Development of New Mental and Physical Health Sequelae among US Veterans after COVID-19

Cardiovascular diseases as risk factors of post-COVID syndrome: a systematic review

BACKGROUND

A growing proportion of people experience incomplete recovery months after contracting coronavirus disease 2019 (COVID-19). These COVID-19 survivors develop a condition known as post-COVID syndrome (PCS), where COVID-19 symptoms persist for > 12 weeks after acute infection. Limited studies have investigated PCS risk factors that notably include pre-existing cardiovascular diseases (CVD), which should be examined considering the most recent PCS data. This review aims to identify CVD as a risk factor for PCS development in COVID-19 survivors.

METHODS

Following the Preferred Reporting Items for Systematic Review and Meta-Analyses (PRISMA) checklist, systematic literature searches were performed in the PubMed, Scopus, and Web of Science databases from the earliest date available to June 2023. Data from observational studies in English that described the association between CVD and PCS in adults (≥ 18 years old) were included. A minimum of two authors independently performed the screening, study selection, data extraction, data synthesis, and quality assessment (Newcastle-Ottawa Scale). The protocol of this review was registered under PROSPERO (ID: CRD42023440834).

RESULTS

In total, 594 studies were screened after duplicates and non-original articles had been removed. Of the 11 included studies, CVD including hypertension (six studies), heart failure (three studies), and others (two studies) were significantly associated with PCS development with different factors considered. The included studies were of moderate to high methodological quality.

CONCLUSION

Our review highlighted that COVID-19 survivors with pre-existing CVD have a significantly greater risk of developing PCS symptomology than survivors without pre-existing CVD. As heart failure, hypertension and other CVD are associated with a higher risk of developing PCS, comprehensive screening and thorough examinations are essential to minimise the impact of PCS and improve patients' disease progression.

Evaluation of Neuropsychiatric outcomes in patients hospitalized with COVID-19 in a nationwide Veterans Health Administration cohort

Hospitalized patients with COVID-19 have an increased risk of developing psychiatric symptoms associated with post-COVID-19 syndrome. We aimed to evaluate the impact of COVID-19 hospitalization on neuropsychiatric healthcare utilization as well as new-onset depression and dementia. This nationwide, retrospective, observational cohort study included hospitalized COVID-19 patients aged 18 years or older across the Veterans Health Administration database from January 1st, 2020 through January 1st, 2022. The COVID-19 group consisted of patients hospitalized with COVID-19 with a positive test within seven days of the hospitalization. The control group consisted of patients hospitalized for reasons other than COVID-19 without a prior positive test or during the study duration. Propensity scores were utilized for 1:1 matching. This study included 50,805 patients in each matched cohort. Average patient population was 69 years old with ∼93 % male. The primary outcome of psychiatry-related hospitalization incidence rates were significantly higher in the COVID-19 group at both 90 days and 180 days. There was also a significant increase in the incidence outpatient mental health visits at 180 days in the COVID-19 cohort. Significantly higher risk of new-onset depression and new-onset dementia in the COVID-19 hospitalization group at 180 days as compared to the non-COVID-19 cohort was noted.

Impact of SARS-CoV-2 Infection on Long-Term Depression Symptoms among Veterans

BACKGROUND

Prior research demonstrates that SARS-COV-2 infection can be associated with a broad range of mental health outcomes including depression symptoms. Veterans, in particular, may be at elevated risk of increased depression following SARS-COV-2 infection given their high rates of pre-existing mental and physical health comorbidities. However, few studies have tried to isolate SARS-COV-2 infection associations with long term, patient-reported depression symptoms from other factors (e.g., physical health comorbidities, pandemic-related stress).

OBJECTIVE

To evaluate the association between SARS-COV-2 infection and subsequent depression symptoms among United States Military Veterans.

DESIGN

Survey-based non-randomized cohort study with matched comparators.

PARTICIPANTS

A matched-dyadic sample from a larger, stratified random sample of participants with and without known to SARS-COV-2 infection were invited to participate in a survey evaluating mental health and wellness 18-months after their index infection date. Sampled participants were stratified by infection severity of the participant infected with SARS-COV-2 (hospitalized or not) and by month of index date. A total of 186 participants in each group agreed to participate in the survey and had sufficient data for inclusion in analyses. Those in the uninfected group who were later infected were excluded from analyses.

MAIN MEASURES

Participants were administered the Patient Health Questionnaire-9 as part of a phone interview survey. Demographics, physical and mental health comorbidities were extracted from VHA administrative data.

KEY RESULTS

Veterans infected with SARS-COV-2 had significantly higher depression symptoms scores compared with those uninfected. In particular, psychological symptoms (e.g., low mood, suicidal ideation) scores were elevated relative to the comparator group (MInfected = 3.16, 95%CI: 2.5, 3.8; MUninfected = 1.96, 95%CI: 1.4, 2.5). Findings were similar regardless of history of depression.

CONCLUSION

SARS-COV-2 infection was associated with more depression symptoms among Veterans at 18-months post-infection. Routine evaluation of depression symptoms over time following SARS-COV-2 infection is important to facilitate adequate assessment and treatment.

The prevalence and risk of depression in aged COVID-19 survivors: a bibliometric and meta-analysis

To explore depression prevalence and related risk factors among elderly coronavirus disease 2019 (COVID-19) survivors, while also evaluating research characteristics. We searched Web of Science, PubMed, Embase, Scopus, CNKI and Wanfang Data for studies that reported COVID-19 and depression in older adults. 'Bibliometrix' facilitated bibliometric analysis and information visualisation. Random-effects models merged depression prevalence and relevant risks. Publication bias and its impact were examined using funnel plots, Begg's test, Egger's linear regression, and trim-and-fill method. Meta-regression, bubble plots, and Baujat plots probed heterogeneity. Sensitivity analysis applied the leave-one-out method. The study is registered with PROSPERO, CRD42023417706. The bibliometric analysis comprised 138 studies. Publication frequency peaked in the US, China, and Italy, reflecting significant growth. The meta-analysis comprised 43 studies. Elderly COVID-19 patients exhibit 28.33% depression prevalence (95% CI: 21.24-35.97). Severe cases (43.91%, 95% CI: 32.28-55.88) experienced higher depression prevalence than mild cases (16.45%, 95% CI: 11.92-21.50). Sex had no depression prevalence impact based on bubble plots. Notably, depression risk did not significantly differ between elderly and young COVID-19 patients (odds ratio (OR) = 1.1808, 95% CI: 0.7323-1.9038). However, COVID-19 infection emerged as a substantial elderly depression risk factor (OR = 1.8521, 95% CI: 1.2877-2.6639). Sensitivity analysis confirmed result robustness. Elderly COVID-19 survivors are likely to develop depression symptoms with regional variations. Severe cases are associated with heightened depression prevalence. COVID-19 infection stands out as a key elderly depression risk factor, while sex does not influence prevalence. The field's expansion necessitates sustained collaboration and extensive research endeavours.

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.

Incidence and individual risk prediction of post-COVID-19 cardiovascular disease in the general population: a multivariable prediction model development and validation study

Aims

Previous studies suggest relatively increased cardiovascular risk after COVID-19 infection. This study assessed incidence and explored individual risk and timing of cardiovascular disease occurring post-COVID-19 in a large primary care database.

Methods and results

Data were extracted from the UK's Clinical Practice Research Datalink. Incidence rates within 180 days post-infection were estimated for arterial or venous events, inflammatory heart disease, and new-onset atrial fibrillation or heart failure. Next, multivariable logistic regression models were developed on 220 751 adults with COVID-19 infection before 1 December 2020 using age, sex and traditional cardiovascular risk factors. All models were externally validated in (i) 138 034 vaccinated and (ii) 503 404 unvaccinated adults with a first COVID-19 infection after 1 December 2020. Discriminative performance and calibration were evaluated with internal and external validation. Increased incidence rates were observed up to 60 days after COVID-19 infection for venous and arterial cardiovascular events and new-onset atrial fibrillation, but not for inflammatory heart disease or heart failure, with the highest rate for venous events (13 per 1000 person-years). The best prediction models had c-statistics of 0.90 or higher. However, <5% of adults had a predicted 180-day outcome-specific risk larger than 1%. These rare outcomes complicated calibration.

Conclusion

Risks of arterial and venous cardiovascular events and new-onset atrial fibrillation are increased within the first 60 days after COVID-19 infection in the general population. Models' c-statistics suggest high discrimination, but because of the very low absolute risks, they are insufficient to inform individual risk management.

Long-term neurological outcome after COVID-19 using all SARS-CoV-2 test results and hospitalisations in Denmark with 22-month follow-up

Hospitalisation with COVID-19 is associated with an increased risk of neurological sequelae; however, representative nationwide studies comparing to other infections with similar severity and also including milder SARS-CoV-2 infections have been lacking. Using the nationwide Danish registers including all SARS-CoV-2 PCR test results and hospitalisations between March 1, 2020, and December 31, 2021, we estimate the risk of any first neurological disorder diagnosed in inpatient, outpatient, or emergency room settings. We show that positive tests increase the rate of neurological disorders by a hazard ratio of 1.96 (95% confidence interval: 1.88-2.05) compared to individuals not tested and by a hazard ratio of 1.11 (95% confidence interval: 1.07-1.16) compared to individuals with negative tests only. However, there is no evidence that the risk of neurological disorders is higher for individuals who test positive compared to non-COVID-19 infections treated with anti-infective medication. The risk of neurological disorders is increased after COVID-19-hospitalisation compared to no COVID-19 hospital admission; however, these risks are comparable to hospitalisation with other respiratory infections (P value 0.328). In conclusion, COVID-19 is associated with an increased risk of neurological disorders, but no more than that observed after other infections of similar severity.