Life stressors significantly impact long-term outcomes and post-acute symptoms 12-months after COVID-19 hospitalization

Prevalence of depression, anxiety, stress, and suicide tendency among individual with long-COVID and determinants: A systematic review and meta-analysis

BACKGROUND

While mental health alterations during active COVID-19 infection have been documented, the prevalence of long-term mental health consequences remains unclear. This study aimed to determine the prevalence of mental health symptoms-depression, anxiety, stress, and suicidal tendencies-and to identify their trends and associated risk factors in individuals with long-COVID.

METHODS

We conducted a systematic literature search of databases including PubMed, EMBASE, Scopus, CINAHL, Cochrane Library, Web of Science, and PsycINFO up to August 2024, targeting observational studies published in English. Study quality was assessed using structured standard tools. The primary outcome was the pooled prevalence of depression, anxiety, stress, and suicidal tendencies in individuals with long-COVID. Secondary outcomes included trends in these mental health problems over time and identification of associated determinants.

RESULTS

A total of 94 eligible studies were included in the analysis. The pooled prevalence estimates, regardless of follow up times duration, were as follows: depression, 25% (95%CI:22-28%; PI:1-59%); anxiety (adjusted via trim and fill method), 23%(95%CI:21-25%;PI:2-35%); composite outcomes of depression and/or anxiety, 25% (95%CI:23-27%;PI:2-51%); stress, 26%(95%CI:13-39%;PI:1-69%); and suicidality, 19%(95%CI:15-22%;PI:13-25%). The results of meta-regression analyses revealed a statistically significant trend showing a gradual decrease in the prevalence of the composite outcome of anxiety and/or depression over time (RD = -0.004,P = 0.022). Meta-regression results indicated that being female and younger age were significantly associated with a higher prevalence of mental health symptoms. Study design and study setting did not contribute to heterogeneity.

CONCLUSION

One-fourth of individual with long-COVID experience mental health symptoms, including depression, anxiety, and stress, which remain prevalent even two years post-infection despite a slight decreasing trend. Factors such as female gender and younger age were linked to higher rates of anxiety and depression. These findings indicate the need for ongoing mental health screening and early interventions to mitigate long-term psychological distress in long-COVID patients.

Brief Outpatient Rehabilitation Program for Post-COVID-19 Condition: A Randomized Clinical Trial

Importance

Post-COVID-19 condition (PCC) is emerging as a common and debilitating condition with few treatment options.

Objective

To assess the effectiveness of a brief outpatient rehabilitation program based on a cognitive and behavioral approach for patients with PCC.

Design, Setting, and Participants

Patients with mild to moderate PCC were randomized 1:1 to an established transdiagnostic rehabilitation program or care as usual at a single referral center recruiting from the region of the South-Eastern Norway Regional Health Authority. Participants were followed up after treatment completion and 12 months after enrollment using participant-reported outcome measures. Data were collected from February 22, 2022, until April 15, 2024. Intention-to-treat analysis was performed.

Intervention

The program consisted of 2 to 8 outpatient encounters with approximately 2 to 6 weeks between each encounter. The intervention was theoretically grounded in the cognitive activation theory of stress, and physicians and physiotherapists were trained in cognitive and behavioral approaches with targeted negative stimuli and response outcome expectancies being particularly important.

Main Outcomes and Measures

Participant-reported physical function assessed by the Short-Form Health Survey 36 Physical Function Subscale (SF-36-PFS) served as the primary outcome. Secondary outcome measures were the remaining subscales of the SF-36, return to work self-efficacy and symptom scores on fatigue, postexertional malaise, breathlessness, cognitive difficulties, sleep problems, anxiety and depression symptoms, and smell and taste abnormalities. Safety measures included primary health care contacts; hospital admissions; initiation of pharmacologic and/or nonpharmacologic therapy; occurrence of novel disease, illness, or other health problems; worsening of selected key symptoms; working abilities; and thoughts of suicide.

Results

A total of 473 patients with mild to moderate PCC were assessed for eligibility (n = 364 physician referred; n = 109 self-referred); 314 were included (225 females [72%]; mean [SD] age, 43 [12] years) and 231 completed the primary end point evaluation. The SF-36-PFS scores improved statistically and clinically significantly in the intervention group (score difference between groups, 9.2; 95% CI, 4.3-14.2; P < .001; Cohen d = 0.43; intention-to-treat analysis). The effect was sustained over time. Most secondary and safety measures favored the intervention.

Conclusions and Relevance

In this randomized clinical trial, a brief outpatient rehabilitation program with a cognitive and behavioral approach in patients with PCC was effective and safe. This trial adds to the evidence supporting such interventions in routine clinical care. Future research should investigate which elements of this approach are the most effective and identify subgroups for which the current treatment is most relevant.

Trial Registration

ClinicalTrials.gov Identifier: NCT05196451.

Association between food insecurity and long COVID in adults from southern Brazil: findings of the PAMPA cohort

BACKGROUND

Social and economic factors, such as food insecurity, contribute to long coronavirus disease (COVID). During the pandemic, a significant rise in food insecurity was observed, both in Brazil and worldwide. We aimed to investigate the association between food insecurity and long COVID in Brazilian adults.

METHODS

Cross-sectional study nested within the Prospective study About Mental and Physical Health in Adults (PAMPA) Cohort. Participants completed an online questionnaire in June 2022. We assessed food insecurity using the Brazilian Scale of Food Insecurity. Long COVID was defined as any post-coronavirus disease 2019 symptoms that persisted for at least 3 months after infection.

RESULTS

A total of 956 participants were included (74.0% female, median age 36 (Interquartile Range [IQR] (29-45.7). The prevalence of food insecurity was 29.4%, and 77.8% had long COVID. Food insecurity was associated with an increased probability of long COVID (prevalence ratio [PR]: 1.15, 95% confidence interval [CI]: 1.08-1.22). Participants in food insecurity situations had a higher likelihood of experiencing neurological (PR: 1.19, 95% CI: 1.10-1.28), pulmonary (PR: 1.33, 95% CI: 1.17-1.52) and gastrointestinal (PR: 1.57, 95% CI: 1.31-1.88) symptoms after infection.

CONCLUSIONS

Food insecurity was associated with long COVID. Governments must plan public policies to mitigate the effects of long COVID and food insecurity.

Long COVID: plasma levels of neurofilament light chain in mild COVID-19 patients with neurocognitive symptoms

It is well known the potential of severe acute respiratory coronavirus type 2 (SARS-CoV-2) infection to induce post-acute sequelae, a condition called Long COVID. This syndrome includes several symptoms, but the central nervous system (CNS) main one is neurocognitive dysfunction. Recently it has been demonstrated the relevance of plasma levels of neurofilament light chain (pNfL), as a biomarker of early involvement of the CNS in COVID-19. The aim of this study was to investigate the relationship between pNfL in patients with post-acute neurocognitive symptoms and the potential of NfL as a prognostic biomarker in these cases. A group of 63 long COVID patients ranging from 18 to 59 years-old were evaluated, submitted to a neurocognitive battery assessment, and subdivided in different groups, according to results. Plasma samples were collected during the long COVID assessment and used for measurement of pNfL with the Single molecule array (SIMOA) assays. Levels of pNfL were significantly higher in long COVID patients with neurocognitive symptoms when compared to HC (p = 0.0031). Long COVID patients with cognitive impairment and fatigue symptoms presented higher pNfL levels when compared to long COVID patients without these symptoms, individually and combined (p = 0.0263, p = 0.0480, and 0.0142, respectively). Correlation analysis showed that levels of cognitive lost and exacerbation of fatigue in the neurocognitive evaluation had a significative correlation with higher pNfL levels (p = 0.0219 and 0.0255, respectively). Previous reports suggested that pNfL levels are related with higher risk of severity and predict lethality of COVID-19. Our findings demonstrate that SARS-CoV-2 infection seems to have a long-term impact on the brain, even in patients who presented mild acute disease. NfL measurements might be useful to identify CNS involvement in long COVID associated with neurocognitive symptoms and to identify who will need continuous monitoring and treatment support.

Clusters of long COVID among patients hospitalized for COVID-19 in New York City

BACKGROUND

Recent studies have demonstrated that individuals hospitalized due to COVID-19 can be affected by "long-COVID" symptoms for as long as one year after discharge.

OBJECTIVES

Our study objective is to identify data-driven clusters of patients using a novel, unsupervised machine learning technique.

METHODS

The study uses data from 437 patients hospitalized in New York City between March 3rd and May 15th of 2020. The data used was abstracted from medical records and collected from a follow-up survey for up to one-year post-hospitalization. Hospitalization data included demographics, comorbidities, and in-hospital complications. The survey collected long-COVID symptoms, and information on general health, social isolation, and loneliness. To perform the analysis, we created a graph by projecting the data onto eight principal components (PCs) and running the K-nearest neighbors algorithm. We then used Louvain's algorithm to partition this graph into non-overlapping clusters.

RESULTS

The cluster analysis produced four clusters with distinct health and social connectivity patterns. The first cluster (n = 141) consisted of patients with both long-COVID neurological symptoms (74%) and social isolation/loneliness. The second cluster (n = 137) consisted of healthy patients who were also more socially connected and not lonely. The third cluster (n = 96) contained patients with neurological symptoms who were socially connected but lonely, and the fourth cluster (n = 63) consisted entirely of patients who had traumatic COVID hospitalization, were intubated, suffered symptoms, but were socially connected and experienced recovery.

CONCLUSION

The cluster analysis identified social isolation and loneliness as important features associated with long-COVID symptoms and recovery after hospitalization. It also confirms that social isolation and loneliness, though connected, are not necessarily the same. Physicians need to be aware of how social characteristics relate to long-COVID and patient's ability to cope with the resulting symptoms.

Immunobiology of COVID-19: Mechanistic and therapeutic insights from animal models

The distribution of the immune system throughout the body complicates in vitro assessments of coronavirus disease 2019 (COVID-19) immunobiology, often resulting in a lack of reproducibility when extrapolated to the whole organism. Consequently, developing animal models is imperative for a comprehensive understanding of the pathology and immunology of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. This review summarizes current progress related to COVID-19 animal models, including non-human primates (NHPs), mice, and hamsters, with a focus on their roles in exploring the mechanisms of immunopathology, immune protection, and long-term effects of SARS-CoV-2 infection, as well as their application in immunoprevention and immunotherapy of SARS-CoV-2 infection. Differences among these animal models and their specific applications are also highlighted, as no single model can fully encapsulate all aspects of COVID-19. To effectively address the challenges posed by COVID-19, it is essential to select appropriate animal models that can accurately replicate both fatal and non-fatal infections with varying courses and severities. Optimizing animal model libraries and associated research tools is key to resolving the global COVID-19 pandemic, serving as a robust resource for future emerging infectious diseases.

Chronic post-COVID neuropsychiatric symptoms persisting beyond one year from infection: a case-control study and network analysis

Our study aims to delineate the phenotypes of chronic neuropsychiatric symptoms among adult subjects recovering from their first COVID that occurred more than one year ago. We also aim to explore the clinical and socioeconomic risk factors of having a high loading of chronic neuropsychiatric symptoms. We recruited a post-COVID group who suffered from their first pre-Omicron COVID more than a year ago, and a control group who had never had COVID. The subjects completed app-based questionnaires on demographic, socioeconomic and health status, a COVID symptoms checklist, mental and sleep health measures, and neurocognitive tests. The post-COVID group has a statistically significantly higher level of fatigue compared to the control group (p < 0.001). Among the post-COVID group, the lack of any COVID vaccination before the first COVID and a higher level of material deprivation before the COVID pandemic predicts a higher load of chronic post-COVID neuropsychiatric symptoms. Partial correlation network analysis suggests that the chronic post-COVID neuropsychiatric symptoms can be clustered into two major (cognitive complaints -fatigue and anxiety-depression) and one minor (headache-dizziness) cluster. A higher level of material deprivation predicts a higher number of symptoms in both major clusters, but the lack of any COVID vaccination before the first COVID only predicts a higher number of symptoms in the cognitive complaints-fatigue cluster. Our result suggests heterogeneity among chronic post-COVID neuropsychiatric symptoms, which are associated with the complex interplay of biological and socioeconomic factors.

Outcome predictors of post-COVID conditions in the European Academy of Neurology COVID-19 registry

Several neurological manifestations are part of the post-COVID condition. We aimed to: (1) evaluate the 6-month outcome in the cohort of patients with neurological manifestations during the COVID-19 acute phase and surviving the infection, and find outcome predictors; (2) define the prevalence and type of neurological symptoms persistent at six months after the infection. Data source was an international registry of patients with COVID-19 infection and neurological symptoms, signs or diagnoses established by the European Academy of Neurology. Functional status at six-month follow-up was measured with the modified Rankin scale (mRS), and defined as: "stable/improved" if the mRS at six months was equal as or lower than the baseline score; "worse" if it was higher than the baseline score. By October 30, 2022, 1,003 lab-confirmed COVID-19 patients were followed up for a median of 6.5 months. Compared to their pre-morbid status, 522 patients (52%) were stable/improved, whereas 465 (46%) were worse (functional status missing for 16). Age, hospitalization, several pre-COVID-19 comorbidities, and COVID-19 general complications were predictors of a worse status. Amongst neurological manifestations, stroke carried the highest risk for worse outcome (OR 5.96), followed by hyperactive delirium (2.8), and peripheral neuropathies (2.37). On the other hand, hyposmia/hypogeusia (0.38), headache (0.40), myalgia (0.45), and COVID-19 vaccination (0.52) were predictors of a favourable prognosis. Persisting neurological symptoms or signs were reported by 316/1003 patients (31.5%), the commonest being fatigue (n = 133), and impaired memory or concentration (n = 103). Our study identified significant long-term prognostic predictors in patients with COVID-19 and neurological manifestations.

Changes in prevalence of anxiety and depression among COVID-19 patients during a two-year recovery period: A systematic review and meta-analysis

OBJECTIVE

To analyze the temporal trend of anxiety and depression prevalences up to 2 years of follow-up for COVID-19 patients during the recovery period and to compare regional differences.

METHODS

We performed a systematic review from PubMed, Embase, Web of Science, CNKI, Wanfang, and VIP using keywords such as "COVID-19", "anxiety", "depression", and "cohort study". Meta-analysis was performed to estimate the pooled prevalence of anxiety and depression at five follow-up time intervals. Subgroup analyses were conducted by different regions.

RESULTS

34 cohort studies were included in the meta-analyses. The pooled anxiety prevalence rates at 0-1 month, 1-3 months, 3-6 months, 6-12 months and 12-24 months were 18% (95% CI: 11% to 28%), 18% (95% CI: 12% to 28%), 22% (95% CI: 16% to 29%), 15% (95% CI: 11% to 21%), and 10% (95% CI: 0.05% to 20%), respectively, and the pooled depression prevalence rates were 22% (95%CI: 15% to 33%), 19% (95% CI: 13% to 29%), 21% (95% CI: 15% to 28%), 15% (95% CI: 11% to 20%), and 9% (95% CI: 0.4% to 21%) respectively. The prevalence of depression in Asian and non-Asian countries was statistically different at 0-1 month (χ2 = 15.248, P < 0.001) and 1-3 months (χ2 = 28.298, P < 0.001), and prevalence of anxiety was statistically different at 3-6 months (χ2 = 9.986, P = 0.002) and 6-12 months (χ2 = 7.378, P = 0.007).

CONCLUSION

The prevalence of anxiety and depression in COVID-19 patients generally tends to decrease after 2 years of recovery, but may temporarily increase at 3-6 months. There are regional differences in the changes in prevalence of anxiety and depression.

The global prevalence of depression, anxiety, and sleep disorder among patients coping with Post COVID-19 syndrome (long COVID): a systematic review and meta-analysis

BACKGROUND

Post COVID-19 syndrome, also known as "Long COVID," is a complex and multifaceted condition that affects individuals who have recovered from SARS-CoV-2 infection. This systematic review and meta-analysis aim to comprehensively assess the global prevalence of depression, anxiety, and sleep disorder in individuals coping with Post COVID-19 syndrome.

METHODS

A rigorous search of electronic databases was conducted to identify original studies until 24 January 2023. The inclusion criteria comprised studies employing previously validated assessment tools for depression, anxiety, and sleep disorders, reporting prevalence rates, and encompassing patients of all age groups and geographical regions for subgroup analysis Random effects model was utilized for the meta-analysis. Meta-regression analysis was done.

RESULTS

The pooled prevalence of depression and anxiety among patients coping with Post COVID-19 syndrome was estimated to be 23% (95% CI: 20%-26%; I2 = 99.9%) based on data from 143 studies with 7,782,124 participants and 132 studies with 9,320,687 participants, respectively. The pooled prevalence of sleep disorder among these patients, derived from 27 studies with 15,362 participants, was estimated to be 45% (95% CI: 37%-53%; I2 = 98.7%). Subgroup analyses based on geographical regions and assessment scales revealed significant variations in prevalence rates. Meta-regression analysis showed significant correlations between the prevalence and total sample size of studies, the age of participants, and the percentage of male participants. Publication bias was assessed using Doi plot visualization and the Peters test, revealing a potential source of publication bias for depression (p = 0.0085) and sleep disorder (p = 0.02). However, no evidence of publication bias was found for anxiety (p = 0.11).

CONCLUSION

This systematic review and meta-analysis demonstrate a considerable burden of mental health issues, including depression, anxiety, and sleep disorders, among individuals recovering from COVID-19. The findings emphasize the need for comprehensive mental health support and tailored interventions for patients experiencing persistent symptoms after COVID-19 recovery.

Sociolocation: A Proposed Conceptual Element in Lifespan Development

Individual identity as a function of human development significantly intersects with and is necessarily influenced by the social world. To describe this intersection and its effects, the term sociolocation was proposed, initially in the context of adolescent development, and defined as "self-identification and recognition of social integration through relationships." Almost a decade later, it is apparent that the processes of sociolocation may continue and repeat through the rest of the lifespan. The purpose of this, therefore, paper is to present an expanded definitional and conceptual analysis of sociolocation using the techniques described by Chinn, Kramer, and Sitzman. Such an analysis is important across nursing science, practice, and education, since in all three domains the nurse may encounter individuals engaged in sociolocation. Understanding what this process is and when and how it may occur can be helpful in care planning, learning, and research endeavors.

How do the Social Determinants of Health Impact the Post-Acute Sequelae of COVID-19: A Critical Review

The review critically analyzes the social determinants of health (SDOH) variables in the current literature of patients with post-acute sequelae (PASC) of COVID-19 in the United States. Race, gender, and age were discussed as well as health outcomes, severity of illness, and phenotypes of long-COVID. Most research was retrospectively with samples that had access to health insurance, which did not capture populations with poor or no access to health care. More research is needed that directly addresses the impact on SDOH on PASC. The current literature is sparse and provides little actionable information.

Mechanisms of long COVID: An updated review

The coronavirus disease 2019 (COVID-19) pandemic has been ongoing for more than 3 years, with an enormous impact on global health and economies. In some patients, symptoms and signs may remain after recovery from severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection, which cannot be explained by an alternate diagnosis; this condition has been defined as long COVID. Long COVID may exist in patients with both mild and severe disease and is prevalent after infection with different SARS-CoV-2 variants. The most common symptoms include fatigue, dyspnea, and other symptoms involving multiple organs. Vaccination results in lower rates of long COVID. To date, the mechanisms of long COVID remain unclear. In this narrative review, we summarized the clinical presentations and current evidence regarding the pathogenesis of long COVID.

Evaluation and treatment approaches for neurological post-acute sequelae of COVID-19: A consensus statement and scoping review from the global COVID-19 neuro research coalition

Post-acute neurological sequelae of COVID-19 affect millions of people worldwide, yet little data is available to guide treatment strategies for the most common symptoms. We conducted a scoping review of PubMed/Medline from 1/1/2020-4/1/2023 to identify studies addressing diagnosis and treatment of the most common post-acute neurological sequelae of COVID-19 including: cognitive impairment, sleep disorders, headache, dizziness/lightheadedness, fatigue, weakness, numbness/pain, anxiety, depression and post-traumatic stress disorder. Utilizing the available literature and international disease-specific society guidelines, we constructed symptom-based differential diagnoses, evaluation and management paradigms. This pragmatic, evidence-based consensus document may serve as a guide for a holistic approach to post-COVID neurological care and will complement future clinical trials by outlining best practices in the evaluation and treatment of post-acute neurological signs/symptoms.

Global prevalence of post-COVID-19 sleep disturbances in adults at different follow-up time points: A systematic review and meta-analysis

Our systematic review and meta-analysis estimated the prevalence of post-COVID sleep disturbances in adult population. We systematically searched relevant studies from four databases that reported post-COVID sleep disturbances prevalence with a mean or median follow-up duration of ≥28 days. We identified 153 eligible papers, with a total COVID-19 population of 252437. Employing multilevel mixed-effects meta-analyses, we estimated the overall pooled prevalence of post-COVID sleep disturbances being 28.98% (25.73-32.34), with the highest prevalence reported in Europe and the lowest in Southeast Asia. Poor sleep quality was the most prevalent definition of sleep disturbances, followed by excessive daytime sleepiness, insomnia, sleep apnea. Prevalence estimates were notably higher when measured with Epworth sleepiness scale, or Pittsburgh sleep quality index compared to symptom questionnaires, self-reports, or personal interviews. Female sex (Odds ratio, OR = 1.59, 1.38-1.83) and severe/critical acute COVID-19 (OR = 1.36, 1.09-1.69) emerged as substantial risk factors. Our review underscore the persistent prevalence of sleep disturbances among COVID-19 survivors, and the importance of factors such as geography, definition, measures of sleep disorders, sex, and severity of acute COVID-19 infection. These findings highlight the urgent need for further investigation into the underlying molecular mechanisms driving these sleep disturbances to develop effective therapeutic strategies.

Long COVID as a functional somatic symptom disorder caused by abnormally precise prior expectations during Bayesian perceptual processing: A new hypothesis and implications for pandemic response

This review proposes a model of Long-COVID where the constellation of symptoms are in fact genuinely experienced persistent physical symptoms that are usually functional in nature and therefore potentially reversible, that is, Long-COVID is a somatic symptom disorder. First, we describe what is currently known about Long-COVID in children and adults. Second, we examine reported "Long-Pandemic" effects that create a risk for similar somatic symptoms to develop in non-COVID-19 patients. Third, we describe what was known about somatization and somatic symptom disorder before the COVID-19 pandemic, and suggest that by analogy, Long-COVID may best be conceptualized as one of these disorders, with similar symptoms and predisposing, precipitating, and perpetuating factors. Fourth, we review the phenomenon of mass sociogenic (functional) illness, and the concept of nocebo effects, and suggest that by analogy, Long-COVID is compatible with these descriptions. Fifth, we describe the current theoretical model of the mechanism underlying functional disorders, the Bayesian predictive coding model for perception. This model accounts for moderators that can make symptom inferences functionally inaccurate and therefore can explain how to understand common predisposing, precipitating, and perpetuating factors. Finally, we discuss the implications of this framework for improved public health messaging during a pandemic, with recommendations for the management of Long-COVID symptoms in healthcare systems. We argue that the current public health approach has induced fear of Long-COVID in the population, including from constant messaging about disabling symptoms of Long-COVID and theorizing irreversible tissue damage as the cause of Long-COVID. This has created a self-fulfilling prophecy by inducing the very predisposing, precipitating, and perpetuating factors for the syndrome. Finally, we introduce the term "Pandemic-Response Syndrome" to describe what previously was labeled Long-COVID. This alternative perspective aims to stimulate research and serve as a lesson learned to avoid a repeat performance in the future.

Long-Term Consequences of COVID-19: A 1-Year Analysis

Long-lasting symptoms after SARS-CoV-2 infection have been described many times in the literature and are referred to as Long COVID. In this prospective, longitudinal, monocentric, observational study, we collected the health complaints of 474 patients (252 ambulatory and 222 hospitalized) at Lausanne University Hospital 1 year after COVID-19 diagnosis. Using a self-reported health survey, we explored cardiopulmonary, vascular, neurological, and psychological complaints. Our results show that age, Charlson comorbidity index, and smoking habits were associated with hospital admission. Regarding the vascular system, we found that having had thromboembolism before SARS-CoV-2 infection was significantly associated with a higher risk of recurrence of thromboembolism at 1 year. In the neurologic evaluation, the most frequent symptom was fatigue, which was observed in 87.5% of patients, followed by “feeling slowed down”, headache, and smell disturbance in 71.5%, 68.5%, and 60.7% of cases, respectively. Finally, our cohort subjects scored higher overall in the STAI, CESD, Maastricht, and PSQI scores (which measure anxiety, depression, fatigue, and sleep, respectively) than the healthy population. Using cluster analysis, we identified two phenotypes of patients prone to developing Long COVID. At baseline, CCS score, prior chronic disease, stroke, and atrial fibrillation were associated with Long COVID. During COVID infection, mechanical ventilation and five neurological complaints were also associated with Long COVID. In conclusion, this study confirms the wide range of symptoms developed after COVID with the involvement of all the major systems. Early identification of risk factors associated with the development of Long COVID could improve patient follow-up; nevertheless, the low specificity of these factors remains a challenge to building a systematic approach.

Racial, ethnic, and sex disparities in the incidence and cognitive symptomology of long COVID-19

BACKGROUND

The pandemic has highlighted and exacerbated health inequities in both acute coronavirus disease 2019 (COVID-19) and its longer-term sequelae. Given the heterogeneity in definitions of long COVID and the lack of centralized registries of patients with the disease, little is known about the differential prevalence among racial, ethnic, and sex subgroups. This study examines long COVID among Black, White, Asian, and Hispanic Americans and evaluates differences in the associated cognitive symptomology.

METHOD

Data from four releases of the Census Bureau's Household Pulse Survey detailing COVID-19 incidence and the duration and type of symptoms among a nationally representative sample of adults from June 1, 2022, through October 17, 2022, were combined. Binary logistic regression assessed the relative likelihood of long COVID among those who had been diagnosed COVID between racial, ethnic, and sex subgroups. Among those reporting long COVID, differences in the prevalence of difficulty understanding and difficulty remembering were assessed. Empirical models accounted for household, regional, vaccination, and insurance differences between respondents. Two-stage selection models were applied to test the robustness of the results.

RESULTS

Among respondents who tested positive for COVID-19, Blacks (OR=1.097, CI=1.034-1.163), females (OR=1.849, CI=1.794-1.907), and Hispanics (OR=1.349, CI=1.286-1.414) were more likely to experience long COVID (symptoms lasting for 3 months or longer) compared to Whites, males, and non-Hispanics respectively. However, those with private health insurance (OR=0.634, CI=0.611-0.658) and who received the COVID vaccine (OR=0.901, CI=0.864-0.94) were less likely to have endured COVID symptoms than their counterparts. Symptoms of long COVID varied significantly between population subgroups. Compared to Whites, Blacks were more likely to have trouble remembering (OR=1.878, CI=1.765-1.808) while Hispanics were more likely to report difficult understanding (OR=1.827, CI=1.413, 2.362). Females, compared to males, were less likely to experience trouble understanding (OR=0.664, CI=0.537, 0.821), but more likely to report trouble remembering (OR=1.34, CI=1.237, 1.451).

CONCLUSIONS

Long COVID is more prevalent among Blacks, Hispanics, and females, but each group appears to experience long COVID differently. Therefore, additional research is needed to determine the best method to treat and manage this poorly understood condition.