Living risk prediction algorithm (QCOVID) for risk of hospital admission and mortality from coronavirus 19 in adults: national derivation and validation cohort study

The characteristics of TCR CDR3 repertoire in COVID-19 patients and SARS-CoV-2 vaccine recipients

The COVID-19 pandemic and large-scale administration of multiple SARS-CoV-2 vaccines have attracted global attention to the short-term and long-term effects on the human immune system. An analysis of the "traces" left by the body's T-cell immune response is needed, especially for the prevention and treatment of breakthrough infections and long COVID-19 and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variant infections. T-cell receptor complementarity determining region 3 (TCR CDR3) repertoire serves as a target molecule for monitoring the effects, mechanisms, and memory of the T-cell response. Furthermore, it has been extensively applied in the elucidation of the infectious mechanism and vaccine refinement of hepatitis B virus (HBV), influenza virus, human immunodeficiency virus (HIV), and SARS-CoV. Laboratories worldwide have utilized high-throughput sequencing (HTS) and scTCR-seq to characterize, share, and apply the TCR CDR3 repertoire in COVID-19 patients and SARS-CoV-2 vaccine recipients. This article focuses on the comparative analysis of the diversity, clonality, V&J gene usage and pairing, CDR3 length, shared CDR3 sequences or motifs, and other characteristics of TCR CDR3 repertoire. These findings provide molecular targets for evaluating T-cell response effects and short-term and long-term impacts on the adaptive immune system following SARS-CoV-2 infection or vaccination and establish a comparative archive of T-cell response "traces."

Development and validation of a risk prediction model for hospital admission in COVID-19 patients presenting to primary care

BACKGROUND

There is a paucity of prognostic models for COVID-19 that are usable for in-office patient assessment in general practice (GP).

OBJECTIVES

To develop and validate a risk prediction model for hospital admission with readily available predictors.

METHODS

A retrospective cohort study linking GP records from 8 COVID-19 centres and 55 general practices in the Netherlands to hospital admission records. The development cohort spanned March to June 2020, the validation cohort March to June 2021. The primary outcome was hospital admission within 14 days. We used geographic leave-region-out cross-validation in the development cohort and temporal validation in the validation cohort.

RESULTS

In the development cohort, 4,806 adult patients with COVID-19 consulted their GP (median age 56, 56% female); in the validation cohort 830 patients did (median age 56, 52% female). In the development and validation cohort respectively, 292 (6.1%) and 126 (15.2%) were admitted to the hospital within 14 days, respectively. A logistic regression model based on sex, smoking, symptoms, vital signs and comorbidities predicted hospital admission with a c-index of 0.84 (95% CI 0.83 to 0.86) at geographic cross-validation and 0.79 (95% CI 0.74 to 0.83) at temporal validation, and was reasonably well calibrated (intercept -0.08, 95% CI -0.98 to 0.52, slope 0.89, 95% CI 0.71 to 1.07 at geographic cross-validation and intercept 0.02, 95% CI -0.21 to 0.24, slope 0.82, 95% CI 0.64 to 1.00 at temporal validation).

CONCLUSION

We derived a risk model using readily available variables at GP assessment to predict hospital admission for COVID-19. It performed accurately across regions and waves. Further validation on cohorts with acquired immunity and newer SARS-CoV-2 variants is recommended.

Risk of death in England following a positive SARS-CoV-2 test: A retrospective national cohort study (March 2020 to September 2022)

BACKGROUND

We aimed to estimate the relative risk of mortality following a first positive SARS-CoV-2 test during the first, second, and third waves of the COVID-19pandemic in England by age, sex, and vaccination status, taking into account pre-existing health conditions and lifestyle factors.

METHODS

We conducted a retrospective cohort study of all individuals registered with the National Health Service (NHS) in England from 1 March 2020 to September 2022. Data for all individuals were obtained and linked including primary care records, hospital admission episodes, SARS-CoV-2 test results, vaccinations, and death registrations. We fitted Cox Proportional Hazards models with time dependent covariates for confirmed SARS-CoV-2 infection to model the risk of subsequent mortality.

RESULTS

The hazard ratio for death after testing positive for subsequent, compared with those not testing positive, amongst unvaccinated individuals, ranged from 11 to 89 by age and sex, in the first four weeks following a positive test in wave one and reduced to 14 to 50 in wave three. This hazard was further reduced amongst those who had three vaccines to between 1.4 and 7 in wave three.

CONCLUSIONS

This study provides robust estimates of increased mortality risk among those who tested positive over the first three waves of the COVID-19 pandemic in England. The estimates show the impact of various factors affecting the risk of mortality from COVID-19. The results provide the first step towards estimating the magnitude and pattern of mortality displacement due to COVID-19, which is essential to understanding subsequent mortality rates in England.

Lung field-based severity score (LFSS): a feasible tool to identify COVID-19 patients at high risk of progressing to critical disease

Background

Coronavirus disease 2019 (COVID-19) still poses a threat to people's physical and mental health. We proposed a new semi-quantitative visual classification method for COVID-19, and this study aimed to evaluate the clinical usefulness and feasibility of lung field-based severity score (LFSS).

Methods

This retrospective study included 794 COVID-19 patients from two hospitals in China between December 2022 and January 2023. Six lung fields on the axial computed tomography (CT) were defined. LFSS and eighteen clinical characteristics were evaluated. LFSS was based on summing up the parenchymal opacification involving each lung field, which was scored as 0 (0%), 1 (1-24%), 2 (25-49%), 3 (50-74%), or 4 (75-100%), respectively (range of LFSS from 0 to 24). Total pneumonia burden (TPB) was calculated using the U-net model. The correlation between LFSS and TPB was analyzed. After performing logistic regression analysis, an LFSS-based model, clinical-based model and combined model were developed. Receiver operating characteristic curves were used to evaluate and compare the performance of three models.

Results

LFSS, age, chronic liver disease, chronic kidney disease, white blood cell, neutrophils, lymphocytes and C-reactive protein differed significantly between the non-critical and critical group (all P<0.05). There was a strong positive correlation of LFSS and TPB (Pearson correlation coefficient =0.767, P<0.001). The area under curves of LFSS-based model, clinical-based model and combined model were 0.799 [95% confidence interval (CI): 0.770-0.827], 0.758 (95% CI: 0.727-0.788), and 0.848 (95% CI: 0.821-0.872), respectively.

Conclusions

The LFSS derived from chest CT may be a potential new tool to help identify COVID-19 patients at high risk of progressing to critical disease.

Vaccinations, cardiovascular drugs, hospitalization, and mortality in COVID-19 and Long COVID

OBJECTIVE

To identify highest-risk subgroups for COVID-19 and Long COVID(LC), particularly in contexts of influenza and cardiovascular disease(CVD).

METHODS

Using national, linked electronic health records for England (NHS England Secure Data Environment via CVD-COVID-UK/COVID-IMPACT Consortium), we studied individuals (of all ages) with COVID-19 and LC (2020-2023). We compared all-cause hospitalization and mortality by prior CVD, high CV risk, vaccination status (COVID-19/influenza), and CVD drugs, investigating impact of vaccination and CVD prevention using population preventable fractions.

RESULTS

Hospitalization and mortality were 15.3% and 2.0% among 17,373,850 individuals with COVID-19 (LC rate 1.3%), and 16.8% and 1.4% among 301,115 with LC. Adjusted risk of mortality and hospitalization were reduced with COVID-19 vaccination ≥ 2 doses(COVID-19:HR 0.36 and 0.69; LC:0.44 and 0.90). With influenza vaccination, mortality was reduced, but not hospitalization (COVID-19:0.86 and 1.01, and LC:0.72 and 1.05). Mortality and hospitalization were reduced by CVD prevention in those with CVD, e.g., anticoagulants- COVID:19:0.69 and 0.92; LC:0.59 and 0.88; lipid lowering- COVID-19:0.69 and 0.86; LC:0.68 and 0.90. COVID-19 vaccination averted 245044 of 321383 and 7586 of 8738 preventable deaths after COVID-19 and LC, respectively.

INTERPRETATION

Prior CVD and high CV risk are associated with increased hospitalization and mortality in COVID-19 and LC. Targeted COVID-19 vaccination and CVD prevention are priority interventions.

FUNDING

NIHR. HDR UK.

Serum 25-hydroxyvitamin D levels and health outcomes of hospitalization owing to COVID-19: a retrospective cross-sectional study

OBJECTIVE

We investigated the role of serum 25(OH)D (25-hydroxyvitamin D) in COVID-related health outcomes.

METHODS

We conducted a retrospective cross-sectional study using data of the National Center of Disease Control and Public Health, Georgia. We extracted patient data including length of hospital stay, transfer to the intensive care unit, requirement for oxygen therapy, treatment with glucocorticoids, and symptoms. After obtaining written informed consent, 384 individuals were enrolled. We divided participants into three groups according to 25(OH)D levels: group 1 = 25(OH)D <12 ng/mL (n = 83), group 2 = 25(OH)D 12-20 ng/mL (n = 141), and group 3 = 25(OH)D >20 ng/mL (n = 160).

RESULTS

The odds ratio (OR) for hospitalization in group 1 versus group 2 was 8.7 (95% confidence interval [CI] 3.6-21.3) and 5.6 for group 1 versus 3 (95% CI 2.7-11.9). Regarding oxygen therapy, OR = 28.41 for group 1 versus 2 (95% CI 3.7-220.5) and OR = 5.2 for group 1 versus 3 (95% CI 1.9-14.1). Regarding treatment with glucocorticoids, OR = 3.7 for group 1 versus 2 (95% CI 1.1-12.5) and OR = 8.4 for group 1 versus 3 (95% CI 1.8-40.7).

CONCLUSION

COVID-19-related morbidity was associated with decreased serum 25(OH)D levels. Future studies should investigate the potential role of vitamin D sufficiency in preventing SARS-CoV-2 infection and mortality.

White blood cells scattergram as a valuable tool for COVID-19 screening: A multicentric study

INTRODUCTION

New tools have been developed to distinguish the COVID-19 diagnosis from other viral infections presenting similar symptomatology and mitigate the lack of sensitivity of molecular testing. We previously identified a specific "sandglass" aspect on the white blood cells (WBC) scattergram of COVID-19 patients, as a highly reliable COVID-19 screening test (sensitivity: 85.9%, specificity: 83.5% and positive predictive value: 94.3%). We then decided to validate our previous data in a multicentric study.

METHODS

This retrospective study involved 817 patients with flu-like illness, among 20 centers, using the same CBC instrument (XN analyzer, SYSMEX, Japan). After training, one specialist per center independently evaluated, under the same conditions, the presence of the "sandglass" aspect of the WDF scattergram, likely representing plasmacytoid lymphocytes.

RESULTS

Overall, this approach showed sensitivity: 59.0%, specificity: 72.9% and positive predictive value: 77.7%. Sensitivity improved with subgroup analysis, including in patients with lymphopenia (65.2%), patients presenting symptoms for more than 5 days (72.3%) and in patients with ARDS (70.1%). COVID-19 patients with larger plasmacytoid lymphocyte cluster (>15 cells) more often have severe outcomes (70% vs. 15% in the control group).

CONCLUSION

Our findings confirm that the WBC scattergram analysis could be added to a diagnostic algorithm for screening and quickly categorizing symptomatic patients as either COVID-19 probable or improbable, especially during COVID-19 resurgence and overlapping with future influenza epidemics. The observed large size of the plasmacytoid lymphocytes cluster appears to be a hallmark of COVID-19 patients and was indicative of a severe outcome. Furthers studies are ongoing to evaluate the value of the new hematological parameters in combination with WDF analysis.

Alterations of plasma metabolomes and their correlations with immunogenicity in maintenance hemodialysis patients receiving different COVID-19 vaccine regimens

Maintenance hemodialysis (MHD) patients exhibit compromised immune responses, leading to lower immunogenicity to the COVID-19 vaccine than the general population. The metabolomic factors influencing COVID-19 vaccine response in MHD patients remain elusive. A cross-sectional study was conducted with 30 MHD patients, divided into three vaccine regimen groups (N= 10 per group): homologous CoronaVac® (SV-SV), homologous ChAdOx1 nCoV-19 (AZ-AZ), and heterologous prime-boost (SV-AZ). Plasma samples were collected at baseline and at 28 days after the final dose to analyze 92 metabolomic levels using targeted metabolomics. The study included 30 MHD patients (mean age 56.67 ± 10.79 years) with similar neutralizing antibody (nAb) levels across vaccine regimens. The most significant differences in metabolomics were found between AZ-AZ and SV-SV, followed by SV-AZ versus SV-SV, and AZ-AZ versus SV-AZ. Overall, the metabolomic changes involved amino acids like glutamate and phenylalanine, and phospholipids. Prevaccination metabolomic profiles, including PG (38:1), lysoPE (20:2), lysoPC (18:2), lysoPI (18:1), and PC (34:2), exhibited negative correlations with postvaccination nAb levels. Different COVID-19 vaccine regimens had unique interactions with the immune response in MHD patients. Amino acid and phospholipid metabolisms play crucial roles in nAb formation, with the phospholipid metabolism being a potentially predictive marker of vaccine immunogenicity among MHD patients.

The digital divide between primary and secondary care: An analysis using SARS-CoV-2 hospital admissions

Using data from two ED. departments of 773 patients admitted with SARS-CoV-2, ICD-10 codes derived from the General Practitioner - Summary Care Record (GP-SCR) and Emergency Department (ED.) records were analysed for code discrepancies and whether this related to increased mortality. The average number of ICD-10 codes in both GP-SCR and ED. records was higher for patients who died than patients who survived (all p < .0001). Pre-existing GP digital data provides a better prediction of mortality than data collected manually during admission clerking in the ED. Up to 78.47% of GP-SCR codes were missed in the ED. records and up to 45.49% of the ED. record codes were not in the GP-SCR. A subset of missed ICD-10 codes were identified as being able to predict outcome; a trend towards increasing death rate as the proportion of missed codes increases. Initiatives to make the GP-SCR available to the wider healthcare community should improve patient care and reduce bias during development of machine learning based algorithms.

Risk of winter hospitalisation and death from acute respiratory infections in Scotland: national retrospective cohort study

OBJECTIVES

We undertook a national analysis to characterise and identify risk factors for acute respiratory infections (ARIs) resulting in hospitalisation during the winter period in Scotland.

DESIGN

A population-based retrospective cohort analysis.

SETTING

Scotland.

PARTICIPANTS

The study involved 5.4 million residents in Scotland.

MAIN OUTCOME MEASURES

Cox proportional hazard models were used to estimate adjusted hazard ratios (aHRs) and 95% confidence intervals (CIs) for the association between risk factors and ARI hospitalisation.

RESULTS

Between 1 September 2022 and 31 January 2023, there were 22,284 (10.9% of 203,549 with any emergency hospitalisation) ARI hospitalisations (1759 in children and 20,525 in adults) in Scotland. Compared with the reference group of children aged 6-17 years, the risk of ARI hospitalisation was higher in children aged 3-5 years (aHR = 4.55; 95% CI: 4.11-5.04). Compared with those aged 25-29 years, the risk of ARI hospitalisation was highest among the oldest adults aged ≥80 years (aHR = 7.86; 95% CI: 7.06-8.76). Adults from more deprived areas (most deprived vs. least deprived, aHR = 1.64; 95% CI: 1.57-1.72), with existing health conditions (≥5 vs. 0 health conditions, aHR = 4.84; 95% CI: 4.53-5.18) or with history of all-cause emergency admissions (≥6 vs. 0 previous emergency admissions, aHR = 7.53; 95% CI: 5.48-10.35) were at a higher risk of ARI hospitalisations. The risk increased by the number of existing health conditions and previous emergency admission. Similar associations were seen in children.

CONCLUSIONS

Younger children, older adults, those from more deprived backgrounds and individuals with greater numbers of pre-existing conditions and previous emergency admission were at increased risk for winter hospitalisations for ARI.

Association between antibody responses post-vaccination and severe COVID-19 outcomes in Scotland

Several population-level studies have described individual clinical risk factors associated with suboptimal antibody responses following COVID-19 vaccination, but none have examined multimorbidity. Others have shown that suboptimal post-vaccination responses offer reduced protection to subsequent SARS-CoV-2 infection; however, the level of protection from COVID-19 hospitalisation/death remains unconfirmed. We use national Scottish datasets to investigate the association between multimorbidity and testing antibody-negative, examining the correlation between antibody levels and subsequent COVID-19 hospitalisation/death among double-vaccinated individuals. We found that individuals with multimorbidity ( ≥ five conditions) were more likely to test antibody-negative post-vaccination and 13.37 [6.05-29.53] times more likely to be hospitalised/die from COVID-19 than individuals without conditions. We also show a dose-dependent association between post-vaccination antibody levels and COVID-19 hospitalisation or death, with those with undetectable antibody levels at a significantly higher risk (HR 9.21 [95% CI 4.63-18.29]) of these serious outcomes compared to those with high antibody levels.

Uptake, effectiveness and safety of COVID-19 vaccines in individuals at clinical risk due to immunosuppressive drug therapy or transplantation procedures: a population-based cohort study in England

BACKGROUND

Immunocompromised individuals are at increased risk of severe COVID-19 outcomes, underscoring the importance of COVID-19 vaccination in this population. The lack of comprehensive real-world data on vaccine uptake, effectiveness and safety in these individuals presents a critical knowledge gap, highlighting the urgency to better understand and address the unique challenges faced by immunocompromised individuals in the context of COVID-19 vaccination.

METHODS

We analysed data from 12,274,946 people in the UK aged > 12 years from 01/12/2020 to 11/04/2022. Of these, 583,541 (4.8%) were immunocompromised due to immunosuppressive drugs, organ transplants, dialysis or chemotherapy. We undertook a cohort analysis to determine COVID-19 vaccine uptake, nested case-control analyses adjusted for comorbidities and sociodemographic characteristics to determine effectiveness of vaccination against COVID-19 hospitalisation, ICU admission and death, and a self-controlled case series assessing vaccine safety for pre-specified adverse events of interest.

RESULTS

Overall, 93.7% of immunocompromised individuals received at least one COVID-19 vaccine dose, with 80.4% having received three or more doses. Uptake reduced with increasing deprivation (hazard ratio [HR] 0.78 [95%CI 0.77-0.79] in the most deprived quintile compared to the least deprived quintile for the first dose). Estimated vaccine effectiveness against COVID-19 hospitalisation 2-6 weeks after the second and third doses compared to unvaccinated was 78% (95%CI 72-83) and 91% (95%CI 88-93) in the immunocompromised population, versus 85% (95%CI 83-86) and 86% (95%CI 85-89), respectively, for the general population. Results showed COVID-19 vaccines were protective against intensive care unit (ICU) admission and death in both populations, with effectiveness of over 92% against COVID-19-related death and up to 95% in reducing ICU admissions for both populations following the third dose. COVID-19 vaccines were generally safe for immunocompromised individuals, though specific doses of ChAdOx1, mRNA-1273 and BNT162b2 raised risks of specific cardiovascular/neurological conditions.

CONCLUSIONS

COVID-19 vaccine uptake is high in immunocompromised individuals on immunosuppressive drug therapy or who have undergone transplantation procedures, with documented disparities by deprivation. Findings suggest that COVID-19 vaccines are protective against severe COVID-19 outcomes in this vulnerable population, and show a similar safety profile in immunocompromised individuals and the general population, despite some increased risk of adverse events. These results underscore the importance of ongoing vaccination prioritisation for this clinically at-risk population to maximise protection against severe COVID-19 outcomes.

Epilepsy and the risk of COVID-19-related hospitalization and death: A population study

OBJECTIVE

People with epilepsy (PWE) may be at an increased risk of severe COVID-19. It is important to characterize this risk to inform PWE and for future health and care planning. We assessed whether PWE were at higher risk of being hospitalized with, or dying from, COVID-19.

METHODS

We performed a retrospective cohort study using linked, population-scale, anonymized electronic health records from the SAIL (Secure Anonymised Information Linkage) databank. This includes hospital admission and demographic data for the complete Welsh population (3.1 million) and primary care records for 86% of the population. We identified 27 279 PWE living in Wales during the study period (March 1, 2020 to June 30, 2021). Controls were identified using exact 5:1 matching (sex, age, and socioeconomic status). We defined COVID-19 deaths as having International Classification of Diseases, 10th Revision (ICD-10) codes for COVID-19 on death certificates or occurring within 28 days of a positive SARS-CoV-2 polymerase chain reaction (PCR) test. COVID-19 hospitalizations were defined as having a COVID-19 ICD-10 code for the reason for admission or occurring within 28 days of a positive SARS-CoV-2 PCR test. We recorded COVID-19 vaccinations and comorbidities known to increase the risk of COVID-19 hospitalization and death. We used Cox proportional hazard models to calculate hazard ratios.

RESULTS

There were 158 (.58%) COVID-19 deaths and 933 (3.4%) COVID-19 hospitalizations in PWE, and 370 (.27%) deaths and 1871 (1.4%) hospitalizations in controls. Hazard ratios for COVID-19 death and hospitalization in PWE compared to controls were 2.15 (95% confidence interval [CI] = 1.78-2.59) and 2.15 (95% CI = 1.94-2.37), respectively. Adjusted hazard ratios (adjusted for comorbidities) for death and hospitalization were 1.32 (95% CI = 1.08-1.62) and 1.60 (95% CI = 1.44-1.78).

SIGNIFICANCE

PWE are at increased risk of being hospitalized with, and dying from, COVID-19 when compared to age-, sex-, and deprivation-matched controls, even when adjusting for comorbidities. This may have implications for prioritizing future COVID-19 treatments and vaccinations for PWE.

Interim 2023/2024 Season Influenza Vaccine Effectiveness in Primary and Secondary Care in the United Kingdom

BACKGROUND

We report 2023/2024 season interim influenza vaccine effectiveness for three studies, namely, primary care in Great Britain, hospital settings in Scotland and hospital settings in England.

METHODS

A test negative design was used to estimate vaccine effectiveness.

RESULTS

Estimated vaccine effectiveness against all influenzas ranged from 63% (95% confidence interval 46 to 75%) to 65% (41 to 79%) among children aged 2-17, from 36% (20 to 49%) to 55% (43 to 65%) among adults 18-64 and from 40% (29 to 50%) to 55% (32 to 70%) among adults aged 65 and over.

CONCLUSIONS

During a period of co-circulation of influenza A(H1N1)pdm09 and A(H3N2) in the United Kingdom, evidence for effectiveness of the influenza vaccine in both children and adults was found.

External validation of six COVID-19 prognostic models for predicting mortality risk in older populations in a hospital, primary care, and nursing home setting

OBJECTIVES

To systematically evaluate the performance of COVID-19 prognostic models and scores for mortality risk in older populations across three health-care settings: hospitals, primary care, and nursing homes.

STUDY DESIGN AND SETTING

This retrospective external validation study included 14,092 older individuals of ≥70 years of age with a clinical or polymerase chain reaction-confirmed COVID-19 diagnosis from March 2020 to December 2020. The six validation cohorts include three hospital-based (CliniCo, COVID-OLD, COVID-PREDICT), two primary care-based (Julius General Practitioners Network/Academisch network huisartsgeneeskunde/Network of Academic general Practitioners, PHARMO), and one nursing home cohort (YSIS) in the Netherlands. Based on a living systematic review of COVID-19 prediction models using Prediction model Risk Of Bias ASsessment Tool for quality and risk of bias assessment and considering predictor availability in validation cohorts, we selected six prognostic models predicting mortality risk in adults with COVID-19 infection (GAL-COVID-19 mortality, 4C Mortality Score, National Early Warning Score 2-extended model, Xie model, Wang clinical model, and CURB65 score). All six prognostic models were validated in the hospital cohorts and the GAL-COVID-19 mortality model was validated in all three healthcare settings. The primary outcome was in-hospital mortality for hospitals and 28-day mortality for primary care and nursing home settings. Model performance was evaluated in each validation cohort separately in terms of discrimination, calibration, and decision curves. An intercept update was performed in models indicating miscalibration followed by predictive performance re-evaluation.

MAIN OUTCOME MEASURE

In-hospital mortality for hospitals and 28-day mortality for primary care and nursing home setting.

RESULTS

All six prognostic models performed poorly and showed miscalibration in the older population cohorts. In the hospital settings, model performance ranged from calibration-in-the-large -1.45 to 7.46, calibration slopes 0.24-0.81, and C-statistic 0.55-0.71 with 4C Mortality Score performing as the most discriminative and well-calibrated model. Performance across health-care settings was similar for the GAL-COVID-19 model, with a calibration-in-the-large in the range of -2.35 to -0.15 indicating overestimation, calibration slopes of 0.24-0.81 indicating signs of overfitting, and C-statistic of 0.55-0.71.

CONCLUSION

Our results show that most prognostic models for predicting mortality risk performed poorly in the older population with COVID-19, in each health-care setting: hospital, primary care, and nursing home settings. Insights into factors influencing predictive model performance in the older population are needed for pandemic preparedness and reliable prognostication of health-related outcomes in this demographic.

Human Bronchial Epithelial Cell Transcriptome Changes in Response to Serum from Patients with Different Status of Inflammation

PURPOSE

To investigate the transcriptome of human bronchial epithelial cells (HBEC) in response to serum from patients with different degrees of inflammation.

METHODS

Serum from 19 COVID-19 patients obtained from the Hannover Unified Biobank was used. At the time of sampling, 5 patients had a WHO Clinical Progression Scale (WHO-CPS) score of 9 (severe illness). The remaining 14 patients had a WHO-CPS of below 9 (range 1-7), and lower illness. Multiplex immunoassay was used to assess serum inflammatory markers. The culture medium of HBEC was supplemented with 2% of the patient's serum, and the cells were cultured at 37 °C, 5% CO2 for 18 h. Subsequently, cellular RNA was used for RNA-Seq.

RESULTS

Patients with scores below 9 had significantly lower albumin and serum levels of E-selectin, IL-8, and MCP-1 than patients with scores of 9. Principal component analysis based on 500 "core genes" of RNA-seq segregated cells into two subsets: exposed to serum from 4 (I) and 15 (II) patients. Cells from a subset (I) treated with serum from 4 patients with a score of 9 showed 5566 differentially expressed genes of which 2793 were up- and 2773 downregulated in comparison with cells of subset II treated with serum from 14 patients with scores between 1 and 7 and one with score = 9. In subset I cells, a higher expression of TLR4 and CXCL8 but a lower CDH1, ACE2, and HMOX1, and greater effects on genes involved in metabolic regulation, cytoskeletal organization, and kinase activity pathways were observed.

CONCLUSION

This simple model could be useful to characterize patient serum and epithelial cell properties.

Ethnicity data resource in population-wide health records: completeness, coverage and granularity of diversity

Intersectional social determinants including ethnicity are vital in health research. We curated a population-wide data resource of self-identified ethnicity data from over 60 million individuals in England primary care, linking it to hospital records. We assessed ethnicity data in terms of completeness, consistency, and granularity and found one in ten individuals do not have ethnicity information recorded in primary care. By linking to hospital records, ethnicity data were completed for 94% of individuals. By reconciling SNOMED-CT concepts and census-level categories into a consistent hierarchy, we organised more than 250 ethnicity sub-groups including and beyond "White", "Black", "Asian", "Mixed" and "Other, and found them to be distributed in proportions similar to the general population. This large observational dataset presents an algorithmic hierarchy to represent self-identified ethnicity data collected across heterogeneous healthcare settings. Accurate and easily accessible ethnicity data can lead to a better understanding of population diversity, which is important to address disparities and influence policy recommendations that can translate into better, fairer health for all.

Undervaccination and severe COVID-19 outcomes: meta-analysis of national cohort studies in England, Northern Ireland, Scotland, and Wales

BACKGROUND

Undervaccination (receiving fewer than the recommended number of SARS-CoV-2 vaccine doses) could be associated with increased risk of severe COVID-19 outcomes-ie, COVID-19 hospitalisation or death-compared with full vaccination (receiving the recommended number of SARS-CoV-2 vaccine doses). We sought to determine the factors associated with undervaccination, and to investigate the risk of severe COVID-19 outcomes in people who were undervaccinated in each UK nation and across the UK.

METHODS

We used anonymised, harmonised electronic health record data with whole population coverage to carry out cohort studies in England, Northern Ireland, Scotland, and Wales. Participants were required to be at least 5 years of age to be included in the cohorts. We estimated adjusted odds ratios for undervaccination as of June 1, 2022. We also estimated adjusted hazard ratios (aHRs) for severe COVID-19 outcomes during the period June 1 to Sept 30, 2022, with undervaccination as a time-dependent exposure. We combined results from nation-specific analyses in a UK-wide fixed-effect meta-analysis. We estimated the reduction in severe COVID-19 outcomes associated with a counterfactual scenario in which everyone in the UK was fully vaccinated on June 1, 2022.

FINDINGS

The numbers of people undervaccinated on June 1, 2022 were 26 985 570 (45·8%) of 58 967 360 in England, 938 420 (49·8%) of 1 885 670 in Northern Ireland, 1 709 786 (34·2%) of 4 992 498 in Scotland, and 773 850 (32·8%) of 2 358 740 in Wales. People who were younger, from more deprived backgrounds, of non-White ethnicity, or had a lower number of comorbidities were less likely to be fully vaccinated. There was a total of 40 393 severe COVID-19 outcomes in the cohorts, with 14 156 of these in undervaccinated participants. We estimated the reduction in severe COVID-19 outcomes in the UK over 4 months of follow-up associated with a counterfactual scenario in which everyone was fully vaccinated on June 1, 2022 as 210 (95% CI 94-326) in the 5-15 years age group, 1544 (1399-1689) in those aged 16-74 years, and 5426 (5340-5512) in those aged 75 years or older. aHRs for severe COVID-19 outcomes in the meta-analysis for the age group of 75 years or older were 2·70 (2·61-2·78) for one dose fewer than recommended, 3·13 (2·93-3·34) for two fewer, 3·61 (3·13-4·17) for three fewer, and 3·08 (2·89-3·29) for four fewer.

INTERPRETATION

Rates of undervaccination against COVID-19 ranged from 32·8% to 49·8% across the four UK nations in summer, 2022. Undervaccination was associated with an elevated risk of severe COVID-19 outcomes.

FUNDING

UK Research and Innovation National Core Studies: Data and Connectivity.

Ethical approval for controlled human infectious model clinical trial protocols - A workshop report

Controlled Human Infectious Model studies (CHIM) involve deliberately exposing volunteers to pathogens. To discuss ethical issues related to CHIM, the European Vaccine Initiative and the International Alliance for Biological Standardization organised the workshop "Ethical Approval for CHIM Clinical Trial Protocols", which took place on May 30-31, 2023, in Brussels, Belgium. The event allowed CHIM researchers, regulators, ethics committee (EC) members, and ethicists to examine the ethical criteria for CHIM and the role(s) of CHIM in pharmaceutical development. The discussions led to several recommendations, including continued assurance that routine ethical requirements are met, assurance that participants are well-informed, and that preparation of study documents must be both ethically and scientifically sound from an early stage. Study applications must clearly state the rationale for the challenge compared to alternative study designs. ECs need to have clear guidance and procedures for evaluating social value and assessing third-party risks. Among other things, public trust in research requires minimisation of harm to healthy volunteers and third-party risk. Other important considerations include appropriate stakeholder engagement, public education, and access to health care for participants after the study.

Risk of severe COVID-19 outcomes after autumn 2022 COVID-19 booster vaccinations: a pooled analysis of national prospective cohort studies involving 7.4 million adults in England, Northern Ireland, Scotland and Wales

Background

UK COVID-19 vaccination policy has evolved to offering COVID-19 booster doses to individuals at increased risk of severe Illness from COVID-19. Building on our analyses of vaccine effectiveness of first, second and initial booster doses, we aimed to identify individuals at increased risk of severe outcomes (i.e., COVID-19 related hospitalisation or death) post the autumn 2022 booster dose.

Methods

We undertook a national population-based cohort analysis across all four UK nations through linked primary care, vaccination, hospitalisation and mortality data. We included individuals who received autumn 2022 booster doses of BNT162b2 (Comirnaty) or mRNA-1273 (Spikevax) during the period September 1, 2022 to December 31, 2022 to investigate the risk of severe COVID-19 outcomes. Cox proportional hazard models were used to estimate adjusted hazard ratios (aHR) and 95% confidence intervals (CIs) for the association between demographic and clinical factors and severe COVID-19 outcomes after the autumn booster dose. Analyses were adjusted for age, sex, body mass index (BMI), deprivation, urban/rural areas and comorbidities. Stratified analyses were conducted by vaccine type. We then conducted a fixed-effect meta-analysis to combine results across the four UK nations.

Findings

Between September 1, 2022 and December 31, 2022, 7,451,890 individuals ≥18 years received an autumn booster dose. 3500 had severe COVID-19 outcomes (2.9 events per 1000 person-years). Being male (male vs female, aHR 1.41 (1.32-1.51)), older adults (≥80 years vs 18-49 years; 10.43 (8.06-13.50)), underweight (BMI <18.5 vs BMI 25.0-29.9; 2.94 (2.51-3.44)), those with comorbidities (≥5 comorbidities vs none; 9.45 (8.15-10.96)) had a higher risk of COVID-19 hospitalisation or death after the autumn booster dose. Those with a larger household size (≥11 people within household vs 2 people; 1.56 (1.23-1.98)) and from more deprived areas (most deprived vs least deprived quintile; 1.35 (1.21-1.51)) had modestly higher risks. We also observed at least a two-fold increase in risk for those with various chronic neurological conditions, including Down's syndrome, immunodeficiency, chronic kidney disease, cancer, chronic respiratory disease, or cardiovascular disease.

Interpretation

Males, older individuals, underweight individuals, those with an increasing number of comorbidities, from a larger household or more deprived areas, and those with specific underlying health conditions remained at increased risk of COVID-19 hospitalisation and death after the autumn 2022 vaccine booster dose. There is now a need to focus on these risk groups for investigating immunogenicity and efficacy of further booster doses or therapeutics.

Funding

National Core Studies-Immunity, UK Research and Innovation (Medical Research Council and Economic and Social Research Council), Health Data Research UK, the Scottish Government, and the University of Edinburgh.

Risk factor associations for severe COVID-19, influenza and pneumonia in people with diabetes to inform future pandemic preparations: UK population-based cohort study

OBJECTIVE

This study aimed to compare clinical and sociodemographic risk factors for severe COVID-19, influenza and pneumonia, in people with diabetes.

DESIGN

Population-based cohort study.

SETTING

UK primary care records (Clinical Practice Research Datalink) linked to mortality and hospital records.

PARTICIPANTS

Individuals with type 1 and type 2 diabetes (COVID-19 cohort: n=43 033 type 1 diabetes and n=584 854 type 2 diabetes, influenza and pneumonia cohort: n=42 488 type 1 diabetes and n=585 289 type 2 diabetes).

PRIMARY AND SECONDARY OUTCOME MEASURES

COVID-19 hospitalisation from 1 February 2020 to 31 October 2020 (pre-COVID-19 vaccination roll-out), and influenza and pneumonia hospitalisation from 1 September 2016 to 31 May 2019 (pre-COVID-19 pandemic). Secondary outcomes were COVID-19 and pneumonia mortality. Associations between clinical and sociodemographic risk factors and each outcome were assessed using multivariable Cox proportional hazards models. In people with type 2 diabetes, we explored modifying effects of glycated haemoglobin (HbA1c) and body mass index (BMI) by age, sex and ethnicity.

RESULTS

In type 2 diabetes, poor glycaemic control and severe obesity were consistently associated with increased risk of hospitalisation for COVID-19, influenza and pneumonia. The highest HbA1c and BMI-associated relative risks were observed in people aged under 70 years. Sociodemographic-associated risk differed markedly by respiratory infection, particularly for ethnicity. Compared with people of white ethnicity, black and south Asian groups had a greater risk of COVID-19 hospitalisation, but a lesser risk of pneumonia hospitalisation. Risk factor associations for type 1 diabetes and for type 2 diabetes mortality were broadly consistent with the primary analysis.

CONCLUSIONS

Clinical risk factors of high HbA1c and severe obesity are consistently associated with severe outcomes from COVID-19, influenza and pneumonia, especially in younger people. In contrast, associations with sociodemographic risk factors differed by type of respiratory infection. This emphasises that risk stratification should be specific to individual respiratory infections.

Severe COVID anxiety among adults in the United Kingdom: cohort study and nested feasibility trial

BACKGROUND

People with severe COVID anxiety have poor mental health and impaired functioning, but the course of severe COVID anxiety is unknown and the quality of evidence on the acceptability and impact of psychological interventions is low.

METHODS

A quantitative cohort study with a nested feasibility trial. Potential participants aged 18 and over, living in the UK with severe COVID anxiety, were recruited online and from primary care services. We examined levels of COVID anxiety in the six months after recruitment, and factors that influenced this, using linear regression. Those scoring above 20 on the short Health Anxiety Inventory were invited to participate in a feasibility trial of remotely delivered Cognitive Behavioural Therapy for Health Anxiety (CBT-HA). Exclusion criteria were recent COVID-19, current self-isolation, or current receipt of psychological treatment. Key outcomes for the feasibility trial were the level of uptake of CBT-HA and the rate of follow-up.

RESULTS

204 (70.2%) of 285 people who took part in the cohort study completed the six month follow-up, for whom levels of COVID anxiety fell from 12.4 at baseline to 6.8 at six months (difference = -5.5, 95% CI = -6.0 to -4.9). Reductions in COVID anxiety were lower among older people, those living with a vulnerable person, those with lower baseline COVID anxiety, and those with higher levels of generalised anxiety and health anxiety at baseline. 36 (90%) of 40 participants enrolled in the nested feasibility trial were followed up at six months. 17 (80.9%) of 21 people in the active arm of the trial received four or more sessions of CBT-HA. We found improved mental health and social functioning among those in the active, but not the control arm of the trial (Mean difference in total score on the Work and Social Adjustment Scale between baseline and follow up, was 9.7 (95% CI = 5.8-13.6) among those in the active, and 1.0 (95% C.I. = -4.6 to 6.6) among those in the control arm of the trial.

CONCLUSIONS

While the mental health of people with severe COVID anxiety appears to improve over time, many continue to experience high levels of anxiety and poor social functioning. Health anxiety is highly prevalent among people with severe COVID anxiety and may provide a target for psychological treatment.

TRIAL REGISTRATION

Retrospectively registered at ISRCTN14973494 on 09/09/2021.

Dynamic updating of clinical survival prediction models in a changing environment

BACKGROUND

Over time, the performance of clinical prediction models may deteriorate due to changes in clinical management, data quality, disease risk and/or patient mix. Such prediction models must be updated in order to remain useful. In this study, we investigate dynamic model updating of clinical survival prediction models. In contrast to discrete or one-time updating, dynamic updating refers to a repeated process for updating a prediction model with new data. We aim to extend previous research which focused largely on binary outcome prediction models by concentrating on time-to-event outcomes. We were motivated by the rapidly changing environment seen during the COVID-19 pandemic where mortality rates changed over time and new treatments and vaccines were introduced.

METHODS

We illustrate three methods for dynamic model updating: Bayesian dynamic updating, recalibration, and full refitting. We use a simulation study to compare performance in a range of scenarios including changing mortality rates, predictors with low prevalence and the introduction of a new treatment. Next, the updating strategies were applied to a model for predicting 70-day COVID-19-related mortality using patient data from QResearch, an electronic health records database from general practices in the UK.

RESULTS

In simulated scenarios with mortality rates changing over time, all updating methods resulted in better calibration than not updating. Moreover, dynamic updating outperformed ad hoc updating. In the simulation scenario with a new predictor and a small updating dataset, Bayesian updating improved the C-index over not updating and refitting. In the motivating example with a rare outcome, no single updating method offered the best performance.

CONCLUSIONS

We found that a dynamic updating process outperformed one-time discrete updating in the simulations. Bayesian updating offered good performance overall, even in scenarios with new predictors and few events. Intercept recalibration was effective in scenarios with smaller sample size and changing baseline hazard. Refitting performance depended on sample size and produced abrupt changes in hazard ratio estimates between periods.

Diversity of symptom phenotypes in SARS-CoV-2 community infections observed in multiple large datasets

Variability in case severity and in the range of symptoms experienced has been apparent from the earliest months of the COVID-19 pandemic. From a clinical perspective, symptom variability might indicate various routes/mechanisms by which infection leads to disease, with different routes requiring potentially different treatment approaches. For public health and control of transmission, symptoms in community cases were the prompt upon which action such as PCR testing and isolation was taken. However, interpreting symptoms presents challenges, for instance, in balancing the sensitivity and specificity of individual symptoms with the need to maximise case finding, whilst managing demand for limited resources such as testing. For both clinical and transmission control reasons, we require an approach that allows for the possibility of distinct symptom phenotypes, rather than assuming variability along a single dimension. Here we address this problem by bringing together four large and diverse datasets deriving from routine testing, a population-representative household survey and participatory smartphone surveillance in the United Kingdom. Through the use of cutting-edge unsupervised classification techniques from statistics and machine learning, we characterise symptom phenotypes among symptomatic SARS-CoV-2 PCR-positive community cases. We first analyse each dataset in isolation and across age bands, before using methods that allow us to compare multiple datasets. While we observe separation due to the total number of symptoms experienced by cases, we also see a separation of symptoms into gastrointestinal, respiratory and other types, and different symptom co-occurrence patterns at the extremes of age. In this way, we are able to demonstrate the deep structure of symptoms of COVID-19 without usual biases due to study design. This is expected to have implications for the identification and management of community SARS-CoV-2 cases and could be further applied to symptom-based management of other diseases and syndromes.

COVID-19 infection, admission and death and the impact of corticosteroids among people with rare autoimmune rheumatic disease during the second wave of COVID-19 in England: results from the RECORDER Project

OBJECTIVES

To calculate the rates of COVID-19 infection and COVID-19-related death among people with rare autoimmune rheumatic diseases (RAIRD) during the second wave of the COVID-19 pandemic in England, and describe the impact of corticosteroids on outcomes.

METHODS

Hospital Episode Statistics data were used to identify people alive on 1 August 2020 with ICD-10 codes for RAIRD from the whole population of England. Linked national health records were used to calculate rates and rate ratios of COVID-19 infection and death up to 30 April 2021. Primary definition of COVID-19-related death was mention of COVID-19 on the death certificate. NHS Digital and Office for National Statistics general population data were used for comparison. The association between 30-day corticosteroid usage and COVID-19-related death, COVID-19-related hospital admissions and all-cause deaths was also described.

RESULTS

Of 168 330 people with RAIRD, 9961 (5.92%) had a positive COVID-19 PCR test. The age-standardized infection rate ratio between RAIRD and the general population was 0.99 (95% CI: 0.97, 1.00). 1342 (0.80%) people with RAIRD died with COVID-19 on their death certificate and the age-sex-standardized mortality rate for COVID-19-related death was 2.76 (95% CI: 2.63, 2.89) times higher than in the general population. There was a dose-dependent relationship between 30-day corticosteroid usage and COVID-19-related death. There was no increase in deaths due to other causes.

CONCLUSIONS

During the second wave of COVID-19 in England, people with RAIRD had the same risk of COVID-19 infection but a 2.76-fold increased risk of COVID-19-related death compared with the general population, with corticosteroids associated with increased risk.

Clinical diagnosis of SARS-CoV-2 infection: An observational study of respiratory tract infection in primary care in the early phase of the pandemic

BACKGROUND

Early in the COVID-19 pandemic, GPs had to distinguish SARS-CoV-2 from other aetiologies in patients presenting with respiratory tract infection (RTI) symptoms on clinical grounds and adapt management accordingly.

OBJECTIVES

To test the diagnostic accuracy of GPs' clinical diagnosis of a SARS-CoV-2 infection in a period when COVID-19 was a new disease. To describe GPs' management of patients presenting with RTI for whom no confirmed diagnosis was available. To investigate associations between patient and clinical features with a SARS-CoV-2 infection.

METHODS

In April 2020-March 2021, 876 patients (9 countries) were recruited when they contacted their GP with symptoms of an RTI of unknown aetiology. A swab was taken at baseline for later analysis. Aetiology (PCR), diagnostic accuracy of GPs' clinical SARS-CoV-2 diagnosis, and patient management were explored. Factors related to SARS-CoV-2 infection were determined by logistic regression modelling.

RESULTS

GPs suspected SARS-CoV-2 in 53% of patients whereas 27% of patients tested positive for SARS-CoV-2. True-positive patients (23%) were more intensively managed for follow-up, antiviral prescribing and advice than true-negatives (42%). False negatives (5%) were under-advised, particularly for social distancing and isolation. Older age (OR: 1.02 (1.01-1.03)), male sex (OR: 1.68 (1.16-2.41)), loss of taste/smell (OR: 5.8 (3.7-9)), fever (OR: 1.9 (1.3-2.8)), muscle aches (OR: 2.1 (1.5-3)), and a known risk factor for COVID-19 (travel, health care worker, contact with proven case; OR: 2.7 (1.8-4)) were predictive of SARS-CoV-2 infection. Absence of loss of taste/smell, fever, muscle aches and a known risk factor for COVID-19 correctly excluded SARS-CoV-2 in 92.3% of patients, whereas presence of 3, or 4 of these variables correctly classified SARS-CoV-2 in 57.7% and 87.1%.

CONCLUSION

Correct clinical diagnosis of SARS-CoV-2 infection, without POC-testing available, appeared to be complicated.

Side effects of COVID-19 vaccines in the middle eastern population

The COVID-19 pandemic has caused severe worldwide health concerns since its first description as the SARS-COV-2 virus in December 2019. The wide dissemination of this virus, together with the lack of treatment, prompted vaccine development within a short period of time to elicit a protective immunity against COVID-19. Due to their rapid development, potential subsequent side effects of COVID-19 vaccines were overlooked, which might lead to many health concerns. This is especially true for patients at a greater risk of harm from COVID-19, such as pregnant women, children, and patients with pre-existing chronic diseases. In this review, we provide a summary of common to rare side effects of administrated COVID-19 vaccines in a Middle Eastern population. We have found that the distinction between side effects from COVID-19 vaccines in terms of frequency and severity is attributed to the differences in study populations, gender, and age. Pain at the injection site, fever, headache, fatigue, and muscle pain were the most common reported side effects. Vaccinated subjects with previous COVID-19 infection exhibited an equivalent neutralizing response after just one dose compared to two doses of vaccine. Consequently, individuals who experienced more side effects had significantly higher antibody levels. This indicates that having better immunity correlates with higher antibody levels, leading to a higher frequency of vaccine side effects. Individuals with underlying comorbidities, particularly having known allergies and with illnesses such as diabetes and cancer, might be more prone to post-vaccination side effects. Studies of a high-risk population in Middle Eastern countries are limited. Future studies should be considered to determine long-term side effects, side effects after booster doses, and side effect differences in cases of heterologous and homologous vaccination for better understanding and proper handling of high-risk populations and patients who experience these side effects.

Association for Human Pharmacology in the Pharmaceutical Industry conference 2022: impending change, innovations and future challenges

The Association for Human Pharmacology in the Pharmaceutical Industry's annual meeting focused on current and impending challenges facing the United Kingdom's (UK) pharmaceutical industry and how these opportunities can inspire innovation and best practice. The UK pharmaceutical landscape is still evolving following Brexit and learnings from the coronavirus disease 2019 (COVID-19) pandemic. As such, the UK's clinical community is in a unique position to steer innovation in a meaningful direction. With the continuation of remote forms of working, further opportunities have arisen to support novel practices away from the clinic. The keynote speaker reflected on clinical development over the past 40 years and how the industry must continue to concentrate on patient welfare. The future of drug development was discussed regarding challenges associated with developing translational gene therapies, and the status of investment markets analyzed from a business strategy and consulting perspective. The patient viewpoint was a core theme throughout the conference with patient-centric blood sampling and decentralized clinical trials providing suggestions for how the industry can save costs and increase efficiency. Moreover, the patient perspective was central to a debate over whether ethics requirements should be the same for oncology patients taking part in first-in-human studies as those for healthy subjects. Discussions continued around the changing roles of the Qualified Person and Principal Investigators which underpins how sponsors may want to run future trials in the UK. Lessons learned from conducting challenge trials in healthy volunteers and patients were discussed following a presentation from the serving Chair of the COVID-19 challenge ethics committee. The current state of interactions with the Medicines and Healthcare products Regulatory Agency were also explored. It was considered how the immediate future for the UK clinical trials community is inevitably still linked with Europe; the newly implemented European Medicines Agency Clinical Trials Information System has been met with lukewarm responses, providing a promising opportunity to ensure UK Phase I units continue to play a vital role in global research.

Effect of the COVID-19 pandemic on asthma exacerbations in New Zealand: An interrupted time series analysis

Background

New Zealand (NZ) implemented some of the strictest restrictions during the novel coronavirus pandemic (coronavirus disease 2019 [COVID-19]), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). How this impacted asthma exacerbation rates in NZ is unknown.

Objective

We sought to explore the effects of the COVID-19 restrictions on asthma exacerbations in NZ during 2020.

Methods

We used a population-based, interrupted time series to examine the impact of the first COVID-19 lockdown in NZ on asthma exacerbation rate. The primary outcome measure was change in the monthly exacerbation rate, defined as hospitalization and/or course of corticosteroids, before and after the first lockdown. In a secondary analysis, we quantified the number of patients with asthma, the actual asthma exacerbation rate from March to December 2019 versus March to December 2020, and the number of asthma hospitalizations.

Results

There was a significant drop in the exacerbation rate immediately after lockdown (-3.02; P < .0001) followed by a significant and sustained increasing trend; the rate postlockdown increased relative to that prelockdown (0.27; P < .0001). Similar patterns were observed in all sociodemographic groups. In our secondary analysis, we identified 507,622 people with asthma; this reduced to 458,023 in 2020 postlockdown. The overall asthma exacerbation rate was 33.3% less in 2020 than in 2019 (reduction from 48.6/1000 patients to 32.4/1000 patients). The rate of asthma hospitalizations decreased from 9.5 per 1000 patients in 2019 to 6.2 per 1000 patients in 2020; this decrease was observed across all demographic groups.

Conclusions

The first COVID-19 lockdown in 2020 in NZ significantly reduced asthma exacerbation rates across all sociodemographic groups. Whether these reductions are sustained requires further investigation.

Understanding covid-19 outcomes among people with intellectual disabilities in England

BACKGROUND

Evidence from the UK from the early stages of the covid-19 pandemic showed that people with Intellectual Disabilities (ID) had higher rates of covid-19 mortality than people without ID. However, estimates of the magnitude of risk vary widely; different studies used different time periods; and only early stages of the pandemic have been analysed. Existing analyses of risk factors have also been limited. The objective of this study was to investigate covid-19 mortality rates, hospitalisation rates, and risk factors in people with ID in England up to the end of 2021.

METHODS

Retrospective cohort study of all people with a laboratory-confirmed SARS-CoV-2 infection or death involving covid-19. Datasets covering primary care, secondary care, covid-19 tests and vaccinations, prescriptions, and deaths were linked at individual level.

RESULTS

Covid-19 carries a disproportionately higher risk of death for people with ID, above their already higher risk of dying from other causes, in comparison to those without ID. Around 2,000 people with ID had a death involving covid-19 in England up to the end of 2021; approximately 1 in 180. The covid-19 standardized mortality ratio was 5.6 [95% CI 5.4, 5.9]. People with ID were also more likely to be hospitalised for covid-19 than people without ID. The main determinants of severe covid-19 outcomes (deaths and/or hospitalisations) in both populations were age, multimorbidity and vaccination status. The key factor responsible for the higher risk of severe covid-19 in the ID population was a much higher prevalence of multimorbidity in this population. AstraZeneca vaccine was slightly less effective in preventing severe covid-19 outcomes among people with ID than among people without ID.

CONCLUSIONS

People with ID should be considered a priority group in future pandemics, such as shielding and vaccinations.

Cardiometabolic risk management: insights from a European Society of Cardiology Cardiovascular Round Table

Metabolic comorbidities are common in patients with cardiorenal disease; they can cause atherosclerotic cardiovascular disease (ASCVD), speed progression, and adversely affect prognosis. Common comorbidities are Type 2 diabetes mellitus (T2DM), obesity/overweight, chronic kidney disease (CKD), and chronic liver disease. The cardiovascular system, kidneys, and liver are linked to many of the same risk factors (e.g. dyslipidaemia, hypertension, tobacco use, diabetes, and central/truncal obesity), and shared metabolic and functional abnormalities lead to damage throughout these organs via overlapping pathophysiological pathways. The COVID-19 pandemic has further complicated the management of cardiometabolic diseases. Obesity, T2DM, CKD, and liver disease are associated with increased risk of poor outcomes of COVID-19 infection, and conversely, COVID-19 can lead to worsening of pre-existing ASCVD. The high rates of these comorbidities highlight the need to improve recognition and treatment of ASCVD in patients with obesity, insulin resistance or T2DM, chronic liver diseases, and CKD and equally, to improve recognition and treatment of these diseases in patients with ASCVD. Strategies to prevent and manage cardiometabolic diseases include lifestyle modification, pharmacotherapy, and surgery. There is a need for more programmes at the societal level to encourage a healthy diet and physical activity. Many pharmacotherapies offer mechanism-based approaches that can target multiple pathophysiological pathways across diseases. These include sodium-glucose cotransporter-2 inhibitors, glucagon-like peptide-1 receptor agonists, selective mineralocorticoid receptor antagonists, and combined glucose-dependent insulinotropic peptide/glucagon-like peptide-1 receptor agonist. Non-surgical and surgical weight loss strategies can improve cardiometabolic disorders in individuals living with obesity. New biomarkers under investigation may help in the early identification of individuals at risk and reveal new treatment targets.

Does fear of infection affect people's dental attendance during COVID-19? A Chinese example to examine the association between COVID anxiety and dental anxiety

Introduction

Little is known about the psychological and behavioural effect of COVID-19 pandemic on patients and their reaction to dental visiting. Patients may delay attendance due to fears of contracting the corona virus at the dentist. The study aims to confirm the psychometric properties of the two COVID-19 scales and then use dental patient responses to assess the associations between the COVID-19 Anxiety Scale (CAS), dental anxiety (MDAS) and the clinical care COVID-19 Anxiety (CCAS).

Methods

A cross-sectional study was conducted among 503 patients visiting a polyclinic of a stomatological hospital in East China in 2020. Patients completed a survey consisting of demographical information, dental attendance, COVID-19 Anxiety Scale, Clinical Care COVID-19 Anxiety Scale and Modified Dental Anxiety Scale. Confirmatory factor analysis was conducted to determine the psychometric characteristics. A further structural model was tested with the combined measurement model and a path analysis was calculated.

Results

The sample (n = 503) consisted of more women than men (63% vs. 37%). A fifth of the sample (21%) claimed regular dental attendance and just over a third (35%) reported delaying their dental visit due to the pandemic. Our analysis showed that both CAS and CCAS possessed a unidimensional structure. The MDAS was divided into anticipatory and treatment components as separate latent variables. The anticipatory component (MDAS_A) had some association to CCAS through its expression on treatment dental anxiety (MDAS_T). General anxiety about COVID (CAS) had a direct effect on CCAS. The fit statistics were acceptable [Chi-square = 183.27, df = 68, p < .001; CFI = 0.973; RMSEA = 0.058 (95%CIs: 0.048-0.068)] and the Standardised Root Mean Square Residuals (SRMR) index was 0.041.

Discussion

The Clinical Care COVID-19 Anxiety has shown satisfactory psychometric properties. Both dental anxiety and general anxiety about the pandemic have strong associations to patients' fear of contracting corona virus when using dental facilities. Our study has practical implications to help healthcare providers better understand how environmental stressors influence patients' overall concerns on infection risks and appropriate dental treatments during the pandemic.

No causal association between COVID-19 and sepsis: a bidirectional two-sample Mendelian randomization study

Background

Sepsis and COVID-19 have a well-established observable relationship. Whether COVID-19 increases the likelihood of developing sepsis and whether patients with sepsis are at increased risk for COVID-19 infection is unknown. Using a bidirectional 2-sample Mendelian randomization (TSMR) analysis techniques in sizable cohorts, we sought to answer this question.

Methods

The current study performed Mendelian randomization (MR) on publicly accessible genome-wide association study (GWAS) summary data in order to investigate the causal linkages between COVID-19 and sepsis. A Two-Sample MR(TSMR) analyses was performed. As instrumental variables, a COVID-19 dataset of single nucleotide polymorphisms (SNPs) with significance value smaller than 5*10-8 was employed and Sepsis dataset of SNPs with significance value smaller than 5*10-7was employed.

Results

The results suggested that Very severe respiratory confirmed COVID-19(VSRC), hospitalized COVID-19(HC) and Infected COVID-19(IC) had no causal influence on sepsis risk using the inverse variance weighted (IVW) technique (VSRC OR = 1.000, 95% CI, 0.956-1.046, P = 0.996, HC OR = 0.976, 95% CI, 0.920-1.036, P = 0.430, IC OR = 0.923, 95% CI, 0.796-1.071, P = 0.291) and there was no causal effect of sepsis on the risk of VSRC, HC and IC (VSRC OR = 0.955, 95% CI, 0.844-1.173, P = 0.953, HC OR = 0.993, 95% CI, 0.859-1.147, P = 0.921, IC OR = 1.001, 95% CI, 0.959-1.045, P = 0.961).

Conclusions

Our findings do not support a causal relationship between COVID-19 and sepsis risk, nor do they suggest a causal link between sepsis and COVID-19. The bidirectional relationship between COVID-19 and sepsis warrants further investigation in large cohorts.

The Case for Human Challenge Trials in COVID-19

The COVID-19 pandemic has necessitated rapid research to aid in the understanding of the disease and the development of novel therapeutics. One option is to conduct controlled human infection trials (CHITs). In this article I examine the history of deliberate human infection and CHITs and their utilization prior to the COVID-19 pandemic, key ethical considerations of CHITs in the COVID-19 setting, an analysis of the World Health Organization's (WHO) Key criteria for the ethical acceptability of COVID-19 human challenge studies, and a review of the two COVID-19 CHITs that have already commenced, their compliance with the WHO criteria and other ethical considerations.

Community focus groups about a COVID-19 individual risk assessment tool: access, understanding and usefulness

To make informed COVID-19 related decisions, individuals need information about their personal risks and how those risks may vary with specific demographic and health characteristics. The Fight COVID Milwaukee web-based risk assessment tool allows for assessment of COVID-19 mortality risk as a function of personal and neighborhood characteristics. The purpose of this study is to explore public understanding of this risk assessment tool and risk perception through community focus groups. Individuals were recruited from the general adult population in Milwaukee County, Wisconsin, USA, to participate in nine online focus groups where the risk assessment tool was presented for feedback. Three main themes were identified in the focus groups regarding the web-based risk assessment tool: some challenges in accessibility, variable ease of understanding, and personal usefulness but uncertain value for others. This paper explores how members of the community interpret individual risk assessments and life expectancy estimations, and how these vary with age, gender, race/ethnicity, socioeconomic status, and pre-existing comorbidities.

Effects on mortality of shielding clinically extremely vulnerable patients in Liverpool, UK, during the COVID-19 pandemic

OBJECTIVE

This study evaluates the impact of England's COVID-19 shielding programme on mortality in the City of Liverpool in North West England.

STUDY DESIGN

Shielded and non-shielded people are compared using data from linked routine health records on all people registered with a general practitioner in Liverpool from April 2020 to June 2021.

METHODS

A discrete time hazard model and interactions between the shielding status and the periods of higher risk of transmission are used to explore the effects of shielding across the major phases of the COVID-19 pandemic.

RESULTS

Shielding was associated with a 34% reduction in the risk of dying (HR = 0.66, 95% CI: 0.58 to 0.76) compared with a propensity-matched non-shielded group. Shielding appeared to reduce mortality during the first and third waves, but not during the second wave, where shielding was not mandated by the government. The effects were similar for males and females, but more protective for those living in the least deprived areas of Liverpool.

CONCLUSIONS

It is likely that the shielding programme in Liverpool saved lives, although this seems to have been a little less effective in more deprived areas. A comprehensive programme for identifying vulnerable groups and providing them with advice and support is likely to be important for future respiratory virus pandemics. Additional support may be necessary for socio-economically disadvantaged groups to avoid increased inequalities.

Thrombocytopenic, thromboembolic and haemorrhagic events following second dose with BNT162b2 and ChAdOx1: self-controlled case series analysis of the English national sentinel cohort

Background

Thrombosis associated with thrombocytopenia was a matter of concern post first and second doses of BNT162b2 and ChAdOx1 COVID-19 vaccines. Therefore, it is important to investigate the risk of thrombocytopenic, thromboembolic and haemorrhagic events following a second dose of BNT162b2 and ChAdOx1 COVID-19 vaccines.

Methods

We conducted a large-scale self-controlled case series analysis, using routine primary care data linked to hospital data, among 12.3 million individuals (16 years old and above) in England. We used the nationally representative Oxford-Royal College of General Practitioners (RCGP) sentinel network database with baseline and risk periods between 8th December 2020 and 11th June 2022. We included individuals who received two vaccine (primary) doses of the BNT162b2 mRNA (Pfizer-BioNTech) and two vaccine doses of ChAdOx1 nCoV-19 (Oxford-AstraZeneca) vaccines in our analyses. We carried out a self-controlled case series (SCCS) analysis for each outcome using a conditional Poisson regression model with an offset for the length of risk period. We reported the incidence rate ratios (IRRs) and 95% confidence intervals (CI) of thrombocytopenic, thromboembolic (including arterial and venous events) and haemorrhagic events, in the period of 0-27 days after receiving a second dose of BNT162b2 or ChAdOx1 vaccines compared to the baseline period (14 or more days prior to first dose, 28 or more days after the second dose and the time between 28 or more days after the first and 14 or more days prior to the second dose). We adjusted for a range of potential confounders, including age, sex, comorbidities and deprivation.

Findings

Between December 8, 2020 and February 11, 2022, 6,306,306 individuals were vaccinated with two doses of BNT162b2 and 6,046,785 individuals were vaccinated with two doses of ChAdOx1. Compared to the baseline, our analysis show no increased risk of venous thromboembolic events (VTE) for both BNT162b2 (IRR 0.71, 95% CI: 0.65-0.770) and ChAdOx1 (IRR 0.91, 95% CI: 0.84-0.98); and similarly there was no increased risk for cerebral venous sinus thrombosis (CVST) for both BNT162b2 (IRR 0.87, 95% CI: 0.41-1.85) and ChAdOx1 (IRR 1.73, 95% CI: 0.82-3.68). We additionally report no difference in IRR for pulmonary embolus, and deep vein thrombosis, thrombocytopenia, including idiopathic thrombocytopenic purpura (ITP), and haemorrhagic events post second dose for both BNT162b2.

Interpretation

Reassuringly, we found no associations between increased risk of thrombocytopenic, thromboembolic and haemorrhagic events post vaccination with second dose for either of these vaccines.

Funding

Data and Connectivity: COVID-19 Vaccines Pharmacovigilance study.

Antithrombotic drugs for cardiovascular risk reduction in patients with lower limb peripheral arterial disease: protocol for a systematic review and network meta-analysis of randomised controlled trials

INTRODUCTION

The optimal antithrombotic regimen to reduce the risk of vascular events in patients with peripheral arterial disease (PAD) is contentious. This systematic review and network meta-analysis (NMA) aims to define the relative efficacy and risks of previously investigated antithrombotic medication regimens in preventing major cardiovascular events, vascular limb events and mortality in patients with PAD.

METHODS AND ANALYSIS

A peer-reviewed, systematic search will be executed in English on Medline, Embase, Cochrane (CENTRAL), Web of Science and Google Scholar databases in late 2022. The WHO International Clinical Trials Registry platform will also be searched for ongoing trials. Abstracts will be screened independently by two researchers for randomised controlled trials meeting the review criteria. All associated publications including the study protocol will be sought and evaluated together against prespecified inclusion/exclusion criteria. Two researchers will extract the data into a prepiloted extraction form. Risk-of-bias assessments will be performed using the Cochrane 'Risk-of-Bias V.2' criteria by individuals with domain expertise. All differences will be resolved by consensus or a third individual for ties.Included trials will be summarised. An NMA will be performed, subject to checks of assumptions. Both primary and secondary outcomes will be analysed on a whole network basis. Pairwise comparisons and league tables will be produced. Prespecified subgroup analyses will include sex, ethnicity, disease status, conservative versus interventional management and key comorbidities. The findings will be evaluated using the Grading of Recommendation Assessment, Development and Evaluation, informed by patient and public involvement work.

ETHICS AND DISSEMINATION

This is a systematic review of data in the public domain and does not require ethical approval. Dissemination will include presentations to key vascular and patient organisations, publication in a peer-reviewed journal and an open-access repository of the study data.

PROSPERO REGISTRATION NUMBER

CRD42023389262.

Assessing the coverage and timeliness of coronavirus vaccination among people experiencing homelessness in Wales, UK: a population-level data-linkage study

BACKGROUND

People experiencing homelessness have elevated morbidity, increasing their risk of COVID-19 related complications and mortality. Achieving high vaccination coverage in a timely manner among homeless populations was therefore important during the mass vaccination programme in Wales to limit adverse outcomes. However, no systematic monitoring of vaccinations among people experiencing homelessness in Wales has been undertaken.

METHODS

Retrospective cohort analysis was conducted using de-identified administrative data. Study cohort members were adults (≥ 18 years old) living in Wales on the 2 December 2020 and who had recently experienced homelessness, defined as experiencing homelessness between 1 July 2020 and 2 December 2020. The outcome of interest was first coronavirus vaccine dose. Follow-up started on 2 December 2020, and ended if the participant died, had a break in address history > 30 days, reached the end of follow up (30 November 2021), or had the outcome of interest. Median-time-to-vaccination was used as a crude measure of 'timeliness' of vaccine uptake. To account for competing risk of death prior to vaccination, vaccine coverage was described using cumulative incidence at 350-days, and at 50-day increments over follow-up (2 December 2020 to 17 November 2021). As a benchmark, all time-to-event measures were generated for the adult population in Wales with similar baseline individual and residential characteristics as the study cohort.

RESULTS

1,595 people with recent experiences of homelessness were identified and included in analysis. The study cohort were disproportionately male (68.8%) and concentrated in the most deprived areas in Wales. Median time-to-vaccination for the study cohort was 196 days (95% CI.: 184-209 days), compared to 141 days (95% CI.: 141-141 days) among the matched adult population in Wales. Cumulative incidence of vaccination after 350-days of follow-up was 60.4% (95% CI.: 57.8-62.8%) among the study cohort, compared to 81.4% (95% CI.: 81.3-81.5%) among the matched adult population. Visual analysis of cumulative incidence over time suggests that vaccine inequality, i.e., difference between study cohort and matched adult population, peaked after 200-days of follow-up, and declined slightly until last follow-up at 350-days.

CONCLUSIONS

Despite being prioritised for vaccination, people experiencing homelessness in Wales appear to have been under-engaged, leading to lower vaccination coverage and greater time unvaccinated, potentially increasing their risk of COVID-19 complications and mortality.

Rationale for the shielding policy for clinically vulnerable people in the UK during the COVID-19 pandemic: a qualitative study

INTRODUCTION

Shielding aimed to protect those predicted to be at highest risk from COVID-19 and was uniquely implemented in the UK during the first year of the pandemic from March 2020. As the first stage in the EVITE Immunity evaluation (Effects of shielding for vulnerable people during COVID-19 pandemic on health outcomes, costs and immunity, including those with cancer:quasi-experimental evaluation), we generated a logic model to describe the programme theory underlying the shielding intervention.

DESIGN AND PARTICIPANTS

We reviewed published documentation on shielding to develop an initial draft of the logic model. We then discussed this draft during interviews with 13 key stakeholders involved in putting shielding into effect in Wales and England. Interviews were recorded, transcribed and analysed thematically to inform a final draft of the logic model.

RESULTS

The shielding intervention was a complex one, introduced at pace by multiple agencies working together. We identified three core components: agreement on clinical criteria; development of the list of people appropriate for shielding; and communication of shielding advice. In addition, there was a support programme, available as required to shielding people, including food parcels, financial support and social support. The predicted mechanism of change was that people would isolate themselves and so avoid infection, with the primary intended outcome being reduction in mortality in the shielding group. Unintended impacts included negative impact on mental and physical health and well-being. Details of the intervention varied slightly across the home nations of the UK and were subject to minor revisions during the time the intervention was in place.

CONCLUSIONS

Shielding was a largely untested strategy, aiming to mitigate risk by placing a responsibility on individuals to protect themselves. The model of its rationale, components and outcomes (intended and unintended) will inform evaluation of the impact of shielding and help us to understand its effect and limitations.

Remote Patient Monitoring for COVID-19: A Retrospective Study on Health Care Utilization

Introduction: Data are limited on the effectiveness of remote patient monitoring (RPM) for acute illnesses, including COVID-19. We conducted a study to determine if enrollment in a COVID-19 RPM program was associated with better outcomes. Methods: From March through September 2020, patients with respiratory symptoms and presumptive COVID-19 were referred to the health system's COVID-19 RPM program. We conducted a retrospective cohort study comparing outcomes for patients enrolled in the RPM (n = 4,435) with those who declined enrollment (n = 2,742). Primary outcomes were emergency room, hospital, and intensive care unit admissions, and death. We used logistic regression to adjust for demographic differences and known risk factors for severe COVID-19. Results: Patients enrolled in the RPM were less likely to have risk factors for severe COVID-19. There was a significant decrease in the odds of death for the group enrolled in the RPM (adjusted odds ratio [OR] = 0.50; 95% confidence interval [CI], 0.30-0.83) and a nonsignificant decrease in the odds of the other primary outcomes. Increased number of interactions with the RPM significantly decreased the odds of hospital admission (OR = 0.92; 95% CI, 0.88-0.95). Conclusions: COVID-19 RPM enrollment was associated with decreased odds of death, and the more patients interacted with the RPM, the less likely they were to require hospital admission. RPM is a promising tool that has the potential to improve patient outcomes for acute illness, but controlled trials are necessary to confirm these findings.

Relationship between periodontitis and COVID-19: A bidirectional two-sample Mendelian randomization study

Background and Aims

Coronavirus disease (COVID-19) is a major danger to world health and has been linked to periodontitis in a number of epidemiological observational studies. However, it is unclear whether COVID-19 causes periodontitis. COVID-19's causal influence on periodontitis was determined using bidirectional Mendelian randomization (MR).

Methods

Large-scale COVID-19 and periodontitis genome wide association study data were analyzed. Inverse variance weighting, MR-Egger, weighted median, and MR-PRESSO were used to estimate causal effects. Sensitivity studies were conducted using the Cochran's Q test, the MR-Egger intercept test, the MR-PRESSO, and the leave-one-out (LOO) analysis. Further investigation of potential mediating factors was performed using risk factor analysis.

Results

The MR presented no causal relationship between periodontitis and hospitalization for COVID-19 (odds ratio [OR] = 0.97, 95% confidence interval [CI] 0.78-1.20; p = 0.76), vulnerability to COVID-19 (OR = 1.04, 95% CI 0.88-1.21; p = 0.65), COVID-19 disease severity (OR = 1.01, 95% CI 0.92-1.11; p = 0.81). Meanwhile, a noncausal effect of genetic hospitalization for COVID-19, illness severity, and vulnerability to periodontitis was detected. Other MR methods yielded identical results to inverse variance weighting. According to sensitivity analysis, horizontal pleiotropy is unlikely to affect causal estimation.

Conclusion

Periodontitis had no link to the risk of COVID-19 hospitalization, susceptibility, or severity. However, the substance in COVID-19 that is responsible for this effect must be studied further.

Clinical features and outcomes of hospitalised patients with COVID-19 and Parkinsonian disorders: A multicentre UK-based study

BACKGROUND

Parkinson's disease has been identified as a risk factor for severe Coronavirus disease 2019 (COVID-19) outcomes. However, whether the significant high risk of death from COVID-19 in people with Parkinson's disease is specific to the disease itself or driven by other concomitant and known risk factors such as comorbidities, age, and frailty remains unclear.

OBJECTIVE

To investigate clinical profiles and outcomes of people with Parkinson's disease and atypical parkinsonian syndromes who tested positive for COVID-19 in the hospital setting in a multicentre UK-based study.

METHODS

A retrospective cohort study of Parkinson's disease patients with a positive SARS-CoV-2 test admitted to hospital between February 2020 and July 2021. An online survey was used to collect data from clinical care records, recording patient, Parkinson's disease and COVID-19 characteristics. Associations with time-to-mortality and severe outcomes were analysed using either the Cox proportional hazards model or logistic regression models, as appropriate.

RESULTS

Data from 552 admissions were collected: 365 (66%) male; median (inter-quartile range) age 80 (74-85) years. The 34-day all-cause mortality rate was 38.4%; male sex, increased age and frailty, Parkinson's dementia syndrome, requirement for respiratory support and no vaccination were associated with increased mortality risk. Community-acquired COVID-19 and co-morbid chronic neurological disorder were associated with increased odds of requiring respiratory support. Hospital-acquired COVID-19 and delirium were associated with requiring an increase in care level post-discharge.

CONCLUSIONS

This first, multicentre, UK-based study on people with Parkinson's disease or atypical parkinsonian syndromes, hospitalised with COVID-19, adds and expands previous findings on clinical profiles and outcomes in this population.

The Association of Body Mass Index with COVID-19 Complications and Survival Rate at a Tertiary Hospital

A high body mass index (BMI) is a known risk factor for coronavirus infection in hospitalized patients. Our study examined the association between BMI and complications and the survival rate among COVID-19 patients. This retrospective analysis used data from a tertiary hospital in the Eastern Region of Saudi Arabia during two waves of the COVID-19 pandemic. The study included 600 participants, with the majority being between 41 and 60 years old (41.3%) and men comprising 63.5% of the sample. Approximately 42.5% of patients were obese, and 31.3% were overweight. The results showed that BMI was significantly linked to respiratory diseases (p = 0.013); end-stage renal disease (p = 0.021); and cardiovascular disease (p = 0.003) but not diabetes mellitus (p = 0.064). Death occurred in 10.8% of patients; 33.8% were admitted to the ICU; 13.8% needed mechanical ventilation; and 60.7% had lung infiltration. Obese patients with oxygen saturation levels below 93% were 2.45 times more likely to require mechanical ventilation than those in the normal-weight group. Overweight and obese patients were also more likely to require mechanical ventilation than normal-weight patients, with odds ratios of 3.66 and 2.81, respectively. The BMI categorized was not associated with survival rate in COVID-19-hospitalized patients using Kaplan-Meier survival plots (p = 0.061). However, the BMI categorized was associated with survival rate in COVID-19 ICU patients (p < 0.001). In addition, the overweight showed a statistically significant higher hazard ratio of 2.22 (p = 0.01) compared to normal-weight patients using a Cox regression model. A high BMI was identified as an independent risk factor for reduced oxygen saturation (<93%), the need for mechanical ventilation, lung infiltration, mortality, and longer ICU stays in COVID-19 patients.

Development and validation of a prediction model for mechanical ventilation based on comorbidities in hospitalized patients with COVID-19

Background

Timely recognition of respiratory failure and the need for mechanical ventilation is crucial in managing patients with coronavirus disease 2019 (COVID-19) and reducing hospital mortality rate. A risk stratification tool could assist to avoid clinical deterioration of patients with COVID-19 and optimize allocation of scarce resources. Therefore, we aimed to develop a prediction model for early identification of patients with COVID-19 who may require mechanical ventilation.

Methods

We included patients with COVID-19 hospitalized in United States. Demographic and clinical data were extracted from the records of the Healthcare Cost and Utilization Project State Inpatient Database in 2020. Model construction involved the use of the least absolute shrinkage and selection operator and multivariable logistic regression. The model's performance was evaluated based on discrimination, calibration, and clinical utility.

Results

The training set comprised 73,957 patients (5,971 requiring mechanical ventilation), whereas the validation set included 10,428 (887 requiring mechanical ventilation). The prediction model incorporating age, sex, and 11 other comorbidities (deficiency anemias, congestive heart failure, coagulopathy, dementia, diabetes with chronic complications, complicated hypertension, neurological disorders unaffecting movement, obesity, pulmonary circulation disease, severe renal failure, and weight loss) demonstrated moderate discrimination (area under the curve, 0.715; 95% confidence interval, 0.709-0.722), good calibration (Brier score = 0.070, slope = 1, intercept = 0) and a clinical net benefit with a threshold probability ranged from 2 to 34% in the training set. Similar model's performances were observed in the validation set.

Conclusion

A robust prognostic model utilizing readily available predictors at hospital admission was developed for the early identification of patients with COVID-19 who may require mechanical ventilation. Application of this model could support clinical decision-making to optimize patient management and resource allocation.

Vaccine effectiveness for prevention of covid-19 related hospital admission during pregnancy in England during the alpha and delta variant dominant periods of the SARS-CoV-2 pandemic: population based cohort study

Objective

To estimate vaccine effectiveness for preventing covid-19 related hospital admission in individuals first infected with the SARS-CoV-2 virus during pregnancy compared with those of reproductive age who were not pregnant when first infected with the virus.

Design

Population based cohort study.

Setting

Office for National Statistics Public Health Data Asset linked dataset, providing national linked census and administrative data in England, 8 December 2020 to 31 August 2021.

Participants

815 477 females aged 18-45 years (mean age 30.4 years) who had documented evidence of a first SARS-CoV-2 infection in the NHS Test and Trace or Hospital Episode Statistics data.

Main outcome measures

Hospital admission where covid-19 was recorded as the primary diagnosis. Cox proportional hazards models, adjusted for calendar time of infection, sociodemographic factors, and pre-existing health conditions related to uptake of the covid-19 vaccine and risk of severe covid-19 outcomes, were used to estimate vaccine effectiveness as the complement of the hazard ratio for hospital admission for covid-19.

Results

Compared with pregnant individuals who were not vaccinated, the adjusted rate of hospital admission for covid-19 was 77% (95% confidence interval 70% to 82%) lower for pregnant individuals who had received one dose and 83% (76% to 89%) lower for those who had received two doses of vaccine. These estimates were similar to those found in the non-pregnant group: 79% (77% to 81%) for one dose and 83% (82% to 85%) for two doses of vaccine. Among those who were vaccinated >90 days before infection, having two doses of vaccine was associated with a greater reduction in risk than one dose.

Conclusions

Covid-19 vaccination was associated with reduced rates of hospital admission in pregnant individuals infected with the SARS-CoV-2 virus, and the reduction in risk was similar to that in non-pregnant individuals. Waning of vaccine effectiveness occurred more quickly after one than after two doses of vaccine.

SARS-CoV-2-specific immune responses and clinical outcomes after COVID-19 vaccination in patients with immune-suppressive disease

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) immune responses and infection outcomes were evaluated in 2,686 patients with varying immune-suppressive disease states after administration of two Coronavirus Disease 2019 (COVID-19) vaccines. Overall, 255 of 2,204 (12%) patients failed to develop anti-spike antibodies, with an additional 600 of 2,204 (27%) patients generating low levels (<380 AU ml-1). Vaccine failure rates were highest in ANCA-associated vasculitis on rituximab (21/29, 72%), hemodialysis on immunosuppressive therapy (6/30, 20%) and solid organ transplant recipients (20/81, 25% and 141/458, 31%). SARS-CoV-2-specific T cell responses were detected in 513 of 580 (88%) patients, with lower T cell magnitude or proportion in hemodialysis, allogeneic hematopoietic stem cell transplantation and liver transplant recipients (versus healthy controls). Humoral responses against Omicron (BA.1) were reduced, although cross-reactive T cell responses were sustained in all participants for whom these data were available. BNT162b2 was associated with higher antibody but lower cellular responses compared to ChAdOx1 nCoV-19 vaccination. We report 474 SARS-CoV-2 infection episodes, including 48 individuals with hospitalization or death from COVID-19. Decreased magnitude of both the serological and the T cell response was associated with severe COVID-19. Overall, we identified clinical phenotypes that may benefit from targeted COVID-19 therapeutic strategies.