COVID-19 Hospital Admissions Research Articles

Tracking changes in SARS-CoV-2 transmission with a novel outpatient sentinel surveillance system in Chicago, USA

Public health indicators typically used for COVID-19 surveillance can be biased or lag changing community transmission patterns. In this study, we investigate whether sentinel surveillance of recently symptomatic individuals receiving outpatient diagnostic testing for SARS-CoV-2 could accurately assess the instantaneous reproductive number R(t) and provide early warning of changes in transmission. We use data from community-based diagnostic testing sites in the United States city of Chicago. Patients tested at community-based diagnostic testing sites between September 2020 and June 2021, and reporting symptom onset within four days preceding their test, formed the sentinel population. R(t) calculated from sentinel cases agreed well with R(t) from other indicators. Retrospectively, trends in sentinel cases did not precede trends in COVID-19 hospital admissions by any identifiable lead time. In deployment, sentinel surveillance held an operational recency advantage of nine days over hospital admissions. The promising performance of opportunistic sentinel surveillance suggests that deliberately designed outpatient sentinel surveillance would provide robust early warning of increasing transmission.

Investigating links between air pollution, COVID-19 and lower respiratory infectious diseases – A review

Background/aim Hundreds of air pollution and COVID-19 papers have been published in a short time varying widely in quality. The Greater London Authority commissioned a comprehensive overview of the most credible evidence for the links between air pollution and COVID-19 and other lung infections. Methods Building on the Brunekreef et al (2021) review, a literature search was performed from November 2020 – May 2021, classifying the evidence by exposure, the potential mechanism and the health outcome. Studies on hospital admissions for lower respiratory infections were reviewed from 2011 Results Long-term exposure increased the risk of hospitalization in people already infected with COVID-19 in two good-quality cohort studies with individual data, perhaps due to respiratory and cardiovascular disease from air pollution increasing vulnerability to COVID-19 adverse outcomes. Mortality results were conflicting. Inconsistent results were found for long-term exposure and COVID-19 cases in ecological studies. Studies on short-term exposure were unclear and hard to evaluate. Several studies demonstrated that inhaled pollutant increased expression of the ACE2 receptor and other host susceptibility genes in both alveolar epithelial cells and macrophages. Susceptibility to infection by SARS-CoV-2 can be inferred from these results but only one study used SARS-CoV-2 directly. Several studies from 2011-2021 showed a link between air pollution and hospital admissions for lung infections although the studies were spread across different age groups and disease definitions. Particulate matter does not appear to play any important part in transporting COVID-19 in the environment, as had been suggested by some earlier studies. Conclusions The publication of cohort studies with individual data in this time period is an important step forward. Results are suggestive for long-term exposure and hospital admissions for COVID-19 and some toxicological effects are plausible but further research will be necessary to strengthen these emerging findings. Keywords Air pollution, COVID-19, lower respiratory infections.

Association between obesity and hospitalization in mild COVID-19 adult outpatients in Brazil: a prospective cohort study.

To evaluate the association between obesity and hospitalization in mild COVID-19 adult outpatients in Brazil. Adults with signs and symptoms suggestive of acute SARS-CoV-2 infection who sought treatment in two hospital (public and private) emergency departments were prospectively enrolled. Patients with confirmed COVID-19 at inclusion were followed by phone calls at days D7, D14 and D28. Multivariable logistic regression models were employed to explore the association between obesity and other potential predictors for hospitalization. A total of 1,050 participants were screened, and 297 completed the 28-day follow-up and were diagnosed with COVID-19 by RT-PCR. The median age was 37.2 (IQR 29.7-44.6) years, and 179 (60.0%) were female. The duration of symptoms was 3.0 (IQR 2.0-5.0) days, and 10.0 (IQR 8.0-12.0) was the median number of symptoms at inclusion. Ninety-five (32.0%) individuals had obesity, and 233 (78.5%) had no previous medical conditions. Twenty-three participants (7.7%) required hospitalization during the follow-up period. After adjusting, obesity (BMI ≥ 30.0 kg/m2) (OR = 2.69, 95% CI 1.63-4.83, P < 0.001) and older age (OR = 1.05, 95% CI 1.01-1.09, P < 0.001) were significantly associated with higher risks of hospitalization. Obesity, followed by aging, was the main factor associated with hospital admission for COVID-19 in a young population in a low-middle income country. Our findings highlighted the need to promote additional protection for individuals with obesity, such as vaccination, and to encourage lifestyle changes.

COVID-19 hospital admissions and mortality among healthcare workers in South Africa, 2020–2021

This study describes the characteristics of admitted HCWs reported to the DATCOV surveillance system, and the factors associated with in-hospital mortality in South African HCWs. Data from March 5, 2020 to April 30, 2021 were obtained from DATCOV, a national hospital surveillance system monitoring COVID-19 admissions in South Africa. Characteristics of HCWs were compared with those of non-HCWs. Furthermore, a logistic regression model was used to assess factors associated with in-hospital mortality among HCWs. In total, there were 169678 confirmed COVID-19 admissions, of which 6364 (3.8%) were HCWs. More of these HCW admissions were accounted for in wave 1 (48.6%; n = 3095) than in wave 2 (32.0%; n = 2036). Admitted HCWs were less likely to be male (28.2%; n = 1791) (aOR 0.3; 95% CI 0.3-0.4), in the 50-59 age group (33.1%; n = 2103) (aOR 1.4; 95% CI 1.1-1.8), or accessing the private health sector (63.3%; n = 4030) (aOR 1.3; 95% CI 1.1-1.5). Age, comorbidities, race, wave, province, and sector were significant risk factors for COVID-19-related mortality. The trends in cases showed a decline in HCW admissions in wave 2 compared with wave 1. Acquired SARS-COV-2 immunity from prior infection may have been a reason for reduced admissions and mortality of HCWs despite the more transmissible and more severe beta variant in wave 2.

OA06.05 Impact of COVID-19 Pandemic on Proportion and Treatment Patterns for Stage I Non-small Cell Lung Cancer in the Netherlands

OA06.05 Impact of COVID-19 Pandemic on Proportion and Treatment Patterns for Stage I Non-small Cell Lung Cancer in the Netherlands

Higher mortality associated with the SARS-CoV-2 Delta variant in the Western Cape, South Africa, using RdRp target delay as a proxy: a cross-sectional study.

Background: The SARS-CoV-2 Delta variant (B.1.617.2) has been associated with more severe disease, particularly when compared to the Alpha variant. Most of this data, however, is from high income countries and less is understood about the variant's disease severity in other settings, particularly in an African context, and when compared to the Beta variant. Methods: A novel proxy marker, RNA-dependent RNA polymerase (RdRp) target delay in the Seegene Allplex TM 2019-nCoV (polymerase chain reaction) PCR assay, was used to identify suspected Delta variant infection in routine laboratory data. All cases diagnosed on this assay in the public sector in the Western Cape, South Africa, from 1 April to 31 July 2021, were included in the dataset provided by the Western Cape Provincial Health Data Centre (PHDC). The PHDC collates information on all COVID-19 related laboratory tests, hospital admissions and deaths for the province. Odds ratios for the association between the proxy marker and death were calculated, adjusted for prior diagnosed infection and vaccination status. Results: A total of 11,355 cases with 700 deaths were included in this study. RdRp target delay (suspected Delta variant) was associated with higher mortality (adjusted odds ratio [aOR] 1.45; 95% confidence interval [CI]: 1.13-1.86), compared to presumptive Beta infection. Prior diagnosed infection during the previous COVID-19 wave, which was driven by the Beta variant, was protective (aOR 0.32; 95%CI: 0.11-0.92) as was vaccination (aOR [95%CI] 0.15 [0.03-0.62] for complete vaccination [≥28 days post a single dose of Ad26.COV2.S or ≥14 days post second BNT162b2 dose]). Conclusion: RdRp target delay, a proxy for infection with the Delta variant, is associated with an increased risk of mortality amongst those who were tested for COVID-19 in our setting.

Occupational differences in COVID-19 hospital admission and mortality between women and men in Scotland: A population-based study using linked administrative data.

ObjectivesWe aim to estimate occupational differences in COVID-19 hospital admission and mortality by sex. Occupations vary with respect to environmental factors that influence exposure to COVID-19 such as ventilation, social contact and protective equipment. Variations between women and men may arise because they occupy different roles within an occupation or from behavioural differences. ApproachWe established an innovative linked data collection combining individual-level data from 2011 Census with health administrative records and household identifiers from Ordnance Survey’s Unique Property Reference Number (UPRN). Using data for a cohort of approximately 1.7 million Scottish adults aged 40 to 64 years, we analysed occupational differences in COVID-19 hospital admission and mortality, during the period between 1 March 2020 and 31 January 2021. We estimated age-standardised incidence rates (ASIRs) for COVID-19 hospital admission and death per 100,000 adults, stratified by sex and occupation. Using Cox proportional hazards models, we estimated COVID-19 hospital admission and death risks, adjusting for socio-economic and pre-pandemic health factors. ResultsGenerally, women had lower ASIRs for COVID-19 hospital admission and mortality compared to men. For COVID-19 mortality, ASIRs were highest among women employed in elementary trades and related occupations (e.g. packers/canners). For hospital admission, high rates were observed among women working in caring personal services (e.g. nursing assistants/ambulance staff). Among men, ASIRs were highest among those in elementary services occupations (kitchen assistants/waiters) and taxi drivers, who also had the highest admission rate. After adjusting for pre-pandemic health factors, we observed lower death risks for women employed as health professionals, and those in associate professional and technical occupations (medical technicians/paramedics), compared to the baseline model. Lower adjusted admission risks were also observed for both women and men in professional occupations (e.g. in science/engineering and teaching/education). Among men, adjusted death risks remained elevated for large vehicle and taxi drivers, who also displayed high admission risks. ConclusionOccupational differences in COVID-19 hospital admission and mortality between women and men may be explained by a mixture of social, workplace and behavioural factors. These need to be considered when designing intervention policies which aim to reduce infections in the workplace.

Safety of mRNA COVID-19 vaccines during pregnancy

Safety of mRNA COVID-19 vaccines during pregnancy

Device-assessed sleep and physical activity in individuals recovering from a hospital admission for COVID-19: a multicentre study

BackgroundThe number of individuals recovering from severe COVID-19 is increasing rapidly. However, little is known about physical behaviours that make up the 24-h cycle within these individuals. This study aimed to describe physical behaviours following hospital admission for COVID-19 at eight months post-discharge including associations with acute illness severity and ongoing symptoms.MethodsOne thousand seventy-seven patients with COVID-19 discharged from hospital between March and November 2020 were recruited. Using a 14-day wear protocol, wrist-worn accelerometers were sent to participants after a five-month follow-up assessment. Acute illness severity was assessed by the WHO clinical progression scale, and the severity of ongoing symptoms was assessed using four previously reported data-driven clinical recovery clusters. Two existing control populations of office workers and individuals with type 2 diabetes were comparators.ResultsValid accelerometer data from 253 women and 462 men were included. Women engaged in a mean ± SD of 14.9 ± 14.7 min/day of moderate-to-vigorous physical activity (MVPA), with 12.1 ± 1.7 h/day spent inactive and 7.2 ± 1.1 h/day asleep. The values for men were 21.0 ± 22.3 and 12.6 ± 1.7 h /day and 6.9 ± 1.1 h/day, respectively. Over 60% of women and men did not have any days containing a 30-min bout of MVPA. Variability in sleep timing was approximately 2 h in men and women. More severe acute illness was associated with lower total activity and MVPA in recovery. The very severe recovery cluster was associated with fewer days/week containing continuous bouts of MVPA, longer total sleep time, and higher variability in sleep timing. Patients post-hospitalisation with COVID-19 had lower levels of physical activity, greater sleep variability, and lower sleep efficiency than a similarly aged cohort of office workers or those with type 2 diabetes.ConclusionsThose recovering from a hospital admission for COVID-19 have low levels of physical activity and disrupted patterns of sleep several months after discharge. Our comparative cohorts indicate that the long-term impact of COVID-19 on physical behaviours is significant.

A deep learning approach for Spatio-Temporal forecasting of new cases and new hospital admissions of COVID-19 spread in Reggio Emilia, Northern Italy

BackgroundSince February 2020, the COVID-19 epidemic has rapidly spread throughout Italy. Some studies showed an association of environmental factors, such as PM10, PM2.5, NO2, temperature, relative humidity, wind speed, solar radiation and mobility with the spread of the epidemic.In this work, we aimed to predict via Deep Learning the real-time transmission of SARS-CoV-2 in the province of Reggio Emilia, Northern Italy, in a grid with a small resolution (12 km × 12 km), including satellite information. MethodsWe focused on the Province of Reggio Emilia, which was severely hit by the first wave of the epidemic. The outcomes included new SARS-CoV-2 infections and COVID-19 hospital admissions. Pollution, meteorological and mobility data were analyzed. The spatial simulation domain included the Province of Reggio Emilia in a grid of 40 cells of (12 km)2. We implemented a ConvLSTM, which is a spatio-temporal deep learning approach, to perform a 7-day moving average to forecast the 7th day after. We used as training and validation set the new daily infections and hospital admissions from August 2020 to March 2021. Finally, we assessed the models in terms of Mean Absolute Error (MAE) compared with Mean Observed Value (MOV) and Root Mean Squared Error (RMSE) on data from April to September 2021. We tested the performance of different combinations of input variables to find the best forecast model. FindingsDaily new cases of infection, mobility and wind speed resulted in being strongly predictive of new COVID-19 hospital admissions (MAE = 2.72 in the Province of Reggio Emilia; MAE = 0.62 in Reggio Emilia city), whereas daily new cases, mobility, solar radiation and PM2.5 turned out to be the best predictors to forecast new infections, with appropriate time lags. InterpretationConvLSTM achieved good performances in forecasting new SARS-CoV-2 infections and new COVID-19 hospital admissions. The spatio-temporal representation allows borrowing strength from data neighboring to forecast at the level of the square cell (12 km)2, getting accurate predictions also at the county level, which is paramount to help optimise the real-time allocation of health care resources during an epidemic emergency.

COVID-19 vaccination for children aged 5–11 years

COVID-19 vaccination for children aged 5–11 years

Corrigendum: The intersection of age, sex, race and socio-economic status in COVID-19 hospital admissions and deaths in South Africa

Original article: https://doi.org/10.17159/sajs.2022/13323 The following terminology was erroneously reported: “non-white race” should be “people of colour”, or “black African, coloured and people of Indian descent”.

High LACE index scores are associated with disproportionate excess deaths in hospital amongst patients with COVID-19

Risk factors for COVID-19-related outcomes have been variably reported. We used the standardised LACE index to examine admissions and in-hospital mortality associated with COVID-19. Data were collected in the pre-pandemic period (01-04-2019 to 29-02-2020) from 10,173 patients (47.7% men: mean age ± standard deviation = 68.3 years ± 20.0) and in the pandemic period (01-03-2019 to 31-03-2021) from 12,434 patients. With the latter, 10,982 were without COVID-19 (47.4% men: mean age = 68.3 years ± 19.6) and 1452 with COVID-19 (58.5% men: mean age = 67.0 years ± 18.4). Admissions and mortality were compared between pre-pandemic and pandemic patients, according to LACE index. Admission rates rose disproportionately with higher LACE indices amongst the COVID-19 group. Mortality rates amongst the pre-pandemic, pandemic non-COVID-19 and COVID-19 groups with LACE index scores < 4 were 0.7%, 0.5%, 0%; for scores 4–9 were 5.0%, 3.7%, 8.9%; and for scores ≥ 10 were: 24.2%, 20.4%, 43.4%, respectively. The area under the curve receiver operating characteristic for predicting mortality by LACE index was 76% for COVID-19 and 77% for all non-COVID-19 patients. The risk of age and sex-adjusted mortality did not differ from the pre-pandemic group for COVID-19 patients with LACE index scores < 4. However, risk increased drastically for scores from 4 to 9: odds ratio = 3.74 (95% confidence interval = 2.63–5.32), and for scores ≥ 10: odds ratio = 4.02 (95% confidence interval = 3.38–4.77). In conclusion, patients with LACE index scores ≥ 4 have disproportionally greater risk of COVID-19 hospital admissions and deaths, in support of previous studies in patients without COVID-19. However, of importance, our data also emphasise their increased risk in patients with COVID-19. Because the LACE index has a good predictive power of mortality, it should be considered for routine use to identify high-risk COVID-19 patients.

Risk of severe COVID-19 outcomes associated with immune-mediated inflammatory diseases and immune-modifying therapies: a nationwide cohort study in the OpenSAFELY platform.

BackgroundThe risk of severe COVID-19 outcomes in people with immune-mediated inflammatory diseases and on immune-modifying drugs might not be fully mediated by comorbidities and might vary by factors such as ethnicity. We aimed to assess the risk of severe COVID-19 in adults with immune-mediated inflammatory diseases and in those on immune-modifying therapies.MethodsWe did a cohort study, using OpenSAFELY (an analytics platform for electronic health records) and TPP (a software provider for general practitioners), analysing routinely collected primary care data linked to hospital admission, death, and previously unavailable hospital prescription data. We included people aged 18 years or older on March 1, 2020, who were registered with TPP practices with at least 12 months of primary care records before March, 2020. We used Cox regression (adjusting for confounders and mediators) to estimate hazard ratios (HRs) comparing the risk of COVID-19-related death, critical care admission or death, and hospital admission (from March 1 to Sept 30, 2020) in people with immune-mediated inflammatory diseases compared with the general population, and in people with immune-mediated inflammatory diseases on targeted immune-modifying drugs (eg, biologics) compared with those on standard systemic treatment (eg, methotrexate).FindingsWe identified 17 672 065 adults; 1 163 438 adults (640 164 [55·0%] women and 523 274 [45·0%] men, and 827 457 [71·1%] of White ethnicity) had immune-mediated inflammatory diseases, and 16 508 627 people (8 215 020 [49·8%] women and 8 293 607 [50·2%] men, and 10 614 096 [64·3%] of White ethnicity) were included as the general population. Of 1 163 438 adults with immune-mediated inflammatory diseases, 19 119 (1·6%) received targeted immune-modifying therapy and 181 694 (15·6%) received standard systemic therapy. Compared with the general population, adults with immune-mediated inflammatory diseases had an increased risk of COVID-19-related death after adjusting for confounders (age, sex, deprivation, and smoking status; HR 1·23, 95% CI 1·20–1·27) and further adjusting for mediators (body-mass index [BMI], cardiovascular disease, diabetes, and current glucocorticoid use; 1·15, 1·11–1·18). Adults with immune-mediated inflammatory diseases also had an increased risk of COVID-19-related critical care admission or death (confounder-adjusted HR 1·24, 95% CI 1·21–1·28; mediator-adjusted 1·16, 1·12–1·19) and hospital admission (confounder-adjusted 1·32, 1·29–1·35; mediator-adjusted 1·20, 1·17–1·23). In post-hoc analyses, the risk of severe COVID-19 outcomes in people with immune-mediated inflammatory diseases was higher in non-White ethnic groups than in White ethnic groups (as it was in the general population). We saw no evidence of increased COVID-19-related death in adults on targeted, compared with those on standard systemic, therapy after adjusting for confounders (age, sex, deprivation, BMI, immune-mediated inflammatory diseases [bowel, joint, and skin], cardiovascular disease, cancer [excluding non-melanoma skin cancer], stroke, and diabetes (HR 1·03, 95% CI 0·80–1·33), and after additionally adjusting for current glucocorticoid use (1·01, 0·78–1·30). There was no evidence of increased COVID-19-related death in adults prescribed tumour necrosis factor inhibitors, interleukin (IL)-12/IL‑23 inhibitors, IL-17 inhibitors, IL-6 inhibitors, or Janus kinase inhibitors compared with those on standard systemic therapy. Rituximab was associated with increased COVID-19-related death (HR 1·68, 95% CI 1·11–2·56), with some attenuation after excluding people with haematological malignancies or organ transplants (1·54, 0·95–2·49).InterpretationCOVID-19 deaths and hospital admissions were higher in people with immune-mediated inflammatory diseases. We saw no increased risk of adverse COVID-19 outcomes in those on most targeted immune-modifying drugs for immune-mediated inflammatory diseases compared with those on standard systemic therapy.FundingUK Medical Research Council, NIHR Biomedical Research Centre at King's College London and Guy's and St Thomas' NHS Foundation Trust, and Wellcome Trust.

Sex Differences in COVID-19 Hospitalization and Hospital Mortality among Patients with COPD in Spain: A Retrospective Cohort Study.

(1) Background: We aimed to assess the effect of COPD in the incidence of hospital admissions for COVID-19 and on the in-hospital mortality (IHM) according to sex. (2) Methods: We used national hospital discharge data to select persons aged ≥40 years admitted to a hospital with a diagnosis of COVID-19 in 2020 in Spain. (3) Results: The study population included 218,301 patients. Age-adjusted incidence rates of COVID-19 hospitalizations for men with and without COPD were 10.66 and 9.27 per 1000 persons, respectively (IRR 1.14; 95% CI 1.08–1.20; p < 0.001). The IHM was higher in men than in women regardless of the history of COPD. The COPD was associated with higher IHM among women (OR 1.09; 95% CI 1.01–1.22) but not among men. The COPD men had a 25% higher risk of dying in the hospital with COVID-19 than women with COPD (OR 1.25, 95% CI 1.1–1.42). (4) Conclusions: Sex differences seem to exist in the effect of COPD among patients suffering COVID-19. The history of COPD increased the risk of hospitalization among men but not among women, and COPD was only identified as a risk factor for IHM among women. In any case, we observed that COPD men had a higher mortality than COPD women. Understanding the mechanisms underlying these sex differences could help predict the patient outcomes and inform clinical decision making to facilitate early treatment and disposition decisions.

Risk factors of long term symptoms and outcomes among patients discharged after covid-19: prospective, multicentre observational study

ObjectiveTo investigate risk factors and subphenotypes associated with long term symptoms and outcomes after hospital admission for covid-19.DesignProspective, multicentre observational study.Setting93 hospitals in France.ParticipantsData from 2187 adults admitted to hospital...

The intersection of age, sex, race and socio-economic status in COVID-19 hospital admissions and deaths in South Africa (with corrigendum)

Older age, male sex, and non-white race have been reported to be risk factors for COVID-19 mortality. Few studies have explored how these intersecting factors contribute to COVID-19 outcomes. This study aimed to compare demographic characteristics and trends in SARS-CoV-2 admissions and the health care they received. Hospital admission data were collected through DATCOV, an active national COVID-19 surveillance programme. Descriptive analysis was used to compare admissions and deaths by age, sex, race, and health sector as a proxy for socio-economic status. COVID-19 mortality and healthcare utilisation were compared by race using random effect multivariable logistic regression models. On multivariable analysis, black African patients (adjusted OR [aOR] 1.3, 95% confidence interval [CI] 1.2, 1.3), coloured patients (aOR 1.2, 95% CI 1.1, 1.3), and patients of Indian descent (aOR 1.2, 95% CI 1.2, 1.3) had increased risk of in-hospital COVID-19 mortality compared to white patients; and admission in the public health sector (aOR 1.5, 95% CI 1.5, 1.6) was associated with increased risk of mortality compared to those in the private sector. There were higher percentages of COVID-19 hospitalised individuals treated in ICU, ventilated, and treated with supplemental oxygen in the private compared to the public sector. There were increased odds of non-white patients being treated in ICU or ventilated in the private sector, but decreased odds of black African patients being treated in ICU (aOR 0.5; 95% CI 0.4, 0.5) or ventilated (aOR 0.5; 95% CI 0.4, 0.6) compared to white patients in the public sector. These findings demonstrate the importance of collecting and analysing data on race and socio-economic status to ensure that disease control measures address the most vulnerable populations affected by COVID-19. Significance: These findings demonstrate the importance of collecting data on socio-economic status and race alongside age and sex, to identify the populations most vulnerable to COVID-19. This study allows a better understanding of the pre-existing inequalities that predispose some groups to poor disease outcomes and yet more limited access to health interventions. Interventions adapted for the most vulnerable populations are likely to be more effective. The national government must provide efficient and inclusive non-discriminatory health services, and urgently improve access to ICU, ventilation and oxygen in the public sector. Transformation of the healthcare system is long overdue, including narrowing the gap in resources between the private and public sectors.

Chronic Oral Anticoagulation Therapy and Prognosis of Patients Admitted to Hospital for COVID-19: Insights from the HOPE COVID-19 Registry.

Background Most evidence regarding anticoagulation and COVID-19 refers to the hospitalization setting, but the role of oral anticoagulation (OAC) before hospital admission has not been well explored. We compared clinical outcomes and short-term prognosis between patients with and without prior OAC therapy who were hospitalized for COVID-19. Methods Analysis of the whole cohort of the HOPE COVID-19 Registry which included patients discharged (deceased or alive) after hospital admission for COVID-19 in 9 countries. All-cause mortality was the primary endpoint. Study outcomes were compared after adjusting variables using propensity score matching (PSM) analyses. Results 7698 patients were suitable for the present analysis (675 (8.8%) on OAC at admission: 427 (5.6%) on VKAs and 248 (3.2%) on DOACs). After PSM, 1276 patients were analyzed (638 with OAC; 638 without OAC), without significant differences regarding the risk of thromboembolic events (OR 1.11, 95% CI 0.59–2.08). The risk of clinically relevant bleeding (OR 3.04, 95% CI 1.92–4.83), as well as the risk of mortality (HR 1.22, 95% CI 1.01–1.47; log-rank p value = 0.041), was significantly increased in previous OAC users. Amongst patients on prior OAC only, there were no differences in the risk of clinically relevant bleeding, thromboembolic events, or mortality when comparing previous VKA or DOAC users, after PSM. Conclusion Hospitalized COVID-19 patients on prior OAC therapy had a higher risk of mortality and worse clinical outcomes compared to patients without prior OAC therapy, even after adjusting for comorbidities using a PSM. There were no differences in clinical outcomes in patients previously taking VKAs or DOACs. This trial is registered with NCT04334291/EUPAS34399.

Gecko: A time-series model for COVID-19 hospital admission forecasting

During the COVID-19 pandemic, concerns about hospital capacity in the United States led to a demand for models that forecast COVID-19 hospital admissions. These short-term forecasts were needed to support planning efforts by providing decision-makers with insight about future demands for health care capacity and resources. We present a SARIMA time-series model called Gecko developed for this purpose. We evaluate its historical performance using metrics such as mean absolute error, predictive interval coverage, and weighted interval scores, and compare to alternative hospital admission forecasting models. We find that Gecko outperformed baseline approaches and was among the most accurate models for forecasting hospital admissions at the state and national levels from January–May 2021. This work suggests that simple statistical methods can provide a viable alternative to traditional epidemic models for short-term forecasting.

Effects of Vitamin D Supplementation on COVID-19 Related Outcomes: A Systematic Review and Meta-Analysis.

The COVID-19 outbreak has rapidly expanded to a global pandemic; however, our knowledge is limited with regards to the protective factors against this infection. The aim of this systematic literature review and meta-analysis was to evaluate the impact of vitamin D supplementation on COVID-19 related outcomes. A systematic search of relevant papers published until January 2022 was conducted to identify randomized controlled trials (RCTs) and non-randomized studies of intervention (NRISs). The primary outcomes included the risk of COVID-19 infection (primary prevention studies on uninfected individuals), hospital admission (secondary prevention studies on mild COVID-19 cases), and ICU admission and mortality rate (tertiary prevention studies on hospitalized COVID-19 patients). We identified five studies (one RCT, four NRISs) on primary prevention, with five (two RCTs, three NRISs) on secondary prevention, and 13 (six RCTs, seven NRISs) on tertiary prevention. Pooled analysis showed no significant effect on the risk of COVID-19 infection. No meta-analysis was possible on hospitalization risk due to paucity of data. Vitamin D supplementation was significantly associated with a reduced risk of ICU admission (RR = 0.35, 95% CI: 0.20, 0.62) and mortality (RR = 0.46, 95% CI: 0.30, 0.70). Vitamin D supplementation had no significant impact on the risk of COVID-19 infection, whereas it showed protective effects against mortality and ICU admission in COVID-19 patients.