To investigate the association between smoking behavior and COVID-19 hospitalization, integrating individual and regional factors such as community resilience and social determinants of health (SDOH), addressing gaps in existing research.

Retrospective cohort study utilizing multilevel analytical methods to evaluate the effects of individual smoking status and regional SDOH on COVID-19 hospitalization.

Washoe County, Nevada, during the first year of the COVID-19 pandemic (March 5, 2020, to April 30, 2021).

All reported laboratory-positive COVID-19-infected adult residents of Washoe County collected by the Washoe County Health District through mandated disease surveillance for which smoking status was recorded, totaling 10,215 cases after data cleaning.

Hospitalization among those with COVID-19 was the primary outcome measure, analyzed in relation to individual smoking status and zip code tabulation area (ZCTA)-level SDOH variables.

The analysis found that individuals infected with COVID-19 who currently and formerly smoked had significantly higher odds of hospitalization compared to those who never had smoked, with odds ratios adjusted for demographics and comorbidities. An increased odds of hospitalization among those with COVID-19 were associated with higher local unemployment, a significant ZCTA-level factor.

Smoking may have increased the odds of hospitalization among those infected with COVID-19, as well as the socioeconomic factor of unemployment. The integration of SDOH into the assessment of health outcomes underscores the need for targeted public health interventions that address both individual behaviors and community-level factors. Future research should continue to explore these factors to inform more effective public health strategies and policy decisions.

Hispanic populations face significant disparities in health and healthcare. The COVID-19 pandemic highlighted and sometimes further exacerbated these disparities. We conducted a multisite, retrospective cohort study of 6494 hospitalized adult patients admitted between March 2020 and January 2022 with a diagnosis of COVID-19 from five sites including academic hospitals in MN, AZ, and FL and community hospitals in MN and WI. This is an ancillary project of the Viral Infection and Respiratory illness Universal Study (VIRUS) registry, supplemented by electronic health record data. We compared in-hospital mortality and length of stay outcomes between Hispanic and non-Hispanic populations admitted with COVID-19 using propensity matched scores to account for imbalances in demographic and clinical covariables. Among a total of 6494 patients, 512 (7.9%) patients were reported deceased and 5982 (92.1%) alive at discharge. We did not find a statistically significant difference between in-hospital mortality nor length of stay between the two groups.

Little is known about the acute and long-term sequelae of COVID-19 and its pathophysiology in African patients, who are known to have a distinct immunological profile compared to Caucasian populations. Here, we established protein signatures to define severe outcomes of acute COVID-19 and determined whether unique protein signatures during the first week of acute illness predict the risk of post-acute sequelae of COVID-19 (Long COVID) in a low-income country (LIC) setting.

Using the Olink inflammatory panel, we measured the abundance of 92 proteins in the plasma of COVID-19 patients (n=55) and non-COVID-19 individuals (n=23). We investigated distinct inflammatory protein signatures in acute severe COVID-19 individuals (n=22) compared to asymptomatic or mild/moderate COVID-19 cases (n=33), and non-COVID-19 controls.

Levels of SLAMF1, CCL25, IL2RB, IL10RA, IL15RA, IL18 and CST5 were significantly upregulated in patients with critical COVID-19 illness compared to individuals negative for COVID-19. The cohort was followed for an average of 20 months, and 23 individuals developed Long COVID, based on the WHO's case definition, while 32 COVID-19 patients recovered fully. Whereas upregulated levels of SLAMF1, TNF, TSLP, IL15RA, IL18, ADA, CXCL9, CXCL10, IL17C, and NT3 at the acute phase of the illness were associated with increased Long COVID risk, upregulated TRANCE was associated with a reduced risk of developing Long COVID. Protein levels of SLAMF1, IL15RA, and IL18 associated with critical illness during the acute phase of COVID-19 also predicted Long COVID risk.

Patients with severe COVID-19 and Long COVID outcomes exhibited distinct proteomic signatures. Unravelling the pathophysiology of severe acute COVID-19 and Long COVID before its advent may contribute to designing novel interventions for diagnosing, treating, and monitoring of SARS-CoV-2 infection and its associated acute and long-term consequences.

Persistent severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection differs from long coronavirus disease (COVID-19) (acute symptoms ≥ 12 weeks post-clearance). The Omicron BA.5 variant has a shorter median clearance time (10-14 days) than the Delta variant, suggesting that the traditional 20-day diagnostic threshold may delay interventions in high-risk populations. This study integrated multi-threshold analysis (14/20/30 days), whole-genome sequencing, and machine learning to investigate diagnostic thresholds for persistent SARS-CoV-2 infection and developed a generalizable risk prediction model.

This retrospective study analyzed data from 1,216 patients with COVID-19 hospitalized at Aerospace Center Hospital between January 2021 and October 2024. We used whole-genome sequencing to genotype all COVID-19 cases and to identify major variants (such as Omicron BA. 5, Delta). The outcome, "persistent SARS-CoV-2 infection," was defined as viral nucleic acid positivity ≥ 14 days. Risk factors associated with persistent infection were identified through subgroup analysis with multiple logistic regression (adjusted for age, comorbidities, vaccination status, and virus strain) and machine learning models (70% training, 30% testing dataset).

Persistent SARS-CoV-2 infection was identified in 15.5% (188/1,216) of hospitalized COVID-19 patients. Key predictors included comorbidities-hypertension, diabetes, and active malignancy-and immune dysfunction, marked by reduced B-cell and CD4 + T-cell counts. Unvaccinated patients exhibited an 82% higher risk of persistent infection. Elevated inflammatory markers (C-reactive protein and interleukin-6) and bilateral lung infiltrates on computed tomography further distinguished persistent cases. The predictive model demonstrated strong discrimination with an area under the curve (AUC) of 0.847 (95% confidence interval: 0.815-0.879) and an AUC of 0.81 externally in external validation, underscoring its clinical utility for risk stratification.

Hypertension, diabetes, malignancy, immunosuppression (low B/CD4 + cells), and non-vaccination are independent risk factors for persistent SARS-CoV-2 infection. Integrating these factors into clinical risk stratification may optimize management of high-risk populations.

COVID-19 mortality disparities underscore the critical role of environmental factors, age, sex, and racial demographics. This study investigates how individual variations in nasal morphology - specifically its air conditioning (temperature and humidity regulation) and filtration functions - may influence respiratory health and contribute to differential COVID-19 outcomes. Analysis reveals significant differences in nasal structure and function across racial, sex, and age groups, demonstrating associations with disparities in respiratory vulnerability to environmental stressors such as air pollution, infectious aerosols, and climatic conditions. Specifically, wider nasal cavities (more common in certain populations), larger male nasal passages, and age-related changes like mucosal atrophy and increased endonasal volume impair air conditioning and filtration efficiency. These morphological variations influence the nose's protective capacity, which is critical for shielding the middle and lower airways from environmental exposures. Populations with inherently reduced nasal filtration and conditioning efficiency demonstrate higher vulnerability, aligning with U.S. mortality patterns for both COVID-19 and air pollution across demographic groups. This suggests a direct link between nasal anatomy and population-level health disparities. These findings provide novel insights into the role of nasal anatomy in mediating respiratory health disparities by modulating individual responses to environmental exposures, air pollution, and pathogens. They highlight the need to address critical gaps in understanding how airway characteristics influence susceptibility to environmental stressors and to develop targeted interventions aimed at reducing health disparities.

A detailed analysis was carried out on the impact of cardiovascular disease on the risk of death of patients hospitalized at a temporary hospital in Gdańsk during the third and fifth waves of the COVID-19 pandemic (in 2021 and 2022, respectively). Background/Objectives: The documentation of 1244 patients was analyzed, of which 701 were hospitalized in 2021 (the Delta variant) and 543 in 2022 (the Omicron variant). The aim of this study was to assess the risk of death of patients with COVID-19 depending on the co-existence of cardiovascular diseases. Methods: A model of logistic regression was used to identify the impact of the patients' age, the coexistence of cardiovascular disease, and the length of hospitalization on the risk of death. Results: In 2021, patients were younger (median of 66 years) than in 2022 (median of 74 years), the length of hospitalization was shorter in 2022 (9 days) than in 2021 (11 days), and there was a higher proportion of patients with cardiovascular and respiratory diseases and a medical history of cancer in 2022. The odds of death were also observed to be higher in older patients with cardiovascular disease, particularly those under 73 years of age. In older patients (over 73 years), the odds were paradoxically reduced. Conclusions: The age of the patient, cardiovascular disease, and duration of hospitalization affect the risk of death. The Delta variant (2021) was more virulent than Omicron (2022). Cardiovascular disease significantly increases the risk of death in patients with COVID-19. The comprehensive diagnosis and treatment of patients with these conditions may reduce mortality. Further studies are needed on the long-term effects of COVID-19 on the cardiovascular system.

Contributions of leukocytes to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) defense have been reported extensively. However, it remains unclear whether there are different leukocyte responses to ancestral SARS-CoV-2 and its variants.

We analyzed peripheral blood leukocyte and subtype concentrations from 575 COVID-19 patients and 950 non-COVID-19 subjects registered at the University of Connecticut John Dempsey Hospital between 2020 and 2022, which covers the ancestral strain, Delta, and Omicron variants.

We found that neutrophils, immature granulocytes, and monocytes were elevated, and lymphocytes were reduced after infection. These hyperactive neutrophils/immature granulocytes and suppressed lymphocytes/monocytes were associated with poorer prognosis in ancestral strain infection. Different from the ancestral strain, hyperactive immature granulocytes were not shown in the decedents of Delta infection, and immature granulocyte concentration was not observed to be associated with mortality. In Omicron infection, suppressed lymphocytes and monocytes were not shown in the decedents, and lymphocyte/monocyte concentrations were not associated with mortality.

Our findings provided insights into different leukocyte immune responses to ancestral SARS-CoV-2, Delta, and Omicron variants.

The infection rates with SARS-CoV 2 virus, known since 2019, are currently significantly weakened in their dynamics. Nevertheless, COVID 19 is still a common disease, which in most cases is overcome quite well and can be treated by the general practitioner. Despite an initially uncomplicated disease progression, the long-term consequences can be considerable. Symptoms persisting over a period of more than 12 weeks after infection are summarized as Post-COVID (PC) syndrome. The aim of this study is to document the symptom expression in PC patients in the outpatient setting, with a major focus on limitations in daily life and consequences for mental health.

This survey is part of a prospective European collaborative study with the German cohort having been slightly extended and evaluated separately. Data collection was performed by telephone interviews of adult SARS CoV 2 positive patients using standardized questionnaires (38 open and 6 closed questions). After an inclusion interview, follow-up interviews were conducted every 4 weeks over a period of 6 months. Participants were recruited in collaboration with the local health department (Wuerzburg, Germany).

Sixty participants were recruited in April and May 2021. After 12 weeks (PC cutoff), 48.3% still reported symptoms related to SARS-CoV-2 infection. The most commonly reported symptoms were fatigue/tiredness (33.3%), reduced concentration (26.7%), and shortness of breath (23.3%). One-quarter of respondents reported impaired functioning, with the most common daily limitations being sports (28.3%), work (25.0%), and social life (15.0%). At 6 months, 21.6% of respondents experienced anxiety and 11.6% reported depressive symptoms. Overall, 40.0% of respondents were concerned that their health would deteriorate again or not fully normalize because of COVID-19. Over two-thirds (70.0%) visited a physician during the course of the study because of COVID-19, 73.8% of whom visited their general practitioner.

PC in outpatient care appears to be a complex and multifaceted condition that not only presents with physical symptoms, but also has a significant impact on mental health and daily life. Although the complexity of the condition is not yet fully understood, our findings suggest that it presents long-term challenges, particularly in outpatient care. Further research, particularly in larger and more diverse cohorts, is needed to confirm these observations. Routine screening for psychosocial comorbidities could be a valuable approach to identify supportive interventions that may help to reduce the risk of chronification and/or somatization.

Patients with COVID-19 can develop excessive inflammation in the brain and consequent neurological complications. The aim of this study was to evaluate the inflammatory, endothelial and brain injury markers in hospitalized COVID-19 patients and compare those with or without neurological symptoms. A total of 30 intensive care unit (ICU) COVID-19 patients were allocated into COVID-19 (without neurological symptoms) or neuro-COVID-19 (with neurological symptoms) groups. Patients with respiratory infection symptoms but negative for COVID-19 were included as a control group. Peripheral blood samples were collected at hospital admission (T1) (controls and ICU patients) and during hospitalization (T2: last 72 h before hospital discharge or in-hospital death) (ICU COVID-19 patients) to analyze inflammatory markers. Higher ICAM-1, CCL26 and VEGF at T1 were identified in both COVID-19 groups compared with control. Neuro-COVID-19 patients presented lower systemic BDNF levels compared with the control group and increased S100B compared with the control and COVID-19 groups. BDNF levels in survivors were lower in the neuro-COVID-19 group compared to the COVID-19 group, while S100B were higher, regardless of the outcome. In addition, all COVID-19 patients presented increased ICAM-1 and CCL26 levels over the hospitalization period (T2 > T1). Furthermore, S100B, ICAM-1, CCL26 and VEGF levels increased in relation to T1 in neuro-COVID-19 patients, with S100B and CCL26 being significantly higher in relation to the COVID-19 group. In conclusion, high levels of brain injury biomarkers were found in patients with neuro-COVID-19, indicating neuroinflammatory and consequent brain injury in the last 72 h of hospitalization.

mRNA-based vaccines played a key role in fighting the global COVID-19 pandemic by saving millions of lives. In rare cases, however, the BNT162b2 vaccine has been associated with severe adverse reactions e.g. myocarditis (OE ratio 2.78; 95% CI 2.61; 2.95) [Faksova in Vaccine 42(9):2200-2211, 2024, https://doi.org/10.1016/j.vaccine.2024.01.100 , Schwab in Clin Res Cardiol 112(3):431-440, 2022, https://doi.org/10.1007/s00392-022-02129-5 ]. Here, we describe the case of a 38-year-old man who developed a wide variety of long-term symptoms (fatigue, dizziness, palpitations with recurrent syncopes, paresthesia, paresis and fasciculations) following his first mRNA-based BNT162b2 COVID-19 vaccination. 143 days after vaccination, a subsequent COVID-19 infection was associated with exacerbation of paresis and a temporary loss of vision. After ruling out other causes and due to the immediate temporal association, an adverse reaction to vaccination appears likely. The fact that these symptoms worsened after a subsequent acute COVID 19 infection hints at the possibility of a common underlying pathophysiology. This case combines two clinical phenomena that have emerged during the COVID 19 pandemic, side effects associated with novel vaccines and Post-COVID Syndrome.

The COVID-19 pandemic has revealed significant disparities in health outcomes across various populations, with children being no exception. Objective: This study aimed to identify factors associated with hospital length of stay and intensive care unit (ICU) utilization among children hospitalized with COVID-19. Methods: The project evaluated inpatient COVID-19 hospitalization data of children aged 0 to 17 years between 2020 and 2021 with a positive PCR COVID-19 test 14 days prior to or during hospitalization. Using a multivariate linear regression model, hospital length of stay and ICU utilization were evaluated by sociodemographic factors, including age, gender, race/ethnicity, primary payer status, comorbidities, CDC Social Vulnerability Index (SVI), and clinical factors. Results: Among 376 hospitalized pediatric patients, 62.2% were non-White minorities, 4.3% had at least one comorbidity, and 58.5% were covered by public insurance. Additionally, 67.6% scored high on the SVI. The average hospital stay was 3.89 days (standard deviation (SD) = 4.8), and 25% of children utilized the ICU during their hospitalization (SD = 0.43). After adjusting for sociodemographic and clinical characteristics, minority patients were more likely to have a longer length of stay by 1.09 days compared to White patients. Minority patients were also 72% more likely to use the ICU than White patients. Conclusions: These findings demonstrate that non-White children experience more severe outcomes related to COVID-19, supporting the need for culturally specific mitigation and intervention strategies for children and families during a pandemic.

Azvudine and nirmatrelvir/ritonavir (Paxlovid) are recommended for COVID-19 treatment in China, but their safety and efficacy in the elderly population are not fully known. In this multicenter, retrospective, cohort study, we identified 5131 elderly hospitalized COVID-19 patients from 32,864 COVID-19 patients admitted to nine hospitals in Henan Province, China, from December 5, 2022, to January 31, 2023. The primary outcome was all-cause death, and the secondary outcome was composite disease progression. Propensity score matching (PSM) was performed to control for confounding factors, including demographics, vaccination status, comorbidities, and laboratory tests. After 2:1 PSM, 1786 elderly patients receiving azvudine and 893 elderly patients receiving Paxlovid were included. Kaplan-Meier and Cox regression analyses revealed that compared with Paxlovid group, azvudine could significantly reduce the risk of all-cause death (log-rank P = 0.002; HR: 0.71, 95% CI: 0.573-0.883, P = 0.002), but there was no difference in composite disease progression (log-rank P = 0.52; HR: 1.05, 95% CI: 0.877-1.260, P = 0.588). Four sensitivity analyses verified the robustness of above results. Subgroup analysis suggested that a greater benefit of azvudine over Paxlovid was observed in elderly patients with primary malignant tumors (P for interaction = 0.005, HR: 0.32, 95% CI: 0.18-0.57) compared to patients without primary malignant tumors. Safety analysis revealed that azvudine treatment had a lower incidence of adverse events and higher lymphocyte levels than Paxlovid treatment. In conclusion, azvudine treatment is not inferior to Paxlovid treatment in terms of all-cause death, composite disease progression and adverse events in elderly hospitalized COVID-19 patients.

Since its emergence in 2019, COVID-19 has become a global epidemic. Several studies have suggested a link between Alzheimer's disease (AD) and COVID-19. However, there is little research into the mechanisms underlying these phenomena. Therefore, we conducted this study to identify key genes in COVID-19 associated with AD, and evaluate their correlation with immune cells characteristics and metabolic pathways.

Transcriptome analyses were used to identify common biomolecular markers of AD and COVID-19. Differential expression analysis and weighted gene co-expression network analysis (WGCNA) were performed on gene chip datasets (GSE213313, GSE5281, and GSE63060) from AD and COVID-19 patients to identify genes associated with both conditions. Gene ontology (GO) enrichment analysis identified common molecular mechanisms. The core genes were identified using machine learning. Subsequently, we evaluated the relationship between these core genes and immune cells and metabolic pathways. Finally, our findings were validated through single-cell analysis.

The study identified 484 common differentially expressed genes (DEGs) by taking the intersection of genes between AD and COVID-19. The black module, containing 132 genes, showed the highest association between the two diseases according to WGCNA. GO enrichment analysis revealed that these genes mainly affect inflammation, cytokines, immune-related functions, and signaling pathways related to metal ions. Additionally, a machine learning approach identified eight core genes. We identified links between these genes and immune cells and also found a association between EIF3H and oxidative phosphorylation.

This study identifies shared genes, pathways, immune alterations, and metabolic changes potentially contributing to the pathogenesis of both COVID-19 and AD.

Nutrients, including bioactive natural compounds, have been demonstrated to affect key metabolic processes implicated in tumor growth and progression, both in preclinical and clinical trials. Although the application of precision nutrition as a complementary approach to improve cancer treatments is still incipient in clinical practice, the development of powerful "omics" techniques has opened new possibilities for delivering nutritional advice to cancer patients. Precision nutrition may contribute to improving the plasticity and function of antitumor immune responses.

Herein, we present the results of a randomized, prospective, longitudinal, double-blind, and parallel clinical trial (NCT05080920) in cancer patients to explore the immune-metabolic effects of a bioactive formula based on diterpenic phenols from rosemary, formulated with bioactive alkylglycerols (Lipchronic© WO/2017/187000). The trial involved cancer patients, including those with lung cancer (LC), colorectal cancer (CRC), and breast cancer (BC), undergoing chemotherapy, targeted biological therapy, and/or immunotherapy. The main readouts of the study were the analysis of Lip on systemic inflammation, hemogram profile, anthropometry, lipid and glucose profiles, and tolerability. Additionally, a deep immune phenotyping of peripheral blood mononuclear cells (PBMCs) was performed to identify the functional effects of Lip on key mediators of the immune system.

Lip was well tolerated. The lung cancer subgroup of patients showed a reduction in biomarkers of systemic inflammation, including the neutrophil-to-lymphocyte ratio (NLR). Furthermore, modulation of key players in the immune system associated with the experimental treatment Lip compared to the control placebo (Pla) treatment was revealed, with particularities among the distinct subgroups of patients. Our results encourage further research to apply molecular nutrition-based strategies as a complementary tool in the clinical management of cancer patients, particularly in the current era of novel immunotherapies.

ClinicalTrials.gov, identifier NCT05080920.

An estimated 1% to 3% of children with SARS-CoV-2 infection will develop post-COVID-19 condition (PCC).

To evaluate the odds of PCC among children with COVID-19 vaccination prior to SARS-CoV-2 infection compared with odds among unvaccinated children.

In this case-control study, children were enrolled in a multisite longitudinal pediatric cohort from July 27, 2021, to September 1, 2022, and followed up through May 2023. Analysis used a case (PCC reported)-control (no PCC reported) design and included children aged 5 to 17 years whose first real time-polymerase chain reaction (RT-PCR)-confirmed SARS-CoV-2 infection occurred during the study period, who were COVID-19 vaccine age-eligible at the time of infection, and who completed a PCC survey at least 60 days after infection. From December 1, 2022, to May 31, 2023, children had weekly SARS-CoV-2 testing and were surveyed regarding PCC (≥1 new or ongoing symptom lasting ≥1 month after infection).

COVID-19 mRNA vaccination status at time of infection was the exposure of interest; participants were categorized as vaccinated (≥2-dose series completed ≥14 days before infection) or unvaccinated. Vaccination status was verified through vaccination cards or vaccine registry and/or medical records when available.

Main outcomes were estimates of the odds of PCC symptoms. Multivariate logistic regression was performed to estimate the odds of PCC among vaccinated children compared with odds of PCC among unvaccinated children.

A total of 622 participants were included, with 28 (5%) case participants and 594 (95%) control participants. Median (IQR) age was 10.0 (7.0-11.9) years for case participants and 10.3 (7.8-12.7) years for control participants (P = .37). Approximately half of both groups reported female sex (13 case participants [46%] and 287 control participants [48%]). Overall, 57% of case participants (16 children) and 77% of control participants (458 children) were vaccinated (P = .05). After adjusting for demographic characteristics, number of acute COVID-19 symptoms, and baseline health, COVID-19 vaccination was associated with decreased odds of 1 or more PCC symptom (adjusted odds ratio [aOR], 0.43; 95% CI, 0.19-0.98) and 2 or more PCC symptoms (aOR, 0.27; 95% CI, 0.10-0.69).

In this study, mRNA COVID-19 vaccination was associated with reduced odds of PCC in children. The aORs correspond to an estimated 57% and 73% reduced likelihood of 1 or more and 2 or more PCC symptoms, respectively, among vaccinated vs unvaccinated children. These findings suggest benefits of COVID-19 vaccination beyond those associated with protection against acute COVID-19 and may encourage increased pediatric uptake.

Data on treatment outcomes among minority populations treated with remdesivir are limited. We sought to evaluate outcomes among patients hospitalized with COVID-19 and treated with remdesivir among a predominantly Black and LatinX population.

This was a retrospective cohort study of adult patients hospitalized with COVID-19 and treated with remdesivir at an urban hospital in Newark, NJ, between May 1, 2020, and April 30, 2021, prior to widespread COVID-19 vaccination uptake. We describe 28-day mortality by demographic, socio-economic, and clinical factors, including clinical status by World Health Organization's (WHO) 8-point Ordinal Scale for Clinical Improvement.

A total of 206 patients met study inclusion criteria (52% were male, 41% non-Hispanic Black and 42% Hispanic). Overall mortality at 28 days was 11%. Eighty-one percent of patients with baseline WHO status of 4 or greater recovered by day 14. Mortality was higher among those who were older (p = 0.01), those with underlying diabetes mellitus (p = 0.047), those with more severe illness on admission by WHO Ordinal Scale (WHO status ≥ 4), and those on concomitant tociluzimab or convalescent plasma use.

We found that remdesivir was effective in treating most COVID-19 patients in our study. Traditional risk factors, such as advanced age and underlying co-morbidities, were associated with worse clinical outcomes and deaths.

Objectives To evaluate the effectiveness of the National Early Warning Score 2 (NEWS2) in predicting the need for hospital admission and close monitoring of suspected patients with COVID-19 presenting to the Emergency Department (ED). This study aims to determine whether NEWS2 can aid in identifying high-risk patients with COVID-19 requiring urgent care and admission. Methodology Retrospective data from electronic health records of 300 patients with COVID-19 who presented to Mediclinic Parkview Hospital ED between January 1, 2021, and June 30, 2021, were analyzed. Collected variables included age, gender, body mass index (BMI), vital signs, and patient disposition. Statistical analysis was conducted to assess the ability of NEWS2 to predict COVID-19 patient disposition. Results A total of 300 patients were included, and their NEWS2 scores were analyzed to predict clinical deterioration. NEWS2, with a cutoff value of 2, predicted hospital admission with 86% sensitivity and 75% specificity. It achieved an average area under the curve (AUC) of 0.86 for predicting outcomes at 24 to 72 hours from the time of initial presentation to the ED. Conclusions NEWS2 demonstrates high sensitivity in predicting the disposition of patients with COVID-19. Our findings support the use of NEWS2 as a useful tool for the initial assessment of patients with COVID-19 presenting to the ED, assisting in identifying patients at risk of deterioration.

COVID-19 is a highly contagious viral disease caused by SARS-CoV-2, leading to a tragic global pandemic, where it was ranked in 2020 as the third leading cause of death in the USA, causing approximately 375,000 deaths, following heart disease and cancer. The CDC reports that the risk of death increases with age and preexisting comorbidities such as such as hypertension, diabetes, respiratory system disease, and cardiovascular disease. this report will delineate and analyze the paramount comorbidities and their repercussions on individuals infected with SARS-CoV-2.

Real-world COVID-19 vaccine effectiveness (VE) studies are investigating exposures of increasing complexity accounting for time since vaccination. These studies require methods that adjust for the confounding that arises when morbidities and demographics are associated with vaccination and the risk of outcome events. Methods based on propensity scores (PS) are well-suited to this when the exposure is dichotomous, but present challenges when the exposure is multinomial.

This simulation study aimed to investigate alternative methods to adjust for confounding in VE studies that have a test-negative design.

Adjustment for a disease risk score (DRS) is compared with multivariable logistic regression. Both stratification on the DRS and direct covariate adjustment of the DRS are examined. Multivariable logistic regression with all the covariates and with a limited subset of key covariates is considered. The performance of VE estimators is evaluated across a multinomial vaccination exposure in simulated datasets.

Bias in VE estimates from multivariable models ranged from -5.3% to 6.1% across 4 levels of vaccination. Standard errors of VE estimates were unbiased, and 95% coverage probabilities were attained in most scenarios. The lowest coverage in the multivariable scenarios was 93.7% (95% CI 92.2%-95.2%) and occurred in the multivariable model with key covariates, while the highest coverage in the multivariable scenarios was 95.3% (95% CI 94.0%-96.6%) and occurred in the multivariable model with all covariates. Bias in VE estimates from DRS-adjusted models was low, ranging from -2.2% to 4.2%. However, the DRS-adjusted models underestimated the standard errors of VE estimates, with coverage sometimes below the 95% level. The lowest coverage in the DRS scenarios was 87.8% (95% CI 85.8%-89.8%) and occurred in the direct adjustment for the DRS model. The highest coverage in the DRS scenarios was 94.8% (95% CI 93.4%-96.2%) and occurred in the model that stratified on DRS. Although variation in the performance of VE estimates occurred across modeling strategies, variation in performance was also present across exposure groups.

Overall, models using a DRS to adjust for confounding performed adequately but not as well as the multivariable models that adjusted for covariates individually.

The increase in severe acute respiratory coronavirus virus 2 (SARS-CoV-2) cases due to the omicron strain led to reduced acute care hospital beds at the Veterans Administration (VA) Hospital, North Texas; veterans with non-severe coronavirus disease 2019 (COVID-19) disease were managed at a community living center (CLC), a VA nursing home. The management of non-severe COVID-19 in VA nursing homes has not been extensively described.

We describe resident characteristics and outcomes, and infection control practices implemented during 2 COVID-19 outbreak periods (January 12-February 15, 2022, June 28-July 14, 2023). Serial testing of all CLC residents was conducted, and residents with polymerase chain reaction-confirmed SARS-CoV-2 (COVID-19) infection were included in the analysis. Resident data were ascertained from the COVID-19 facility dashboard and medical record system.

From January 12 to February 15, 2022, and June 28-July 14, 2023, 62 adults residing at the CLC were diagnosed with COVID-19. Overall, the median age was 75 years [interquartile range, 71-80], and 57 (91.9%) were men. Residents were cohorted by COVID-19 test results. A multidisciplinary team was convened, and staff were fit tested for appropriate personal protective equipment (PPE) and received refresher training on hand hygiene, donning, and doffing of PPE. Thirty-seven (59.7%) residents were symptomatic. Overall, 55 (88.7%) residents were documented to have received the SARS-CoV-2 primary vaccination series. Most residents were managed at the CLC, while 12 (19.3%) were hospitalized in acute care.

It is feasible to manage high-risk residents with non-severe COVID-19 disease in a CLC utilizing a multidisciplinary approach and implementing Infection Prevention and Control strategies.

Health systems are increasingly required to conduct health-related social needs screening. However, how social resources negatively and positively affect recovery from acute illnesses, such as COVID-19, is incompletely understood.

To examine how social determinants of health (SDOH) influence recovery from COVID-19.

In this qualitative study, patients were recruited for semistructured interviews from a post-COVID-19 pulmonary clinic at a southeastern US academic medical center between November 2022 and March 2023. Caregivers were included in dyadic interviews when available. Interviews queried participants about SDOH domains, as defined by the US Centers for Disease Control and Prevention, and their relationship with COVID-19 recovery.

Phenomenologic analysis identified themes characterizing participant perspectives on the influence of SDOH on COVID-19 recovery.

A total of 24 interviews were conducted: 10 (42%) with patient-caregiver dyads, 13 (54%) with patients alone, and 1 (4%) with 2 patients who also served as each other's caregiver. Most participants were female (18 patients [72%] and 6 caregivers [60%]). The median age of patients was 57 years (IQR, 44-61 years) and of caregivers was 47 years (IQR, 39-62 years). Three cross-cutting themes that overlapped SDOH domains were identified. Participants noted that innovative mobilization of social resources (eg, policies to secure income during time away from work) supported recovery from COVID-19 illness, but destabilization and change introduced by illness (eg, disrupted social support networks) and mistrust of previously established institutions (eg, public health misinformation) hindered recovery.

Participants identified 3 distinct SDOH domains positively and negatively influencing recovery from COVID-19 illness. The findings suggest that longitudinal, multidomain data on SDOH are needed to best address barriers and identify resources for patients recovering from acute illness and may help determine opportunities for system- and policy-level interventions that can mitigate the influence of long-standing structural inequities on health.

There have been over 670 million confirmed cases of SARS-CoV-2 infection globally, resulting in over 6.87 million deaths. With approximately 0.1 %-6.8 % experiencing reinfection. This retrospective cohort study aimed to compare the risk of short-term circulatory and respiratory sequelae between SARS-CoV-2 reinfection and initial infection, and assess the impact of vaccination.

Data from the TriNetX US Collaborative network (2020-2022) were used to create two cohorts based on reinfection status. The main outcome assessed were medical utilization, circulatory and respiratory symptoms, and circulatory and respiratory diseases. The Kaplan-Meier method was used to compare the risks between two cohorts. Four subgroup analyses (vaccination status, age, sex, race) and six sensitivity analyses (rigorous definition, modified exclusion criteria, treatment, different COVID-19 variants timeline, address survivorship bias, and E-value calculation) were also conducted.

The reinfection cohort showed a significant reduction in medical utilization [ Hazard ratio, HR: 0.867, (95 % confidence interval, CI:0.839-0.896) for hospitalization, 0.488 (0.418-0.570) for critical care services, and 0.476 (0.360-0.629) for mechanical ventilation], lower risk of circulatory diseases [ HR: 0.701 (95 % CI:0.637-0.772), 0.695 (0.583-0.829), 0.660 (0.605-0.719), 0.741 (0.644-0.854), 0.614 (0.535-0.705), and 0.758 (0.656-0.876) for ischemic heart disease, inflammatory heart disease, dysrhythmias, venous thromboembolism, other cardiac disorders, and cerebrovascular diseases, respectively], and lower risk of respiratory diseases such as pneumonia, other acute lower respiratory infections, asthma, and hypoxemia [HR: 0.302 (95 % CI: 0.273-0.333), 0.811 (0.686-0.958), 0.791 (0.735-0.850), and 0.392 (0.338-0.455), respectively]. The vaccinated reinfection cohort showed no significant differences in medical utilization, circulatory diseases, or respiratory conditions but had a higher risk of breathing abnormalities. breathing abnormalities [HR: 1.195 (95 % CI:1.087-1.313)].

The individuals who experienced reinfection exhibited milder short-term sequelae in the circulatory and respiratory systems. Vaccine administration protects against cardiovascular or respiratory systems.

Introduction Obstructive sleep apnea (OSA) is characterized by repetitive upper airway collapse resulting in episodes of apnea and hypopnea. Studies have shown worsened coronavirus disease 2019 (COVID-19) severity due to coexisting respiratory conditions and suggest increased severity of COVID-19 in patients with or at high risk of OSA. However, the extent of this correlation is unclear. This retrospective study aimed to evaluate the association between OSA severity and COVID-19 severity and assess the impact of continuous positive airway pressure (CPAP) compliance. Methods This single-center retrospective study was conducted at King Abdulaziz University Hospital (KAUH), a tertiary care center in Jeddah, Saudi Arabia. Data were collected from 62 adult patients with OSA who were diagnosed via polysomnography (PSG) and had a positive documented severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) polymerase chain reaction (PCR) test result. COVID-19 severity was categorized into mild, moderate, and severe. Results There was no significant correlation between OSA severity as measured by the apnea-hypopnea index (AHI), low oxyhemoglobin desaturation (LSAT), arousal index (AI), respiratory disturbance index (RDI), or the type of treatment used, including adherence to CPAP, and the outcomes of COVID-19. However, higher arousal with respiratory index (ARI) and a lower percentage of time with SpO2 < 90% (T90) values were linked to moderate COVID-19 severity with significant p-values of 0.046 and 0.007, respectively. Conclusion There was no significant correlation between the severity or types of OSA treatment and the severity of COVID-19. Further research including multicenter studies with bigger populations and extensive sleep study data is warranted. Understanding the OSA-COVID-19 link may improve risk stratification and patient management.

Nirmatrelvir with ritonavir (Paxlovid) is indicated for patients with Coronavirus Disease 2019 (COVID-19) who are at risk for progression to severe disease due to the presence of one or more risk factors. Millions of treatment courses have been prescribed in the United States alone. Paxlovid was highly effective at preventing hospitalization and death in clinical trials. Several studies have found a protective association in real-world data, but they variously used less recent study periods, correlational methods, and small, local cohorts. Their estimates also varied widely. The real-world effectiveness of Paxlovid remains uncertain, and it is unknown whether its effect is homogeneous across demographic strata. This study leverages electronic health record data in the National COVID Cohort Collaborative's (N3C) repository to investigate disparities in Paxlovid treatment and to emulate a target trial assessing its effectiveness in reducing severe COVID-19 outcomes.

This target trial emulation used a cohort of 703,647 patients with COVID-19 seen at 34 clinical sites across the United States between April 1, 2022 and August 28, 2023. Treatment was defined as receipt of a Paxlovid prescription within 5 days of the patient's COVID-19 index date (positive test or diagnosis). To emulate randomization, we used the clone-censor-weight technique with inverse probability of censoring weights to balance a set of covariates including sex, age, race and ethnicity, comorbidities, community well-being index (CWBI), prior healthcare utilization, month of COVID-19 index, and site of care provision. The primary outcome was hospitalization; death was a secondary outcome. We estimated that Paxlovid reduced the risk of hospitalization by 39% (95% confidence interval (CI) [36%, 41%]; p < 0.001), with an absolute risk reduction of 0.9 percentage points (95% CI [0.9, 1.0]; p < 0.001), and reduced the risk of death by 61% (95% CI [55%, 67%]; p < 0.001), with an absolute risk reduction of 0.2 percentage points (95% CI [0.1, 0.2]; p < 0.001). We also conducted stratified analyses by vaccination status and age group. Absolute risk reduction for hospitalization was similar among patients that were vaccinated and unvaccinate, but was much greater among patients aged 65+ years than among younger patients. We observed disparities in Paxlovid treatment, with lower rates among black and Hispanic or Latino patients, and within socially vulnerable communities. This study's main limitation is that it estimates causal effects using observational data and could be biased by unmeasured confounding.

In this study of Paxlovid's real-world effectiveness, we observed that Paxlovid is effective at preventing hospitalization and death, including among vaccinated patients, and particularly among older patients. This remains true in the era of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) Omicron subvariants. However, disparities in Paxlovid treatment rates imply that the benefit of Paxlovid's effectiveness is not equitably distributed.

Chronic disease is a lifelong disorder that necessitates continuing medical care and is more prone to infections such as COVID-19, compared to healthy individuals. Therefore, this study aimed to assess the severity of COVID-19 among chronic disease patients in the Kingdom of Saudi Arabia.

A cross-sectional study was conducted in selected hospitals in the Riyadh region in Saudi Arabia, over 6 months in 2022. All participants' records were reviewed for socio-demographic data including age, gender, residence, marital status, level of education, occupation, and special habits such as smoking or addiction. In addition to this main complaint and present history, history of chronic illnesses, drug intake, surgical interference, general examination findings including vital signs, state of consciousness, general condition at admission and discharge, and outcome of cases were recorded.

The mean age of the patient was 54.46 ± 15.85 (median of 53.67 years). In this study, the severity of COVID-19 was significantly associated with chronic diseases. For instance, 22.31% of the patients with diabetes reported mild symptoms, compared with 77.69% of the patients without diabetes. The current findings reported 2.18% of COVID-19 patients with respiratory diseases and 97.82% of the patients without respiratory diseases reported mild symptoms of COVID-19 infection. In comparison, 97.75% of COVID-19 patients without respiratory diseases and 2.25% of patients with respiratory diseases reported moderately severe COVID-19 infection.

The current findings revealed that 66.2% of the COVID-19 patients with chronic diseases were free of symptoms, 5.3% of them died and 0.9% of the patients were in a worse situation. The severity of COVID-19 was significantly associated with the presence of chronic diseases. Additionally, medical practitioners must be more knowledgeable about the long-term illnesses that put patients at risk for serious COVID-19 challenges and mortality.

During the COVID-19 pandemic, high-risk clients' and caregivers' access to essential personal protective equipment (PPE) was limited especially in many remote areas of Appalachia. A multidisciplinary team of community and university partners explored how to coordinate the use of community health workers (CHWs) and drone technologies to increase access to PPE in rural and remote Appalachian regions. CHWs recruited 10 Homeplace clients in an exploratory study of drone-based package delivery of PPE to assess importance and effectiveness of PPE self-efficacy related to PPE use, use of PPE, and ease and acceptability of drone delivery (following delivery only). CHWs educated each participant via in-person and Zoom meetings on the reasons for using PPE and proper use of PPE using Centers for Disease Control and Prevention guidelines. Most participants found the drone delivery of PPE easy and 80% were extremely satisfied with the drone delivery process. The frequency of mask-wearing increased from 60% at baseline to 90% at follow-up. On average, participants rated all types of PPE as effective in preventing the spread of disease. Drone officials used the findings of this pilot study to develop a waiver application to the U.S. Federal Aviation Administration to request permission to fly beyond visual line of sight in remote areas. Aerial drone technology could be a cutting-edge approach to health promotion in remote areas. The study results provide the proof of concept to assist investigators in designing future projects to promote healthy homes by collecting air and water samples and testing novel interventions deploying drone technology in remote Appalachian regions.

The spread of the COVID-19 epidemic, as well as its high contagiousness, increased students' anxiety and stress. Anxiety may affect individuals' functioning and undermine their self-efficacy. Therefore, the present study aimed to determine the relationship between COVID-19 anxiety and self-efficacy among adolescent students.

This cross-sectional descriptive correlational study was conducted on 306 adolescent students in southern Iran. The research tools were the Corona Disease Anxiety Scale consisting of physical and psychological dimensions of anxiety and the Self-Efficacy Scale composed of three subscales: academic, social, and emotional self-efficacy. Data were analyzed using SPSS 25. Pearson correlation was used to investigate the relationship between COVID-19 anxiety and self-efficacy using the total score of both scales and their dimensions as well. T-Test and one-way ANOVA were used to see whether sociodemographic variables of participants significantly varied in self-efficacy and COVID-19 anxiety.

The mean score of COVID-19 anxiety was 11.70 ± 9.25, representing mild anxiety, and the mean score of the psychological dimension was higher than that of the physical dimension. The mean self-efficacy score was 81.29 ± 12.98 indicating high level of self-efficacy. In addition, the mean score of academic self-efficacy was higher than that of social and emotional self-efficacy. There was an inverse, significant, and mild to moderate relationship between COVID-19 anxiety and the total score of self-efficacy (r = -.28, p < .001) and all its dimensions (r = -. 18, p = .002 for social and academic self-efficacy; r = -.32, p <. 001 for emotional self-efficacy). While the physical dimension of COVID-19 anxiety correlated significantly and negatively with self-efficacy total and subscale scores, the mental subscale of COVID-19 anxiety only correlated with the self-efficacy total score (r = -.20, p < .001) and emotional self-efficacy (r = -.28, p < .001).

The study results revealed that the higher the COVID-19 anxiety, the lower the self-efficacy among adolescents. It is important to prioritize the enhancement of self-efficacy among adolescents to ensure their success across various life domains including managing stressors brought about by pandemics like COVID-19. This requires a collaborative effort from parents and teachers as they are a primary source of reassurance and information. Parents and teachers can also serve as role models in showcasing resilience and positive coping with the pandemic and allow adolescent students to master adaptive coping and provide positive reinforcement for effective behaviors.

COVID-19 pandemic was accompanied by many healthcare-related issues. Concrete national data regarding the care performance of critical ill cases of COVID-19 does not exist in Korea. The current study aimed to describe the treatment outcome and healthcare resource utilization of critically ill COVID-19 patients. Our multicenter retrospective cohort study enrolled critically ill COVID-19 patients from 22 tertiary care hospitals in Korea. Inclusion criteria: (1) patients aged 19 years or older, (2) patients with laboratory-confirmed SARS-CoV-2 infection who received at least one of following initial treatments such as high-flow oxygen therapy (HFOT) or noninvasive ventilation (NIV) or invasive mechanical ventilation (IMV) or extracorporeal membrane oxygenation. During the study wave, a total of 1358 eligible participants were enrolled, with 21 institutions participating in the study. Among them, data from 1113 patients were available and analyzed. Of 921 (82.7%), 621 (55.8%) were supported by IMV. Of the 921 patients supported by HFOT or NIV, 438 (47.6%) recovered without IMV, 429 (46.6%) required IMV, and 54 died who DNR after NIV was applied. Prone position ventilation was administered to 163 (33.1%) patients with IMV and 25 (6.2%) patients with HFOT. Extracorporeal membrane oxygenation was administered to 128 (20.6%) patients treated with IMV. The overall mortality rate was 26.4%. In South Korea, mortality rates for patients with severe COVID-19 pneumonia have been shown substantial fatality, with the highest mortality rates observed in wave 3. The increased mortality rate in wave 3 could be associated with the rapid escalation of critically ill COVID-19 patients and the consequent saturation of intensive care unit capacities. Patients received NIV therapy and prone position ventilation more frequently in wave 3 as the number of cases increased.

The coronavirus disease 2019 (COVID-19) pandemic has disproportionately affected Black and Latinx communities. Ecologic analyses have shown that counties with a higher percentage of Latinx and Black people have worse COVID-19 outcome rates. Few ecologic analyses have been published at the neighborhood (census tract) level. We sought to determine whether certain sociodemographic neighborhood ecologies were associated with COVID-19 case and death rates in metropolitan Atlanta, Georgia.

We used census data and principal-component analysis to identify unique neighborhood ecologies. We then estimated correlation coefficients to determine whether the neighborhood profiles produced by a principal-component analysis were correlated with COVID-19 case and death rates. We conducted geographically weighted regression models to assess how correlation coefficients varied spatially for neighborhood ecologies and COVID-19 outcomes.

We identified two unique neighborhood profiles: (1) high percentage of residents, Hispanic ethnicity, without a high school diploma, without health insurance, living in crowded households, and lower percentage older than 65 years; and (2) high percentage of residents, Black race, living in poverty, unemployed, and households receiving Supplemental Nutrition Assistance Program benefits. Profile 1 was associated with COVID-19 case rate (Pearson r = 0.462, P < 0.001) and profile 2 was associated with COVID-19 death rate (Spearman r = 0.279, P < 0.001). Correlations between neighborhood profiles and COVID-19 outcomes varied spatially.

Neighborhoods were differentially at risk of COVID-19 cases or deaths depending on their sociodemographic ecology at the beginning of the COVID-19 pandemic. Prevention methods and interventions may need to consider different social determinants of health when addressing potential cases and deaths during future emergent epidemics.

Seasonal influenza accounts for 9.3 million-41 million illnesses, 100,000-710,000 hospitalizations, and 4,900-51,000 deaths annually in the United States. Since 2003, the Influenza Hospitalization Surveillance Network (FluSurv-NET) has been conducting population-based surveillance for laboratory-confirmed influenza-associated hospitalizations in the United States, including weekly rate estimations and descriptions of clinical characteristics and outcomes for hospitalized patients. However, a comprehensive summary of trends in hospitalization rates and clinical data collected from the surveillance platform has not been available.

2010-11 through 2022-23 influenza seasons.

FluSurv-NET conducts population-based surveillance for laboratory-confirmed influenza-associated hospitalizations among children and adults. During the reporting period, the surveillance network included 13-16 participating sites each influenza season, with prespecified geographic catchment areas that covered 27 million-29 million persons and included an estimated 8.8%-9.5% of the U.S. population. A case was defined as a person residing in the catchment area within one of the participating states who had a positive influenza laboratory test result within 14 days before or at any time during their hospitalization. Each site abstracted case data from hospital medical records into a standardized case report form, with selected variables submitted to CDC on a weekly basis for rate estimations. Weekly and cumulative laboratory-confirmed influenza-associated hospitalization rates per 100,000 population were calculated for each season from 2010-11 through 2022-23 and stratified by patient age (0-4 years, 5-17 years, 18-49 years, 50-64 years, and ≥65 years), sex, race and ethnicity, influenza type, and influenza A subtype. During the 2020-21 season, only the overall influenza hospitalization rate was reported because case counts were insufficient to estimate stratified rates.

During the 2010-11 to 2022-23 influenza seasons, laboratory-confirmed influenza-associated hospitalization rates varied significantly across seasons. Before the COVID-19 pandemic, hospitalization rates per 100,000 population ranged from 8.7 (2011-12) to 102.9 (2017-18) and had consistent seasonality. After SARS-CoV-2 emerged, the hospitalization rate for 2020-21 was 0.8, and the rate did not return to recent prepandemic levels until 2022-23. Inconsistent seasonality also was observed during 2020-21 through 2022-23, with influenza activity being very low during 2020-21, extending later than usual during 2021-22, and occurring early during 2022-23. Molecular assays, particularly multiplex standard molecular assays, were the most common influenza test type in recent seasons, increasing from 12% during 2017-18 for both pediatric and adult cases to 43% and 55% during 2022-23 for pediatric and adult cases, respectively. During each season, adults aged ≥65 years consistently had the highest influenza-associated hospitalization rate across all age groups, followed in most seasons by children aged 0-4 years. Black or African American and American Indian or Alaska Native persons had the highest age-adjusted influenza-associated hospitalization rates across these seasons. Among patients hospitalized with influenza, the prevalence of at least one underlying medical condition increased with increasing age, ranging from 36.9% among children aged 0-4 years to 95.4% among adults aged ≥65 years. Consistently across each season, the most common underlying medical conditions among children and adolescents were asthma, neurologic disorders, and obesity. The most common underlying medical conditions among adults were hypertension, obesity, chronic metabolic disease, chronic lung disease, and cardiovascular disease. The proportion of FluSurv-NET patients with acute respiratory signs and symptoms at hospital admission decreased from 90.6% during 2018-19 to 83.2% during 2022-23. Although influenza antiviral use increased during the 2010-11 through the 2017-18 influenza seasons, it decreased from 90.2% during 2018-19 to 79.1% during 2022-23, particularly among children and adolescents. Admission to the intensive care unit, need for invasive mechanical ventilation, and in-hospital death ranged from 14.1% to 22.3%, 4.9% to 11.1%, and 2.2% to 3.5% of patients hospitalized with influenza, respectively, during the reported surveillance period.

Influenza continues to cause severe morbidity and mortality, particularly in older adults, and disparities have persisted in racial and ethnic minority groups. Persons with underlying medical conditions represented a large proportion of patients hospitalized with influenza. Increased use of multiplex tests and other potential changes in facility-level influenza testing practices (e.g., influenza screening at all hospital admissions) could have implications for the detection of influenza infections among hospitalized patients. Antiviral use decreased in recent seasons, and explanations for the decrease should be further evaluated.

Continued robust influenza surveillance is critical to monitor progress in efforts to encourage antiviral treatment and improve clinical outcomes for persons hospitalized with influenza. In addition, robust influenza surveillance can potentially reduce disparities by informing efforts to increase access to preventive measures for influenza and monitoring any subsequent changes in hospitalization rates.

The ISARIC 4C Mortality score was developed to predict mortality risk among patients with COVID-19. Its performance among vaccinated individuals is understudied. This is a retrospective study of all patients with SARS-CoV-2 infection admitted to the National Centre for Infectious Diseases, Singapore, from January-2020 to December-2021. Demographic, clinical, and laboratory data were extracted, and multiple logistic regression (MLR) models were developed to predict the relationship between ISARIC score, vaccination status, anti-S antibody titre, and severe COVID-19. A total of 6377 patients were identified, of which 5329 met the study eligibility criteria. The median age of the patients was 47 years (IQR 35-71), 1264 (23.7%) were female, and 1239 (25.7%) were vaccinated. Severe disease occurred in 499 (9.4%) patients, including 133 (2.5%) deaths. After stratification, 3.0% of patients with low (0-4), 17.8% of patients with moderate (5-9), and 36.2% of patients with high (≥10) ISARIC scores developed severe COVID-19. Vaccination was associated with a reduced risk of progression to severe COVID-19 in the MLR model: aOR 0.88 (95% CI: 0.86-0.90), and the risk of severe COVID-19 decreased inversely to anti-S antibody titres. The anti-S antibody titre should be further investigated as an adjunct to the ISARIC score to triage COVID-19 patients for hospital admission and antiviral therapy.

The objective is to characterize the impact of COVID-19 on major healthcare for diabetes, including hospitalization, emergency department (ED) visits and primary care visits in Alberta, Canada.

Participants from Alberta's Tomorrow Project (ATP) with pre-existing diabetes prior to 1 April 2018 were included and followed up to 31 March 2021. A time-segmented regression model was used to characterize the impact of COVID-19 on healthcare utilization after adjusting for seasonality, socio-demographic factors, lifestyle behaviors and comorbidity profile of patients.

Among 6099 participants (53.5% females, age at diagnosis 56.1 ± 9.9 y), the overall rate of hospitalization, ED visits and primary care visits was 151.5, 525.9 and 8826.9 per 1000 person-year during the COVID-19 pandemic (up to 31 March 2021), which means they reduced by 12% and 22% and increased by 6%, compared to pre-pandemic rates, respectively. Specifically, the first COVID-19 state of emergency (first wave of the outbreak) was associated with reduced rates of hospitalization, ED visits and primary care visits, by 79.4% (95% CI: 61.3-89.0%), 93.2% (95% CI: 74.6-98.2%) and 65.7% (95% CI: 47.3-77.7%), respectively. During the second state of emergency, healthcare utilization continued to decrease; however, a rebound (increase) of ED visits was observed during the period when the public health state of emergency was relaxed.

The declared COVID-19 states of emergency had a negative impact on healthcare utilization for people with diabetes, especially for hospital and ED services, which suggests the importance of enhancing the capacity of these two healthcare sectors during future COVID-19-like public health emergencies.

Electronic medical records (EMRs) are important for rapidly compiling information to determine disease characteristics (eg, symptoms) and risk factors (eg, underlying comorbidities, medications) for disease-related outcomes. To assess EMR data accuracy, agreement between EMR abstractions and patient interviews was evaluated. Symptoms, medical history, and medication use among patients with COVID-19 collected from EMRs and patient interviews were compared using overall agreement (ie, same answer in EMR and interview), reported agreement (yes answer in both EMR and interview among those who reported yes in either), and κ statistics. Overall, patients reported more symptoms in interviews than in EMR abstractions. Overall agreement was high (≥50% for 20 of 23 symptoms), but only subjective fever and dyspnea had reported agreement of ≥50%. The κ statistics for symptoms were generally low. Reported medical conditions had greater agreement with all condition categories (n = 10 of 10) having ≥50% overall agreement and half (n = 5 of 10) having ≥50% reported agreement. More nonprescription medications were reported in interviews than in EMR abstractions, leading to low reported agreement (28%). Discordance was observed for symptoms, medical history, and medication use between EMR abstractions and patient interviews. Investigations using EMRs to describe clinical characteristics and identify risk factors should consider the potential for incomplete data, particularly for symptoms and medications.