Collider bias undermines our understanding of COVID-19 disease risk and severity

Effectiveness and durability of mRNA-1273 BA.4/BA.5 bivalent vaccine (mRNA-1273.222) against SARS-CoV-2 BA.4/BA.5 and XBB sublineages

Emerging SARS-CoV-2 sublineages continue to cause serious COVID-19 disease, but most individuals have not received any COVID-19 vaccine for >1 year. Assessment of long-term effectiveness of bivalent COVID-19 vaccines against circulating sublineages is important to inform the potential need for vaccination with updated vaccines. In this test-negative study at Kaiser Permanente Southern California, sequencing-confirmed BA.4/BA.5- or XBB-related SARS-CoV-2-positive cases (September 1, 2022 to June 30, 2023), were matched 1:3 to SARS-CoV-2-negative controls. We assessed mRNA-1273 bivalent relative (rVE) and absolute vaccine effectiveness (VE) compared to ≥2 or 0 doses of original monovalent vaccine, respectively. The rVE analysis included 20,966 cases and 62,898 controls. rVE (95%CI) against BA.4/BA.5 at 14-60 days and 121-180 days was 52.7% (46.9-57.8%) and 35.5% (-2.8-59.5%) for infection, and 59.3% (49.7-67.0%) and 33.2% (-28.2-68.0%) for Emergency Department/Urgent Care (ED/UC) encounters. For BA.4/BA.5-related hospitalizations, rVE was 71.3% (44.9-85.1%) and 52.0% (-1.2-77.3%) at 14-60 days and 61-120 days, respectively. rVE against XBB at 14-60 days and 121-180 days was 48.8% (33.4-60.7%) and -3.9% (-18.1-11.3%) for infection, 70.7% (52.4-82.0%) and 15.7% (-6.0-33.2%) for ED/UC encounters, and 87.9% (43.8-97.4%) and 57.1% (17.0-77.8%) for hospitalization. VE and subgroup analyses (age, immunocompromised status, previous SARS-CoV-2 infection) results were similar to rVE analyses. rVE of mRNA-1273 bivalent vaccine against BA.4/BA.5 and XBB infections, ED/UC encounters, and hospitalizations waned over time. Periodic revaccination with vaccines targeting emerging variants may be important in reducing COVID-19 morbidity and mortality.

Slaveholder ancestry and current net worth of members of the United States Congress

BACKGROUND

Whether and how much past slavery affects contemporary social and economic conditions in the United States is an area of active debate. Newly available data on which members of the United States Congress are descendants of slaveholders provides an opportunity to examine this topic. This study sought to determine the relationship between slaveholder ancestry and net worth among members of Congress.

METHODS

Total assets and liabilities were collected from financial declarations of all members of Congress as of April 15, 2021. Net worth was estimated as the difference between total assets and liabilities. Information on slaveholder ancestry was obtained from a Reuters investigative series based on an extensive review of historical documents and verification by board-certified genealogists. Quantile regression was used to determine the association between net worth and slaveholder ancestry after adjustment for demographic factors.

RESULTS

The median net worth of the 535 members of Congress was $1.28 million (interquartile range $0.11-5.87 million). On univariate analysis, net worth was associated with increased age, White race, increased education, and number of individuals enslaved by ancestors. On multivariate analysis, net worth was independently associated with age, White race, and number enslaved. Legislators whose ancestors enslaved 16 or more individuals had a $3.93 million (95% confidence interval 2.39-5.46) higher net worth compared to legislators whose ancestors were not slave owners after adjustment for age, sex, race, ethnicity, and education.

CONCLUSIONS

Past slaveholding practices are independently associated with current wealth among members of Congress. Because members of Congress are a highly selected group, further work is needed to understand how slaveholder ancestry affects current wealth in the general population to inform efforts to reduce social and economic disparities.

Characteristics Associated With Long-Term Outcomes in Severe COVID-19 Patients After a Post-Acute Care Hospitalization: A Prospective Cohort Study

OBJECTIVES

To describe characteristics associated with long-term outcomes in severe COVID-19 patients admitted to a post-acute care facility (PACF).

DESIGN

Prospective cohort.

SETTING AND PARTICIPANTS

Consecutive severe COVID-19 admitted to a PACF from April 2020 to August 2021.

METHODS

Patients were followed for 180 days after discharge. Functional outcomes were measured by the modified Barthel index and further stratified into good outcome (for those independent, mildly dependent, or moderately dependent) and into bad outcome (for those severely dependent, completely dependent, or dead). Multivariate binary logistic regression was performed to evaluate between patients' characteristics and long-term outcomes.

RESULTS

A total of 186 patients admitted from 17 different acute hospitals were included. Median age was 67 years, 88% of patients were previously independent, 95% were admitted to the ICU, and 85% were mechanically ventilated during the acute hospitalization. Median (interquartile range) Barthel indexes at admission, discharge, and 180-day follow-up were 9 (1-23), 81 (45-92), and 100 (98-100) (P < .001), respectively. In addition, 180-day mortality was 17.2%. Baseline functional status, comorbidities, and functional status at admission to the PACF were associated with bad outcome at 180-day follow-up, after multivariate binary logistic regression.

CONCLUSIONS AND IMPLICATIONS

Patients with severe COVID-19 admitted to a PACF had substantial functional improvements at PACF discharge and during 180-day follow-up. These findings may help prognosticate and manage post-acute severe COVID-19 patients.

Disentangling discordant vitamin D associations with prostate cancer incidence and fatality in a large, nested case-control study

BACKGROUND

Published analyses of prostate cancer nested case-control and survival data in the Alpha-Tocopherol, Beta-Carotene Cancer Prevention (ATBC) Study cohort suggested that men with higher baseline vitamin D [25(OH)D] concentrations have both (i) increased prostate cancer risk and (ii) decreased prostate cancer-specific fatality.

METHODS

To investigate possible factors responsible for a spurious association with prostate cancer fatality, we reanalysed baseline serum vitamin D associations with prostate cancer risk and prostate cancer-specific fatality in case-control data nested within the ATBC Study (1000 controls and 1000 incident prostate cancer cases). Conditional logistic regression and Cox proportion hazard models were used, respectively, to estimate odds ratios for risk and hazard ratios for prostate cancer-specific fatality, overall and by disease aggressiveness. We replicated these case-control analyses using baseline serum measurements of alpha-tocopherol (vitamin E), beta-carotene and retinol (vitamin A), and used the entire ATBC Study cohort (n = 29 085) to estimate marginal associations between these baseline vitamins and prostate cancer incidence and fatality following blood collection.

RESULTS

Vitamin D analyses agreed closely with those originally published, with opposite risk and fatality associations. By contrast, the analyses of alpha-tocopherol, beta-carotene and retinol yielded concordant associations for prostate cancer incidence and prostate cancer-specific fatality.

CONCLUSIONS

We found evidence of neither artefacts in the nested prostate cancer case-control data set nor detection or collider biases in the fatality analyses. The present findings therefore support a valid inverse (i.e. beneficial) association between vitamin D and prostate cancer-specific survival that warrants further evaluation, including possibly in controlled trials.

Impact of COVID-19 and Non-COVID-19 Hospitalized Pneumonia on Longer-Term Cardiovascular Mortality in People With Type 2 Diabetes: A Nationwide Prospective Cohort Study From Scotland

OBJECTIVE

In this study we examine whether hospitalized coronavirus disease 2019 (COVID-19) pneumonia increases long-term cardiovascular mortality more than other hospitalized pneumonias in people with type 2 diabetes and aim to quantify the relative cardiovascular disease (CVD) mortality risks associated with COVID-19 versus non-COVID-19 pneumonia.

RESEARCH DESIGN AND METHODS

With use of the SCI-Diabetes register, two cohorts were identified: individuals with type 2 diabetes in 2016 and at the 2020 pandemic onset. Hospital and death records were linked for determination of pneumonia exposure and CVD deaths. Poisson regression estimated rate ratios (RRs) for CVD death associated with both pneumonia types, with adjustment for confounders. Median follow-up durations were 1,461 days (2016 cohort) and 700 days (2020 cohort).

RESULTS

The adjusted RR for CVD death following non-COVID-19 pneumonia was 5.51 (95% CI 5.31-5.71) prepandemic and 7.3 (6.86-7.76) during the pandemic. For COVID-19 pneumonia, the RR was 9.13 (8.55-9.75). Beyond 30 days post pneumonia, the RRs converged, to 4.24 (3.90-4.60) for non-COVID-19 and 3.35 (3.00-3.74) for COVID-19 pneumonia, consistent even with exclusion of prior CVD cases.

CONCLUSIONS

Hospitalized pneumonia, irrespective of causal agent, marks an increased risk for CVD death immediately and over the long-term. COVID-19 pneumonia poses a higher CVD death risk than other pneumonias in the short-term, but this distinction diminishes over time. These insights underscore the need for including pneumonia in CVD risk assessments, with particular attention to the acute impact of COVID-19 pneumonia.

Using Genetics to Investigate Relationships between Phenotypes: Application to Endometrial Cancer

Genome-wide association studies (GWAS) have accelerated the exploration of genotype-phenotype associations, facilitating the discovery of replicable genetic markers associated with specific traits or complex diseases. This narrative review explores the statistical methodologies developed using GWAS data to investigate relationships between various phenotypes, focusing on endometrial cancer, the most prevalent gynecological malignancy in developed nations. Advancements in analytical techniques such as genetic correlation, colocalization, cross-trait locus identification, and causal inference analyses have enabled deeper exploration of associations between different phenotypes, enhancing statistical power to uncover novel genetic risk regions. These analyses have unveiled shared genetic associations between endometrial cancer and many phenotypes, enabling identification of novel endometrial cancer risk loci and furthering our understanding of risk factors and biological processes underlying this disease. The current status of research in endometrial cancer is robust; however, this review demonstrates that further opportunities exist in statistical genetics that hold promise for advancing the understanding of endometrial cancer and other complex diseases.

Associations of proton pump inhibitors with susceptibility to influenza, pneumonia, and COVID-19: Evidence from a large population-based cohort study

Background

Adverse effects of proton pump inhibitors (PPIs) have raised wide concerns. The association of PPIs with influenza is unexplored, while that with pneumonia or COVID-19 remains controversial. Our study aims to evaluate whether PPI use increases the risks of these respiratory infections.

Methods

The current study included 160,923 eligible participants at baseline who completed questionnaires on medication use, which included PPI or histamine-2 receptor antagonist (H2RA), from the UK Biobank. Cox proportional hazards regression and propensity score-matching analyses were used to estimate the hazard ratios (HRs) and 95% confidence intervals (CIs).

Results

Comparisons with H2RA users were tested. PPI use was associated with increased risks of developing influenza (HR 1.32, 95% CI 1.12-1.56) and pneumonia (hazard ratio [HR] 1.42, 95% confidence interval [CI] 1.26-1.59). In contrast, the risk of COVID-19 infection was not significant with regular PPI use (HR 1.08, 95% CI 0.99-1.17), while the risks of severe COVID-19 (HR 1.19. 95% CI 1.11-1.27) and mortality (HR 1.37. 95% CI 1.29-1.46) were increased. However, when compared with H2RA users, PPI users were associated with a higher risk of influenza (HR 1.74, 95% CI 1.19-2.54), but the risks with pneumonia or COVID-19-related outcomes were not evident.

Conclusions

PPI users are associated with increased risks of influenza, pneumonia, as well as COVID-19 severity and mortality compared to non-users, while the effects on pneumonia or COVID-19-related outcomes under PPI use were attenuated when compared to the use of H2RAs. Appropriate use of PPIs based on comprehensive evaluation is required.

Funding

This work is supported by the National Natural Science Foundation of China (82171698, 82170561, 81300279, 81741067, 82100238), the Program for High-level Foreign Expert Introduction of China (G2022030047L), the Natural Science Foundation for Distinguished Young Scholars of Guangdong Province (2021B1515020003), the Guangdong Basic and Applied Basic Research Foundation (2022A1515012081), the Foreign Distinguished Teacher Program of Guangdong Science and Technology Department (KD0120220129), the Climbing Program of Introduced Talents and High-level Hospital Construction Project of Guangdong Provincial People's Hospital (DFJH201923, DFJH201803, KJ012019099, KJ012021143, KY012021183), and in part by VA Clinical Merit and ASGE clinical research funds (FWL).

A practical introduction to holo-omics

Holo-omics refers to the joint study of non-targeted molecular data layers from host-microbiota systems or holobionts, which is increasingly employed to disentangle the complex interactions between the elements that compose them. We navigate through the generation, analysis, and integration of omics data, focusing on the commonalities and main differences to generate and analyze the various types of omics, with a special focus on optimizing data generation and integration. We advocate for careful generation and distillation of data, followed by independent exploration and analyses of the single omic layers to obtain a better understanding of the study system, before the integration of multiple omic layers in a final model is attempted. We highlight critical decision points to achieve this aim and flag the main challenges to address complex biological questions regarding the integrative study of host-microbiota relationships.

NHS national data opt-outs: trends and potential consequences for health data research

BACKGROUND

The English NHS data opt-out allows people to prevent use of their health data for purposes other than direct care. In 2021, the number of opt-outs increased in response to government-led proposals to create a centralised pseudonymised primary care record database.

AIM

To describe the potential impact of NHS national data opt-outs in 2021 on health data research.

DESIGN & SETTING

We conducted a descriptive analysis of opt-outs using publicly available data and the potential consequences on research are discussed.

METHOD

Trends in opt-outs in England were described by age, sex, and region. Using a hypothetical study, we explored statistical and epidemiological implications of opt-outs.

RESULTS

During the lead up to a key government-led deadline for registering opt-outs (from 31 May 2021-30 June 2021), 1 339 862 national data opt-outs were recorded; increasing the percentage of opt-outs in England from 2.77% to 4.97% of the population. Among females, percentage opt-outs increased by 83% (from 3.02% to 5.53%) compared with 76% in males (from 2.51% to 4.41%). Across age groups, the highest relative increase was among people aged 40-49 years, which rose from 2.89% to 6.04%. Considerable geographical variation was not clearly related to deprivation. Key research consequences of opt-outs include reductions in sample size and unpredictable distortion of observed measures of the frequency of health events or associations between these events.

CONCLUSION

Opt-out rates varied by age, sex, and place. The impact of this and variation by other characteristics on research is not quantifiable. Potential effects of opt-outs on research and consequences for health policies based on this research must be considered when creating future opt-out solutions.

Parametric g-formula for Testing Time-Varying Causal Effects: What It Is, Why It Matters, and How to Implement It in Lavaan

Psychologists leverage longitudinal designs to examine the causal effects of a focal predictor (i.e., treatment or exposure) over time. But causal inference of naturally observed time-varying treatments is complicated by treatment-dependent confounding in which earlier treatments affect confounders of later treatments. In this tutorial article, we introduce psychologists to an established solution to this problem from the causal inference literature: the parametric g-computation formula. We explain why the g-formula is effective at handling treatment-dependent confounding. We demonstrate that the parametric g-formula is conceptually intuitive, easy to implement, and well-suited for psychological research. We first clarify that the parametric g-formula essentially utilizes a series of statistical models to estimate the joint distribution of all post-treatment variables. These statistical models can be readily specified as standard multiple linear regression functions. We leverage this insight to implement the parametric g-formula using lavaan, a widely adopted R package for structural equation modeling. Moreover, we describe how the parametric g-formula may be used to estimate a marginal structural model whose causal parameters parsimoniously encode time-varying treatment effects. We hope this accessible introduction to the parametric g-formula will equip psychologists with an analytic tool to address their causal inquiries using longitudinal data.

Changes in sick notes associated with COVID-19 from 2020 to 2022: a cohort study in 24 million primary care patients in OpenSAFELY-TPP

OBJECTIVES

Long-term sickness absence from employment has negative consequences for the economy and can lead to widened health inequalities. Sick notes (also called 'fit notes') are issued by general practitioners when a person cannot work for health reasons for more than 7 days. We quantified the sick note rate in people with evidence of COVID-19 in 2020, 2021 and 2022, as an indication of the burden for people recovering from COVID-19.

DESIGN

Cohort study.

SETTING

With National Health Service (NHS) England approval, we used routine clinical data (primary care, hospital and COVID-19 testing records) within the OpenSAFELY-TPP database.

PARTICIPANTS

People 18-64 years with a recorded positive test or diagnosis of COVID-19 in 2020 (n=365 421), 2021 (n=1 206 555) or 2022 (n=1 321 313); general population matched in age, sex and region in 2019 (n=3 140 326), 2020 (n=3 439 534), 2021 (n=4 571 469) and 2022 (n=4 818 870); people hospitalised with pneumonia in 2019 (n=29 673).

PRIMARY OUTCOME MEASURE

Receipt of a sick note in primary care.

RESULTS

Among people with a positive SARS-CoV-2 test or COVID-19 diagnosis, the sick note rate was 4.88 per 100 person-months (95% CI 4.83 to 4.93) in 2020, 2.66 (95% CI 2.64 to 2.67) in 2021 and 1.73 (95% CI 1.72 to 1.73) in 2022. Compared with the age, sex and region-matched general population, the adjusted HR for receipt of a sick note over the entire follow-up period (up to 10 months) was 4.07 (95% CI 4.02 to 4.12) in 2020 decreasing to 1.57 (95% CI 1.56 to 1.58) in 2022. The HR was highest in the first 30 days postdiagnosis in all years. Among people hospitalised with COVID-19, after adjustment, the sick note rate was lower than in people hospitalised with pneumonia.

CONCLUSIONS

Given the under-recording of postacute COVID-19-related symptoms, these findings contribute a valuable perspective on the long-term effects of COVID-19. Despite likely underestimation of the sick note rate, sick notes were issued more frequently to people with COVID-19 compared with those without, even in an era when most people are vaccinated. Most sick notes occurred in the first 30 days postdiagnosis, but the increased risk several months postdiagnosis may provide further evidence of the long-term impact.

Deaths with COVID-19 and from all-causes following first-ever SARS-CoV-2 infection in individuals with preexisting mental disorders: A national cohort study from Czechia

BACKGROUND

Evidence suggests reduced survival rates following Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) infection in people with preexisting mental disorders, especially psychotic disorders, before the broad introduction of vaccines. It remains unknown whether this elevated mortality risk persisted at later phases of the pandemic and when accounting for the confounding effect of vaccination uptake and clinically recorded physical comorbidities.

METHODS AND FINDINGS

We used data from Czech national health registers to identify first-ever serologically confirmed SARS-CoV-2 infections in 5 epochs related to different phases of the pandemic: 1st March 2020 to 30th September 2020, 1st October 2020 to 26th December 2020, 27th December 2020 to 31st March 2021, 1st April 2021 to 31st October 2021, and 1st November 2021 to 29th February 2022. In these people, we ascertained cases of mental disorders using 2 approaches: (1) per the International Classification of Diseases 10th Revision (ICD-10) diagnostic codes for substance use, psychotic, affective, and anxiety disorders; and (2) per ICD-10 diagnostic codes for the above mental disorders coupled with a prescription for anxiolytics/hypnotics/sedatives, antidepressants, antipsychotics, or stimulants per the Anatomical Therapeutic Chemical (ATC) classification codes. We matched individuals with preexisting mental disorders with counterparts who had no recorded mental disorders on age, sex, month and year of infection, vaccination status, and the Charlson Comorbidity Index (CCI). We assessed deaths with Coronavirus Disease 2019 (COVID-19) and from all-causes in the time period of 28 and 60 days following the infection using stratified Cox proportional hazards models, adjusting for matching variables and additional confounders. The number of individuals in matched-cohorts ranged from 1,328 in epoch 1 to 854,079 in epoch 5. The proportion of females ranged from 34.98% in people diagnosed with substance use disorders in epoch 3 to 71.16% in individuals diagnosed and treated with anxiety disorders in epoch 5. The mean age ranged from 40.97 years (standard deviation [SD] = 15.69 years) in individuals diagnosed with substance use disorders in epoch 5 to 56.04 years (SD = 18.37 years) in people diagnosed with psychotic disorders in epoch 2. People diagnosed with or diagnosed and treated for psychotic disorders had a consistently elevated risk of dying with COVID-19 in epochs 2, 3, 4, and 5, with adjusted hazard ratios (aHRs) ranging from 1.46 [95% confidence intervals (CIs), 1.18, 1.79] to 1.93 [95% CIs, 1.12, 3.32]. This patient group demonstrated also a consistently elevated risk of all-cause mortality in epochs 2, 3, 4, and 5 (aHR from 1.43 [95% CIs, 1.23, 1.66] to 1.99 [95% CIs, 1.25, 3.16]). The models could not be reliably fit for psychotic disorders in epoch 1. People diagnosed with substance use disorders had an increased risk of all-cause mortality 28 days postinfection in epoch 3, 4, and 5 (aHR from 1.30 [95% CIs, 1.14, 1.47] to 1.59 [95% CIs, 1.19, 2.12]) and 60 days postinfection in epoch 2, 3, 4, and 5 (aHR from 1.22 [95% CIs, 1.08, 1.38] to 1.52 [95% CIs, 1.16, 1.98]). Cases ascertained based on diagnosis of substance use disorders and treatment had increased risk of all-cause mortality in epoch 2, 3, 4, and 5 (aHR from 1.22 [95% CIs, 1.03, 1.43] to 1.91 [95% CIs, 1.25, 2.91]). The models could not be reliably fit for substance use disorders in epoch 1. In contrast to these, people diagnosed with anxiety disorders had a decreased risk of death with COVID-19 in epoch 2, 3, and 5 (aHR from 0.78 [95% CIs, 0.69, 0.88] to 0.89 [95% CIs, 0.81, 0.98]) and all-cause mortality in epoch 2, 3, 4, and 5 (aHR from 0.83 [95% CIs, 0.77, 0.90] to 0.88 [95% CIs, 0.83, 0.93]). People diagnosed and treated for affective disorders had a decreased risk of both death with COVID-19 and from all-causes in epoch 3 (aHR from 0.87 [95% CIs, 0.79, 0.96] to 0.90 [95% CIs, 0.83, 0.99]), but demonstrated broadly null effects in other epochs. Given the unavailability of data on a number of potentially influential confounders, particularly body mass index, tobacco smoking status, and socioeconomic status, part of the detected associations might be due to residual confounding.

CONCLUSIONS

People with preexisting psychotic, and, less robustly, substance use disorders demonstrated a persistently elevated risk of death following SARS-CoV-2 infection throughout the pandemic. While it cannot be ruled out that part of the detected associations is due to residual confounding, this excess mortality cannot be fully explained by lower vaccination uptake and more clinically recorded physical comorbidities in these patient groups.

The associations between religious/spiritual beliefs and behaviours and study participation in a prospective cohort study (ALSPAC) in Southwest England

Background

Longitudinal studies are key to understanding risk factors for health, well-being, and disease, yet associations may be biased if study invitation and participation are non-random. Religious/spiritual beliefs and behaviours (RSBB) are increasingly recognised as having potentially important relationships with health. However, it is unclear whether RSBB is associated with study participation. We examine whether RSBB is associated with participation in the longitudinal birth cohort ALSPAC (Avon Longitudinal Study of Parents and Children).

Methods

Three RSBB factors were used: religious belief (belief in God/a divine power; yes/not sure/no), religious affiliation (Christian/none/other), and religious attendance (frequency of attendance at a place of worship). Participation was measured in three ways: i) total number of questionnaires/clinics completed (linear and ordinal models); ii) completion of the most recent questionnaire (logistic model); and iii) length of participation (survival model). Analyses were repeated for the ALSPAC mothers, their partners, and the study children, and were adjusted for relevant socio-demographic confounders.

Results

Religious attendance was positively associated with participation in all adjusted models in all three cohorts. For example, study mothers who attended a place of worship at least once a month on average completed two more questionnaires (out of a possible 50), had 50% greater odds of having completed the most recent questionnaire, and had 25% reduced risk of drop-out, relative to those who did not attend. In the adjusted analyses, religious belief and attendance were not associated with participation. However, the majority of unadjusted models showed associations between RSBB and participation.

Conclusion

After adjusting for confounders, religious attendance - not religious belief or affiliation - was associated with participation in ALSPAC. These results indicate that use of RSBB variables (and religious attendance in particular) may result in selection bias and spurious associations; these potential biases should be explored and discussed in future studies using these data.

Risk of Blood Clots After COVID-19 Vaccination and Infection: A Risk-Benefit Analysis

We analyzed the risk-benefit of COVID-19 vaccine using a causal model to explain and weigh up possible risk factors of blood clots after vaccination. A self-controlled case series method was used to examine the association between blood clots and COVID-19 vaccination. To avoid bias due to the under-reported infection among non-hospitalized subjects, a case-control study was used to compare the risk of blood clots in infected subjects to control subjects who were hospitalized due to physical injury. We found increased risks of blood clots after vaccination (incidence rate ratio is 1.13, 95% CI: [1.03,1.24] after the first dose and 1.23, 95% CI: [1.13,1.34] after the second dose). Furthermore, vaccination attenuated the increased risk of blood clots associated with infection (odds ratio is 2.16, 95% CI: [1.93,2.42] in unvaccinated versus 1.46, 95% CI: [1.25,1.70] in vaccinated). After accounting for vaccine efficacy against infection and the protection against infection-associated blood clots, receiving the COVID-19 vaccines decreases the risk of blood clots, especially during high infection rate period.

COVID-19 Vaccine Effectiveness and Digital Pandemic Surveillance in Germany (eCOV Study): Web Application-Based Prospective Observational Cohort Study

BACKGROUND

The COVID-19 pandemic posed significant challenges to global health systems. Efficient public health responses required a rapid and secure collection of health data to improve the understanding of SARS-CoV-2 and examine the vaccine effectiveness (VE) and drug safety of the novel COVID-19 vaccines.

OBJECTIVE

This study (COVID-19 study on vaccinated and unvaccinated subjects over 16 years; eCOV study) aims to (1) evaluate the real-world effectiveness of COVID-19 vaccines through a digital participatory surveillance tool and (2) assess the potential of self-reported data for monitoring key parameters of the COVID-19 pandemic in Germany.

METHODS

Using a digital study web application, we collected self-reported data between May 1, 2021, and August 1, 2022, to assess VE, test positivity rates, COVID-19 incidence rates, and adverse events after COVID-19 vaccination. Our primary outcome measure was the VE of SARS-CoV-2 vaccines against laboratory-confirmed SARS-CoV-2 infection. The secondary outcome measures included VE against hospitalization and across different SARS-CoV-2 variants, adverse events after vaccination, and symptoms during infection. Logistic regression models adjusted for confounders were used to estimate VE 4 to 48 weeks after the primary vaccination series and after third-dose vaccination. Unvaccinated participants were compared with age- and gender-matched participants who had received 2 doses of BNT162b2 (Pfizer-BioNTech) and those who had received 3 doses of BNT162b2 and were not infected before the last vaccination. To assess the potential of self-reported digital data, the data were compared with official data from public health authorities.

RESULTS

We enrolled 10,077 participants (aged ≥16 y) who contributed 44,786 tests and 5530 symptoms. In this young, primarily female, and digital-literate cohort, VE against infections of any severity waned from 91.2% (95% CI 70.4%-97.4%) at week 4 to 37.2% (95% CI 23.5%-48.5%) at week 48 after the second dose of BNT162b2. A third dose of BNT162b2 increased VE to 67.6% (95% CI 50.3%-78.8%) after 4 weeks. The low number of reported hospitalizations limited our ability to calculate VE against hospitalization. Adverse events after vaccination were consistent with previously published research. Seven-day incidences and test positivity rates reflected the course of the pandemic in Germany when compared with official numbers from the national infectious disease surveillance system.

CONCLUSIONS

Our data indicate that COVID-19 vaccinations are safe and effective, and third-dose vaccinations partially restore protection against SARS-CoV-2 infection. The study showcased the successful use of a digital study web application for COVID-19 surveillance and continuous monitoring of VE in Germany, highlighting its potential to accelerate public health decision-making. Addressing biases in digital data collection is vital to ensure the accuracy and reliability of digital solutions as public health tools.

Demographic and socioeconomic predictors of religious/spiritual beliefs and behaviours in a prospective cohort study (ALSPAC) in Southwest England: Results from the offspring generation

Background

We explored associations between possible demographic and socioeconomic causes of religious/spiritual beliefs and behaviours (RSBB) in the offspring generation of the Avon Longitudinal Study of Parents and Children (ALSPAC).

Methods

We examined approximately 4,450 offspring aged 28 years with RSBB data from a prospective birth cohort study (ALSPAC) in Southwest England. Three RSBB outcome measures were assessed: religious belief (belief in God/a divine power; yes/not sure/no), religious affiliation (Christian/none/other) and religious attendance (frequency of attendance at a place of worship). We explored age- and sex-adjusted associations between 35 demographic and socioeconomic exposures and each of the three RSBB outcomes using multinomial regression. Exposure-sex interactions were also examined.

Results

Some sociodemographic factors were associated with RSBB in this cohort; for instance, being female and from an ethnicity other than White were associated with increased religiosity across all domains. For many other exposures, however, associations were frequently null or inconsistent, often depending on the specific exposure and outcome combination. As an example, higher educational attainment was associated with higher rates of religious attendance, but not with religious belief or affiliation; in contrast, higher income was associated with lower levels of religiosity. No consistent interactions between sex and the exposures on RSBB were found. Effect sizes were also rather weak, with most pseudo- R 2 values below 0.5% and a maximum of 1.2%.

Conclusions

The results highlight that several demographic and socioeconomic factors are associated with RSBB in this cohort. However, the number of these associations, and their magnitude, is smaller than comparable results from the parental generation of these offspring, suggesting that patterns of sociodemographic factors associated with RSBB differ between these generations. In addition to describing these associations, this paper will help inform future studies using these data, particularly regarding the choice of potential sociodemographic confounders.

Cannabis, Tobacco Use, and COVID-19 Outcomes

Importance

It is unclear whether cannabis use is associated with adverse health outcomes in patients with COVID-19 when accounting for known risk factors, including tobacco use.

Objective

To examine whether cannabis and tobacco use are associated with adverse health outcomes from COVID-19 in the context of other known risk factors.

Design, Setting, and Participants

This retrospective cohort study used electronic health record data from February 1, 2020, to January 31, 2022. This study included patients who were identified as having COVID-19 during at least 1 medical visit at a large academic medical center in the Midwest US.

Exposures

Current cannabis use and tobacco smoking, as documented in the medical encounter.

Main Outcomes and Measures

Health outcomes of hospitalization, intensive care unit (ICU) admission, and all-cause mortality following COVID-19 infection. The association between substance use (cannabis and tobacco) and these COVID-19 outcomes was assessed using multivariable modeling.

Results

A total of 72 501 patients with COVID-19 were included (mean [SD] age, 48.9 [19.3] years; 43 315 [59.7%] female; 9710 [13.4%] had current smoking; 17 654 [24.4%] had former smoking; and 7060 [9.7%] had current use of cannabis). Current tobacco smoking was significantly associated with increased risk of hospitalization (odds ratio [OR], 1.72; 95% CI, 1.62-1.82; P < .001), ICU admission (OR, 1.22; 95% CI, 1.10-1.34; P < .001), and all-cause mortality (OR, 1.37, 95% CI, 1.20-1.57; P < .001) after adjusting for other factors. Cannabis use was significantly associated with increased risk of hospitalization (OR, 1.80; 95% CI, 1.68-1.93; P < .001) and ICU admission (OR, 1.27; 95% CI, 1.14-1.41; P < .001) but not with all-cause mortality (OR, 0.97; 95% CI, 0.82-1.14, P = .69) after adjusting for tobacco smoking, vaccination, comorbidity, diagnosis date, and demographic factors.

Conclusions and Relevance

The findings of this cohort study suggest that cannabis use may be an independent risk factor for COVID-19-related complications, even after considering cigarette smoking, vaccination status, comorbidities, and other risk factors.

Missing data and missed infections: investigating racial and ethnic disparities in SARS-CoV-2 testing and infection rates in Holyoke, Massachusetts

Routinely collected testing data have been a vital resource for public health response during the COVID-19 pandemic and have revealed the extent to which Black and Hispanic persons have borne a disproportionate burden of SARS-CoV-2 infections and hospitalizations in the United States. However, missing race and ethnicity data and missed infections due to testing disparities limit the interpretation of testing data and obscure the true toll of the pandemic. We investigated potential bias arising from these 2 types of missing data through a case study carried out in Holyoke, Massachusetts, during the prevaccination phase of the pandemic. First, we estimated SARS-CoV-2 testing and case rates by race and ethnicity, imputing missing data using a joint modeling approach. We then investigated disparities in SARS-CoV-2 reported case rates and missed infections by comparing case rate estimates with estimates derived from a COVID-19 seroprevalence survey. Compared with the non-Hispanic White population, we found that the Hispanic population had similar testing rates (476 tested per 1000 vs 480 per 1000) but twice the case rate (8.1% vs 3.7%). We found evidence of inequitable testing, with a higher rate of missed infections in the Hispanic population than in the non-Hispanic White population (79 infections missed per 1000 vs 60 missed per 1000).

Trends in weight gain recorded in English primary care before and during the Coronavirus-19 pandemic: An observational cohort study using the OpenSAFELY platform

BACKGROUND

Obesity and rapid weight gain are established risk factors for noncommunicable diseases and have emerged as independent risk factors for severe disease following Coronavirus Disease 2019 (COVID-19) infection. Restrictions imposed to reduce COVID-19 transmission resulted in profound societal changes that impacted many health behaviours, including physical activity and nutrition, associated with rate of weight gain. We investigated which clinical and sociodemographic characteristics were associated with rapid weight gain and the greatest acceleration in rate of weight gain during the pandemic among adults registered with an English National Health Service (NHS) general practitioner (GP) during the COVID-19 pandemic.

METHODS AND FINDINGS

With the approval of NHS England, we used the OpenSAFELY platform inside TPP to conduct an observational cohort study of routinely collected electronic healthcare records. We investigated changes in body mass index (BMI) values recorded in English primary care between March 2015 and March 2022. We extracted data on 17,742,365 adults aged 18 to 90 years old (50.1% female, 76.1% white British) registered with an English primary care practice. We estimated individual rates of weight gain before (δ-prepandemic) and during (δ-pandemic) the pandemic and identified individuals with rapid weight gain (>0.5 kg/m2/year) in each period. We also estimated the change in rate of weight gain between the prepandemic and pandemic period (δ-change = δ-pandemic-δ-prepandemic) and defined extreme accelerators as the 10% of individuals with the greatest increase in their rate of weight gain (δ-change ≥1.84 kg/m2/year) between these periods. We estimated associations with these outcomes using multivariable logistic regression adjusted for age, sex, index of multiple deprivation (IMD), and ethnicity. P-values were generated in regression models. The median BMI of our study population was 27.8 kg/m2, interquartile range (IQR) [24.3, 32.1] in 2019 (March 2019 to February 2020) and 28.0 kg/m2, IQR [24.4, 32.6] in 2021. Rapid pandemic weight gain was associated with sex, age, and IMD. Male sex (male versus female: adjusted odds ratio (aOR) 0.76, 95% confidence interval (95% CI) [0.76, 0.76], p < 0.001), older age (e.g., 50 to 59 years versus 18 to 29 years: aOR 0.60, 95% CI [0.60, 0.61], p < 0.001]); and living in less deprived areas (least-deprived-IMD-quintile versus most-deprived: aOR 0.77, 95% CI [0.77, 0.78] p < 0.001) reduced the odds of rapid weight gain. Compared to white British individuals, all other ethnicities had lower odds of rapid pandemic weight gain (e.g., Indian versus white British: aOR 0.69, 95% CI [0.68, 0.70], p < 0.001). Long-term conditions (LTCs) increased the odds, with mental health conditions having the greatest effect (e.g., depression (aOR 1.18, 95% CI [1.17, 1.18], p < 0.001)). Similar characteristics increased odds of extreme acceleration in the rate of weight gain between the prepandemic and pandemic periods. However, changes in healthcare activity during the pandemic may have introduced new bias to the data.

CONCLUSIONS

We found female sex, younger age, deprivation, white British ethnicity, and mental health conditions were associated with rapid pandemic weight gain and extreme acceleration in rate of weight gain between the prepandemic and pandemic periods. Our findings highlight the need to incorporate sociodemographic, physical, and mental health characteristics when formulating research, policies, and interventions targeting BMI in the period of post pandemic service restoration and in future pandemic planning.

Mortality risk in patients with obesity and COVID-19 infection: a systematic review and meta-analysis

Obesity is a risk factor for severe respiratory diseases, including COVID-19 infection. Meta-analyses on mortality risk were inconsistent. We systematically searched 3 databases (Medline, Embase, CINAHL) and assessed the quality of studies using the Newcastle-Ottawa tool (CRD42020220140). We included 199 studies from US and Europe, with a mean age of participants 41.8-78.2 years, and a variable prevalence of metabolic co-morbidities of 20-80 %. Exceptionally, one third of the studies had a low prevalence of obesity of <20 %. Compared to patients with normal weight, those with obesity had a 34 % relative increase in the odds of mortality (p-value 0.002), with a dose-dependent relationship. Subgroup analyses showed an interaction with the country income. There was a high heterogeneity in the results, explained by clinical and methodologic variability across studies. We identified one trial only comparing mortality rate in vaccinated compared to unvaccinated patients with obesity; there was a trend for a lower mortality in the former group. Mortality risk in COVID-19 infection increases in parallel to an increase in BMI. BMI should be included in the predictive models and stratification scores used when considering mortality as an outcome in patients with COVID-19 infections. Furthermore, patients with obesity might need to be prioritized for COVID-19 vaccination.

The Association of Asthma and Metabolic Dysfunction With Outcomes of Hospitalized Patients With COVID-19

BACKGROUND

There have been conflicting results on the association of asthma with the severity of coronavirus disease 2019 (COVID-19). Poor metabolic health has been previously associated with both severe COVID-19 and inflammation in asthma.

OBJECTIVES

To examine the association between asthma and COVID-19 outcomes and whether these associations are modified by metabolic syndrome.

METHODS

We performed an international, observational cohort study of adult patients hospitalized for COVID-19 from February 2020 through October 2021. The primary outcome was hospital mortality.

RESULTS

The study included 27,660 patients from 164 hospitals, 12,114 (44%) female, with a median (interquartile range) age of 63 years (51-75). After adjusting for age, sex, smoking, race, ethnicity, geographic region, and Elixhauser comorbidity index, we found that patients with asthma were not at greater risk of hospital death when compared with patients with no chronic pulmonary disease (controls) (adjusted odds ratio [aOR], 0.97; 95% CI, 0.90-1.04; P = .40). Patients with asthma, when compared with controls, required higher respiratory support identified by the need for supplemental oxygen (aOR, 1.07; 95% CI, 1.01-1.14; P = .02), high-flow nasal cannula or noninvasive mechanical ventilation (aOR, 1.06; 95% CI, 1.00-1.13; P = .04), and invasive mechanical ventilation (aOR, 1.09; 95% CI, 1.03-1.16; P = .003). Metabolic syndrome increased the risk of death in patients with asthma, but the magnitude of observed association was similar to controls in stratified analysis (interaction P value .24).

CONCLUSIONS

In this international cohort of hospitalized COVID-19 patients, asthma was not associated with mortality but was associated with increased need for respiratory support. Although metabolic dysfunction was associated with increased risks in COVID-19, these risks were similar for patients with or without asthma.

Walking time and genetic predisposition for Alzheimer's disease: Results from the HELIAD study

Objective: Our study aimed to explore whether physical condition might affect the association between genetic predisposition for Alzheimer's Disease (AD) and AD incidence. Methods: The sample of participants consisted of 561 community-dwelling adults over 64 years old, without baseline dementia (508 cognitively normal and 53 with mild cognitive impairment), deriving from the HELIAD, an ongoing longitudinal study with follow-up evaluations every 3 years. Physical condition was assessed at baseline through walking time (WT), while a Polygenic Risk Score for late onset AD (PRS-AD) was used to estimate genetic predisposition. The association between WT and PRS-AD with AD incidence was evaluated with Cox proportional hazard models adjusted for age, sex, education years, global cognition score and APOE ε-4 genotype. Then, the association between WT and AD incidence was investigated after stratifying participants by low and high PRS-AD. Finally, we examined the association between PRS-AD and AD incidence after stratifying participants by WT. Results: Both WT and PRS-AD were connected with increased AD incidence (p < 0.05), after adjustments. In stratified analyses, in the slow WT group participants with a greater genetic risk had a 2.5-fold higher risk of developing AD compared to participants with lower genetic risk (p = 0.047). No association was observed in the fast WT group or when participants were stratified based on PRS-AD. Conclusions: Genetic predisposition for AD is more closely related to AD incidence in the group of older adults with slow WT. Hence, physical condition might be a modifier in the relationship of genetic predisposition with AD incidence.

Association between COVID-19 severity and tobacco smoking status: a retrospective cohort study using propensity score matching weights analysis

INTRODUCTION

The COVID-19 pandemic continues to be a global threat to public health, with over 766 million confirmed cases and more than 6 million reported deaths. Patients with a smoking history are at a greater risk of severe respiratory complications and death due to COVID-19. This study investigated the association between smoking history and adverse clinical outcomes among COVID-19 patients admitted to a designated medical centre in Saudi Arabia.

METHODS

A retrospective observational cohort study was conducted using patient chart review data from a large tertiary medical centre in the eastern region of the country. Patients admitted between January and December 2020 were screened. The inclusion criteria were ≥18 years of age and confirmed COVID-19 infection via reverse-transcription-PCR. The exclusion criteria were unconfirmed COVID-19 infection, non-COVID-19 admissions, unconfirmed smoking status, vaccinated individuals, essential chart information missing or refusal to consent. Statistical analyses comprised crude estimates, matching weights (as the main analysis) and directed acyclic graphs (DAGs) causal pathway analysis using an ordinal regression model.

RESULTS

The sample comprised 447 patients (never-smoker=321; ever-smoker=126). The median age (IQR) was 50 years (39-58), and 73.4% of the sample were males. A matching weights procedure was employed to ensure covariate balance. The analysis revealed that the odds of developing severe COVID-19 were higher in the ever-smoker group with an OR of 1.44 (95% CI 0.90 to 2.32, p=0.130). This was primarily due to an increase in non-invasive oxygen therapy with an OR of 1.05 (95% CI 0.99 to 1.10, p=0.101). The findings were consistent across the different analytical methods employed, including crude estimates and DAGs causal pathway analysis.

CONCLUSION

Our findings suggest that smoking may increase the risk of adverse COVID-19 outcomes. However, the study was limited by its retrospective design and small sample size. Further research is therefore needed to confirm the findings.

Biases and limitations in observational studies of Long COVID prevalence and risk factors: A rapid systematic umbrella review

BACKGROUND

Observational studies form the foundation of Long COVID knowledge, however combining data from Long COVID observational studies has multiple methodological challenges. This umbrella review synthesizes estimates of Long COVID prevalence and risk factors as well as biases and limitations in the primary and review literatures.

METHODS AND FINDINGS

A systematic literature search was conducted using multiple electronic databases (PubMed, EMBASE, LitCOVID) from Jan 1, 2019 until June 9, 2023. Eligible studies were systematic reviews including adult populations assessed for at least one Long COVID symptom four weeks or more after SARS-CoV-2 infection. Overall and subgroup prevalence and risk factors as well as risk of bias (ROB) assessments were extracted and descriptively analyzed. The protocol was registered with PROSPERO (CRD42023434323). Fourteen reviews of 5-196 primary studies were included: 8 reported on Long COVID prevalence, 5 on risk/protective factors, and 1 on both. Prevalence of at least 1 Long COVID symptom ranged from 21% (IQR: 8.9%-35%) to 74.5% (95% CI: 55.6%-78.0%). Risk factor reviews found significant associations between vaccination status, sex, acute COVID-19 severity, and comorbidities. Both prevalence and risk factor reviews frequently identified selection and ascertainment biases. Using the AMSTAR 2 criteria, the quality of included reviews, particularly the prevalence reviews, were concerning for the adequacy of ROB assessments and justifications for conducting meta-analysis.

CONCLUSION

A high level of heterogeneity render the interpretation of pooled prevalence estimates of Long COVID challenging, further hampered by the lack of robust critical appraisals in the included reviews. Risk factor reviews were of higher quality overall and suggested consistent associations between Long COVID risk and patient characteristics.

A Capture-Recapture-based Ascertainment Probability Weighting Method for Effect Estimation With Under-ascertained Outcomes

Outcome under-ascertainment, characterized by the incomplete identification or reporting of cases, poses a substantial challenge in epidemiologic research. While capture-recapture methods can estimate unknown case numbers, their role in estimating exposure effects in observational studies is not well established. This paper presents an ascertainment probability weighting framework that integrates capture-recapture and propensity score weighting. We propose a nonparametric estimator of effects on binary outcomes that combines exposure propensity scores with data from two conditionally independent outcome measurements to simultaneously adjust for confounding and under-ascertainment. Demonstrating its practical application, we apply the method to estimate the relationship between health care work and coronavirus disease 2019 testing in a Swedish region. We find that ascertainment probability weighting greatly influences the estimated association compared to conventional inverse probability weighting, underscoring the importance of accounting for under-ascertainment in studies with limited outcome data coverage. We conclude with practical guidelines for the method's implementation, discussing its strengths, limitations, and suitable scenarios for application.

Association between allergic conditions and COVID-19 susceptibility and outcomes

BACKGROUND

The relationship between underlying type 2 inflammation and immune response to COVID-19 is unclear.

OBJECTIVE

To assess the relationships between allergic conditions and COVID-19 susceptibility and outcomes.

METHODS

In the Optum database, adult patients with and without major allergic conditions (asthma, atopic dermatitis [AD], allergic rhinitis, food allergy, anaphylaxis, or eosinophilic esophagitis) and patients with and without severe asthma/AD were identified. Adjusted incidence rate ratios for COVID-19 were compared among patients with vs without allergic conditions or severe asthma/AD vs non-severe asthma/AD during April 1, 2020, to December 31, 2020. Among patients with COVID-19, adjusted hazard ratios (aHRs) of 30-day COVID-19-related hospitalization/all-cause mortality were estimated for the same comparisons during April 1, 2020, to March 31, 2022.

RESULTS

Patients with (N = 1,273,231; asthma, 47.2%; AD, 1.5%; allergic rhinitis, 58.6%; food allergy, 5.1%; anaphylaxis, 4.1%; eosinophilic esophagitis, 0.9%) and without allergic conditions (N = 2,278,571) were identified. Allergic conditions (adjusted incidence rate ratios [95% CI], 1.22 [1.21-1.24]) and asthma severity (1.12 [1.09-1.15]) were associated with increased incidence of COVID-19. Among patients with COVID-19 (patients with [N = 261,076] and without allergic conditions [N = 1,098,135] were matched on age, sex, region, index month), having an allergic condition had minimal impact on 30-day COVID-19-related hospitalization/all-cause mortality (aHR [95% CI] 0.96 [0.95-0.98]) but was associated with a lower risk of mortality (0.80 [0.78-0.83]). Asthma was associated with a higher risk of COVID-19-related hospitalization/all-cause mortality vs non-asthma allergic conditions (aHR [95% CI], 1.27 [1.25-1.30]), mostly driven by higher hospitalization.

CONCLUSION

Allergic conditions were associated with an increased risk of receiving COVID-19 diagnosis but reduced mortality after infection.

ANTsX neuroimaging-derived structural phenotypes of UK Biobank

UK Biobank is a large-scale epidemiological resource for investigating prospective correlations between various lifestyle, environmental, and genetic factors with health and disease progression. In addition to individual subject information obtained through surveys and physical examinations, a comprehensive neuroimaging battery consisting of multiple modalities provides imaging-derived phenotypes (IDPs) that can serve as biomarkers in neuroscience research. In this study, we augment the existing set of UK Biobank neuroimaging structural IDPs, obtained from well-established software libraries such as FSL and FreeSurfer, with related measurements acquired through the Advanced Normalization Tools Ecosystem. This includes previously established cortical and subcortical measurements defined, in part, based on the Desikan-Killiany-Tourville atlas. Also included are morphological measurements from two recent developments: medial temporal lobe parcellation of hippocampal and extra-hippocampal regions in addition to cerebellum parcellation and thickness based on the Schmahmann anatomical labeling. Through predictive modeling, we assess the clinical utility of these IDP measurements, individually and in combination, using commonly studied phenotypic correlates including age, fluid intelligence, numeric memory, and several other sociodemographic variables. The predictive accuracy of these IDP-based models, in terms of root-mean-squared-error or area-under-the-curve for continuous and categorical variables, respectively, provides comparative insights between software libraries as well as potential clinical interpretability. Results demonstrate varied performance between package-based IDP sets and their combination, emphasizing the need for careful consideration in their selection and utilization.

Associations between COVID-19 incidence, weight status, and social participation restrictions in the U.S.: evidence from the national population, cross-sectional study

BACKGROUND

To explore the associations between coronavirus infection incidence and weight status and social participation restrictions among community-dwelling adults in the United States.

METHODS

We analyzed data from the 2021 National Health Interview Survey (NHIS), which included a representative sample of 29,394 individuals (Coronavirus disease 2019 (COVID-19): 3,205) and a weighted total of 252,461,316 individuals (COVID-19: 31,697,404), considering the complex sampling design used in the survey.

RESULTS

Age, race/ethnicity, education level, family income index, body mass index (BMI), and smoking status were significantly associated with COVID-19 infection. Weight status was significantly correlated with social participation restrictions and strongly associated with COVID-19 infection, particularly among individuals who were overweight or obese.

CONCLUSION

Weight status was shown to be associated not only with social participation restrictions but also with COVID-19 infection among U.S. adults. Understanding the complex interplay between weight status, social participation, and COVID-19 is crucial for developing effective preventive measures and promoting overall well-being in the community population.

Usefulness of Heart Failure Categories Based on Left Ventricular Ejection Fraction

BACKGROUND

Heart failure guidelines have recently introduced a narrow category with mildly reduced left ventricular ejection fraction (LVEF) (heart failure with mildly reduced ejection fraction; LVEF 41%-49%) between the previous categories of reduced (heart failure with reduced ejection fraction; LVEF ≤40%) and preserved (heart failure with preserved ejection fraction; LVEF ≥50%) ejection fraction. Grouping of continuous measurements into narrow categories can be questioned if their variability is high.

METHODS AND RESULTS

We constructed a cohort of all 9716 new cases of chronic heart failure with an available LVEF in Stockholm, Sweden, from January 1, 2015, until December 31, 2020. All values of LVEF were collected over time, and patients were followed up until death, moving out of Stockholm, or end of study. Mixed models were used to quantify within-person variance in LVEF, and multistate Markov models, with death as an absorbing state, to quantify the stability of LVEF categories. LVEF values followed a normal distribution. The SD of the within-person variance in LVEF over time was 7.4%. The mean time spent in any LVEF category before transition to another category was on average <1 year for heart failure with mildly reduced ejection fraction. Probabilities of transitioning between categories during the first year were substantial; patients with heart failure with mildly reduced ejection fraction had a probability of <25% of remaining in that category 1 year later.

CONCLUSIONS

LVEF follows a normal distribution and has considerable variability over time, which may impose a risk for underuse of efficient treatment. The heart failure with mildly reduced ejection fraction category is especially inconstant. Assumptions of a patient's current LVEF should take this variability and the normal distribution of LVEF into account.

Association of day-case rates with post COVID-19 recovery of elective laparoscopic cholecystectomy activity across England

INTRODUCTION

The aim of this study was to investigate the safety of day-case laparoscopic cholecystectomy, and the association between day-case rates and, post the COVID-19 pandemic, recovery of activity to prepandemic levels for integrated care boards (ICBs) in England.

METHODS

This was a retrospective observational study of the Hospital Episodes Statistics (HES) data set. Elective laparoscopic cholecystectomies for the period 1 January 2019 to 31 December 2022 were identified. Activity levels for 2022 were compared with those for the whole of 2019 (baseline). Day-case activity was identified where the length of stay recorded in the HES was zero days.

RESULTS

Data were available for 184,252 patients across the 42 ICBs in England, of which 120,408 (65.3%) were day-case procedures. By December 2022, activity levels for the whole of England had returned to 88.2% of prepandemic levels. The South West region stood out as having recovered activity levels to the greatest extent, with activity at 97.3% of prepandemic levels during 2022. The South West also had the highest postpandemic day-case rate at 74.9% of all patients seen as a day-case during 2022; this compares with an England average of 65.3%. At an ICB level, there was a significant correlation between day-case rates and postpandemic activity levels (r = 0.362, p = 0.019). There was no strong or consistent evidence that day-case surgery had poorer patient outcomes than inpatient surgery.

CONCLUSIONS

Recovery of elective laparoscopic cholecystectomy activity has been better in South West England than in other regions. Increasing day-case rates may be important if ICBs in other regions are to increase activity levels up to and beyond prepandemic levels.

Psychiatric Symptoms, Treatment Uptake, and Barriers to Mental Health Care Among US Adults With Post-COVID-19 Condition

Importance

Psychiatric symptoms are reportedly common among adults with post-COVID-19 condition (PCC). However, nationally representative data regarding symptom prevalence, treatment uptake, and barriers to care are needed to inform the development of care models.

Objectives

To evaluate the prevalence of psychiatric symptoms in US adults with PCC compared with those without PCC and assess treatment uptake and cost-related barriers to treatment.

Design, Setting, and Participants

Data from the 2022 National Health Interview Survey (NHIS), a nationally representative US cross-sectional survey, were analyzed between October 2023 and February 2024.

Exposure

Current PCC, defined as new symptoms following SARS-CoV-2 infection lasting more than 3 months and ongoing at the time of interview.

Main Outcomes and Measures

Depression symptoms were evaluated by the Patient Health Questionnaire-8 and anxiety symptoms were assessed using the General Anxiety Disorder-7 instrument. Participants were classified as having received treatment if they received mental health counseling or therapy or medications for mental health. Sleep difficulties, cognitive difficulties, disabling fatigue, and cost-related barriers were assessed from additional NHIS questions.

Results

Of the 25 122 participants representing approximately 231 million US adults (median [IQR] age, 46 [32-61] years; 49.8% male and 50.2% female participants), a weighted prevalence (wPr) of 3.4% (95% CI, 3.1%-3.6%) had current PCC. Compared with other US adults, participants with current PCC were more likely to have depression symptoms (wPr, 16.8% vs 7.1%; adjusted odds ratio [AOR], 1.96; 95% CI, 1.51-2.55), anxiety symptoms (wPr, 16.7% vs 6.3%; AOR, 2.21; 95% CI, 1.53-3.19), sleep difficulties (wPr, 41.5% vs 22.7%; AOR 1.95; 95% CI, 1.65-2.29), cognitive difficulties (wPr, 35.0% vs 19.5%; AOR, 2.04; 95% CI, 1.66-2.50), and disabling fatigue (wPr, 4.0% vs 1.6%; AOR, 1.85; 95% CI, 1.20-2.86). Among participants who had depression or anxiety symptoms, those with PCC had a similar likelihood of not having received treatment (wPr, 28.2% vs 34.9%; AOR, 1.02; 95% CI, 0.66-1.57). However, participants with current PCC were more likely to report a cost-related barrier to accessing mental health counseling or therapy (wPr, 37.2% vs 23.3%; AOR, 2.05; 95% CI, 1.40-2.98).

Conclusions and Relevance

The findings of this study suggest that people with PCC have a higher prevalence of psychiatric symptoms than other adults but are more likely to experience cost-related barriers to accessing therapy. Care pathways for PCC should consider prioritizing mental health screening and affordable treatment.

COVID-19 Outcome and Tobacco Product Use: Case-Control and Retrospective Cohort Studies Using Nationwide Samples

BACKGROUND

Conflicting evidence exists regarding the association between smoking and the risk of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. We investigated the association between combustible cigarette (CC) smoking, noncombustible tobacco product (NCTP) use, and the use of any tobacco product with various coronavirus disease 2019 (COVID-19) outcomes.

METHODS

A case-control study was conducted using the Korea Disease Control and Prevention Agency-COVID19-National Health Insurance Service (NHIS) cohort. A retrospective cohort study was conducted using 12,571,698 individuals from the NHIS cohort. Logistic regression evaluated the association between CC smoking, NCTP use, and use of any tobacco product with SARS-CoV-2 infection. Poisson regression evaluated the association between these forms of tobacco product use and COVID-19-related hospitalization and mortality.

RESULTS

In the case-control study, we identified 30,878 cases of SARS-CoV-2 infection. The odds ratios (95% confidence intervals [CIs]) for SARS-CoV-2 infection were lower among current CC smokers (0.51, 0.48-0.54), current- and former-NCTP users (0.80, 0.74-0.88; 0.82, 0.74-0.91), and current users of any tobacco product (0.52, 0.49-0.55) relative to never user controls. In retrospective cohort study, we identified 16,521 COVID-19-related hospitalization and 362 COVID-19-related deaths. The relative risks (95% CIs) for COVID-19-related hospitalization were lower among current CC smokers (0.51, 0.48-0.54) and current users of any tobacco product (0.53, 0.50-0.56) relative to never user controls. There was no association between the use of tobacco product and COVID-19-related mortality.

CONCLUSION

Current CC smokers and current users of any tobacco product showed reduced risk of SARS-CoV-2 infection and COVID-19-related hospitalization. It remains uncertain whether these relationships are causal.

Clinical and laboratory characteristics of patients hospitalized with severe COVID-19 in New Orleans, August 2020 to September 2021

Louisiana experienced high morbidity and mortality from COVID-19. To assess possible explanatory factors, we conducted a cohort study (ClinSeqSer) of patients hospitalized with COVID-19 in New Orleans during August 2020-September 2021. Following enrollment, we reviewed medical charts, and performed SARS-CoV-2 RT-PCR testing on nasal and saliva specimens. We used multivariable logistic regression to assess associations between patient characteristics and severe illness, defined as ≥ 6 L/min oxygen or intubation. Among 456 patients, median age was 56 years, 277 (60.5%) were Black non-Hispanic, 436 (95.2%) had underlying health conditions, and 358 were unvaccinated (92.0% of 389 verified). Overall, 187 patients (40.1%) had severe illness; 60 (13.1%) died during admission. In multivariable models, severe illness was associated with age ≥ 65 years (OR 2.08, 95% CI 1.22-3.56), hospitalization > 5 days after illness onset (OR 1.49, 95% CI 1.01-2.21), and SARS CoV-2 cycle threshold (Ct) result of < 32 in saliva (OR 4.79, 95% CI 1.22-18.77). Among patients who were predominantly Black non-Hispanic, unvaccinated and with underlying health conditions, approximately 1 in 3 patients had severe COVID-19. Older age and delayed time to admission might have contributed to high case-severity. An association between case-severity and low Ct value in saliva warrants further investigation.

Transcatheter Aortic Valve Implantation Wait-Time Management: Derivation and Validation of the Canadian TAVI Triage Tool (CAN3T)

BACKGROUND

Transcatheter aortic valve implantation (TAVI) has seen indication expansion and thus exponential growth in demand over the past decade. In many jurisdictions, the growing demand has outpaced capacity, increasing wait times and preprocedural adverse events. In this study, we derived prediction models that estimate the risk of adverse events on the waitlist and developed a triage tool to identify patients who should be prioritized for TAVI.

METHODS AND RESULTS

We included adult patients in Ontario, Canada referred for TAVI and followed up until one of the following events first occurred: death, TAVI procedure, removal from waitlist, or end of the observation period. We used subdistribution hazards models to find significant predictors for each of the following outcomes: (1) all-cause death while on the waitlist; (2) all-cause hospitalization while on the waitlist; (3) receipt of urgent TAVI; and (4) a composite outcome. The median predicted risk at 12 weeks was chosen as a threshold for a maximum acceptable risk while on the waitlist and incorporated in the triage tool to recommend individualized wait times. Of 13 128 patients, 586 died while on the waitlist, and 4343 had at least 1 hospitalization. A total of 6854 TAVIs were completed, of which 1135 were urgent procedures. We were able to create parsimonious models for each outcome that included clinically relevant predictors.

CONCLUSIONS

The Canadian TAVI Triage Tool (CAN3T) is a triage tool to assist clinicians in the prioritization of patients who should have timely access to TAVI. We anticipate that the CAN3T will be a valuable tool as it may improve equity in access to care, reduce preventable adverse events, and improve system efficiency.

Determinants of immunoglobulin G responses to respiratory syncytial virus and rhinovirus in children and adults

Introduction

Exposure to respiratory viruses is a significant cause of morbidity and affects virus-specific antibody levels. Little is known about determinants associated with immune response to these viruses. We aimed to investigate the determinants of respiratory syncytial virus (RSV)- and rhinovirus (RV)- specific IgG responses in both children and adults.

Methods

The study is based on the EGEA cohort, composed of 530 samples of children in EGEA1 (1991-95) and 1241 samples of adults in EGEA2 (2003-07). Cumulative RV-specific IgG levels (species A, B and C) and IgG levels to RSV-G protein were measured by using micro-array technoloy. Multiple linear mixed models (random effect to account for familial dependence) were performed to assess associations between age, sex, body mass index (BMI), tobacco smoke exposure and season of blood sampling with RSV-and RV-specific IgG levels.

Results

In children (11.1 ± 2.8 years old, 57% boys), higher RV-specific IgG levels were associated with older age (only for RV-B), female sex and lower BMI, while only older age was associated with higher RSV-specific IgG levels. In adults (43.5 ± 16.7 years old, 48% men), younger age, female sex, lower BMI, active smoking and all seasons except summer were associated with higher RV-specific IgG levels. Older age, active smoking and all seasons except summer were associated with higher RSV-specific IgG levels.

Conclusion

Personal and seasonal determinants of RSV- and RV-specific IgG levels seem to vary according to the respiratory virus type and between children and adults, suggesting different patterns of responses along the life course.

Who is more vulnerable to effects of long-term exposure to air pollution on COVID-19 hospitalisation?

OBJECTIVE

Factors that shape individuals' vulnerability to the effects of air pollution on COVID-19 severity remain poorly understood. We evaluated whether the association between long-term exposure to ambient NO2, PM2.5, and PM10 and COVID-19 hospitalisation differs by age, sex, individual income, area-level socioeconomic status, arterial hypertension, diabetes mellitus, and chronic obstructive pulmonary disease.

METHODS

We analysed a population-based cohort of 4,639,184 adults in Catalonia, Spain, during 2020. We fitted Cox proportional hazard models adjusted for several potential confounding factors and evaluated the interaction effect between vulnerability indicators and the 2019 annual average of NO2, PM2.5, and PM10. We evaluated interaction on both additive and multiplicative scales.

RESULTS

Overall, the association was additive between air pollution and the vulnerable groups. Air pollution and vulnerability indicators had a synergistic (greater than additive) effect for males and individuals with low income or living in the most deprived neighbourhoods. The Relative Excess Risk due to Interaction (RERI) was 0.21, 95 % CI, 0.15 to 0.27 for NO2 and 0.16, 95 % CI, 0.11 to 0.22 for PM2.5 for males; 0.13, 95 % CI, 0.09 to 0.18 for NO2 and 0.10, 95 % CI, 0.05 to 0.14 for PM2.5 for lower individual income and 0.17, 95 % CI, 0.12 to 0.22 for NO2 and 0.09, 95 % CI, 0.05 to 0.14 for PM2.5 for lower area-level socioeconomic status. Results for PM10 were similar to PM2.5. Results on multiplicative scale were inconsistent.

CONCLUSIONS

Long-term exposure to air pollution had a larger synergistic effect on COVID-19 hospitalisation for males and those with lower individual- and area-level socioeconomic status.

Air pollution, lung function and mortality: survival and mediation analyses in UK Biobank

Background

Air pollution is associated with lower lung function, and both are associated with premature mortality and cardiovascular disease (CVD). Evidence remains scarce on the potential mediating effect of impaired lung function on the association between air pollution and mortality or CVD.

Methods

We used data from UK Biobank (n∼200 000 individuals) with 8-year follow-up to mortality and incident CVD. Exposures to particulate matter <10 µm (PM10), particulate matter <2.5 µm (PM2.5) and nitrogen dioxide (NO2) were assessed by land-use regression modelling. Lung function (forced expiratory volume in 1 s (FEV1), forced vital capacity (FVC) and the FEV1/FVC ratio) was measured between 2006 and 2010 and transformed to Global Lung Function Initiative (GLI) z-scores. Adjusted Cox proportional hazards and causal proportional hazards mediation analysis models were fitted, stratified by smoking status.

Results

Lower FEV1 and FVC were associated with all-cause and CVD mortality, and incident CVD, with larger estimates in ever- than never-smokers (all-cause mortality hazard ratio per FEV1 GLI z-score decrease 1.29 (95% CI 1.24-1.34) for ever-smokers and 1.16 (95% CI 1.12-1.21) for never-smokers). Long-term exposure to PM2.5 or NO2 was associated with incident CVD, with similar effect sizes for ever- and never-smokers. Mediated proportions of the air pollution-all-cause mortality estimates driven by FEV1 were 18% (95% CI 2-33%) for PM2.5 and 27% (95% CI 3-51%) for NO2. Corresponding mediated proportions for incident CVD were 9% (95% CI 4-13%) for PM2.5 and 16% (95% CI 6-25%) for NO2.

Conclusions

Lung function may mediate a modest proportion of associations between air pollution and mortality and CVD outcomes. Results likely reflect the extent of either shared mechanisms or direct effects relating to lower lung function caused by air pollution.

Sex differences in post-acute neurological sequelae of SARS-CoV-2 and symptom resolution in adults after coronavirus disease 2019 hospitalization: an international multi-centre prospective observational study

Although it is known that coronavirus disease 2019 can present with a range of neurological manifestations and in-hospital complications, sparse data exist on whether these initial neurological symptoms of coronavirus disease 2019 are closely associated with post-acute neurological sequelae of SARS-CoV-2 (severe acute respiratory syndrome coronavirus 2; PANSC) and whether female versus male sex impacts symptom resolution. In this international, multi-centre, prospective, observational study across 407 sites from 15 countries (30 January 2020 to 30 April 2022), we report the prevalence and risk factors of PANSC among hospitalized adults and investigate the differences between males and females on neurological symptom resolution over time. PANSC symptoms included altered consciousness/confusion, fatigue/malaise, anosmia, dysgeusia and muscle ache/joint pain, on which information was collected at index hospitalization and during follow-up assessments. The analysis considered a time to the resolution of individual and all neurological symptoms. The resulting times were modelled by Weibull regression, assuming mixed-case interval censoring, with sex and age included as covariates. The model results were summarized as cumulative probability functions and age-adjusted and sex-adjusted median times to resolution. We included 6862 hospitalized adults with coronavirus disease 2019, who had follow-up assessments. The median age of the participants was 57 years (39.2% females). Males and females had similar baseline characteristics, except that more males (versus females) were admitted to the intensive care unit (30.5 versus 20.3%) and received mechanical ventilation (17.2 versus 11.8%). Approximately 70% of patients had multiple neurological symptoms at the first follow-up (median = 102 days). Fatigue (49.9%) and myalgia/arthralgia (45.2%) were the most prevalent symptoms of PANSC at the initial follow-up. The reported prevalence in females was generally higher (versus males) for all symptoms. At 12 months, anosmia and dysgeusia were resolved in most patients, although fatigue, altered consciousness and myalgia remained unresolved in >10% of the cohort. Females had a longer time to the resolution (5.2 versus 3.4 months) of neurological symptoms at follow-up for those with more than one neurological symptom. In the multivariable analysis, males were associated with a shorter time to the resolution of symptoms (hazard ratio = 1.53; 95% confidence interval = 1.39-1.69). Intensive care unit admission was associated with a longer time to the resolution of symptoms (hazard ratio = 0.68; 95% confidence interval = 0.60-0.77). Post-discharge stroke was uncommon (0.3% in females and 0.5% in males). Despite the methodological challenges involved in the collection of survey data, this international multi-centre prospective cohort study demonstrated that PANSC following index hospitalization was high. Symptom prevalence was higher and took longer to resolve in females than in males. This supported the fact that while males were sicker during acute illness, females were disproportionately affected by PANSC.

Social Inequalities in Long-Term Health Effects After COVID-19-A Scoping Review

Objectives: We aimed to map and synthesize evidence about social inequalities in long-term health effects after COVID-19 (LTHE), often referred to as "long COVID" or "post-COVID-19 conditions." Methods: We conducted a scoping review of peer-reviewed articles by searching the databases Embase and Scopus. According to predefined inclusion criteria, titles/abstracts and full texts were screened for eligibility. Additionally, reference lists of all included studies were hand-searched for eligible studies. This study followed the PRISMA guidelines for scoping reviews. Results: Nineteen articles were included. LTHE were analysed according to ethnicity, education, income, employment and deprivation indices. The studies varied significantly in their definitions of LTHE. Eighty-two analyses showed no statistically significant associations. At least 12 studies had a high risk of type II errors. Only studies associating deprivation indices and long COVID tended to show a higher prevalence of LTHE in deprived areas. Conclusion: Although some studies indicated social inequalities in LTHE, evidence was generally weak and inconclusive. Further studies with larger sample sizes specifically designed to detect social inequalities regarding LTHE are needed to inform future healthcare planning and public health policies.

Development and validation of a risk model for hospital-acquired venous thrombosis: the Medical Inpatients Thrombosis and Hemostasis study

BACKGROUND

Regulatory organizations recommend assessing hospital-acquired (HA) venous thromboembolism (VTE) risk for medical inpatients.

OBJECTIVES

To develop and validate a risk assessment model (RAM) for HA-VTE in medical inpatients using objective and assessable risk factors knowable at admission.

METHODS

The development cohort included people admitted to medical services at the University of Vermont Medical Center (Burlington, Vermont) between 2010 and 2019, and the validation cohorts included people admitted to Hennepin County Medical Center (Minneapolis, Minnesota), University of Michigan Medical Center (Ann Arbor, Michigan), and Harris Health Systems (Houston, Texas). Individuals with VTE at admission, aged <18 years, and admitted for <1 midnight were excluded. We used a Bayesian penalized regression technique to select candidate HA-VTE risk factors for final inclusion in the RAM.

RESULTS

The development cohort included 60 633 admissions and 227 HA-VTE, and the validation cohorts included 111 269 admissions and 651 HA-VTE. Seven HA-VTE risk factors with t statistics ≥1.5 were included in the RAM: history of VTE, low hemoglobin level, elevated creatinine level, active cancer, hyponatremia, increased red cell distribution width, and malnutrition. The areas under the receiver operating characteristic curve and calibration slope were 0.72 and 1.10, respectively. The areas under the receiver operating characteristic curve and calibration slope were 0.70 and 0.93 at Hennepin County Medical Center, 0.70 and 0.87 at the University of Michigan Medical Center, and 0.71 and 1.00 at Harris Health Systems, respectively. The RAM performed well stratified by age, sex, and race.

CONCLUSION

We developed and validated a RAM for HA-VTE in medical inpatients. By quantifying risk, clinicians can determine the potential benefits of measures to reduce HA-VTE.

Integration of individualized and population-level molecular epidemiology data to model COVID-19 outcomes

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants with enhanced transmissibility and immune escape have emerged periodically throughout the coronavirus disease 2019 (COVID-19) pandemic, but the impact of these variants on disease severity has remained unclear. In this single-center, retrospective cohort study, we examined the association between SARS-CoV-2 clade and patient outcome over a two-year period in Chicago, Illinois. Between March 2020 and March 2022, 14,252 residual diagnostic specimens were collected from SARS-CoV-2-positive inpatients and outpatients alongside linked clinical and demographic metadata, of which 2,114 were processed for viral whole-genome sequencing. When controlling for patient demographics and vaccination status, several viral clades were associated with risk for hospitalization, but this association was negated by the inclusion of population-level confounders, including case count, sampling bias, and shifting standards of care. These data highlight the importance of integrating non-virological factors into disease severity and outcome models for the accurate assessment of patient risk.

Prospective study design and data analysis in UK Biobank

Population-based prospective studies, such as UK Biobank, are valuable for generating and testing hypotheses about the potential causes of human disease. We describe how UK Biobank's study design, data access policies, and approaches to statistical analysis can help to minimize error and improve the interpretability of research findings, with implications for other population-based prospective studies being established worldwide.

Estimating the heritability of SARS-CoV-2 susceptibility and COVID-19 severity

SARS-CoV-2 has infected over 340 million people, prompting therapeutic research. While genetic studies can highlight potential drug targets, understanding the heritability of SARS-CoV-2 susceptibility and COVID-19 severity can contextualize their results. To date, loci from meta-analyses explain 1.2% and 5.8% of variation in susceptibility and severity respectively. Here we estimate the importance of shared environment and additive genetic variation to SARS-CoV-2 susceptibility and COVID-19 severity using pedigree data, PCR results, and hospitalization information. The relative importance of genetics and shared environment for susceptibility shifted during the study, with heritability ranging from 33% (95% CI: 20%-46%) to 70% (95% CI: 63%-74%). Heritability was greater for days hospitalized with COVID-19 (41%, 95% CI: 33%-57%) compared to shared environment (33%, 95% CI: 24%-38%). While our estimates suggest these genetic architectures are not fully understood, the shift in susceptibility estimates highlights the challenge of estimation during a pandemic, given environmental fluctuations and vaccine introduction.

COVID-19 Convalescent Plasma Therapy: Long-term Implications

Background

The long-term effect of coronavirus disease 2019 (COVID-19) acute treatments on postacute sequelae of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection (PASC) is unknown. The CONTAIN-Extend study explores the long-term impact of COVID-19 convalescent plasma (CCP) therapy on postacute sequelae of SARS-CoV-2 infection (PASC) symptoms and general health 18 months following hospitalization.

Methods

The CONTAIN-Extend study examined 281 participants from the original CONTAIN COVID-19 trial (CONTAIN-RCT, NCT04364737) at 18 months post-hospitalization for acute COVID-19. Symptom surveys, global health assessments, and biospecimen collection were performed from November 2021 to October 2022. Multivariable logistic and linear regression estimated associations between the randomization arms and self-reported symptoms and Patient-Reported Outcomes Measurement Information System (PROMIS) scores and adjusted for covariables, including age, sex, race/ethnicity, disease severity, and CONTAIN enrollment quarter and sites.

Results

There were no differences in symptoms or PROMIS scores between CCP and placebo (adjusted odds ratio [aOR] of general symptoms, 0.95; 95% CI, 0.54-1.67). However, females (aOR, 3.01; 95% CI, 1.73-5.34), those 45-64 years (aOR, 2.55; 95% CI, 1.14-6.23), and April-June 2020 enrollees (aOR, 2.39; 95% CI, 1.10-5.19) were more likely to report general symptoms and have poorer PROMIS physical health scores than their respective reference groups. Hispanic participants (difference, -3.05; 95% CI, -5.82 to -0.27) and Black participants (-4.48; 95% CI, -7.94 to -1.02) had poorer PROMIS physical health than White participants.

Conclusions

CCP demonstrated no lasting effect on PASC symptoms or overall health in comparison to the placebo. This study underscores the significance of demographic factors, including sex, age, and timing of acute infection, in influencing symptom reporting 18 months after acute hypoxic COVID-19 hospitalization.

COVID-19 vaccination effectiveness in the population of Friuli Venezia Giulia, North-East Italy. Control of bias associated with divergent compliance to policies in a test-negative case-control study

BACKGROUND

Vaccine effectiveness (VE) studies consolidate knowledge of real-world effectiveness in different contexts. However, methodological issues may undermine their conclusions: to assess the VE against COVID-19 within the Italian population, a specific threat to validity is related to the consequences of divergent compliance to the Green Pass policy.

METHODS

To address this challenge we conducted a test negative case-control (TNCC) study and multiple sensitivity analysis among residents aged ≥ 12 in Friuli Venezia Giulia Region (FVG), North-east Italy, from February 1, 2021 to March 31, 2022. Information regarding 211,437 cases of COVID-19 infection and 845,748 matched controls was obtained from the regional computerized health database. The investigation considered: COVID-19 infection, hospitalization, and death. Multiple conditional logistic regressions adjusted for covariates were performed and VE was estimated as (1-OR COVID-19vaccinated vs. unvaccinated)x100. Mediation analyses were carried out to offset potential collider variables, particularly, the number of swabs performed after the introduction of pandemic restrictions.

RESULTS

Full-cycle VE against infection decreased from 96% (95% CI: 96, 97) in the Alpha period to 43% (95% CI: 42, 45) in the Omicron period. Booster dose raised the protection in Omicron period to 67% (95% CI: 66, 67). Against the evasive Omicron variant, the protection of the booster dose was 87% (95% CI: 83, 90) for hospitalization and 90% (95% CI: 82, 95) for death. The number of swabs performed was included as a covariate in the adjustments, and the mediation analysis confirmed that it was a strong mediator between vaccination and COVID-19-related outcomes.

CONCLUSIONS

The study suggests that, under similar TNCC settings, mediation analysis and adjustment for number of diagnostic tests should be included, as an effective approach to the challenge of differential testing behavior that may determine substantial selection bias. This correction allowed us to align with results from other studies that show how full-cycle VE against infection was initially high but decreased over time by variant circulation, counterbalanced by booster dose that raised protection across variants and outcome severity.

High-throughput target trial emulation for Alzheimer's disease drug repurposing with real-world data

Target trial emulation is the process of mimicking target randomized trials using real-world data, where effective confounding control for unbiased treatment effect estimation remains a main challenge. Although various approaches have been proposed for this challenge, a systematic evaluation is still lacking. Here we emulated trials for thousands of medications from two large-scale real-world data warehouses, covering over 10 years of clinical records for over 170 million patients, aiming to identify new indications of approved drugs for Alzheimer's disease. We assessed different propensity score models under the inverse probability of treatment weighting framework and suggested a model selection strategy for improved baseline covariate balancing. We also found that the deep learning-based propensity score model did not necessarily outperform logistic regression-based methods in covariate balancing. Finally, we highlighted five top-ranked drugs (pantoprazole, gabapentin, atorvastatin, fluticasone, and omeprazole) originally intended for other indications with potential benefits for Alzheimer's patients.

Social determinants of ethnic disparities in SARS-CoV-2 infection: UK Biobank SARS-CoV-2 Serology Study

BACKGROUND

The social determinants of ethnic disparities in risk of SARS-CoV-2 infection during the first wave of the pandemic in the UK remain unclear.

METHODS

In May 2020, a total of 20 195 adults were recruited from the general population into the UK Biobank SARS-CoV-2 Serology Study. Between mid-May and mid-November 2020, participants provided monthly blood samples. At the end of the study, participants completed a questionnaire on social factors during different periods of the pandemic. Logistic regression yielded ORs for the association between ethnicity and SARS-CoV-2 immunoglobulin G antibodies (indicating prior infection) using blood samples collected in July 2020, immediately after the first wave.

RESULTS

After exclusions, 14 571 participants (mean age 56; 58% women) returned a blood sample in July, of whom 997 (7%) had SARS-CoV-2 antibodies. Seropositivity was strongly related to ethnicity: compared with those of White ethnicity, ORs (adjusted for age and sex) for Black, South Asian, Chinese, Mixed and Other ethnic groups were 2.66 (95% CI 1.94-3.60), 1.66 (1.15-2.34), 0.99 (0.42-1.99), 1.42 (1.03-1.91) and 1.79 (1.27-2.47), respectively. Additional adjustment for social factors reduced the overall likelihood ratio statistics for ethnicity by two-thirds (67%; mostly from occupational factors and UK region of residence); more precise measurement of social factors may have further reduced the association.

CONCLUSIONS

This study identifies social factors that are likely to account for much of the ethnic disparities in SARS-CoV-2 infection during the first wave in the UK, and highlights the particular relevance of occupation and residential region in the pathway between ethnicity and SARS-CoV-2 infection.

Demographic Characteristics of Unvaccinated Asymptomatic and Symptomatic SARS-CoV-2 Cases in Barwon South West, Victoria, Australia

We investigated 328 SARS-CoV-2 cases in Barwon South West, Victoria, Australia, in the 2020 pre-vaccination period, comparing infections with symptoms to those that remained asymptomatic. De-identified self-reported data on case characteristics and symptom progression from three sequential questionnaires were examined. Multivariable logistic regression was used to model associations between demographic profiles and symptoms. Asymptomatic infections were more than three times as likely to be seen in ethnic minority groups than the Caucasian population after adjusting for gender and age [OR 3.2, 95% CI 1.5-6.7, p < 0.01] and were more common among cases of Asian background [OR 2.8, 95%CI 1.2-6.4]. Asymptomatic infections were also more common in youth and younger adults, but cases were approximately seven times more likely to be in seniors (≥65 years) compared with those 24 years of age or younger after adjusting for sex and ethnicity [OR 6.9, 95% CI 1.3-35.8]. The overrepresentation of ethnic minority groups among asymptomatic infections is suggestive of genetic haplotype variability by ethnic group, conferring greater cross-protection from other coronaviruses in the initial phase of the COVID-19 pandemic. Replication of this analysis in the post-vaccination era and reassessment of symptom expression according to ethnicity in a community with established vaccine and infection-induced immunity would determine whether this is a sustained association or one confined to the early stages of a pandemic in an immunologically naive population. These findings may, in part, reflect differences in testing patterns by ethnicity and true differences in disease expression, both of which are important to understand in order to inform transmission prevention strategies and tailored risk messaging according to ethnic background.

Uncovering associations between pre-existing conditions and COVID-19 Severity: A polygenic risk score approach across three large biobanks

OBJECTIVE

To overcome the limitations associated with the collection and curation of COVID-19 outcome data in biobanks, this study proposes the use of polygenic risk scores (PRS) as reliable proxies of COVID-19 severity across three large biobanks: the Michigan Genomics Initiative (MGI), UK Biobank (UKB), and NIH All of Us. The goal is to identify associations between pre-existing conditions and COVID-19 severity.

METHODS

Drawing on a sample of more than 500,000 individuals from the three biobanks, we conducted a phenome-wide association study (PheWAS) to identify associations between a PRS for COVID-19 severity, derived from a genome-wide association study on COVID-19 hospitalization, and clinical pre-existing, pre-pandemic phenotypes. We performed cohort-specific PRS PheWAS and a subsequent fixed-effects meta-analysis.

RESULTS

The current study uncovered 23 pre-existing conditions significantly associated with the COVID-19 severity PRS in cohort-specific analyses, of which 21 were observed in the UKB cohort and two in the MGI cohort. The meta-analysis yielded 27 significant phenotypes predominantly related to obesity, metabolic disorders, and cardiovascular conditions. After adjusting for body mass index, several clinical phenotypes, such as hypercholesterolemia and gastrointestinal disorders, remained associated with an increased risk of hospitalization following COVID-19 infection.

CONCLUSION

By employing PRS as a proxy for COVID-19 severity, we corroborated known risk factors and identified novel associations between pre-existing clinical phenotypes and COVID-19 severity. Our study highlights the potential value of using PRS when actual outcome data may be limited or inadequate for robust analyses.

Cigarette smoking and risk of severe infectious respiratory diseases in UK adults: 12-year follow-up of UK biobank

BACKGROUND

The relevance of tobacco smoking for infectious respiratory diseases (IRD) is uncertain. We investigated the associations of cigarette smoking with severe IRD resulting in hospitalization or death in UK adults.

METHODS

We conducted a prospective study of cigarette smoking and risk of severe IRD in UK Biobank. The outcomes included pneumonia, other acute lower respiratory tract infections (OA-LRTI) and influenza. Multivariable Cox regression analyses were used to estimate hazard ratios (HRs) of severe IRD associated with smoking habits after adjusting for confounding factors.

RESULTS

Among 341 352 participants with no prior history of major chronic diseases, there were 12 384 incident cases with pneumonia, 7054 with OA-LRTI and 795 with influenza during a 12-year follow-up. Compared with non-smokers, current smoking was associated with ⁓2-fold higher rates of severe IRD (HR 2.40 [2.27-2.53] for pneumonia, 1.99 [1.84-2.14] for OA-LRTI and 1.82 [95% confidence interval: 1.47-2.24] for influenza). Incidence of all severe IRDs were positively associated with amount of cigarettes smoked. The HRs for each IRD (except influenza) also declined with increasing duration since quitting.

CONCLUSIONS

Current cigarette smoking was positively associated with higher rates of IRD and the findings extend indications for tobacco control measures and vaccination of current smokers for prevention of severe IRD.