Asthma is a risk factor for general fatigue of long COVID in Japanese nation-wide cohort study

Long Covid Symptom Clusters, Correlates and Predictors in a Highly Vaccinated Australian Population in 2023

BACKGROUND

Limited data exists regarding long Covid burden following Omicron infection in highly vaccinated populations.

OBJECTIVE

To (1) characterise long Covid prevalence and predictors and (2) identify key symptom clusters and their correlates among long Covid patients, during an Omicron-predominant period in a highly vaccinated population.

DESIGN

Anonymous, online, cross-sectional survey.

SETTING

January 2023, Australia.

PARTICIPANTS

Residents aged ≥ 18 years with self-reported history of test-positive Covid-19. The main variables studied were socio-demographic characteristics, Covid-19 risk factors, vaccination, infection history and experiences with long Covid.

MAIN OUTCOME MEASURES

Long Covid symptoms. Symptom-based clustering was used to identify long Covid symptom clusters and their functional correlates. Predictors of long Covid occurrence and severity were assessed using multivariable logistic regression.

RESULTS

Overall, 240/1205 participants (19.9%) reported long Covid. Long Covid risk was significantly higher for women OR 1.71 (95% CI: 1.17-2.51), people with comorbidities 2.19 (95% CI: 1.56-3.08) and those using steroid inhalers for Covid-19 treatment (2.34 [95% CI: 1.29-4.24]). Long-Covid risk increased with increasing Covid-19 infection severity (moderately severe symptoms: 2.23 [95% CI: 1.50-3.30], extremely severe symptoms: 5.80 [95% CI: 3.48-9.66], presented to ED/hospitalised: 7.22 [95% CI: 3.06-17.03]). We found no significant difference in the likelihood of long Covid between the Omicron and pre-Omicron periods, vaccination status and participant age. We identified two long Covid clusters (pauci-symptomatic, n = 170, vs. polysymptomatic, n = 66). Polysymptomatic cluster membership was associated with worse functioning (impacts on work, moderate activity, emotions and energy). Severity acute infection was strongly predictive of polysymptomatic cluster membership (5.72 [2.04-17.58]). Monoclonal antibody treatment was strongly associated with pauci-symptomatic cluster membership (0.02 [0.00-0.13]).

DISCUSSION

Our study shows that long Covid is an important health burden in Australia, including during the Omicron era, and identifies several risk factors. We found a subgroup of patients characterised by more symptoms and worse functional outcomes. Our findings can inform policies for protecting vulnerable populations and frameworks for long Covid risk assessment and management.

CONCLUSIONS

One-in-five people may suffer long Covid after acute Covid-19 infection, with similar risk across age groups. Omicron variants appear not to have a lower risk compared to earlier variants in our study. A cumulative number of symptoms can help triage long Covid patients.

PATIENT OR PUBLIC CONTRIBUTION

We did not involve patients or the public in the design of the questionnaire. However, after a soft launch, we revised some survey questions by reviewing early responses from patients and the public.

Analysis of risk factors for long COVID after mild COVID-19 during the Omicron wave in Japan

BACKGROUND

Post-COVID-19 syndrome, referred to as "long COVID," is characterized by persistent symptoms that develop during or after SRAS-CoV-2 infection lasting for ≥12 weeks, which cannot be explained by factors other than COVID-19. Previous studies before the Omicron pandemic have identified female sex, older age (≥50 years), severity of illness, obesity, diabetes, and smoking as risk factors for long COVID. However, data on long COVID following the emergence of the Omicron variants are limited.

METHODS

An online survey was conducted among outpatients diagnosed with mild COVID-19 at 14 participating institutions in Japan between July 30, 2022, and December 31, 2023.

RESULTS

Of the included 246 cases, 76 (35.5%) experienced at least one long COVID symptom 12 weeks after onset. Logistic regression analysis revealed that age ≥40 years was significantly associated with an increased risk of respiratory (odds ratio [OR]: 3.80, 95% confidence interval [CI]: 1.67-8.65) and neurologic symptoms (OR: 4.53, 95% CI: 1.84-11.13). Conversely, antiviral drug use was associated with a decreased risk of respiratory symptoms (OR: 0.31, 95% CI: 0.11-0.93).

CONCLUSION

Caution is warranted when treating patients over 40 years of age with mild COVID-19 due to their higher susceptibility to developing long COVID. Antiviral drugs may be beneficial in managing respiratory symptoms and mitigating disease severity.

Symptoms of Depression and Anxiety After COVID-19 Despite Systematic Telemedical Care: Results From the Prospective COVID-SMART Study

Background: Long-COVID has attracted increased attention with rising numbers of affected patients and high individual symptom burden. Prior studies have described its prevalence, course of disease, and severity. Yet, the influence of intensive care, including telemedical support for patients at risk for a severe course of the initial COVID-19 disease, on the occurrence of Long-COVID and its associated symptoms is studied to a lesser extent. Methods: Here, we report the long-term results of the COVID-SMART study, which randomized at-risk COVID-19 patients to either smartwatch-based monitoring with telemedical support or standard care. We investigate Long-COVID symptoms, including symptoms of depression and anxiety after 12 months. Findings: Between October 2020 and May 2022, we enrolled 607 patients in the COVID-SMART study. Complete 12-month follow-up was available for 573 patients, with 288 patients randomized to the intervention group and 285 to the control group. Overall, 234 participants (40.8%) reported COVID-related symptoms, with a high prevalence of symptoms of depression (209 participants, 36.5%) and anxiety (232 participants, 40.5%). However, telemedical support did not reduce these symptoms at follow-up. Multivariable regression analysis identified sex, active smoking, and pre-existing asthma as significant predictors of both outcomes. Interpretation: COVID-SMART is the first prospective, randomized clinical trial to systematically assess the impact of telemedical care on the development of Long-COVID associated risk of depression and anxiety. We identify in part modifiable risk factors for these outcomes. However, telemedical support does not appear to be beneficial in reducing symptoms of anxiety and depression and should hence be focused to the acute infection phase. Trial Registration: ClinicalTrials.gov identifier: NCT04471636.

Overview of Long COVID: Navigating the Aftermath

The coronavirus disease (COVID-19) pandemic was a global health crisis with far-reaching consequences. Among these were physical and mental health complications that emerged weeks or even months after the initial COVID-19 infection, collectively termed "long COVID" or "post-COVID syndrome." Identifying the epidemiology, risk factors, clinical manifestations, and management strategies for long COVID is crucial for both clinicians and patients, which is the focus of this review. The prevalence of long COVID varies across studies, generally ranging from 5% to 20%. Prominent risk factors include female sex, older age, a high number of acute symptoms, lower socioeconomic status, and underlying comorbidities such as diabetes, asthma, or chronic obstructive pulmonary disease. The clinical manifestations of long COVID are diverse; beyond the commonly reported symptoms of fatigue, malaise, ageusia, and anosmia, neuropsychiatric complications such as headache, cognitive deficits, and depression are also potential outcomes. Although there is currently no consensus on the management of long COVID, multidisciplinary care teams with appropriate referrals and follow-up diagnostic studies are essential in evaluating the clinical course of long COVID patients.

The global burden and trends of asthma from 1990 to 2021, and its changes during the COVID-19 pandemic: An observational study

OBJECTIVES

This study aims to comprehensively analyze the global burden and trends of asthma, along with their variations during the COVID-19 pandemic.

STUDY DESIGN

An observational study.

METHODS

The data on age-standardized rates of incidence (ASIR), prevalence (ASPR), and deaths (ASDR) for asthma were accessed from the Global Burden of Disease 2021. Estimated annual percentage changes (EAPCs) and annual percent changes (APCs) were calculated to describe secular trends. The rate differences between the average rates of 2020-2021 and those of 2018-2019 represent the change in the burden of asthma before and during the COVID-19 pandemic.

RESULTS

In 2021, the global ASIR, ASPR, and ASDR of asthma were 516.70, 3340.12, and 5.2 per 100,000, with EAPCs of -1.04 %, -1.59 %, and -2.03 %, respectively. However, from 2018 to 2021, the global ASIR and ASPR of asthma showed a significant upward trend, with APCs of 0.41 % (95 % CI: 0.11 %-0.86 %) and 0.28 % (95 % CI: 0.04 %-0.69 %), respectively. During the COVID-19 pandemic, the global ASIR and ASPR increased significantly (rate differences were 5.26 and 23.10 per 100,000, respectively), especially in the high SDI regions (rate differences were 16.28 and 51.05 per 100,000, respectively), and among children aged under 5 (rate differences were 12.73 and 82.09 per 100,000, respectively).

CONCLUSION

During the COVID-19 pandemic period in 2020-2021, the incidence and prevalence of asthma have exhibited an upward trend globally, especially in high SDI regions and among children under 5 years old. This necessitates increased attention and intervention.

The Relationship Between Long Covid Symptoms and Vaccination Status in COVID-19 Survivors

BACKGROUND

The positive effects of vaccination status on the course of Long COVID symptoms have not been fully elucidated. Our aim is to determine the most common Long COVID symptoms in patients monitored in the COVID-19 follow-up clinic and to examine whether there is a difference between the recovery rates of those who are vaccinated and those who are not vaccinated.

METHOD

Between December 1, 2020 and April 30, 2022, prospectively collected data of 916 patients who were admitted to the COVID-19 follow-up outpatient clinic of a tertiary hospital for the first time were evaluated as a retrospective cohort in this study. The frequencies of the ten most common symptoms in the first and last examinations of 478 patients with Long COVID symptoms were determined, and their recovery was compared. Patients were divided into two groups according to their vaccination status. The values showing the recovery rates obtained for these two groups were compared between themselves again.

RESULTS

The average age of the patients in the study group was 54.43 ± 11.71 years, and 255 (53.3%) were male. The median follow-up period was 10 months. 84.7% of patients had received at least one dose of vaccine. Statistically significant results were found for improvement in all ten symptoms in vaccinated patients compared to the never-vaccinated group. There was no statistically significant difference between the CoronaVac, BNT162b2, and heterologous (CoronaVac+ BNT162b2) vaccine groups. Factors affecting recovery for the three most common symptoms (dyspnea, fatigue, forgetfulness) were examined with univariate logistic regression analysis, and only vaccination or non-vaccination was found to be a significant risk factor.

CONCLUSION

This study showed that receiving vaccination may be effective in improving Long COVID symptoms. Although there were no statistically significant differences between the inactive vaccine CoronaVac, the mRNA vaccine BNT162b2, and the heterologous (CoronaVac+ BNT162b2) vaccine in terms of reducing Long COVID symptoms, higher recovery rates were detected in those who received the mRNA vaccine BNT162b2.

Risk of long covid in patients with pre-existing chronic respiratory diseases: a systematic review and meta-analysis

BACKGROUND

An estimated 10-30% of people with COVID-19 experience debilitating long-term symptoms or long covid. Underlying health conditions associated with chronic inflammation may increase the risk of long covid.

METHODS

We conducted a systematic review and meta-analysis to examine whether long covid risk was altered by pre-existing asthma or chronic obstructive pulmonary disease (COPD) in adults. We identified studies by searching the PubMed and Embase databases from inception to 13 September 2024. We excluded studies that focused on children or defined long covid only in terms of respiratory symptoms. We used random-effects, restricted maximum likelihood models to analyse data pooled from 51 studies, which included 43 analyses of asthma and 30 analyses of COPD. The risk of bias was assessed using a ROBINS-E table.

RESULTS

We found 41% increased odds of long covid with pre-existing asthma (95% CI 1.29 to 1.54); pre-existing COPD was associated with 32% increased odds (95% CI 1.16 to 1.51). Pre-existing asthma, but not COPD, was associated with increased odds of long covid-associated fatigue. We observed heterogeneity in the results of studies of asthma related to hospitalisation status. Potential confounding and inconsistent measurement of exposure and outcome variables were among the identified limitations.

CONCLUSIONS

Our findings support the hypothesis that pre-existing asthma and COPD increase the risk of long covid, including chronic fatigue outcomes in patients with asthma. Because COVID-19 targets the respiratory tract, these inflammatory conditions of the lower respiratory tract could provide mechanistic clues to a common pathway for the development of long-term sequelae in patients with long covid.

Utilization frequency and patient-reported effectiveness of symptomatic therapies in post-COVID syndrome

BACKGROUND

To date there is no causal treatment for post-COVID syndrome, leaving symptomatic treatments as the primary recourse. However, the practical implementation and effectiveness of these interventions remain underexplored. This study aimed to investigate the utilization frequency of symptomatic therapies and patient-reported effectiveness across various treatment modalities at a German post-COVID center.

METHODS

As the baseline investigation we conducted a single-cohort retrospective study to analyze the frequency of symptomatic therapies among post-COVID patients who attended the post-COVID center of the University Hospital of Erlangen, between December 2022 to July 2023. Additionally, we administered a follow-up at least 3 months after the initial presentation, using a questionnaire to assess patient-reported improvements in post-COVID symptoms associated with the symptomatic therapies received.

RESULTS

Our study included 200 patients (mean age: 44.6 ± 12.6 years; 69.0% women; mean duration since acute infection: 15.3 ± 8.3 months). Pharmacotherapy was the predominant symptomatic treatment (79.5%), with psychotropic drugs (32.5%) and analgesics (31.5%) being the most frequently prescribed. Over half of the patients (55.5%) utilized vitamins and nutritional supplements. Hospital admission rates to acute care occurred in 35.5% of cases; 33.0% underwent inpatient rehabilitation and 31.0% pursued outpatient psychotherapy. Cardiologists (76.5%), pulmonologists (67.5%), and neurologists (65.5%) were the most consulted specialists. Therapies involving medical devices were infrequently employed (12.0%). In a follow-up questionnaire (response rate: 82.5%, 6.3 ± 2.2 months post-baseline), beta-blockers were the most effective pharmacological intervention with 31.5% of patients reporting strong to very strong symptom improvement, followed by antibiotics (29.6%). Furthermore, 33.0% of the patients perceived plasmapheresis to strongly alleviate symptoms. Only a small proportion of the sample attributed a strong or very strong symptom improvement to outpatient psychotherapy (11.0%).

CONCLUSION

This study provides initial insights into symptomatic therapy utilization and patient-reported symptom improvement in post-COVID syndrome. Further research into symptoms clusters and interdisciplinary collaboration are warranted to comprehensively address the multifaceted physical and psychological symptomatology.

TRIAL REGISTRATION

The study was registered at the German Clinical Trials Register (DRKS-ID: DRKS00033621) on March 20, 2024.

Long COVID is not the same for everyone: a hierarchical cluster analysis of Long COVID symptoms 9 and 12 months after SARS-CoV-2 test

BACKGROUND

Identifying symptom clusters in Long COVID is necessary for developing effective therapies for this diverse condition and improving the quality of life of those affected by this heterogeneous condition. In this study, we aimed to identify and compare symptom clusters at 9 and 12 months after a SARS-CoV-2 positive test and describe each cluster regarding factors at infection.

METHODS

This is a cross-sectional study with individuals randomly selected from the Portuguese National System of Epidemiological Surveillance (SINAVE) database. Individuals who had a positive RT-PCR SARS-CoV-2 test in August 2022 were contacted to participate in a telephonic interview approximately 9 and 12 months after the test. A hierarchical clustering analysis was performed, using Euclidean distance and Ward's linkage. Clustering was performed in the 35 symptoms reported 9 and 12 months after the SARS-CoV-2 positive test and characterised considering age, sex, pre-existing health conditions and symptoms at time of SARS-CoV-2 infection.

RESULTS

552 individuals were included at 9 months and 458 at 12 months. The median age was 52 years (IQR: 40-64 years) and 59% were female. Hypertension and high cholesterol were the most frequently reported pre-existing health conditions. Memory loss, fatigue or weakness and joint pain were the most frequent symptoms reported 9 and 12 months after the positive test. Four clusters were identified at both times: no or minor symptoms; multi-symptoms; joint pain; and neurocognitive-related symptoms. Clusters remained similar in both times, but, within the neurocognitive cluster, memory loss and concentration issues increased in frequency at 12 months. Multi-symptoms cluster had older people, more females and more pre-existing health conditions at 9 months. However, at 12 months, older people and those with more pre-existing health conditions were in joint pain cluster.

CONCLUSIONS

Our results suggest that Long COVID is not the same for everyone. In our study, clusters remained similar at 9 and 12 months, except for a slight variation in the frequency of symptoms that composed each cluster. Understanding Long COVID clusters might help identify treatments for this condition. However, further validation of the observed clusters and analysis of its risk factors is needed.

Prevalence and characteristics in long COVID among adults with asthma in the United States

OBJECTIVE

The purpose of this study was to assess: (1) the prevalence of long COVID by asthma status, and (2) the characteristics associated with developing long COVID among adults with asthma in the United States.

METHODS

Data from the 2022 National Health Interview Survey were used. The prevalence of long COVID was reported and stratified by asthma status. The multivariable logistic regression model was conducted to identify the factors associated with developing long COVID.

RESULTS

In 2022, the overall prevalence of long COVID among U.S. adults was 6.9%. When stratified by asthma status, the prevalence of long COVID was 13.9% among adults with asthma, and 6.2% among adults without asthma. Among adults with asthma, certain characteristics, including age over 55 years, female sex, obesity, problems paying medical bills and a history of asthma attacks, were significantly associated with developing long COVID.

CONCLUSIONS

This study revealed that the prevalence of long COVID among adults with asthma was much higher than the general adult population in the United States. The limited validity of the collected information in this study should prompt caution when interpreting our findings. Further studies on the association between asthma and long COVID could be valuable for the clinical practice.

Connecting the dots: the role of fatigue in female infertility

Fatigue, an increasingly acknowledged symptom in various chronic diseases, has garnered heightened attention, during the medical era of bio-psycho-social model. Its persistence not only significantly compromises an individual's quality of life but also correlates with chronic organ damage. Surprisingly, the intricate relationship between fatigue and female reproductive health, specifically infertility, remains largely unexplored. Our exploration into the existing body of evidence establishes a compelling link between fatigue with uterine and ovarian diseases, as well as conditions associated with infertility, such as rheumatism. This observation suggests a potentially pivotal role of fatigue in influencing overall female fertility. Furthermore, we propose a hypothetical mechanism elucidating the impact of fatigue on infertility from multiple perspectives, postulating that neuroendocrine, neurotransmitter, inflammatory immune, and mitochondrial dysfunction resulting from fatigue and its co-factors may further contribute to endocrine disorders, menstrual irregularities, and sexual dysfunction, ultimately leading to infertility. In addition to providing this comprehensive theoretical framework, we summarize anti-fatigue strategies and accentuate current knowledge gaps. By doing so, our aim is to offer novel insights, stimulate further research, and advance our understanding of the crucial interplay between fatigue and female reproductive health.