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Coronavirus disease 2019 (COVID-19) can lead to persistent symptoms, sequelae, and other medical complications that may last for weeks or months after recovery. The aim of the study is to assess the prevalence and risk factors of long COVID-19 persisting for 2 years in Hainan Province, China, to aid in its recognition, prevention, and treatment. Between July and August 2022, 960 individuals with confirmed SARS-CoV-2 infection in Hainan, China, were recruited. An epidemiological questionnaire was conducted via phone interviews to assess participants' recovery status after 2 years. Among the participants, 120 patients (12.5%) experienced at least one long COVID-19 complication. The most common symptoms were cough (33.3%, 40/120), followed by fatigue (25.9%, 31/120), hair loss (23.3%, 28/120), and dizziness (20.8%, 25/120). Independent risk factors included age over 65, moderate to severe infection, chronic diseases, irregular diet, late sleeping, anxiety, and fewer than 2 vaccinations (p < 0.05). While most individuals infected with COVID-19 fully recover, approximately 12.5% experience intermediate or long-term effects. This study is the first to identify the incidence and associated risk factors of long COVID-19 with the longest follow-up time, providing valuable insights for the timely restoration of pre-COVID-19 health. [ABSTRACT FROM AUTHOR]

Background and Objectives: Long COVID-19 syndrome may cause difficulties in functionality during daily life in young people. Our objective was to investigate the respiratory and functional sequelae in young adults with asymptomatic or mild COVID-19 compared with healthy peers 3–6 months and 6–12 months after COVID-19 infection. Materials and Methods: Participants aged 18–25 who had COVID-19 within the last 3–6 months (Post-COVID Group 1, n = 25) and 6–12 months (Post-COVID Group 2, n = 25) and age–gender-matched healthy controls (n = 25) were included in this study. Respiratory functions and muscle strength were measured. Physical function was assessed with 6 min walking test (6MWT) and an Incremental Shuttle Walk Test (ISWT). The 1 min sit-to-stand test (1-MSTST) and hand grip strength (HGS) were used to assess muscle performance. Fatigue and dyspnea severity were questioned. Results: The FVC%pred (p = 0.023) and MEP (p = 0.034) were higher, and 1-MSTST repetitions were lower in Post-COVID Group-1 compared to Post-COVID Group-2 (p = 0.029). The PEF%pred (p = 0.025), MEP (p = 0.001), and ISWT distance were lower in Post-COVID Group-2 compared to healthy controls. The number of 1-MSTST repetitions and 6MWT distance were lower in Post-COVID Group-1 (p = 0.003, p = 0.001) and Post-COVID Group-2 (p = 0.003, p = 0.017) than in healthy controls. Exercise-induced blood lactate change during the ISWT, HGS, fatigue, and dyspnea were not significantly different between post-COVID groups and healthy controls. Conclusions: Young adults who pass asymptomatic or mild SARS-CoV-2 infection exhibit a decline in FVC%pred, PEF%pred, lower extremity muscle performance, and physical function within 3–6 months. In addition, the deterioration in respiratory and physical functions becomes apparent within 6–12 months. [ABSTRACT FROM AUTHOR]

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Objective: Lung involvement due to COVID-19 infection relates to patient clinical outcomes. However, little evidence exists on whether an abnormal lung sonogram, during an initial outpatient infection, may signal an abnormal immunologic response and lasting abnormalities. The aim of this study was to observe whether high-risk outpatients, previously infected with SARS CoV-2 and found to have an initial abnormal lung sonogram, had persistent diagnostic findings at a 1-year re-examination. Materials and Methods: A prospective longitudinal cohort study was performed, based on a prior study completed in January 2022 wherein 55/201 (27%) of consecutive outpatients infected with SARS-CoV-2 received therapy at an outpatient monoclonal antibody clinic and had presented with an abnormal lung ultrasound containing at least 3 apical lung B-line artifacts (LUS+). One year later, the original 55 LUS+ patients were contacted for re-examination; as a result, 14 LUS+ patients consented to a repeat LUS tospecifically recheck the apical area of the lungs for persistent B-line artifacts. The same ultrasound equipment system and imaging methodology were used for this cohort of patients. Additional data was collected regarding COVID-19 test-positive re-infection, persistent pulmonary symptoms during the past year, and COVID-19 vaccination status. Results: Of the 14 LUS+ patients, the mean cohort age was 63 ± 9 years, of which 71% were men. Over the ensuing year, 43% had persistent symptoms, 71% had updated vaccination, and 36% had a self-reported re-infection. The re-infection was reported to have occurred a median of 7 months after the initial infection. The cohort was sub-divided into those with persistent LUS+ compared to those that reverted to a normal scan. The mean age was 69 ± 10 years among those LUS+ compared to 56 ± 8 years in the normalized group. The body mass index (BMI) was 32 kg/m2 in those LUS+ compared to 27 kg/m2 in the normalized group. The cohort has 6 men and 2 women in the LUS+ group compared to 4 men and 2 women in the normalized group. One LUS+ patient out of eight reportedly had been reinfected compared to four normalized patients out of six stated being reinfected. Three LUS+ patients out of eight reported having persistent symptoms compared to three normalized patients out of six complaining of continued COVID-19 symptoms. Conclusion: Based on the 1-year repeated LUS, for this cohort, there was a high prevalence of persistent symptoms and lung abnormalities, in those who had mild-moderate outpatient COVID-19 and received monoclonal antibody therapy. The longitudinal data collection on this cohort of COVID-19 positive outpatients may suggest that individual immune responses or viral virulence factors may play a role in B-line persistence. Certainly, future LUS results may be confounded by a previous COVID-19 infection. [ABSTRACT FROM AUTHOR]

Objective: This study was designed to assess the severity of lung tissue changes due to COVID-19 in a pediatric cohort that still complained of post-COVID-19 symptoms. Materials and Methods: Parents and adolescents, 13 to 22 years old and have had a confirmatory positive polymerase chain reaction (+PCR) and/or rapid antigen test for COVID-19, consented to have a series of diagnostic tests to determine the level of lung tissue changes due to COVID-19. Sixteen adolescents completed the intake form and lung sonography. The lung sonogram was completed using the bedside lung ultrasound in emergency (BLUE) point method and a GE Logiq I laptop ultrasound system, as well as a linear 7.5-MHz or 3.0-MHz convex-array transducers. Thirteen adolescents completed a chest magnetic resonance imaging (MRI) examination on a 0.55T Siemens MAGNETOM Free.Max scanner. The examination included the heart and lungs of each participant and took about 90 minutes. A radiologist, sonographer, and computed tomography (CT) technologist reviewed and scored the images. Those positive lung sonogram scores were matched anatomically to the same slice within the chest MRI examination. Results: Based on the 13 participants, the acoustic mapping process demonstrated no diagnostic matches for positively scored sonograms at the pleural line or pulmonary parenchyma with the corresponding MRI image slices. There were diagnostic matches for negatively scored sonograms at the pleural line or pulmonary parenchyma with the corresponding MRI image slices. Conclusion: With lingering post-COVID-19 symptomology, this adolescent cohort demonstrated that acoustic mapping of their lung sonograms and chest MRI images had important combined diagnostic value. Lung sonography demonstrated diagnostic effectiveness for evaluating the periphery of the lung tissue, in this cohort but limited in viewing deeper structures. Conversely, MRI provided definitive views of the entire chest cavity and lung tissue, which is important for properly evaluating deeper pulmonary parenchyma. [ABSTRACT FROM AUTHOR]

This study investigated the incidence of new-onset cardiovascular disorders up to 3.5 years post SARS-CoV-2 infection for 56,400 individuals with COVID-19 and 1,093,904 contemporary controls without COVID-19 in the Montefiore Health System (03/11/2020 to 07/01/2023). Outcomes were new incidence of major adverse cardiovascular event (MACE), arrhythmias, inflammatory heart disease, thrombosis, cerebrovascular disorders, ischemic heart disease and other cardiac disorders between 30 days and (up to) 3.5 years post index date. Results were also compared with a pre-pandemic cohort over similar observation duration (N = 64,541). Cumulative incidence and hazard ratios adjusted for competitive risks were analyzed. Compared to contemporary controls, hospitalized COVID-19 patients had significantly higher risk of developing MACE (aHR = 2.29, 95% confidence interval [2.27, 2.31], p < 0.001), arrhythmias (aHR = 2.54[2.50, 2.58], p < 0.001), inflammatory heart disease (aHR = 5.34[4.79, 5.96], p < 0.001), cerebrovascular (aHR = 2.05[2.00, 2.11], p < 0.001), other cardiac disorders (aHR = 2.31[2.26, 2.35], p < 0.001), thrombosis (aHR = 4.25[4.15, 4.36], p < 0.001), and ischemic heart disease (aHR = 1.89[1.86, 1.92], p < 0.001). Non-hospitalized COVID-19 patients had slightly higher risk of developing MACE (aHR = 1.04[1.03, 1.06], p < 0.001), arrhythmias (aHR = 1.10[1.08, 1.12], p < 0.001), inflammatory heart disease (aHR = 2.29 [2.03, 2.59], p < 0.001), cerebrovascular (aHR = 1.11[1.07, 1.15], p < 0.001), and ischemic heart disease (aHR = 1.10[1.08, 1.13], p < 0.001). Race and ethnicity were mostly not associated with increased risks (p > 0.05). aHRs with contemporary controls as a reference were similar to those with pre-pandemic cohort as a reference. We concluded that new incident cardiovascular disorders in COVID-19 patients, especially those hospitalized for COVID-19, were higher than those in controls. Identifying risk factors for developing new-onset cardiovascular disorders may draw clinical attention for the need for careful follow-up in at-risk individuals. [ABSTRACT FROM AUTHOR]

Introduction: Post-COVID-19 syndrome (PCS) is a severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection-associated chronic condition characterized by long-term violations of physical and mental health. People with type 2 diabetes (T2D) are at high risk for severe COVID-19 and PCS. Aim: The current study aimed to define the predictors of PCS development in people with T2D for further planning of preventive measures and improving patient outcomes. Materials and methods: The data were collected through the national survey targeting persons with T2D concerning the history of COVID-19 course and signs and symptoms that developed during or after COVID-19 and continued for more than 12 weeks and were not explained by an alternative diagnosis. In total, 469 patients from different regions of Ukraine were enrolled in the study. Among them, 227 patients reported PCS development (main group), while 242 patients did not claim PCS symptoms (comparison group). Stepwise multivariate logistic regression and probabilistic neural network (PNN) models were used to select independent risk factors. Results: Based on the survey data, 8 independent factors associated with the risk of PCS development in T2D patients were selected: newly diagnosed T2D (OR 4.86; 95% CI 2.55–9.28; p<0.001), female sex (OR 1.29; 95% CI 0.86–1.94; p=0.220), COVID-19 severity (OR 1.35 95% CI 1.05–1.70; p=0.018), myocardial infarction (OR 2.42 95% CI 1.26–4.64; p=0.002) and stroke (OR 3.68 95% CI 1.70–7.96; p=0.001) in anamnesis, HbA1c above 9.2% (OR 2.17 95% CI 1.37–3.43; p=0.001), and the use of insulin analogs (OR 2.28 95% CI 1.31–3.94; p=0.003) vs human insulin (OR 0.67 95% CI 0.39–1.15; p=0.146). Although obesity aggravated COVID-19 severity, it did not impact PCS development. In ROC analysis, the 8-factor multilayer perceptron (MLP) model exhibited better performance (AUC 0.808; 95% CІ 0.770–0.843), allowing the prediction of the risk of PCS development with a sensitivity of 71.4%, specificity of 76%, PPV of 73.6% and NPV of 73.9%. Conclusions: Patients who were newly diagnosed with T2D, had HbA1c above 9.2%, had previous cardiovascular or cerebrovascular events, and had severe COVID-19 associated with mechanical lung ventilation were at high risk for PCS. [ABSTRACT FROM AUTHOR]

Backgrounds: Although COVID-19 is primarily known as a respiratory disease, there is growing evidence of neurological complications, such as ischemic stroke, in infected individuals. This study aims to evaluate the impact of COVID-19 on acute ischemic stroke (AIS) using radiomic features extracted from brain MR images and machine learning methods. Methods: This retrospective study included MRI data from 57 patients diagnosed with AIS who presented to the Department of Radiology at Hacettepe University Hospital between March 2020 and September 2021. Patients were stratified into COVID-19-positive (n = 30) and COVID-19-negative (n = 27) groups based on PCR results. Radiomic features were extracted from brain MR images following image processing steps. Various feature selection algorithms were applied to identify the most relevant features, which were then used to train and evaluate machine learning classification models. Model performance was evaluated using a range of classification metrics, including measures of predictive accuracy and diagnostic reliability, with 95% confidence intervals provided to enhance reliability. Results: This study assessed the performance of dimensionality reduction and classification algorithms in distinguishing COVID-19-negative and COVID-19-positive cases using radiomics data from brain MR scans. Without feature selection, ANN achieved the highest AUC of 0.857 (95% CI: 0.806–0.900), demonstrating strong discriminative power. Using the Boruta method for feature selection, the k-NN classifier attained the best performance, with an AUC of 0.863 (95% CI: 0.816–0.904). LASSO-based feature selection showed comparable results across k-NN, RF, and ANN classifiers, while SVM exhibited excellent specificity and high PPV. The RFE method yielded the highest overall performance, with the k-NN classifier achieving an AUC of 0.882 (95% CI: 0.838–0.924) and an accuracy of 79.1% (95% CI: 73.6–83.8). Among the methods, RFE provided the most consistent results, with k-NN and the ANN identified as the most effective classifiers for COVID-19 detection. Conclusions: The proposed radiomics-based classification model effectively distinguishes AIS associated with COVID-19 from brain MRI. These findings demonstrate the potential of AI-driven diagnostic tools to identify high-risk patients, support optimized treatment strategies, and ultimately improve clinical implications. [ABSTRACT FROM AUTHOR]

Long or Post COVID-19 is a condition of collected symptoms persisted after recovery from COVID-19. Host genetic factors play a crucial role in developing Long COVID-19, and GWAS studies identified several SNPs/genes in various ethnic populations. In African-American population two SNPS, rs10999901 (C>T, p = 3.6E-08, OR = 1.39, MAF-0,27, GRCH38, chr10:71584799 bp) and rs1868001 (G>A, p = 6.7E-09, OR = 1.40, MAF-0.46, GRCH38, chr10:71587815 bp) and in Hispanic population, rs3759084 (A>C, p = 9.7E-09, OR = 1.56, MAF-0.17, chr12: 81,110,156 bp) are strongly associated with Long COVID-19. All these three SNPs reside in noncoding regions implying their regulatory function in the genome. In silico dissection suggests that rs10999901 and rs1868001 physically interact with the CDH23 and C10orf105 genes. Both SNPs act as distant enhancers and bind with several transcription factors (TFs). Further, rs10999901 SNP is a CpG that is methylated in CD4++ T cells and monocytes and loses its methylation due to transition from C>T. rs3759084 is located in the promoter (− 687 bp) of MYF5, acts as a distant enhancer, and physically interacts with PTPRQ. These results offer plausible explanations for their association and provide the basis for experiments to dissect the development of symptoms of Long COVID-19. [ABSTRACT FROM AUTHOR]

The S1 subunit of SARS-CoV-2 Spike is crucial for ACE2 recognition and viral entry into human cells. It has been found in the blood of COVID-19 patients and vaccinated individuals. Using BioGRID, I identified 146 significant human proteins that interact with S1. I then created an interactome model that made it easier to study functional activities. Through a reverse engineering approach, 27 specific one-to-one interactions of S1 with the human proteome were selected. S1 interacts in this manner independently from the biological context in which it operates, be it infection or vaccination. Instead, when it works together with viral proteins, they carry out multiple attacks on single human proteins, showing a different functional engagement. The functional implications and tropism of the virus for human organs/tissues were studied using Cytoscape. The nervous system, liver, blood, and lungs are among the most affected. As a single protein, S1 operates in a complex metabolic landscape which includes 2557 Biological Processes (GO), much more than the 1430 terms controlled when operating in a group. A Data Merging approach shows that the total proteins involved by S1 in the cell are over 60,000 with an average involvement per single biological process of 26.19. However, many human proteins become entangled in over 100 different biological activities each. Clustering analysis showed significant activations of many molecular mechanisms, like those related to hepatitis B infections. This suggests a potential involvement in carcinogenesis, based on a viral strategy that uses the ubiquitin system to impair the tumor suppressor and antiviral functions of TP53, as well as the role of RPS27A in protein turnover and cellular stress responses. [ABSTRACT FROM AUTHOR]

The COVID-19 outbreak, caused by the SARS-CoV-2 virus, was linked to significant neurological and psychiatric manifestations. This review examines the physiopathological mechanisms underlying these neuropsychiatric outcomes and discusses current management strategies. Primarily a respiratory disease, COVID-19 frequently leads to neurological issues, including cephalalgia and migraines, loss of sensory perception, cerebrovascular accidents, and neurological impairment such as encephalopathy. Lasting neuropsychological effects have also been recorded in individuals following SARS-CoV-2 infection. These include anxiety, depression, and cognitive dysfunction, suggesting a lasting impact on mental health. The neuroinvasive potential of the virus, inflammatory responses, and the role of angiotensin-converting enzyme 2 (ACE2) in neuroinflammation are critical factors in neuropsychiatric COVID-19 manifestations. In addition, the review highlights the importance of monitoring biomarkers to assess Central Nervous System (CNS) involvement. Management strategies for these neuropsychiatric conditions include supportive therapy, antiepileptic drugs, antithrombotic therapy, and psychotropic drugs, emphasizing the need for a multidisciplinary approach. Understanding the long-term neuropsychiatric implications of COVID-19 is essential for developing effective treatment protocols and improving patient outcomes. [ABSTRACT FROM AUTHOR]

COVID-19, a highly infectious disease, caused a worldwide pandemic in early 2020. According to the World Health Organization (WHO), COVID-19 has resulted in approximately 774 million cases and around 7 million deaths. The effects of COVID-19 are well known; however, there is a lack of information on the pathophysiological mechanisms underlying the symptoms that comprise Post-Acute COVID-19 Syndrome (PACS) or Long COVID-19. Neurological sequelae are common, with cognitive dysfunction being one of the foremost symptoms. Research indicates that elevated inflammatory levels and increased oxidative stress may play a role in the etiology and severity of PACS. Treatment options are extremely limited, and there is no consensus among the medical and scientific communities on how to manage the disease. Nevertheless, many scientists advocate for using antioxidants for symptomatic therapy and cognitive behavior therapy for supportive care. Additionally, current research aims to ameliorate several aspects of the inflammatory cascade. This review highlights the intracellular and extracellular pathways crucial to the neurological manifestations of PACS, providing valuable information for healthcare professionals and scientists. Given the complex nature of PACS, understanding these pathways is essential for developing new treatment options. Assessing PACS is challenging, and reviewing current therapeutic options while proposing a triad of potential therapeutic elements will add value to clinical assays and guidelines. Current therapeutic strategies, such as antioxidants/vitamin supplements, neurogenic stem cell therapy, and mitochondrial therapy, could be combined to enhance their effectiveness. Future research should focus on validating these approaches and exploring new avenues for the effective treatment of PACS. [ABSTRACT FROM AUTHOR]

Background and Objectives: Coronavirus disease 2019 (COVID-19) is associated with various manifestations even after infection resolution. This study aimed to assess the prevalence of post-COVID-19 fatigue and its predictors. Methods: We conducted a nationwide cross-sectional study among Polymerase Chain Reaction test confirmed COVID-19 cases in Saudi Arabia from July 2021 to February 2022. We collected data through telephonic interviews covering socio-demographics, comorbidities, body mass index, smoking, illness severity, and COVID-19 vaccination status. We assessed fatigue using Fatigue Severity Scale while depression was assessed using Patient Health Questionnaire-2. Logistic regression was employed to analyze the relationship between post-COVID-19 fatigue and depression. Results: The analysis included 361 participants with a mean age of 37 ± 10.5 years, among whom 43% were female. Approximately 10% had comorbidities, and 21% were current smokers. Nearly two-thirds (68%) of the participants reported mild illness. The prevalence of perceived fatigue was 22.7%, while fatigue measured by the Fatigue Severity Scale was 14.4%. The multivariable logistic regression model revealed that COVID-19 severity and depression were significant predictors of post-COVID-19 fatigue; adjusted odds ratio 1.87 (95% CI: 1.10 to 3.18) and 14.3 (95% CI: 4.55 to 45.0), respectively. Conclusion: Our findings suggest a higher prevalence of perceived fatigue compared to that measured by the Fatigue Severity Scale, underscoring the importance of using a valid assessment tool for fatigue among COVID-19 patients to ensure proper management. The significant association between post-COVID-19 fatigue and depression highlights the need for psychological assessment of COVID-19 patients to enhance their post-infection quality of life. [ABSTRACT FROM AUTHOR]

This study aims to evaluate the effectiveness of anti‐severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2) vaccines in preventing the post‐acute sequelae of SARS‐CoV‐2 infection (PASC), commonly known as long COVID, and reducing all‐cause mortality among older patients. A retrospective cohort study was conducted using the TriNetX database. The study cohort consisted of older patients (age ≥ 65 years) with their first COVID‐19 illness between January 1, 2022, and May 31, 2024. Participants were divided into vaccinated and unvaccinated groups based on their vaccination status. Propensity score matching (PSM) was used to balance baseline characteristics. Cox regression models and log‐rank tests were applied to estimate the hazard ratio (HR) for PASC and all‐cause mortality during 30–180 days of follow‐up. The study included 189 059 geriatric patients who contracted SARS‐CoV‐2, with 5615 vaccinated and 183 444 unvaccinated. After PSM, each group contained 5615 patients. Vaccinated patients exhibited a significantly lower incidence of PASC symptoms (HR = 0.852, 95% CI: 0.778–0.933, p = 0.0005), particularly anxiety and depression, with a HR of 0.710 (95% CI: 0.575–0.878, p = 0.0015). Vaccination was also significantly associated with reduced all‐cause mortality (HR = 0.231, 95% CI: 0.136–0.394, p < 0.0001). The findings highlight the effectiveness of COVID‐19 vaccination in mitigating the development of PASC and decreasing mortality among older patients. [ABSTRACT FROM AUTHOR]

Abstract Background The manufacturing sector in Malaysia has been severely impacted by the COVID-19 pandemic. This is further exacerbated by Long COVID-19 symptoms among the manufacturing workers, which are proven to influence work performance and quality of life. Of note, there is currently a lack of knowledge regarding the burden of Long COVID-19 in the Malaysian manufacturing sector. As such, our study aims to investigate the prevalence and risk factors of Long COVID-19 symptoms among the manufacturing workers, and subsequently assess the prevalence and risk factors of adverse work outcomes among the workers with Long Covid-19 symptoms. Methods This is an exploratory mixed-methods study. In phase 1 (qualitative phase), three groups of participants (i.e., clinicians, employers, and workers) will be invited to participate to focus group discussions (FGDs) until thematic saturation. The aim of the FGDs is to explore the understanding, experience, and potential risk factors of Long Covid-19 among manufacturing workers. Findings from the FGDs will be analysed thematically. Themes generated from the FGDs will be used to generate items in a new questionnaire. The newly developed questionnaire will be validated using a fuzzy Delphi study, which will also be conducted among clinicians, employers, and workers. Phase 2 is a cross-sectional study that will be conducted among manufacturing workers across all states in Malaysia to identify the prevalence and risk factors of Long COVID-19, as well as the prevalence and risk factors of adverse work outcomes among workers with Long COVID-19. A multistage cluster sampling will be used to collect data from 4500 manufacturing workers in Malaysia. Logistic regression will be performed to determine the association between risk factors with both Long COVID-19 and adverse work outcomes. Conclusion Once the prevalence and risk factors of Long COVID and its associated adverse work outcome are identified, timely support and effective interventions could be provided to manufacturing workers to maintain their health and productivity. Ethical considerations Ethical approval has been granted by the Research Ethics Committee of the National University of Malaysia (JEP-2023-607) and the Medical Research and Ethics Committee (MREC) Malaysia (NMRR ID-23-03310-H3E).

Abstract Background The advent of new chronic conditions such as long COVID-19 raises the question of whether and, if so, how best to establish new disease registries for such conditions. Prompted by the potential need for a long COVID-19 registry, we examined experiences of existing UK disease registries to understand barriers and enablers to establishing and sustaining a register, and how these have changed over time. Methods We undertook semi-structured interviews between November 2022 and April 2023 with individuals representing six disease registries that collect individual-level longitudinal data on people diagnosed with a chronic condition. Results Registries examined were developed by a few individuals, usually clinicians, to gain a greater understanding of the disease. Patient voices were largely absent from initial agenda setting processes, but, over time, all registries sought to increase patient involvement. Securing long-term funding was cited as the biggest challenge; due to limited funds, one of the registries examined no longer actively recruits patients. Charities devoted to the diseases in question were key funders, though most registries also sought commercial opportunities. Inclusion on the NIHR Clinical Research Network Portfolio was also considered a vital resource to support recruitment and follow-up of participants. All registries have sought to minimise the primary data collected to reduce the burden on clinicians and patients, increasingly relying on linkage to other data sources. Several registries have developed consent procedures that enable participants to be contacted for additional data collection. In some cases, the initial patient consent and data sharing permissions obtained had limited the flexibility to adapt the registry to changing data needs. Finally, there was a need to foster buy-in from the community of patients and clinicians who provide and/or use the data. Conclusion We identified six key considerations when establishing a sustainable disease registry: (1) include a diverse set of stakeholders; (2) involve patients at every stage; (3) collect a core data set for all participants; (4) ensure the data system is flexible and interoperable with the wider data landscape; (5) anticipate changing data needs over time; and (6) identify financial opportunities to sustain the registry’s activities for the long term.

The COVID-19 pandemic has posed significant challenges to global healthcare systems, leaving behind a myriad of unanswered questions and long-term consequences. One such consequence is the emergence of a clinical phenomenon known as Long COVID, characterized by persistent symptoms following an acute COVID-19 infection. The long-term ramifications of this condition remain largely unknown. In this review article, the aim is to explore the most common symptoms associated with Long COVID, shed light on the difficulties in diagnosing the condition, and provide recommendations for its management. By examining existing literature and clinical observations, we seek to enhance our understanding of Long COVID and contribute to the development of effective strategies for its diagnosis and treatment. We searched PUBMED and SCOPUS for relevant research published in the last few years with the keywords ‘Long COVID’, ‘Long Haulers’, ‘Post-COVID-19 syndrome’, ‘Chronic COVID’, ‘Post-acute COVID-19’ and narrowed down to the 37 most relevant studies. The following is a discussion and review of the findings from the aforementioned.

Abstract Background and Objectives Coronavirus disease 2019 (COVID-19) is associated with various manifestations even after infection resolution. This study aimed to assess the prevalence of post-COVID-19 fatigue and its predictors. Methods We conducted a nationwide cross-sectional study among Polymerase Chain Reaction test confirmed COVID-19 cases in Saudi Arabia from July 2021 to February 2022. We collected data through telephonic interviews covering socio-demographics, comorbidities, body mass index, smoking, illness severity, and COVID-19 vaccination status. We assessed fatigue using Fatigue Severity Scale while depression was assessed using Patient Health Questionnaire-2. Logistic regression was employed to analyze the relationship between post-COVID-19 fatigue and depression. Results The analysis included 361 participants with a mean age of 37 ± 10.5 years, among whom 43% were female. Approximately 10% had comorbidities, and 21% were current smokers. Nearly two-thirds (68%) of the participants reported mild illness. The prevalence of perceived fatigue was 22.7%, while fatigue measured by the Fatigue Severity Scale was 14.4%. The multivariable logistic regression model revealed that COVID-19 severity and depression were significant predictors of post-COVID-19 fatigue; adjusted odds ratio 1.87 (95% CI: 1.10 to 3.18) and 14.3 (95% CI: 4.55 to 45.0), respectively. Conclusion Our findings suggest a higher prevalence of perceived fatigue compared to that measured by the Fatigue Severity Scale, underscoring the importance of using a valid assessment tool for fatigue among COVID-19 patients to ensure proper management. The significant association between post-COVID-19 fatigue and depression highlights the need for psychological assessment of COVID-19 patients to enhance their post-infection quality of life.

Abstract Background Long term respiratory complications of Corona Virus Disease-2019 (COVID-19) are of great concern. Many studies have reported altered respiratory patterns in COVID-19 recovered individuals and most of them were from severe to critically ill patients. The association of viral load at the time of infection with symptoms of long COVID-19 specifically on pulmonary functions after months of recovery is still not known. This study was aimed to assess the impact of SARS-CoV-2 viral load during mild-moderate COVID-19 disease on pulmonary functions in middle-aged population after 6–8 months of acute infection. Methods This study included 300 (102 healthy controls and 198 COVID-19 recovered) individuals between age 30–60 of either gender. Mild-moderate COVID-19 recovered individuals were recruited between a period of 6–8 months post-acute infection. Spirometry was performed with MIR-Spirolab-III. The association of spirometry pattern was compared with SARS-CoV-2 viral loads during acute infection. Results We observed up to 70% of the participants presented with either shortness of breath (11.5%), body aches (23.5%), recurrent cough (4.4%), recurrent respiratory infections (9.5%) and/or fatigue (33.3%) at follow up. In our study, 35.5% of COVID-19 recovered individuals had abnormal respiratory patterns (33.5% had restrictive and 2% had obstructive patterns). Viral load ≤ 20 CT value was associated with restrictive respiratory patterns (p = 0.004). No association was found between viral load and disease severity (p = 0.23). Conclusion In this study, we found one third of mild-moderate COVID-19 recovered individuals have restrictive respiratory patterns after 6–8 months of recovery. These findings had a strong association with SARS-CoV-2 viral loads during acute infection which has been reported for the first time in our study. Studying the relationship between viral load and pulmonary functions can contribute to identifying potential risk factors for long COVID and developing preventive measures to mitigate the long-term impact on lung health. Clinical trial number Not applicable.

Abstract Background Long COVID-19 is characterized by systemic deterioration of the entire body, leading to significant physical and mental disorders. Exercise training has the potential to improve persistent symptoms and cardiopulmonary functions. Method This was a single-center, randomized, controlled trial. Twenty-four patients aged 18 to 75 years who had a history of SARS-CoV-2 infection and long COVID symptoms. Patients were randomly allocated in a 1:1 ratio to receive either a 4-week exercise training program or an attention control group. The training group participated in 12 supervised aerobic sessions on a cycling ergometer over 4 weeks. The outcomes were to assess the impact of a 4-week aerobic exercise on the persistent symptoms and cardiopulmonary fitness, the surrogate endpoints of COVID-19 recovery and cardiopulmonary health. Results After the 4-week intervention, significant reductions were observed in the total number of symptoms in the training group. Specifically, 67.8% of patients in the training group exhibited reduced or completely resolved symptoms, in comparison to 16.7% in the control group (P = 0.013). After adjusting for gender, significant improvements in the training group were observed for exercise time (P group*time = 0.028), maximum load (P group*time = 0.01), and peak VO2 (P group*time = 0.001), as well as O2 pulse (P group*time = 0.042) and maximum heart rate (P group*time = 0.007). The score of Short Form-12, depression, anxiety, perceived stress, and insomnia did not show significant changes between groups (P group*time > 0.05). Conclusion A supervised aerobic training program has the potential to alleviate persistent symptoms and improve exercise tolerance in patients with long COVID-19. Further research is necessary to confirm these effects in a large population. This intervention could be easily implemented in non-hospital settings, potentially benefiting a broader range of individuals. Trial registration number ClinicalTrials.gov NCT05961462. Registered on July 25, 2023.

Abstract Background Post-COVID- 19 syndrome (PCS) significantly impacts the quality of life of survivors. There is, however, a lack of a standardized approach to PCS diagnosis and management. Our bidirectional cohort study aimed to estimate PCS incidence, identify risk factors and biomarkers, and classify clinical phenotypes for enhanced management to improve patient outcomes. Methods A bidirectional prospective cohort study was conducted at five medical sites in Hatyai district in Songkhla Province, Thailand. Participants were randomly selected from among the survivors of COVID-19 aged≥18 years between May 15, 2022, and January 31, 2023. The selected participants underwent a scheduled outpatient visit for symptom and health assessments 12 to 16 weeks after the acute onset of infection, during which PCS was diagnosed and blood samples were collected for hematological, inflammatory, and serological tests. PCS was defined according to the World Health Organization criteria. Univariate and multiple logistic regression analyses were used to identify biomarkers associated with PCS. Moreover, three clustering methods (agglomerative hierarchical, divisive hierarchical, and K-means clustering) were applied, and internal validation metrics were used to determine clustering and similarities in phenotypes. Findings A total of 300 survivors were enrolled in the study, 47% of whom developed PCS according to the World Health Organization (WHO) definition. In the sampled cohort, 66.3% were females, and 79.4% of them developed PCS (as compared to 54.7% of males, p-value

Abstract Background Long COVID-19 challenges health and social systems globally. International research finds major inequalities in prevalence and healthcare utilization as patients describe difficulties with accessing health care. In order to improve long-term outcomes it is vital to understand any underlying access barriers, for which relevant evidence on long COVID-19 is thus far lacking in a universal healthcare system like Austria. This study aims to comprehensively identify access barriers and facilitators faced by long COVID-19 patients in Austria and explore potential socioeconomic and demographic drivers in health and social care access. Methods Applying an exploratory qualitative approach, we conducted semi-structured interviews with 15 experts including medical professionals and senior health officials as well as focus groups with 18 patients with confirmed long COVID-19 diagnosis reflecting varying participant characteristics (age, gender, urbanicity, occupation, education, insurance status) (July-Nov 2023). Data were analysed following a thematic framework approach, drawing on a comprehensive ‘access to health care’ model. Results Based on expert and patient experiences, several access barriers and facilitators emerged along all dimensions of the model. Main themes included scepticism and stigma by medical professionals, difficulties in finding knowledgeable doctors, limited specialist capacities in the ambulatory care sector, long waiting times for specialist care, and limited statutory health insurance coverage of treatments resulting in high out-of-pocket payments. Patients experienced constant self-organization of their patient pathway as stressful, emphasizing the need for multidisciplinary care and centralized coordination. Facilitators included supportive social environments, telemedicine, and informal information provided by a nationwide patient-led support group. Differences in patient experiences emerged, among others, as women and younger patients faced gender- and age-based stigmatization. Complementary health insurance reduced the financial strain, however, did not ease capacity constraints, which were particularly challenging for those living in rural areas. Conclusions The findings of this study indicate a call for action to improve the long COVID-19 situation in Austria by empowering both providers and patients via increased information offerings, strengthened interdisciplinary treatment structures and telemedicine offerings as well as research funding. Our insights on potentially relevant socioeconomic and demographic drivers in access barriers lay the necessary foundation for future quantitative inequality research.

Background: The advent of new chronic conditions such as long COVID-19 raises the question of whether and, if so, how best to establish new disease registries for such conditions. Prompted by the potential need for a long COVID-19 registry, we examined experiences of existing UK disease registries to understand barriers and enablers to establishing and sustaining a register, and how these have changed over time. Methods: We undertook semi-structured interviews between November 2022 and April 2023 with individuals representing six disease registries that collect individual-level longitudinal data on people diagnosed with a chronic condition. Results: Registries examined were developed by a few individuals, usually clinicians, to gain a greater understanding of the disease. Patient voices were largely absent from initial agenda setting processes, but, over time, all registries sought to increase patient involvement. Securing long-term funding was cited as the biggest challenge; due to limited funds, one of the registries examined no longer actively recruits patients. Charities devoted to the diseases in question were key funders, though most registries also sought commercial opportunities. Inclusion on the NIHR Clinical Research Network Portfolio was also considered a vital resource to support recruitment and follow-up of participants. All registries have sought to minimise the primary data collected to reduce the burden on clinicians and patients, increasingly relying on linkage to other data sources. Several registries have developed consent procedures that enable participants to be contacted for additional data collection. In some cases, the initial patient consent and data sharing permissions obtained had limited the flexibility to adapt the registry to changing data needs. Finally, there was a need to foster buy-in from the community of patients and clinicians who provide and/or use the data. Conclusion: We identified six key considerations when establishing a sustainable disease registry: (1) include a diverse set of stakeholders; (2) involve patients at every stage; (3) collect a core data set for all participants; (4) ensure the data system is flexible and interoperable with the wider data landscape; (5) anticipate changing data needs over time; and (6) identify financial opportunities to sustain the registry's activities for the long term. [ABSTRACT FROM AUTHOR]

COVID-19 infection has resulted in a high prevalence of a post-infectious syndrome, known as post-acute sequelae of SARS-CoV-2 (PASC) or "Long COVID". PASC is a heterogeneous disease with a high prevalence of sleep disturbances, varying from an insomnia disorder to excessive daytime sleepiness. Patients seen in the Covid Survivorship Program at the Beth Israel Deaconess Medical Center Boston, USA, were screened for sleep disorders as part of a comprehensive multi-system evaluation. Those who screened positive were referred for a comprehensive sleep evaluation in a dedicated COVID-19-Sleep clinic, followed by diagnostic sleep testing and treatment. This report summarizes patients who completed an American Academy of Sleep Medicine (AASM) accredited facility-based diagnostic evaluation. International Classification of Sleep Disorders 3rd Edition-Revised criteria were met for all diagnoses. In 42 patients with PASC, five categories of sleep disorder syndromes were observed following a sleep clinic evaluation, including obstructive sleep apnea, chronic insomnia disorder, primary hypersomnia, REM behavior disorder (RBD), and new onset circadian phase delay. Seven patients met criteria for idiopathic hypersomnia, and two had narcolepsy type 2. RBD patients were infected in three different waves; circadian disturbance patients were all infected in the winter wave of 2020/21, and the primary hypersomnolence group occurred during all waves, predominantly the initial wave of 2020. A peculiar form of insomnia was a persistent loss of sleep regularity. Specific sleep symptoms/syndromes are reported in this select group of patients with PASC/Long Covid. As new onset sleep complaints are prevalent in PASC, we recommend a complete clinical and investigative sleep evaluation for persistent severe sleep symptoms following COVID-19 infection. • Sleep complaints in PASC are frequent, varying from insomnia to excessive daytime sleepiness. • Noted syndromes: sleep apnea, insomnia, primary hypersomnia, REM behavior disorder, and circadian phase delay. • All circadian disturbances patients were infected in the Winter 20/21 wave. • The response to therapy for hypersomnia and narcolepsy has so far been unremarkable. • Vaccination could have influenced the incidence of PACS patients and their sleep syndromes. [ABSTRACT FROM AUTHOR]

The COVID‐19 pandemic had a disproportionate impact on ethnically minoritised and other marginalised communities, yet little is known about the impacts of long COVID‐19 (LC) on this group. Living with LC takes its toll both physically, emotionally and financially and even more so when a diagnosis is hard to come by. By using qualitative interviews centring the view of undiagnosed and marginalised communities already classed as 'underserved' in the medical literature, we show the range of barriers and impacts faced by these groups in the UK, and the strategies of resilience they use. Whether trapped on a 'diagnostic odyssey' at the level of primary care, struggling to maintain employment and businesses, or managing family commitments, we argue many minoritised communities are caught in a liminal space of misrecognition, invalidation and ambiguity. We show how these impacts are generated by tensions and challenges in the process and categorisation of diagnosis, and how this effects the daily lives of many individuals already on the receiving end of health inequity. We also offer some examples and suggestions for best practices. [ABSTRACT FROM AUTHOR]

Long-term sequelae of coronavirus disease 2019 (COVID-19) infection are common and can have debilitating consequences. There is a need to understand risk factors for Long COVID-19 to give impetus to the development of targeted yet holistic clinical and public health interventions to reduce its associated healthcare and economic burden. Given the large number and variety of predictors implicated spanning health-related and sociodemographic factors, machine learning becomes a valuable tool. As such, this study aims to employ machine learning to produce an algorithm to predict Long COVID-19 risk, and thereby identify key predisposing factors. Longitudinal cohort data were sourced from the UK's "Understanding Society: COVID-19 Study" (n = 601 participants with past symptomatic COVID-19 infection confirmed by serology testing). The random forest classification algorithm demonstrated good overall performance with 97.4% sensitivity and modest specificity (65.4%). Significant risk factors included early timing of acute COVID-19 infection in the pandemic, greater number of hours worked per week, older age and financial insecurity. Loneliness and having uncommon health conditions were associated with lower risk. Sensitivity analysis suggested that COVID-19 vaccination is also associated with lower risk, and asthma with an increased risk. The results are discussed with emphasis on evaluating the value of machine learning; potential clinical utility; and some benefits and limitations of machine learning for health science researchers given its availability in commonly used statistical software. [ABSTRACT FROM AUTHOR]

Background: Long COVID-19 challenges health and social systems globally. International research finds major inequalities in prevalence and healthcare utilization as patients describe difficulties with accessing health care. In order to improve long-term outcomes it is vital to understand any underlying access barriers, for which relevant evidence on long COVID-19 is thus far lacking in a universal healthcare system like Austria. This study aims to comprehensively identify access barriers and facilitators faced by long COVID-19 patients in Austria and explore potential socioeconomic and demographic drivers in health and social care access. Methods: Applying an exploratory qualitative approach, we conducted semi-structured interviews with 15 experts including medical professionals and senior health officials as well as focus groups with 18 patients with confirmed long COVID-19 diagnosis reflecting varying participant characteristics (age, gender, urbanicity, occupation, education, insurance status) (July-Nov 2023). Data were analysed following a thematic framework approach, drawing on a comprehensive 'access to health care' model. Results: Based on expert and patient experiences, several access barriers and facilitators emerged along all dimensions of the model. Main themes included scepticism and stigma by medical professionals, difficulties in finding knowledgeable doctors, limited specialist capacities in the ambulatory care sector, long waiting times for specialist care, and limited statutory health insurance coverage of treatments resulting in high out-of-pocket payments. Patients experienced constant self-organization of their patient pathway as stressful, emphasizing the need for multidisciplinary care and centralized coordination. Facilitators included supportive social environments, telemedicine, and informal information provided by a nationwide patient-led support group. Differences in patient experiences emerged, among others, as women and younger patients faced gender- and age-based stigmatization. Complementary health insurance reduced the financial strain, however, did not ease capacity constraints, which were particularly challenging for those living in rural areas. Conclusions: The findings of this study indicate a call for action to improve the long COVID-19 situation in Austria by empowering both providers and patients via increased information offerings, strengthened interdisciplinary treatment structures and telemedicine offerings as well as research funding. Our insights on potentially relevant socioeconomic and demographic drivers in access barriers lay the necessary foundation for future quantitative inequality research. [ABSTRACT FROM AUTHOR]

Background: The aim of this study was to investigate the effects of pulmonary rehabilitation (PR) and additional progressive muscle relaxation (PMR) techniques in patients with long-term COVID-19 symptoms. Methods: We included 61 patients with long COVID-19 symptoms and randomly assigned them to two groups: PR only (group 1 with 30 subjects) and PR with PMR (group 2 with 31 subjects). The PR program consisted of gradual aerobic conditioning, strength training, and breathing exercises. Group 2 received additional 20 min daily sessions of progressive muscle relaxation techniques. Results: Following a 21-day intervention, it was observed that both groups had noteworthy improvements in lung function, exercise capacity, and sleep quality with statistical significance (p < 0.0001). Group 2 showed significant improvements in overall health (as measured by the General Health Questionnaire-12), patient health (as assessed by the Patient Health Questionnaire-9), general anxiety levels (as indicated by the Generalized Anxiety Disorders Scale-7), and sleep quality (as measured by the Pittsburgh Sleep Quality Index), with statistical significance (p < 0.0001), compared to group 1. Moreover, the statistical analysis demonstrated no significant difference in exercise capacity improvement between group 1 and group 2, as indicated by a p-value of 0.1711. Conclusions: The addition of progressive muscle relaxation to pulmonary rehabilitation significantly enhances mental health outcomes, particularly in reducing anxiety and improving sleep quality, for patients with long-term COVID-19 symptoms. These findings suggest that incorporating PMR into PR programs offers a valuable non-pharmacological approach to improving overall patient well-being during long-term COVID-19 recovery. [ABSTRACT FROM AUTHOR]

Background: Post-COVID- 19 syndrome (PCS) significantly impacts the quality of life of survivors. There is, however, a lack of a standardized approach to PCS diagnosis and management. Our bidirectional cohort study aimed to estimate PCS incidence, identify risk factors and biomarkers, and classify clinical phenotypes for enhanced management to improve patient outcomes. Methods: A bidirectional prospective cohort study was conducted at five medical sites in Hatyai district in Songkhla Province, Thailand. Participants were randomly selected from among the survivors of COVID-19 aged≥18 years between May 15, 2022, and January 31, 2023. The selected participants underwent a scheduled outpatient visit for symptom and health assessments 12 to 16 weeks after the acute onset of infection, during which PCS was diagnosed and blood samples were collected for hematological, inflammatory, and serological tests. PCS was defined according to the World Health Organization criteria. Univariate and multiple logistic regression analyses were used to identify biomarkers associated with PCS. Moreover, three clustering methods (agglomerative hierarchical, divisive hierarchical, and K-means clustering) were applied, and internal validation metrics were used to determine clustering and similarities in phenotypes. Findings: A total of 300 survivors were enrolled in the study, 47% of whom developed PCS according to the World Health Organization (WHO) definition. In the sampled cohort, 66.3% were females, and 79.4% of them developed PCS (as compared to 54.7% of males, p-value <0.001). Comorbidities were present in 19% (57/300) of all patients, with 11% (18/159) in the group without PCS and 27.7% (39/141) in the group with PCS. The incidence of PCS varied depending on the criteria used and reached 13% when a quality of life indicator was added to the WHO definition. Common PCS symptoms were hair loss (22%) and fatigue (21%), while mental health symptoms were less frequent (insomnia 3%, depression 3%, anxiety 2%). According to our univariate analysis, we found significantly lower hematocrit and IgG levels and greater ALP levels in PCS patients than in patients who did not develop PCS (p-value < 0.05). According to our multivariable analysis, adjusted ALP levels remained a significant predictor of PCS (OR 1.02, p-value= 0.005). Clustering analysis revealed four groups characterized by severe clinical symptoms and mental health concerns (Cluster 1, 4%), moderate physical symptoms with predominant mental health issues (Cluster 2, 9%), moderate mental health issues with predominant physical symptoms (Cluster 3, 14%), and mild to no PCS (Cluster 4, 77%). The quality of life and ALP levels varied across the clusters. Interpretation: This study challenges the prevailing diagnostic criteria for PCS, emphasizing the need for a holistic approach that considers quality of life. The identification of ALP as a biomarker associated with PCS suggests that its monitoring could be used for early detection of the onset of PCS. Cluster analysis revealed four distinct clinical phenotypes characterized by different clinical symptoms and mental health concerns that 'exhibited varying impacts on quality of life. This finding suggested that accounting for the reduced quality of life in the definition of PCS could enhance its diagnosis and management and that moving toward personalized interventions could both improve patient outcomes and help reduce medicalization and optimally target the available resources. Funding: The research publication received funding support from Medical Council of Thailand (Police General Dr. Jongjate Aojanepong Foundation), Hatyai Hospital Charity and Wellcome Trust. [ABSTRACT FROM AUTHOR]

Background: Long COVID-19 is an emerging chronic illness of significant public health concern due to a myriad of neuropsychiatric sequelae, including increased suicidal ideation (SI) and behavior (SB). Methods: This review provides a concise synthesis of clinical evidence that points toward the dysfunction of astrocytes, the most abundant glial cell type in the central nervous system, as a potential shared pathology between SI/SB and COVID-19. Results: Depression, a suicide risk factor, and SI/SB were both associated with reduced frequencies of various astrocyte subsets and complex proteomic/transcriptional changes of astrocyte-related markers in a brain-region-specific manner. Astrocyte-related circulating markers were increased in depressed subjects and, to a less consistent extent, in COVID-19 patients. Furthermore, reactive astrocytosis was observed in subjects with SI/SB and those with COVID-19. Conclusions: Astrocyte dysfunctions occurred in depression, SI/SB, and COVID-19. Reactive-astrocyte-mediated loss of the blood–brain barrier (BBB) integrity and subsequent neuroinflammation—a factor previously linked to SI/SB development—might contribute to increased suicide in individuals with long COVID-19. As such, the formulation of new therapeutic strategies to restore astrocyte homeostasis, enhance BBB integrity, and mitigate neuroinflammation may reduce SI/SB-associated neuropsychiatric manifestations among long COVID-19 patients. [ABSTRACT FROM AUTHOR]

Objective: To determine, the impact of long COVID-19 on oculomotor behaviour. Design: A case–control study. Setting: Spanish Association of Persistent COVID. Participant: Participants were 75 cases (64 women, 11 men, mean age 46.4 years ±8.9) and 42 controls (22 women, 20 men, mean age 53.5 years ±13.13). Intervention: An eye-tracking test based on visual search paradigm and the Adult Developmental Eye Movement Test were used to evaluate the participants. Main measures: The primary outcomes in the Adult Developmental Eye Movement Test were horizontal reading time, vertical reading time, and their ratio. And for the eye-tracking test the time to find the target, the duration, and the number of eye fixations. Results: In cases and controls, eye movement test results were horizontal(Hadj) reading time 74.2 ± 22.7 s vs 52.0 ± 6.1 s (p <.0001); vertical(Vadj) reading time 67.6 ± 17.8 s vs 50.4 ± 6.9 s (p <.0001); Hadj/Vadj ratio 0.9 ± 0.1 vs 1.0 ± 0 (p =.0032), respectively; and eye-tracking test results were fixation number 11.3 ± 3.07 vs 3.51 ± 2.57 (p <.0001); fixation duration 2.01 ± 0.79 s vs 1.5 ± 0.4 s (p =.0013), and time to find target 24.5 ± 8.0 vs 18 ± 9.4 (p =.0034), respectively. Conclusions: Data showed a lower performance in oculomotor behaviour in people with long COVID-19, compared to healthy individuals. It cannot be affirmed an ocular musculature dysfunction; the differentiated behaviour could be associated to cognitive alterations affected in these people. Both tests used could be an useful tool for the clinical assessment of these participants. Further studies are needed to explore the utility of these procedures. [ABSTRACT FROM AUTHOR]

Background: Long term respiratory complications of Corona Virus Disease-2019 (COVID-19) are of great concern. Many studies have reported altered respiratory patterns in COVID-19 recovered individuals and most of them were from severe to critically ill patients. The association of viral load at the time of infection with symptoms of long COVID-19 specifically on pulmonary functions after months of recovery is still not known. This study was aimed to assess the impact of SARS-CoV-2 viral load during mild-moderate COVID-19 disease on pulmonary functions in middle-aged population after 6–8 months of acute infection. Methods: This study included 300 (102 healthy controls and 198 COVID-19 recovered) individuals between age 30–60 of either gender. Mild-moderate COVID-19 recovered individuals were recruited between a period of 6–8 months post-acute infection. Spirometry was performed with MIR-Spirolab-III. The association of spirometry pattern was compared with SARS-CoV-2 viral loads during acute infection. Results: We observed up to 70% of the participants presented with either shortness of breath (11.5%), body aches (23.5%), recurrent cough (4.4%), recurrent respiratory infections (9.5%) and/or fatigue (33.3%) at follow up. In our study, 35.5% of COVID-19 recovered individuals had abnormal respiratory patterns (33.5% had restrictive and 2% had obstructive patterns). Viral load ≤ 20 CT value was associated with restrictive respiratory patterns (p = 0.004). No association was found between viral load and disease severity (p = 0.23). Conclusion: In this study, we found one third of mild-moderate COVID-19 recovered individuals have restrictive respiratory patterns after 6–8 months of recovery. These findings had a strong association with SARS-CoV-2 viral loads during acute infection which has been reported for the first time in our study. Studying the relationship between viral load and pulmonary functions can contribute to identifying potential risk factors for long COVID and developing preventive measures to mitigate the long-term impact on lung health. Clinical trial number: Not applicable. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

BackgroundSurvivors of coronavirus disease 2019 (COVID-19) often face persistent and significant challenges that affect their physical, mental, and financial wellbeing, which can significantly diminish their overall quality of life. The emergence of new symptoms or the persistence of existing ones after a severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) diagnosis has given rise to a complex clinical issue known as “long COVID-19” (LC). This situation has placed additional strain on global healthcare systems, underscoring the urgent need for ongoing clinical management of these patients. While numerous studies have been conducted on the long-term effects of COVID-19, our systematic review, and meta-analysis, is the first of its kind in sub-Saharan Africa, providing a comprehensive understanding of the situation in the region and highlighting the necessity for continuous clinical management.ObjectiveThis study aimed to systematically synthesize evidence on the persistent sequelae of COVID-19 and their predictors in sub-Saharan Africa.MethodsA thorough search was conducted across multiple databases, including PubMed/MEDLINE, Web of Science, Google/Google Scholar, African online journals, and selected reference lists, from the inception of these databases until January 12, 2024. A meta-analysis of proportions was conducted using the random-effects restricted maximum-likelihood model. The association between various factors was also analyzed to determine the pooled factors that influence long COVID-19 outcomes.ResultsOur comprehensive analysis of 16 research articles, involving a total of 18,104 participants revealed a pooled prevalence of COVID-19 sequelae at 42.1% (95% CI: 29.9–55.4). The long-term health sequelae identified in this review included persistent pulmonary sequelae (27.5%), sleep disturbance (22.5%), brain fog (27.4%), fatigue (17.4%), anxiety (22.3%), and chest pain (13.2%). We also found a significant association was observed between comorbidities and long COVID-19 sequelae [POR = 4.34 (95% CI: 1.28–14.72)], providing a comprehensive understanding of the factors influencing long COVID-19 outcomes.ConclusionCOVID-19 can have long-lasting effects on various organ systems, even after a person has recovered from the infection. These effects can include brain fog, pulmonary symptoms, sleep disturbances, anxiety, fatigue, and other neurological, psychiatric, respiratory, cardiovascular, and general symptoms. It is crucial for individuals who have recovered from COVID-19 to receive careful follow-up care to assess and reduce any potential organ damage and maintain their quality of life.Systematic review registrationClinicaltrial.gov, identifier CRD42024501158.

BackgroundMycoplasma pneumoniae (M. pneumoniae) is one of the most common pathogens of community-acquired pneumonia (CAP) in children. Although Mycoplasma pneumoniae pneumonia (MPP) is considered a self-limiting disease, severe MPP (SMPP) occurs in some cases. This study aims to analyze clinical features of MPP and to explore predictive indicators in the early stage of M. pneumoniae infection.MethodsWe retrospectively enrolled patients with MPP and non-MPP (NMPP) hospitalized to the Department of Pediatrics, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine from 2023 to 2024. A total of 757 children with CAP were divided into MPP group and NMPP group. Patients with MPP included SMPP group and mild MPP (MMPP) group. Demographic and clinical characteristics as well as laboratory and imaging tests were deemed to be baseline data within 24 h after admission. We compared differences between MPP group and NMPP group as well as SMPP group and MMPP group. To exclude the impacts of age and gender, analysis of covariance and Logical regression was used to account for the baseline differences in the probability between MPP group and NMPP group, SMPP group and MMPP group. Logistic regression analysis was used to screen markers as potential early clinical predictors. ROC curves were applied to estimate the diagnostic and predictive value of different indicators for SMPP group.ResultsAmong the 757 cases of CAP, 464 cases were MPP group and 226 cases were SMPP group. There were significant differences in hospital stay and fever duration between the MPP and NMPP groups. Compared to NMPP group, MPP group exhibited higher levels of platelet count (PLT), heparin-binding protein (HBP), erythrocyte sedimentation rate (ESR), immunoglobulin G (IgG) (P

IntroductionPost-COVID-19 syndrome (PCS) is a severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection-associated chronic condition characterized by long-term violations of physical and mental health. People with type 2 diabetes (T2D) are at high risk for severe COVID-19 and PCS.AimThe current study aimed to define the predictors of PCS development in people with T2D for further planning of preventive measures and improving patient outcomes.Materials and methodsThe data were collected through the national survey targeting persons with T2D concerning the history of COVID-19 course and signs and symptoms that developed during or after COVID-19 and continued for more than 12 weeks and were not explained by an alternative diagnosis. In total, 469 patients from different regions of Ukraine were enrolled in the study. Among them, 227 patients reported PCS development (main group), while 242 patients did not claim PCS symptoms (comparison group). Stepwise multivariate logistic regression and probabilistic neural network (PNN) models were used to select independent risk factors.ResultsBased on the survey data, 8 independent factors associated with the risk of PCS development in T2D patients were selected: newly diagnosed T2D (OR 4.86; 95% CI 2.55–9.28; p

The SARS-CoV-2 virus responsible for the COVID-19 pandemic has profoundly impacted global health, economics, and society. This review seeks to encompass an overview of current knowledge on COVID-19, including its transmission, pathogenesis, and clinical presentation related to various systems within the human body. COVID-19 is a highly contagious illness that has rapidly spread worldwide. As of August 4, 2023, the WHO reported over 570 million confirmed cases of COVID-19 and over 6.3 million deaths. Although the virus is most common in adults, children can also be infected. Respiratory droplets that are produced when an infected person coughs or sneezes are the primary transmission mode for COVID-19. Additionally, the virus can be disseminated via contact with contaminated surfaces or objects, as it can remain viable for several hours or days. SARS-CoV-2 is a respiratory virus that enters cells by bonding with the angiotensin-converting enzyme 2 (ACE2) receptor. Once inside the cell, the virus replicates and produces new particles that can infect other cells. Interestingly, the effects of post-acute sequelae of SARS-CoV-2 infection (PASC) encompass more than just respiratory system. The findings presented in the data suggest that PASC significantly impacts multiple organs and their respective physiological processes. In light of these observations, we aim to provide a detailed discussion of the relevant findings in this paper. Through our review, we hope to provide healthcare professionals with a deeper understanding of the effects of PASC on the human body, which could ultimately lead to improved patient outcomes and treatment strategies.

Abstract Purpose To investigate the prevalence of insomnia among nurses with long COVID-19, analyze the potential risk factors and establish a nomogram model. Methods Nurses in Ningbo, China, were recruited for this study. General demographic information and insomnia, burnout, and stress assessment scores were collected through a face-to face questionnaire survey administered at a single center from March to May 2023. We used LASSO regression to identify potential factors contributing to insomnia. Then, a nomogram was plotted based on the model chosen to visualize the results and evaluated by receiver operating characteristic curves and calibration curves. Results A total of 437 nurses were recruited. 54% of the nurses had insomnia according to the Insomnia Severity Index (ISI) score. Eleven variables, including family structure, years of work experience, relaxation time, respiratory system sequelae, nervous system sequelae, others sequelae, attitudes toward COVID-19, sleep duration before infection, previous sleep problems, stress, and job burnout, were independently associated with insomnia. The R-squared value was 0.464, and the area under the curve was 0.866. The derived nomogram showed that neurological sequelae, stress, job burnout, sleep duration before infection, and previous sleep problems contributed the most to insomnia. The calibration curves showed significant agreement between the nomogram models and actual observations. Conclusion This study focused on insomnia among nurses with long COVID-19 and identified eleven risk factors related to nurses’ insomnia. A nomogram model was established to illustrate and visualize these factors, which will be instrumental in future research for identifying nurses with insomnia amid pandemic normalization and may increase awareness of the health status of healthcare workers with long COVID-19.

Objective: To evaluate and characterize the cognitive changes in COVID-19 participants at 6-month follow-up, and to explore a possible association with clinical symptoms, emotional disturbance and disease severity. Methods: This single-center longitudinal cohort study included participants aged 20 and 60 years old to exclude cognitive impairment age-associated with confirmed COVID-19 infection. The initial evaluation occurred 10 to 30 days after hospital or ambulatory discharge, with a subsequent follow-up at 6 months. Patients who had a history of cognitive impairment, neurological conditions, or serious psychiatric disorders were not included. Information on demographics and laboratory results was gathered from medical records. Cognitive outcomes were assessed with a neuropsychological battery including attention, verbal and visual memory, language and executive function tests. Results: A total of 200 participants were included in the study, and 108 completed the follow-up visit. At the 6-month follow-up, comparing the means from baseline with those of the follow-up evaluation, significant overall improvement was observed in verbal and visual memory subtests (p = 0.001), processing speed (p = 0.001), executive function (p = 0.028; p = 0.016) and naming (p = 0.001), independently of disease severity and cognitive complaints. Anxiety and depression were significantly higher in groups with Subjective Cognitive Complaints (SCC) compared to those without (p < 0.01 for both). Conclusions: Persistent symptoms are common regardless of disease severity and are often linked to cognitive complaints. Six months after COVID-19, the most frequently reported symptoms included headache, dyspnea, fatigue, cognitive complaints, anxiety, and depression. No cognitive impairment was found to be associated with the severity of COVID-19. Overall, neuropsychological and psychopathological improvement was observed at 6 months regardless of disease severity and cognitive complaints.

Background: Reticulation, ground glass opacities and post-infection bronchiectasis are present three months following hospitalisation in patients recovering from SARS-CoV-2 infection and are associated with the severity of acute infection. However, scarce data exist on small airways impairment and lung hyperinflation in patients with long COVID-19. Aim: To evaluate small airways function and lung hyperinflation in previously hospitalised patients with long COVID-19 and their association with post-COVID-19 breathlessness. Methods: In total, 33 patients (mean ± SD, 53 ± 11 years) with long COVID-19 were recruited 149 ± 90 days following hospital discharge. Pulmonary function tests were performed and lung hyperinflation was defined as RV/TLC ≥ 40%. Small airways function was evaluated by measuring the closing volume (CV) and closing capacity (CC) using the single-breath nitrogen washout technique (SBN2W). Results: CC was 115 ± 28% pred. and open capacity (OC) was 90 ± 19. CC was abnormal in 13 patients (39%), CV in 2 patients (6.1%) and OC in 9 patients (27%). Lung hyperinflation was present in 15 patients, whilst the mean mMRC score was 2.2 ± 1.0. Lung hyperinflation was associated with CC (r = 0.772, p = 0.001), OC (r = 0.895, p = 0.001) and mMRC (r = 0.444, p = 0.010). Conclusions: Long COVID-19 patients present with small airways dysfunction and lung hyperinflation, which is associated with persistent dyspnoea, following hospitalisation.

Objectives: We aimed to assess the prevalence of long COVID-19 and estimate the average time to its diagnosis and meta-regression for covariates. Methods: We conducted a systematic review, meta-analysis, and meta-regression from 43 studies (367,236 patients) (June 2020–August 2022). With the random-effects model, the pooled prevalence of long COVID-19 was measured. Publication bias was ascertained, and meta-regression analysis was performed on predetermined covariates. The trial was registered with PROSPERO (CRD42022328509). Results: The pooled prevalence of long COVID-19 was 42.5% (95% CI 36% to 49.3%), with 25% and 66% at four and two months, respectively. Mostly, long COVID-19 signs and symptoms occurred at three (54.3%) to six (57%) months (p < 0.0001), further increasing at 12 months (57.9%, p = 0.0148). Hypertension was significantly associated with long COVID-19 at 32% (0.322 (95% CI 0.166, 0.532) (p < 0.001) and hospital re-admission contributed to 17% (Q = 8.70, df = 1, p = 0.0032) (R2 = 0.17). All the covariates explained at least some of the variance in effect size on long COVID-19 at 53% (Q = 38.81, df = 19, p = 0.0047) (R2 analog = 0.53). Conclusion: The prevalence of long COVID-19 was 42.5% when linked with a cardiovascular disorder. Hospital re-admission majorly predicted the incidence of long COVID-19. Clinical and methodological characteristics in a specific study contributed to over 50% of long COVID-19 events, with most signs and symptoms occurring between 3 and 6 months and increasing at 12 months.

Abstract Background The study aimed to evaluate the prevalence and pattern of long COVID-19 (LC) symptoms among individuals who had contracted COVID-19, to calculate the incidence of LC, and to provide insights into risk factors associated with developing LC in this population. Methods This population-based cross-sectional survey was conducted in Fars province in 2023. Adult participants with a history of COVID-19 were recruited using a cluster random sampling method, alongside a control group with similar characteristics through the same methodology. Data were collected through in-person interviews using two researcher-developed data collection forms focused on demographic and clinical information. Results A total of 2010 participants, comprising 1561 (77.7%) and 449 (22.3%) individuals with and without a previous history of COVID-19 were included. Among those with COVID-19 history, the prevalence of experiencing any symptoms was 93.7% (95% CI of 92.3%-94.8%) during the disease acute phase and 36.4% (95% CI of 34.0%-38.8%) after recovery. The incidence of symptoms specifically related to COVID-19, calculated by comparing the symptom rates between participants with and without a history of COVID-19, was found to be 13%. Factors such as older age, previous hospitalization for COVID-19, presence of cardiovascular disease, and use of steroids/chemotherapy were associated with LC symptoms. Conclusions Our investigation sheds light on long-term aspects of COVID-19, demonstrating a significant prevalence of LC with diverse manifestations. It also underscores the importance of establishing standardized criteria and control groups in research on LC to address challenges related to heterogeneity and potential overestimation of symptoms.

Introduction: Post-COVID-19 is an increasing chronic disease for which potential treatment options require further development and examination. A well-established approach to symptom management in post-COVID-19 patients could be e-Health interventions. To enhance the implementation and utilization of e-Health interventions, the needs and demands of patients should be taken into consideration. The aim of this study was to investigate needs and demands of post-COVID-19 patients concerning e-Health symptom management interventions. Methods: A total of 556 patients participated in this cross-sectional online survey study. Recruitment was performed from January 19 to May 24, 2022. Data related to the needs and demands for e-Health interventions were analyzed, along with medical and sociodemographic information. Results: The majority of the patients preferred interventions accessible on smartphones (95.3%). The favored content formats were applications (82.7%), interactive training (69.3%), or audio and video materials (61.1%). Furthermore, the preferred session length was about 10–20 min. The most desired topics included "quality of life," "information about how intensively I may exert myself or do sports," "adjustment to new life situation," and "handling physical changes." Conclusions: This study provides a detailed framework for the content and design of e-Health interventions to support patients managing their post-COVID-19 symptoms. The findings could significantly influence the further development of tailored e-Health interventions to address this pressing global health concern. [ABSTRACT FROM AUTHOR]

Purpose: To investigate the prevalence of insomnia among nurses with long COVID-19, analyze the potential risk factors and establish a nomogram model. Methods: Nurses in Ningbo, China, were recruited for this study. General demographic information and insomnia, burnout, and stress assessment scores were collected through a face-to face questionnaire survey administered at a single center from March to May 2023. We used LASSO regression to identify potential factors contributing to insomnia. Then, a nomogram was plotted based on the model chosen to visualize the results and evaluated by receiver operating characteristic curves and calibration curves. Results: A total of 437 nurses were recruited. 54% of the nurses had insomnia according to the Insomnia Severity Index (ISI) score. Eleven variables, including family structure, years of work experience, relaxation time, respiratory system sequelae, nervous system sequelae, others sequelae, attitudes toward COVID-19, sleep duration before infection, previous sleep problems, stress, and job burnout, were independently associated with insomnia. The R-squared value was 0.464, and the area under the curve was 0.866. The derived nomogram showed that neurological sequelae, stress, job burnout, sleep duration before infection, and previous sleep problems contributed the most to insomnia. The calibration curves showed significant agreement between the nomogram models and actual observations. Conclusion: This study focused on insomnia among nurses with long COVID-19 and identified eleven risk factors related to nurses' insomnia. A nomogram model was established to illustrate and visualize these factors, which will be instrumental in future research for identifying nurses with insomnia amid pandemic normalization and may increase awareness of the health status of healthcare workers with long COVID-19. [ABSTRACT FROM AUTHOR]

Objective: To evaluate and characterize the cognitive changes in COVID-19 participants at 6-month follow-up, and to explore a possible association with clinical symptoms, emotional disturbance and disease severity. Methods: This single-center longitudinal cohort study included participants aged 20 and 60 years old to exclude cognitive impairment age-associated with confirmed COVID-19 infection. The initial evaluation occurred 10 to 30 days after hospital or ambulatory discharge, with a subsequent follow-up at 6 months. Patients who had a history of cognitive impairment, neurological conditions, or serious psychiatric disorders were not included. Information on demographics and laboratory results was gathered from medical records. Cognitive outcomes were assessed with a neuropsychological battery including attention, verbal and visual memory, language and executive function tests. Results: A total of 200 participants were included in the study, and 108 completed the follow-up visit. At the 6-month follow-up, comparing the means from baseline with those of the follow-up evaluation, significant overall improvement was observed in verbal and visual memory subtests (p = 0.001), processing speed (p = 0.001), executive function (p = 0.028; p = 0.016) and naming (p = 0.001), independently of disease severity and cognitive complaints. Anxiety and depression were significantly higher in groups with Subjective Cognitive Complaints (SCC) compared to those without (p < 0.01 for both). Conclusions: Persistent symptoms are common regardless of disease severity and are often linked to cognitive complaints. Six months after COVID-19, the most frequently reported symptoms included headache, dyspnea, fatigue, cognitive complaints, anxiety, and depression. No cognitive impairment was found to be associated with the severity of COVID-19. Overall, neuropsychological and psychopathological improvement was observed at 6 months regardless of disease severity and cognitive complaints. [ABSTRACT FROM AUTHOR]

Objectives: We aimed to assess the prevalence of long COVID-19 and estimate the average time to its diagnosis and meta-regression for covariates. Methods: We conducted a systematic review, meta-analysis, and meta-regression from 43 studies (367,236 patients) (June 2020–August 2022). With the random-effects model, the pooled prevalence of long COVID-19 was measured. Publication bias was ascertained, and meta-regression analysis was performed on predetermined covariates. The trial was registered with PROSPERO (CRD42022328509). Results: The pooled prevalence of long COVID-19 was 42.5% (95% CI 36% to 49.3%), with 25% and 66% at four and two months, respectively. Mostly, long COVID-19 signs and symptoms occurred at three (54.3%) to six (57%) months (p < 0.0001), further increasing at 12 months (57.9%, p = 0.0148). Hypertension was significantly associated with long COVID-19 at 32% (0.322 (95% CI 0.166, 0.532) (p < 0.001) and hospital re-admission contributed to 17% (Q = 8.70, df = 1, p = 0.0032) (R2 = 0.17). All the covariates explained at least some of the variance in effect size on long COVID-19 at 53% (Q = 38.81, df = 19, p = 0.0047) (R2 analog = 0.53). Conclusion: The prevalence of long COVID-19 was 42.5% when linked with a cardiovascular disorder. Hospital re-admission majorly predicted the incidence of long COVID-19. Clinical and methodological characteristics in a specific study contributed to over 50% of long COVID-19 events, with most signs and symptoms occurring between 3 and 6 months and increasing at 12 months. [ABSTRACT FROM AUTHOR]

Soon after the outbreak of coronavirus disease 2019 (COVID-19), unexplained sustained fatigue, cognitive disturbance, and muscle ache/weakness were reported in patients who had recovered from acute COVID-19 infection. This abnormal condition has been recognized as "long COVID (postacute sequelae of COVID-19 [PASC])" with a prevalence estimated to be from 10 to 20% of convalescent patients. Although the pathophysiology of PASC has been studied, the exact mechanism remains obscure. Microclots in circulation can represent one of the possible causes of PASC. Although hypercoagulability and thrombosis are critical mechanisms of acute COVID-19, recent studies have reported that thromboinflammation continues in some patients, even after the virus has cleared. Viral spike proteins and RNA can be detected months after patients have recovered, findings that may be responsible for persistent thromboinflammation and the development of microclots. Despite this theory, long-term results of anticoagulation, antiplatelet therapy, and vascular endothelial protection are inconsistent, and could not always show beneficial treatment effects. In summary, PASC reflects a heterogeneous condition, and microclots cannot explain all the presenting symptoms. After clarification of the pathomechanisms of each symptom, a symptom- or biomarker-based stratified approach should be considered for future studies. [ABSTRACT FROM AUTHOR]

A rise in fungal infections has been observed worldwide among patients with extended hospital stays because of the severe infection caused by the new coronavirus pandemic. A 62-year-old female patient was admitted with a severe form of Coronavirus disease 2019 (COVID-19) and spent four weeks in the intensive care unit (ICU) requiring mechanical ventilation support before being moved to a tertiary hospital for further testing. Aspergillus fumigatus filamentous fungus, Candida spp., and positive bacteriology for multidrug-resistant Klebsiella pneumoniae and Proteus mirabilis were identified by bronchial aspirate cultures. The patient's progress was gradually encouraging while receiving oral antifungal and broad-spectrum antibiotic therapy along with respiratory physical therapy; but ultimately, thoracic surgery was necessary. Long-lasting tissue damage and severe, persistent inflammatory syndrome were the two main pathophysiological mechanisms that led to significant outcomes regarding lung lesions that were rapidly colonized by fungi and resistant flora, cardiac damage with sinus tachycardia at the slightest effort, and chronic inflammatory syndrome, which was characterized by marked asthenia, myalgias, and exercise intolerance. [ABSTRACT FROM AUTHOR]