation coefficients were completely consistent with the frequency of long-COVID symptoms in the Chinese population, but slightly different in the European population. Furthermore, the cathepsin C (CTSC) gene was found to be a potential COVID-19-related gene by a path module correlation coefficient correction rate. Our study can help to explore other long-COVID symptoms that have not yet been discovered and provide a new perspective to research this syndrome. Meanwhile, the path module correlation coefficient correction rate can help to find more species-specific genes related to COVID-19 in the future.
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Purpose: The purpose of this study is to describe long COVID-19 symptoms in patients receiving outpatient treatment.Materials and Methods: This prospective, observational, descriptive study was conducted in the COVID-19 clinic of a university hospital in February-May 2022. Patients who applied to the outpatient clinic and were diagnosed with COVID-19 were included in the study. Patients were follow up for prolonged COVID-19 symptoms for a 12 -week period. It was investigated whether there was a relationship between long COVID-19 symptoms frequency and gender, age and blood type.Results: At least one long COVID symptom was observed in 23% of 7139 patients included in the study. Myalgia was the most common symptom detected in 4.33% of all patients. Cough and loss of taste/smell were the most common symptoms in women, and dizziness in men. The frequency of 26 of 29 symptoms varied with age. While the symptoms most affected by the Body Mass Index were peripheral neuropathy and tinnitus, the least affected symptoms were loss of taste/smell, anxiety and depression.Conclusion: Long COVID symptoms were widely detected in COVID-19 outpatients. Age, gender and BMI may be factors affecting long COVID symptoms.
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Long COVID is a new term, introduced by patients, to account for multiple symptoms that last months and interfere with daily life, yet have no clear medical explanation. Disease is defined by organ damage, such as when a biopsy reveals cancer. A disease is characterized by its symptoms, such as pain or exhaustion, as well as physical signs, such as fever or swelling. Well-controlled studies have demonstrated that patients hospitalized with COVID-19 have much greater, persistent health problems than uninfected subjects. Women had more long-COVID symptoms than men, including greater fatigue, anxiety, or depression, and greater dyspnea, which was documented with abnormal pulmonary function testing. In controlled reports comparing hospitalized COVID-19 patients to noninfected community controls, about 10% of patients meet criteria for long COVID at three to six months after hospital discharge. Neuropsychiatric symptoms, including cognitive disturbances, particularly confusion, and mood disturbances were much more common in the non-hospitalized patients. © 2023 John Wiley & Sons Ltd. All rights reserved.
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BACKGROUND: Previous studies have reported Blood type O to confer a lower risk of SARS-CoV-2 infection, while secretor status and other blood groups have been suspected to have a similar effect as well. STUDY DESIGN AND METHODS: To determine whether any other blood groups influence testing positive for SARS-CoV-2, COVID-19 severity, or prolonged COVID-19, we used a large cohort of 650,156 Danish blood donors with varying available data for secretor status and blood groups ABO, Rh, Colton, Duffy, Diego, Dombrock, Kell, Kidd, Knops, Lewis, Lutheran, MNS, P1PK, Vel, and Yt. Of these, 36,068 tested positive for SARS-CoV-2 whereas 614,088 tested negative between 2020-02-17 and 2021-08-04. Associations between infection and blood groups were assessed using logistic regression models with sex and age as covariates. RESULTS: The Lewis blood group antigen Lea displayed strongly reduced SARS-CoV-2 susceptibility OR 0.85 CI[0.79-0.93] p < .001. Compared to blood type O, the blood types B, A, and AB were found more susceptible toward infection with ORs 1.1 CI[1.06-1.14] p < .001, 1.17 CI[1.14-1.2] p < .001, and 1.2 CI[1.14-1.26] p < .001, respectively. No susceptibility associations were found for the other 13 blood groups investigated. There was no association between any blood groups and COVID-19 hospitalization or long COVID-19. No secretor status associations were found. DISCUSSION: This study uncovers a new association to reduced SARS-CoV-2 susceptibility for Lewis type Lea and confirms the previous link to blood group O. The new association to Lea could be explained by a link between mucosal microbiome and SARS-CoV-2.
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BACKGROUND: The COVID-19 pandemic is a substantial public health crisis that negatively affects human health and well-being. As a result of being infected with the coronavirus, patients can experience long-term health effects called long COVID syndrome. Multiple symptoms characterize this syndrome, and it is crucial to identify these symptoms as they may negatively impact patients' day-to-day lives. Breathlessness, fatigue, and brain fog are the 3 most common continuing and debilitating symptoms that patients with long COVID have reported, often months after the onset of COVID-19. OBJECTIVE: This study aimed to understand the patterns and behavior of long COVID symptoms reported by patients on the Twitter social media platform, which is vital to improving our understanding of long COVID. METHODS: Long COVID-related Twitter data were collected from May 1, 2020, to December 31, 2021. We used association rule mining techniques to identify frequent symptoms and establish relationships between symptoms among patients with long COVID in Twitter social media discussions. The highest confidence level-based detection was used to determine the most significant rules with 10% minimum confidence and 0.01% minimum support with a positive lift. RESULTS: Among the 30,327 tweets included in our study, the most frequent symptoms were brain fog (n=7812, 25.8%), fatigue (n=5284, 17.4%), breathing/lung issues (n=4750, 15.7%), heart issues (n=2900, 9.6%), flu symptoms (n=2824, 9.3%), depression (n=2256, 7.4%) and general pains (n=1786, 5.9%). Loss of smell and taste, cold, cough, chest pain, fever, headache, and arm pain emerged in 1.6% (n=474) to 5.3% (n=1616) of patients with long COVID. Furthermore, the highest confidence level-based detection successfully demonstrates the potential of association analysis and the Apriori algorithm to establish patterns to explore 57 meaningful relationship rules among long COVID symptoms. The strongest relationship revealed that patients with lung/breathing problems and loss of taste are likely to have a loss of smell with 77% confidence. CONCLUSIONS: There are very active social media discussions that could support the growing understanding of COVID-19 and its long-term impact. These discussions enable a potential field of research to analyze the behavior of long COVID syndrome. Exploratory data analysis using natural language processing methods revealed the symptoms and medical conditions related to long COVID discussions on the Twitter social media platform. Using Apriori algorithm-based association rules, we determined interesting and meaningful relationships between symptoms.
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Background: Although COVID-19 vaccination decreases the risk of severe illness, it is unclear whether vaccine administration may impact the prevalence of long-COVID. The aim of this systematic review is to investigate the association between COVID-19 vaccination and long-COVID symptomatology. Methods: MEDLINE, CINAHL, PubMed, EMBASE, and Web of Science databases, as well as medRxiv and bioRxiv preprint servers were searched up to June 20, 2022. Peer-reviewed studies or preprints monitoring multiple symptoms appearing after acute SARS-CoV-2 infection either before or after COVID-19 vaccination collected by personal, telephone or electronic interviews were included. The methodological quality of the studies was assessed using the Newcastle-Ottawa Scale. Findings: From 2584 studies identified, 11 peer-reviewed studies and six preprints were included. The methodological quality of 82% (n=14/17) studies was high. Six studies (n=17,256,654 individuals) investigated the impact of vaccines before acute SARS-CoV-2 infection (vaccine-infection-long-COVID design). Overall, vaccination was associated with reduced risks or odds of long-COVID, with preliminary evidence suggesting that two doses are more effective than one dose. Eleven studies (n=36,736 COVID-19 survivors) investigated changes in long-COVID symptoms after vaccination (infection-long-COVID-vaccine design). Seven articles showed an improvement in long-COVID symptoms at least one dose post-vaccination, while four studies reported no change or worsening in long-COVID symptoms after vaccination. Interpretation: Low level of evidence (grade III, case-controls, cohort studies) suggests that vaccination before SARS-CoV-2 infection could reduce the risk of subsequent long-COVID. The impact of vaccination in people with existing long-COVID symptoms is still controversial, with some data showing changes in symptoms and others did not. These assumptions are limited to those vaccines used in the studies. Funding: The LONG-COVID-EXP-CM study supported by a grant of Comunidad de Madrid.
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A growing body of research documents the persistence of physical and neuropsychiatric symptoms following the resolution of acute COVID-19 infection. To the best of our knowledge, no published study has examined the interaction between insomnia and mental health. Accordingly, we proposed to examine new diagnoses of insomnia, and referrals to pulmonary and sleep medicine clinics for treatment of sleep disorders, in patients presenting to one post-acute COVID-19 recovery clinic. Additionally, we aimed to examine the relationship between poor sleep quality, depression, anxiety, and post-traumatic stress. Patients presented to the clinic on average 2 months following COVID-19 infection; 51.9% (n = 41) were hospitalized, 11.4% (n = 9) were in the intensive care unit, 2.5% (n = 2) were on a mechanical ventilator, and 38.0% (n = 30) were discharged on oxygen. The most commonly reported symptom was fatigue (88%, n = 70), with worse sleep following a COVID-19 infection reported in 50.6% (n = 40). The mean PSQI score was 9.7 (82.3%, n = 65 with poor sleep quality). The mean GAD-7 score was 8.3 (22.8%, n = 14 with severe depression). The mean PHQ-9 was 10.1 (17.8%, n = 18 with severe anxiety). The mean IES-6 was 2.1 (54.4%, n = 43 with post-traumatic stress). Poor sleep quality was significantly associated with increased severity of depression, anxiety, and post-traumatic stress. Future work should follow patients longitudinally to examine if sleep, fatigue, and mental health symptoms improve over time.
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BACKGROUND: The majority of coronavirus disease 2019 (COVID-19) symptom presentations in adults and children appear to run their course within a couple of weeks. However, a subgroup of adults has started to emerge with effects lasting several months or more after initial infection, which raises questions about the long-term physical, mental and social health effects of COVID-19 in the pediatric population. The purpose of this review was to determine these impacts well into the second year of the pandemic. METHODS: A search was conducted using PubMed, Web of Science, Science Direct, and Cochrane between 11/1/2019 and 9/1/2021. Search inclusion criteria were as follows: (1) COVID-19 illness and symptoms in children; (2) severe acute respiratory syndrome coronavirus 2 in children; (3) English language; and (4) human studies only. RESULTS: The few studies that have documented long-term physical symptoms in children show that fatigue, difficulty in concentrating (brain fog), sleep disturbances, and sensory problems are the most reported outcomes. Most studies examining the impact of COVID-19 in pediatric populations have focused on initial clinical presentation, and symptoms, which are similar to those in adult populations. In addition, COVID-19 has had a moderate impact on children and adolescents' social environment, which may exacerbate current and future physiological, psychological, behavioral, and academic outcomes. CONCLUSIONS: There are limited studies reporting long physical symptoms of COVID-19 in the pediatric population. However, pediatric COVID-19 cases are underreported due to low rates of testing and symptomatic infection, which calls for more longitudinal studies. Children who have experienced COVID-19 illness should be monitored for long physiological, psychological, behavioral, and academic outcomes.