Prevalence of and factors associated with post-COVID-19 condition in the 12 months following the diagnosis of COVID-19 in adults followed in general practices in Germany

Association of psychiatric disorders with clinical diagnosis of long COVID in US veterans

BACKGROUND

Psychiatric disorders may be a risk factor for long COVID, broadly defined as COVID-19 conditions continuing three months post-acute infection. In US Veterans with high psychiatric burden, we examined associations between psychiatric disorders and clinical diagnosis of long COVID.

METHODS

We conducted a retrospective cohort study using health records from VA patients with a positive SARS-CoV-2 test from February 2020 to February 2023. Generalized linear models estimated associations between any psychiatric disorder and likelihood of subsequent diagnosis with long COVID (i.e. two or more long COVID clinical codes). Models were adjusted for socio-demographic, medical, and behavioral factors. Secondary models examined individual psychiatric disorders and age-stratified associations.

RESULTS

Among 660 217 VA patients with positive SARS-CoV-2 tests, 56.3% had at least one psychiatric disorder diagnosis and 1.4% were diagnosed with long COVID. Individuals with any psychiatric disorder had higher risk for long COVID diagnosis in models adjusted for socio-demographic factors, vaccination status, smoking, and medical comorbidities (relative risk, RR = 1.28, 95% CI 1.21-1.35), with the strongest associations in younger individuals. Considering specific disorders, depressive, anxiety, and stress-related disorders were associated with increased risk for long COVID diagnoses (RRs = 1.36-1.48), but associations were in the opposite direction for substance use and psychotic disorders (RRs = 0.78-0.88).

CONCLUSIONS

Psychiatric disorder diagnoses were associated with increased long COVID diagnosis risk in VA patients, with the strongest associations observed in younger individuals. Improved surveillance, treatment, and prevention for COVID-19 and its long-term sequelae should be considered for individuals with psychiatric conditions.

Symptoms before and after COVID-19: a population and case-control study using prospective data

BACKGROUND

Some individuals experience prolonged illness after acute coronavirus disease 2019 (COVID-19). We assessed whether pre-infection symptoms affected post-acute COVID illness duration.

METHODS

Survival analysis was performed in adults (n=23 452) with community-managed severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection prospectively self-logging data through the ZOE COVID Symptom Study app, at least weekly, from 8 weeks before to 12 weeks after COVID-19 onset, conditioned on presence versus absence of baseline symptoms (4-8 weeks before COVID-19). A case-control study was performed in 1350 individuals with long illness (≥8 weeks, including 906 individuals (67.1%) with illness ≥12 weeks), matched 1:1 (for age, sex, body mass index, testing week, prior infection, vaccination, smoking, index of multiple deprivation) with 1350 individuals with short illness (<4 weeks). Baseline symptoms were compared between the two groups, and against post-COVID symptoms.

RESULTS

Individuals reporting baseline symptoms had longer COVID-related symptom duration (median 15 days versus 10 days for individuals without baseline symptoms) with baseline fatigue nearly doubling duration. Two-thirds (910 (67.4%) of 1350) of individuals with long illness were asymptomatic beforehand. However, 440 (32.6%) had baseline symptoms, versus 255 (18.9%) of 1350 individuals with short illness (p<0.0001). Baseline symptoms doubled the odds ratio for long illness (2.14, 95% CI 1.78-2.57). Prior comorbidities were more common in individuals with long versus short illness. In individuals with long illness, baseline symptomatic (versus asymptomatic) individuals were more likely to be female, younger, and have prior comorbidities; and baseline and post-acute symptoms, and symptom burden, correlated strongly.

CONCLUSIONS

Individuals experiencing symptoms before COVID-19 had longer illness duration and increased odds of long illness. However, many individuals with long illness were well before SARS-CoV-2 infection.

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.

Burden of Long COVID-19 in a Cohort of Recovered COVID-19 Patients in Delhi, India

BACKGROUND

The long COVID phase is characterized by signs and symptoms persisting for at least three months after recovery from acute COVID-19 illness. There is limited data on comprehensive long-term clinical follow-up of COVID-19 patients.

AIMS

This study aims to explore the burden and symptomatology of long COVID syndrome and its association with various health parameters.

SETTINGS AND DESIGN

This prospective observational study was conducted in Delhi from May 2022 to March 2023.

METHODS AND MATERIAL

A total of 553 adult patients who had recovered from COVID-19 were enrolled in the study. A sociodemographic and clinical profile was obtained using validated questionnaires, along with an evaluation of biochemical parameters to assess the associated factors.

STATISTICAL ANALYSIS USED

Chi-square test, unpaired t-test, and bivariate regression analysis were applied using Statistical Product and Service Solutions (SPSS, version 28; IBM SPSS Statistics for Windows, Armonk, NY). A p value of <0.05 was considered significant.

RESULTS

A total of 252 patients (45.6%) had long COVID syndrome, which was significantly associated with the presence of any pre-existing comorbidity (OR=1.46 (1.02-2.09); p=0.039), previous history of hypertension (OR=1.82 (1.07-3.09); p=0.027), and vaccination against COVID-19 (OR=1.392 (1.171-1.656); p=0.003). The most common symptoms reported were persistent fatigue (33.3%) and persistent dry cough (28.5%). Patients with long COVID syndrome are also reported to have poorer sleep quality. Biochemical findings showed abnormal T lymphocytes (9.3%) and raised HbA1c (11.9%).

CONCLUSIONS

Multiple risk factors and symptoms associated with long COVID syndrome were identified in this study. Research efforts and knowledge regarding the pattern of illness will aid in long-term monitoring and development of interventional strategies and guidelines for the care of recovered COVID-19 patients.

The long-term effects of COVID-19 on pulmonary status and quality of life

Background

Few studies have looked at how SARS-CoV-2 affects pulmonary function, exercise capacity, and health-related quality of life over time. The purpose of this study was to evaluate these characteristics in post COVID-19 subjects 1 year after recovery.

Methods

The study included two groups. The case group included post COVID-19 subjects who had recovered after a year, and the control group included healthy participants who had never tested positive for COVID-19.

Results

The study screened 90 participants, 42 of whom met the eligibility criteria. The findings revealed that the majority of post COVID-19 subjects had relatively normal lung function 1-year post-recovery. A significant reduction in DLCO (B/P%) was observed in the case group vs. control. The exercise capacity test revealed a clinically significant difference in distance walked and a significant difference in the dyspnea post-walk test in the case group compared to the control group. The case group's health-related quality of life domain scores were significantly affected in terms of energy/fatigue, general health, and physical function.

Conclusions

The post COVID-19 subjects were shown to have well-preserved lung function after 1 year. However, some degree of impairment in diffusion capacity, exercise capacity, and health-related quality of life remained.

Persistent symptoms and risk factors predicting prolonged time to symptom-free after SARS‑CoV‑2 infection: an analysis of the baseline examination of the German COVIDOM/NAPKON-POP cohort

PURPOSE

We aimed to assess symptoms in patients after SARS-CoV-2 infection and to identify factors predicting prolonged time to symptom-free.

METHODS

COVIDOM/NAPKON-POP is a population-based prospective cohort of adults whose first on-site visits were scheduled ≥ 6 months after a positive SARS-CoV-2 PCR test. Retrospective data including self-reported symptoms and time to symptom-free were collected during the survey before a site visit. In the survival analyses, being symptom-free served as the event and time to be symptom-free as the time variable. Data were visualized with Kaplan-Meier curves, differences were tested with log-rank tests. A stratified Cox proportional hazard model was used to estimate adjusted hazard ratios (aHRs) of predictors, with aHR < 1 indicating a longer time to symptom-free.

RESULTS

Of 1175 symptomatic participants included in the present analysis, 636 (54.1%) reported persistent symptoms after 280 days (SD 68) post infection. 25% of participants were free from symptoms after 18 days [quartiles: 14, 21]. Factors associated with prolonged time to symptom-free were age 49-59 years compared to < 49 years (aHR 0.70, 95% CI 0.56-0.87), female sex (aHR 0.78, 95% CI 0.65-0.93), lower educational level (aHR 0.77, 95% CI 0.64-0.93), living with a partner (aHR 0.81, 95% CI 0.66-0.99), low resilience (aHR 0.65, 95% CI 0.47-0.90), steroid treatment (aHR 0.22, 95% CI 0.05-0.90) and no medication (aHR 0.74, 95% CI 0.62-0.89) during acute infection.

CONCLUSION

In the studied population, COVID-19 symptoms had resolved in one-quarter of participants within 18 days, and in 34.5% within 28 days. Over half of the participants reported COVID-19-related symptoms 9 months after infection. Symptom persistence was predominantly determined by participant's characteristics that are difficult to modify.

Association between long COVID and vaccination: A 12-month follow-up study in a low- to middle-income country

OBJECTIVE

There is a lack of estimates regarding the at-risk population associated with long COVID in Pakistan due to the absence of prospective longitudinal studies. This study aimed to determine the prevalence of long COVID and its association with disease severity and vaccination status of the patient.

DESIGN AND DATA SOURCES

This prospective cohort study was conducted at the Aga Khan University Hospital and recruited patients aged > 18 years who were admitted between February 1 and June 7, 2021. During this time, 901 individuals were admitted, after excluding patients with missing data, a total of 481 confirmed cases were enrolled.

RESULTS

The mean age of the study population was 56.9±14.3 years. Among patients with known vaccination status (n = 474), 19%(n = 90) and 19.2%(n = 91) were fully and partially vaccinated, respectively. Severe/critical disease was present in 64%(n = 312). The mortality rate following discharge was 4.58%(n = 22). Around 18.9%(n = 91) of the population required readmission to the hospital, with respiratory failure (31.8%, n = 29) as the leading cause. Long COVID symptoms were present in 29.9%(n = 144), and these symptoms were more prevalent in the severe/critical (35.5%, n = 111) and unvaccinated (37.9%, n = 105) cohort. The most prominent symptoms were fatigue (26.2%, n = 126) and shortness of breath (24.1%, n = 116), followed by cough (15.2%, n = 73). Vaccinated as compared to unvaccinated patients had lower readmissions (13.8% vs. 21.51%) and post-COVID pulmonary complications (15.4% vs. 24.2%). On multivariable analysis, after adjusting for age, gender, co-morbidity, and disease severity, lack of vaccination was found to be an independent predictor of long COVID with an Odds ratio of 2.42(95% CI 1.52-3.84). Fully and partially vaccinated patients had 62% and 56% reduced risk of developing long COVID respectively.

CONCLUSIONS

This study reports that the patients continued to have debilitating symptoms related to long COVID, one year after discharge, and most of its effects were observed in patients with severe/critical disease and unvaccinated patients.

Long-term health impacts of COVID-19 among 242,712 adults in England

The COVID-19 pandemic is having a lasting impact on health and well-being. We compare current self-reported health, quality of life and symptom profiles for people with ongoing symptoms following COVID-19 to those who have never tested positive for SARS-CoV-2 infection and those who have recovered from COVID-19. Overall, 276,840/800,000 (34·6%) of invited participants took part. Mental health and health-related quality of life were worse among participants with ongoing persistent symptoms post-COVID compared with those who had never had COVID-19 or had recovered. In this study, median duration of COVID-related symptoms (N = 130,251) was 1·3 weeks (inter-quartile range 6 days to 2 weeks), with 7·5% and 5·2% reporting ongoing symptoms ≥12 weeks and ≥52 weeks respectively. Female sex, ≥1 comorbidity and being infected when Wild-type variant was dominant were associated with higher probability of symptoms lasting ≥12 weeks and longer recovery time in those with persistent symptoms. Although COVID-19 is usually of short duration, some adults experience persistent and burdensome illness.

Psychological Resilience to Trauma and Risk of COVID-19 Infection and Somatic Symptoms Across 2 Years

OBJECTIVE

Exposure to trauma increases the risk of somatic symptoms, as well as acute and chronic physical diseases. However, many individuals display psychological resilience, showing positive psychological adaptation despite trauma exposure. Resilience to prior trauma may be a protective factor for physical health during subsequent stressors, including the COVID-19 pandemic.

METHODS

Using data from 528 US adults in a longitudinal cohort study, we examined psychological resilience to lifetime potentially traumatic events early in the pandemic and the risk of COVID-19 infection and somatic symptoms across 2 years of follow-up. Resilience was defined as level of psychological functioning relative to lifetime trauma burden, assessed in August 2020. Outcomes included COVID-19 infection and symptom severity, long COVID, and somatic symptoms assessed every 6 months for 24 months. Using regression models, we examined associations between resilience and each outcome adjusting for covariates.

RESULTS

Higher psychological resilience to trauma was associated with a lower likelihood of COVID-19 infection over time, with one standard deviation higher resilience score associated with a 31% lower likelihood of COVID-19 infection, adjusting for sociodemographics and vaccination status. Furthermore, higher resilience was associated with lower levels of somatic symptoms during the pandemic, adjusting for COVID-19 infection and long COVID status. In contrast, resilience was not associated with COVID-19 disease severity or long COVID.

CONCLUSIONS

Psychological resilience to prior trauma is associated with lower risk of COVID-19 infection and lower somatic symptoms during the pandemic. Promoting psychological resilience to trauma may benefit not only mental but also physical health.

Risk Factors Associated With Post-COVID-19 Condition: A Systematic Review and Meta-analysis

Importance

Post-COVID-19 condition (PCC) is a complex heterogeneous disorder that has affected the lives of millions of people globally. Identification of potential risk factors to better understand who is at risk of developing PCC is important because it would allow for early and appropriate clinical support.

Objective

To evaluate the demographic characteristics and comorbidities that have been found to be associated with an increased risk of developing PCC.

Data sources

Medline and Embase databases were systematically searched from inception to December 5, 2022.

Study Selection

The meta-analysis included all published studies that investigated the risk factors and/or predictors of PCC in adult (≥18 years) patients.

Data Extraction and Synthesis

Odds ratios (ORs) for each risk factor were pooled from the selected studies. For each potential risk factor, the random-effects model was used to compare the risk of developing PCC between individuals with and without the risk factor. Data analyses were performed from December 5, 2022, to February 10, 2023.

Main Outcomes and Measures

The risk factors for PCC included patient age; sex; body mass index, calculated as weight in kilograms divided by height in meters squared; smoking status; comorbidities, including anxiety and/or depression, asthma, chronic kidney disease, chronic obstructive pulmonary disease, diabetes, immunosuppression, and ischemic heart disease; previous hospitalization or ICU (intensive care unit) admission with COVID-19; and previous vaccination against COVID-19.

Results

The initial search yielded 5334 records of which 255 articles underwent full-text evaluation, which identified 41 articles and a total of 860 783 patients that were included. The findings of the meta-analysis showed that female sex (OR, 1.56; 95% CI, 1.41-1.73), age (OR, 1.21; 95% CI, 1.11-1.33), high BMI (OR, 1.15; 95% CI, 1.08-1.23), and smoking (OR, 1.10; 95% CI, 1.07-1.13) were associated with an increased risk of developing PCC. In addition, the presence of comorbidities and previous hospitalization or ICU admission were found to be associated with high risk of PCC (OR, 2.48; 95% CI, 1.97-3.13 and OR, 2.37; 95% CI, 2.18-2.56, respectively). Patients who had been vaccinated against COVID-19 with 2 doses had a significantly lower risk of developing PCC compared with patients who were not vaccinated (OR, 0.57; 95% CI, 0.43-0.76).

Conclusions and Relevance

This systematic review and meta-analysis demonstrated that certain demographic characteristics (eg, age and sex), comorbidities, and severe COVID-19 were associated with an increased risk of PCC, whereas vaccination had a protective role against developing PCC sequelae. These findings may enable a better understanding of who may develop PCC and provide additional evidence for the benefits of vaccination.

Trial Registration

PROSPERO Identifier: CRD42022381002.

Predictive Attributes for Developing Long COVID-A Study Using Machine Learning and Real-World Data from Primary Care Physicians in Germany

(1) In the present study, we used data comprising patient medical histories from a panel of primary care practices in Germany to predict post-COVID-19 conditions in patients after COVID-19 diagnosis and to evaluate the relevant factors associated with these conditions using machine learning methods. (2) Methods: Data retrieved from the IQVIA^TM Disease Analyzer database were used. Patients with at least one COVID-19 diagnosis between January 2020 and July 2022 were selected for inclusion in the study. Age, sex, and the complete history of diagnoses and prescription data before COVID-19 infection at the respective primary care practice were extracted for each patient. A gradient boosting classifier (LGBM) was deployed. The prepared design matrix was randomly divided into train (80%) and test data (20%). After optimizing the hyperparameters of the LGBM classifier by maximizing the F2 score, model performance was evaluated using several test metrics. We calculated SHAP values to evaluate the importance of the individual features, but more importantly, to evaluate the direction of influence of each feature in our dataset, i.e., whether it is positively or negatively associated with a diagnosis of long COVID. (3) Results: In both the train and test data sets, the model showed a high recall (sensitivity) of 81% and 72% and a high specificity of 80% and 80%; this was offset, however, by a moderate precision of 8% and 7% and an F2-score of 0.28 and 0.25. The most common predictive features identified using SHAP included COVID-19 variant, physician practice, age, distinct number of diagnoses and therapies, sick days ratio, sex, vaccination rate, somatoform disorders, migraine, back pain, asthma, malaise and fatigue, as well as cough preparations. (4) Conclusions: The present exploratory study describes an initial investigation of the prediction of potential features increasing the risk of developing long COVID after COVID-19 infection by using the patient history from electronic medical records before COVID-19 infection in primary care practices in Germany using machine learning. Notably, we identified several predictive features for the development of long COVID in patient demographics and their medical histories.