COVID-19 is no longer a global health emergency, but it remains challenging to predict its prognosis.

To develop and validate an instrument to predict COVID-19 progression for critically ill hospitalized patients in a Brazilian population.

Observational study with retrospective follow-up. Participants were consecutively enrolled for treatment in non-critical units between January 1, 2021, to February 28, 2022. They were included if they were adults, with a positive RT-PCR result, history of exposure, or clinical or radiological image findings compatible with COVID-19. The outcome was characterized as either transfer to critical care or death. Predictors such as demographic, clinical, comorbidities, laboratory, and imaging data were collected at hospitalization. A logistic model with lasso or elastic net regularization, a random forest classification model, and a random forest regression model were developed and validated to estimate the risk of disease progression.

Out of 301 individuals, the outcome was 41.8 %. The majority of the patients in the study lacked a COVID-19 vaccination. Diabetes mellitus and systemic arterial hypertension were the most common comorbidities. After model development and cross-validation, the Random Forest regression was considered the best approach, and the following eight predictors were retained: D-dimer, Urea, Charlson comorbidity index, pulse oximetry, respiratory frequency, Lactic Dehydrogenase, RDW, and Radiologic RALE score. The model's bias-corrected intercept and slope were - 0.0004 and 1.079 respectively, the average prediction error was 0.028. The ROC AUC curve was 0.795, and the variance explained was 0.289.

The prognostic model was considered good enough to be recommended for clinical use in patients during hospitalization (https://pedrobrasil.shinyapps.io/INDWELL/). The clinical benefit and the performance in different scenarios are yet to be known.

Nationwide data are unavailable regarding changes in intensive care unit (ICU) outcomes and use of life support over the past 10 years, limiting understanding of practice changes.

To portray the epidemiology of US critical care before, during, and after the COVID-19 pandemic.

Retrospective cohort study of adult patients admitted to an ICU for any reason, using data from the 54 US health systems continuously contributing to the Epic Cosmos database from 2014-2023.

Patient demographics, COVID-19 status, and pandemic era.

In-hospital mortality unadjusted and adjusted for patient demographics, comorbidities, and illness severity; ICU length of stay; and receipt of life-support interventions, including mechanical ventilation and vasopressor medications.

Of 3 453 687 admissions including ICU care, median age was 65 (IQR, 53-75) years. Patients were 55.3% male; 17.3% Black and 6.1% Hispanic or Latino; and overall in-hospital mortality was 10.9%. The adjusted in-hospital mortality was elevated during the pandemic in COVID-negative (adjusted odds ratio [aOR], 1.3 [95% CI, 1.2-1.3]) and COVID-positive (aOR, 4.3 [95% CI, 3.8-4.8]) patients and returned to baseline by mid-2022. The median ICU length of stay was 2.1 (IQR, 1.1-4.2) days, with increases during the pandemic among COVID-positive patients (difference for COVID-positive vs COVID-negative patients, 2.0 days [95% CI, 2.0-2.1]). Rates of invasive mechanical ventilation were 23.2% (95% CI, 23.1%-23.2%) before the pandemic, increased to 25.8% (95% CI, 25.8%-25.9%) during the pandemic, and declined below prepandemic baseline thereafter (22.0% [95% CI, 21.9%-22.2%]). The use of vasopressors increased from 7.2% to 21.6% of ICU stays.

Pandemic-era increases in length of stay and adjusted in-hospital mortality among US ICU patients returned to recent historical baselines. Fewer patients are now receiving mechanical ventilation than prior to the pandemic, while more patients are administered vasopressor medications.

Clinical outcomes for patients with severe acute respiratory failure caused by different variants of the coronavirus disease 2019 (COVID-19) supported with extracorporeal membrane oxygenation (ECMO) are incompletely understood. Clinical characteristics, pre-ECMO management, and hospital mortality at 90 days for adults with COVID-19 who received venovenous ECMO (VV-ECMO) at North American centers during waves predominated by Delta (August 16 to December 12, 2021) and Omicron (January 31 to May 31, 2022) severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants were compared in a competing risks framework. One thousand seven hundred and sixty-six patients (1,580 Delta, 186 Omicron) received VV-ECMO for COVID-19 during the Delta- and Omicron-predominant waves in North American centers. In the unadjusted competing risks model, no significant difference was observed in risk of hospital mortality at 90 days between patients during the Delta- versus Omicron-predominant wave (subhazard ratio [sHR], 0.94; 95% confidence interval [CI], 0.74-1.19), but patients supported with VV-ECMO during the Omicron-predominant wave had a significantly lower adjusted risk of hospital mortality at 90 days (subhazard ratio, 0.71; 95% CI, 0.51-0.99). Patients receiving VV-ECMO during the Omicron-predominant wave had a similar unadjusted risk of hospital mortality at 90 days, but a significantly lower adjusted risk of hospital mortality at 90 days than those receiving VV-ECMO during the Delta-predominant wave.

During the COVID-19 pandemic in Shanghai, medical workers were more vulnerable to psychological problems. This two-phase cross-sectional survey was conducted by online questionnaires to investigate the symptoms of depression, anxiety, stress, post-traumatic stress disorder (PTSD), and fatigue in healthcare workers during the outbreak of COVID-19 and after the resumption of work and production in Shanghai. The questionnaire included the Depression Anxiety Stress Scale-21 (DASS-21), the Impact of Event Scale-Revised (IES-R), and the Fatigue Assessment Instrument (FAI). In Phase I (n=2192), the prevalence of depression, anxiety, stress, and PTSD symptoms among medical staff was 45.48, 41.93, 20.35, and 75.55%. In Phase II (n=1031), after work resumed in Shanghai, the prevalence was 19.79, 21.44, 28.23, and 12.22%, respectively. Fatigue had a mean score of 121.23±45.776 in Phase I and 144.73±44.141 in Phase II. Binary logistic regression identified risk factors associated with this psychological status: personal and familial chronic disease history; occupation, including doctor, nurse, or administrative staff; working in the fever clinic, infectious disease department, emergency or intensive care unit, hemodialysis room, or clinical laboratory; work experience of 3-6 years or 7-10 years; and involvement in nucleic acid sampling team. Medical staff self-reported comparatively high rates of depression, anxiety, stress, and, especially, PTSD symptoms during the COVID-19 pandemic in Shanghai. Our study indicated that after work resumption in Shanghai, it appeared that the overall mental health of medical staff improved somewhat. Nevertheless, the high level of fatigue exhibited still cannot be ignored.

The virulence and severity of SARS-CoV-2 infections have decreased over time in the general population due to vaccinations and improved antiviral treatments. Whether a similar trend has occurred in patients with cirrhosis is unclear. We used the National COVID Cohort Collaborative (N3C) to describe the outcomes over time.

We utilized the N3C level 3 data set with uncensored dates to identify all patients with chronic liver disease (CLD) with and without cirrhosis who had SARS-CoV-2 infection as of November 2023. We described the observed 30-day case fatality rate (CFR) by month of infection. We used adjusted survival analyses to calculate relative hazard of death by month of infection compared with infection at the onset of the COVID-19 pandemic.

We identified 117,811 total patients with CLD infected with SARS-CoV-2 between March 2020 and November 2023: 27,428 (23%) with cirrhosis and 90,383 (77%) without cirrhosis. The observed 30-day CFRs during the entire study period were 1.1% (1016) for patients with CLD without cirrhosis and 6.3% (1732) with cirrhosis. Observed 30-day CFRs by month of infection varied throughout the pandemic and showed a sustained downward trend since 2022. Compared with infection in Quarter 2 of 2020 (at the beginning of the pandemic), the adjusted hazards of death at 30 days for infection in Quarter 3 of 2023 were 0.20 (95% confidence interval [CI], 0.08-0.50) for patients with CLD without cirrhosis and 0.35 (95% CI, 0.18-0.69) for patients with CLD with cirrhosis.

In this N3C study, we found that the observed 30-day CFR decreased progressively for patients with CLD both with and without cirrhosis, consistent with broader trends seen in the general population.

This study presents a wastewater-based mathematical model for assessing the transmission dynamics of the SARS-CoV-2 pandemic in Miami-Dade County, Florida. The model, which takes the form of a deterministic system of nonlinear differential equations, monitors the temporal dynamics of the disease, as well as changes in viral RNA concentration in the county's wastewater system (which consists of three sewage treatment plants). The model was calibrated using the wastewater data during the third wave of the SARS-CoV-2 pandemic in Miami-Dade (specifically, the time period from July 3, 2021 to October 9, 2021). The calibrated model was used to predict SARS-CoV-2 case and hospitalization trends in the county during the aforementioned time period, showing a strong correlation between the observed (detected) weekly case data and the corresponding weekly data predicted by the calibrated model. The model's prediction of the week when maximum number of SARS-CoV-2 cases will be recorded in the county during the simulation period precisely matches the time when the maximum observed/reported cases were recorded (which was August 14, 2021). Furthermore, the model's projection of the maximum number of cases for the week of August 14, 2021 is about 15 times higher than the maximum observed weekly case count for the county on that day (i.e., the maximum case count estimated by the model was 15 times higher than the actual/observed count for confirmed cases). This result is consistent with the result of numerous SARS-CoV-2 modeling studies (including other wastewater-based modeling, as well as statistical models) in the literature. Furthermore, the model accurately predicts a one-week lag between the peak in weekly COVID-19 case and hospitalization data during the time period of the study in Miami-Dade, with the model-predicted hospitalizations peaking on August 21, 2021. Detailed time-varying global sensitivity analysis was carried out to determine the parameters (wastewater-based, epidemiological and biological) that have the most influence on the chosen response function-the cumulative viral load in the wastewater. This analysis revealed that the transmission rate of infectious individuals, shedding rate of infectious individuals, recovery rate of infectious individuals, average fecal load per person per unit time and the proportion of shed viral RNA that is not lost in sewage before measurement at the wastewater treatment plant were most influential to the response function during the entire time period of the study. This study shows, conclusively, that wastewater surveillance data can be a very powerful indicator for measuring (i.e., providing early-warning signal and current burden) and predicting the future trajectory and burden (e.g., number of cases and hospitalizations) of emerging and re-emerging infectious diseases, such as SARS-CoV-2, in a community.

Since April 2022, the SARS-CoV-2 Omicron variant has caused a notable increase in pediatric COVID-19 cases in Taiwan. During the acute phase of infection, some children required admissions to pediatric intensive care units (PICU). This study aimed to analyze their clinical presentations and outcomes while exploring associated factors.

Medical records were retrospectively collected from patients with COVID-19 (aged <18 years) admitted to our PICU from April 2022-March 2023. Early stage is defined as the period without adequate vaccination and treatment guidelines for children from April-June 2022, and the remaining months are referred to as late stage. Clinical characteristics and outcomes were compared between patients in early and late stages.

We enrolled 78 children with COVID-19, with a median length of stay (LOS) in PICU of 3 days and a 5% mortality rate. Patients admitted during the early stage had lower vaccination rates (7% vs. 50%), higher pediatric logistic organ dysfunction scores (2 vs. 0.1), and longer LOS in the PICU (6 vs. 2 days) than those admitted during the late stage. Multivariate analysis identified admission during the early stage as a risk factor for prolonged LOS (>7 days) in the PICU (odds ratio: 3.65, p = 0.047).

Without available vaccinations and suitable treatment guidelines, children with COVID-19 tended to have more severe illness and prolonged LOS in the PICU. These observations highlight the importance of vaccinations and familiarity of medical providers with adequate management of this newly-emerging infectious disease.

There is conflicting evidence regarding the impact of chronic hepatitis B virus (HBV) on SARS-CoV-2 outcomes. Additionally, the impact of SARS-CoV-2 vaccination and variant periods on outcomes in HBV/SARS-CoV-2 coinfection remain unexplored.

We utilized the TriNetX database to compare adults with HBV/SARS-CoV-2 (vs SARS-CoV-2 alone) across 97 US healthcare systems from 2020 to 2023. We assessed the odds of all inpatient hospitalizations, intensive care unit admissions, mechanical ventilation, 30-day, 90-day, and overall mortality. In sensitivity analyses, we excluded HIV, hepatitis C virus, and transplant cases and stratified the HBV/SARS-CoV-2 cohort by cirrhosis status. We applied propensity score matching to address confounding and reported odds ratios (OR) with 95% confidence intervals (CI).

Of 4 206 774 individuals with SARS-CoV-2, about 0.2% (8293) were HBV/SARS-CoV-2. Individuals with HBV/SARS-CoV-2 (vs SARS-CoV-2 alone) had higher odds of intensive care unit admissions (OR, 1.18; 95% CI, 1.02-1.36), 90-day (OR, 1.22; 95% CI, 1.01-1.41) and overall mortality (OR, 1.18; 95% CI, 1.06-1.33). In sensitivity analyses, those with HBV/SARS-CoV-2 and cirrhosis had a 2.0- to 2.50-fold higher odds of adverse outcomes. Notably, even individuals with HBV/SARS-CoV-2 without cirrhosis had higher odds of mortality. Vaccinated (vs unvaccinated) individuals with HBV/SARS-CoV-2 had 57%, 54%, and 29% reduction in 30-day, 90-day, and overall mortality, respectively. The pre-Delta variant period was associated with higher odds of hospitalization compared to the Omicron but not the Delta period.

Chronic HBV was associated with worse SARS-CoV-2 outcomes, whereas SARS-CoV-2 vaccination reduced the likelihood of adverse outcomes.

 This study aimed to determine the effect of the Omicron variant on pregnancy-related and neonatal outcomes among the Black-dominant population.

 We performed a single-center, retrospective cohort study during the prepandemic period from December 1, 2019, to February 29, 2020, and the Omicron surging period from December 1, 2021, to February 28, 2022. A total of 518 pregnant women were admitted for delivery during the study period. Multiple gestations (n = 21) and deliveries at less than 20 weeks of gestation (n = 5) were excluded. We analyzed and compared the sociodemographic and clinical data from mothers and their neonates between the two cohorts as well as between severe acute respiratory syndrome-coronavirus-2 (SARS-CoV-2) positive and negative mothers during the Omicron surge. Subgroup analyses were also conducted specifically among the Black-only population.

 The cohorts were predominantly Black (88.6%), with smaller proportions of Hispanic (8.9%), Asian (0.8%), White (0.8%), and other ethnicities (0.8%). Of 492 singleton deliveries, 275 live births, 8 (2.8%) stillbirths, and 31 (11.3%) preterm births (PTBs) occurred during the prepandemic period, and 207 live births, 2 (1%) stillbirths, and 33 (15.9%) PTBs occurred during the Omicron wave. There was no statistically significant difference in the rates of PTBs, stillbirths, medically indicated PTBs, and cesarean delivery between the two cohorts. SARS-CoV-2-positive mothers were not at an increased risk of adverse outcomes. However, neonatal intensive care unit (NICU) admission rate significantly increased among neonates born to SARS-CoV-2 positive mothers compared with negative mothers (32.3 vs. 16.5%, p = 0.038). In subgroup analyses among Black individuals, this difference was not observed.

 There was no significant difference in pregnancy-related or neonatal outcomes in the Black-dominant population between the two cohorts. SARS-CoV-2 infection did not alter these findings except for an increased NICU admission rate among neonates born to SARS-CoV-2-positive mothers.

· Most pregnant women infected with SARS-CoV-2 during the Omicron wave were asymptomatic.. · The Omicron wave did not increase the risk of pregnancy-related or neonatal adverse outcomes when compared with the prepandemic period.. · Maternal SARS-CoV-2 infection increased NICU admission rate.. · Among Black individuals, no significant increase in adverse outcomes was observed during the Omicron pandemic..

This study investigates the relationship between SARS-CoV-2 RT-PCR cycle threshold (Ct) values and key COVID-19 transmission and outcome metrics across five years of the pandemic in Jalisco, Mexico. Utilizing a comprehensive time-series analysis, we evaluated weekly median Ct values as proxies for viral load and their temporal associations with positivity rates, reproduction numbers (Rt), hospitalizations, and mortality. Cross-correlation and lagged regression analyses revealed significant lead-lag relationships, with declining Ct values consistently preceding surges in positivity rates and hospitalizations, particularly during the early phases of the pandemic. Granger causality tests and vector autoregressive modeling confirmed the predictive utility of Ct values, highlighting their potential as early warning indicators. The study further observed a weakening association in later pandemic stages, likely influenced by the emergence of new variants, hybrid immunity, changes in human behavior, and diagnostic shifts. These findings underscore the value of Ct values as scalable tools for public health surveillance and highlight the importance of contextualizing their analysis within specific epidemiological and temporal frameworks. Integrating Ct monitoring into surveillance systems could enhance pandemic preparedness, improve outbreak forecasting, and strengthen epidemiological modeling.

Participants: The study population included UIC-affiliated gala attendees. Outbreak-associated cases tested positive for COVID-19 between April 2 and April 11, 2022. Attendees who did not test positive or develop symptoms within ten days of the event were classified as contacts.

Methods: We ascertained cases through phone-based contact tracing and a survey and evaluated symptom severity using a novel classification system.

Results: Among 307 UIC students registered to attend the gala, the minimum attack rate was 14.0%. Approximately 56% of cases were mildly symptomatic, and 38.9% reported severe symptoms.

Conclusions: Our findings align with prior research documenting heightened transmissibility of Omicron-variant-related strains and highlight the need for nuanced symptom assessment methodologies.

To describe the demographic/clinical characteristics, treatment patterns, and mortality among patients hospitalized with COVID-19 during Omicron predominance by immunocompromised and high-risk status.

Retrospective observational study of patients hospitalized with COVID-19 between January 1, 2022 and November 30, 2022, using data from the Optum de-identified Clinformatics Data Mart Database. Patient demographic/clinical characteristics, treatments, mortality and costs, were assessed, during the emergence of BA.1 BA.4, BA.5, BA.2.12.1, BA.2.75, BQ.1, XBB Omicron viral subvariants.

Overall, 43,123 patients were included, with a mean (standard deviation [SD]) age of 75.5 (12.4) years, 51.8% were female. Immunocompromised patients accounted for 36% of hospitalized patients while only 5.8% received any outpatient COVID-19 treatment within 30 days of hospital admission. The mean (SD) hospital length of stay was 7.9 (7.5) days with 15.5% mortality within 30 days of admission. Mean (SD) hospital costs were $33,975 ($26,392), and 30-day all-cause readmission was 15.1%. Patients with immunocompromised status and those with a higher number of high-risk conditions proceeded to have an elevated proportion of hospital readmissions and mortality within 30 days. Moreover, a higher proportion of mortality was observed during the BA.1 period (20.1%) relative to other variant periods (11.0%).

COVID-19 imposed a large healthcare burden, particularly among immunocompromised patients and those with underlying high-risk conditions during Omicron period. Low utilization of outpatient COVID-19 treatments was observed in these high-risk populations eligible for treatment. Continued surveillance and research regarding COVID-19 variants and the impact of outpatient treatment options on high-risk patients is crucial to inform and guide public health action.

Severe disease due to COVID-19 has declined dramatically as a result of widespread vaccination and natural immunity in the population. With the emergence of SARS-CoV-2 variants that largely escape vaccine-elicited neutralizing antibody responses, the efficacy of the original vaccines has waned and has required vaccine updating and boosting. Nevertheless, hospitalizations and deaths due to COVID-19 have remained low. In this review, we summarize current knowledge of immune responses that contribute to population immunity and the mechanisms how vaccines attenuate COVID-19 disease severity.

To describe the 12-month mortality of Dutch COVID-19 intensive care unit patients, the total COVID-19 population and various subgroups on the basis of the number of comorbidities, age, sex, mechanical ventilation, and vasoactive medication use.

We included all patients admitted with COVID-19 between March 1, 2020, and March 29, 2022, from the Dutch National Intensive Care (NICE) database. The crude 12-month mortality rate is presented via Kaplan-Meier survival curves for each patient subgroup. We used Cox regression models to analyze the effects of patient characteristics on 12-month mortality after hospital discharge.

We included 16,605 COVID-19 patients. The in-hospital mortality rate was 28.1%, and the 12-month mortality rate after intensive care unit admission was 29.8%. Among hospital survivors, 12-month mortality after hospital discharge was 2.5% (300/11,931). The hazard of death at 12 months after hospital discharge was greater in patients between 60 and 79 years (HR 4.74; 95%CI 2.23 - 10.06) and ≥ 80 years (HR 22.77; 95%CI 9.91 - 52.28) than in patients < 40 years of age; in male patients than in female patients (HR 1.38; 95%CI 1.07 - 1.78); and in patients with one (adjusted HR 1.95; 95%CI 1.5 - 2.53), two (adjusted HR 4.49; 95%CI 3.27 - 6.16) or more than two comorbidities (adjusted HR 4.99; 95%CI 2.62 - 9.5) than in patients with no comorbidities. Neither vasoactive medication use nor mechanical ventilation resulted in statistically significant results.

For Dutch COVID-19 intensive care unit patients, most deaths occurred during their hospital stay. For hospital survivors, the crude 12-month mortality rate was low. Patient age (older than 60), sex and the number of comorbidities were associated with a greater hazard of death at 12 months after hospital discharge, whereas mechanical ventilation and vasoactive medication were not.

Fungal infections are significant complications of severe coronavirus disease 2019 (COVID-19). Although various risk factors for poor outcomes in patients with COVID-19 have been identified, clinical and treatment factors associated with fungal infections in patients with severe COVID-19 remain unclear. This study aimed to elucidate clinical factors associated with fungal infections during severe COVID-19 treatment.

This was a post hoc analysis of the J-RECOVER study, a multicenter retrospective observational study involving patients with COVID-19 who required admission at 66 hospitals between January and September 2020. Inclusion criteria were ages ≥ 18 years, COVID-19 diagnosis with reverse-transcription polymerase chain reaction, and treatment with mechanical ventilation (MV). Patients who received antifungal drugs before MV were excluded. Potential predictors were identified through univariate analysis of patient and treatment characteristics between patients with- and those without fungal infection, which was defined as antifungal agent use for ≥ 5 days. To account for facility-specific data clustering, generalized estimating equations (GEE) were employed as adjusted analyses to calculate the relative risks of potentially associated factors. Two sensitivity analyses were performed with modified definitions for the two groups: patients who received antifungal drugs for ≤ 4 days were excluded, and fungal infection was re-defined as antifungal drug use for ≥ 14 days.

Among 4,915 patients in the J-RECOVER study, 559 adults with COVID-19 who required MV were included. Fungal infections occurred in 57 (10.2%) patients. Univariate analyses identified age, age ≥ 65 years, D-dimer level, remdesivir use, steroid use, and duration of steroid therapy as potential predictors of fungal infections. Multivariate analysis using GEE on these six factors revealed that only the duration of steroid use was significantly associated with an increased risk of fungal infection (odds ratio [OR] for a day increase: 1.01; 95% confidence interval [CI]: 1.00-1.01; p < 0.001). The two sensitivity analyses similarly showed that the duration of steroid use was associated with fungal infection (odds ratio for a day increase: 1.01; 95% CI: 1.00-1.01; p < 0.001 for both).

In patients with severe COVID-19 requiring MV, each additional day of steroid use was associated with prolonged use of antifungal medications for ≥ 5 days.

Growing evidence suggests SARS-CoV-2 infection increases the risk of long term cardiovascular, neurological, and other effects. However, post-acute health care costs following SARS-CoV-2 infection are not known.

Beginning 56 days following SARS-CoV-2 polymerase chain reaction (PCR) testing, we compared person-specific total and component health care costs (2020 CAD$) for the first year of follow-up at the mean and 99th percentiles of health care costs for matched test-positive and test-negative adults in Ontario, Canada, between January 1, 2020, and March 31, 2021. Matching included demographics, baseline clinical characteristics, and two-week time blocks.

For 531,182 people, mean person-specific total health care costs were $513.83 (95% CI $387.37-$638.40) higher for test-positive females and $459.10 (95% CI $304.60-$615.32) higher for test-positive males, which were driven by hospitalization, long-term care, and complex continuing care costs. At the 99th percentile of each subgroup, person-specific health care costs were $12,533.00 (95% CI $9008.50-$16,473.00) higher for test-positive females and $14,604.00 (95% CI $9565.50-$19,506.50) for test-positive males, driven by hospitalization, specialist (males), and homecare costs (females). Cancer costs were lower. Six-month and 1-year cost differences were similar.

Post-acute health care costs after a positive SARS-CoV-2 PCR test were significantly higher than matched test-negative individuals, and these increased costs persisted for at least one year. The largest increases health care costs came from hospitalizations, long-term care, complex continuing care, followed by outpatient specialists (for males) and homecare costs (for women). Given the magnitude of ongoing viral spread, policymakers, clinicians, and patients should be aware of higher post-acute health care costs following SARS-CoV-2 infection.

To explore the risk factors of proteinuria in Omicron variant patients and to construct and verify the risk predictive model.

1091 Omicron patients who were hospitalized from August 2022 to November 2022 at Tianjin First Central Hospital were defined as the derivation cohort. 306 Omicron patients who were hospitalized from January 2022 to March 2022 at the same hospital were defined as the validation cohort. The risk factors of proteinuria in derivation cohort were screened by univariate and multivariate logistic regression analysis, and proteinuria predicting scoring system was constructed and the receiver operating characteristic(ROC)curve was drawn to test the prediction ability. The proteinuria risk model was externally validated in validation cohort.

7 factors including comorbidities, blood urea nitrogen (BUN), serum sodium (Na), uric acid (UA), C reactive protein (CRP) and vaccine dosages were included to construct a risk predictive model. The score ranged from -5 to 16. The area under the ROC curve(AUC) of the model was 0.8326(95% CI 0.7816 to 0.8835, p < 0.0001). Similarly to that observed in derivation cohort, the AUC is 0.833(95% CI 0.7808 to 0.9002, p < 0.0001), which verified good prediction ability and diagnostic accuracy in validation cohort.

The risk model of proteinuria after Omicron infection had better assessing efficiency which could provide reference for clinical prediction of the risk of proteinuria in Omicron patients.

To compare the clinical characteristics of symptoms and laboratory findings across SARS-CoV-2 variants (Wild-type, Alpha, Delta, Omicron) and assess the effectiveness of COVID-19 vaccines in preventing symptoms and laboratory abnormalities.

We conducted a retrospective cohort study of individuals with SARS-CoV-2 infection at Beijing Ditan Hospital, Capital Medical University. Patients were grouped by the SARS-CoV-2 variant (Wild-type, Alpha, Delta, Omicron) based on whole-genome sequencing. Thirteen symptoms and 22 laboratory indices were compared across variants, and Omicron patients were further analyzed by vaccination status with generalized estimating equations (GEE) model.

One thousand four hundred and thirteen participants were included for the analysis as following: Wild-type group (N=322), Alpha group (N=67), Delta group (N=98), and Omicron group (N=926). Omicron patients showed the highest proportion (30.1%) of respiratory symptoms across groups. Patients displayed normal laboratory manifestation, except for inflammatory markers, coagulation function index and glucose. Meanwhile, the Omicron variant was featured by higher inflammatory biomarkers (serum amyloid A protein [SAA] and C-reactive protein [CRP]). In addition, Omicron patients with three or more vaccine doses had fewer symptoms and higher values of SAA and CRP compared to those with fewer than three doses. Results of GEE showed, when compared with ≤ 1 vaccine dose, red blood cell count, white blood cell count, neutrophil count, platelet count, haemoglobin, and C-reactive protein in patients with ≥ 3 doses of vaccine significantly increased; while aspartic transaminase, creatine kinase, blood urea nitrogen, activated partial thromboplastin time, prothrombin time and thrombin time dramatically decreased, respectively.

Omicron variant resulted in abnormal inflammatory response. Individuals with three or more vaccine doses are more likely to experience fewer symptoms and have stronger protection against the virus. This study highlights key differences in symptom onset and laboratory profiles across SARS-CoV-2 variants, reinforcing the importance of three vaccine doses in providing strong protection against the Omicron variant.

We aim to estimate the incidence rates (IRs) of SARS-CoV-2 infections stratified by disease severity and comorbidities in pediatric population and to describe the COVID-19 vaccination coverage in children with and without comorbidities. A population-based cohort study was conducted in 6 electronic healthcare records databases from Italy, Spain, and Norway. The study lasted from 1 January 2020 to the latest databases' available data in each site, i.e., in Italian ARS Tuscany and PEDIANET: December 2021, in Spanish BIFAP: February 2022; SIDIAP: June 2022, and VID: December 2021. Finally, in Norwegian Health Registries: December 2021. Children and adolescents were included and stratified into three age categories (< 5, 5- < 12, and 12- < 18 years old). IRs (95% confidence intervals) per 100 person-years (PY) for non-severe (positive SARS-CoV-2 test or diagnosis without hospitalization) and severe COVID-19 (hospitalization, intensive care unit admission, and death after COVID-19) are reported. The cumulative COVID-19 vaccination rollout was stratified by population with and without comorbidities. The study population comprised 5,654,040 individuals < 18 years of age (51% females) across the six European databases (median age: 6 years), with 1.4 to 8.5% of them having at least one at-risk comorbidity for severe COVID-19. Incidence rates of severe COVID-19 were low (0-1 per 100 PY) but 3 to 4 times higher among children and adolescents with comorbidities during Omicron BA.1-2 wave in December 2021-January 2022. Percentages of vaccination rollout in the general population were between 13% in PEDIANET-IT and 64% in BIFAP-ICU-ES. In ARS-IT and SIDIAP-IT, vaccination rate in children with comorbidities was slightly lower than that in the general population.

Severe COVID-19 was rare across databases, but up to 3 to 4 times higher in children with comorbidities during the predominance of Omicron BA.1-2 variant in winter 2021-2022. COVID-19 vaccination coverage was slightly lower in children with comorbidities in ARS (Tuscany) and SIDIAP (Catalonia) data sources. Our findings will inform future public policies aimed to protect the pediatric population, both within these countries and globally.

• Pediatric population is susceptible to SARS-CoV-2 infection. • COVID-19 severity rates in children vary across study settings and context.

• This study confirms the low severity rates of COVID-19 in the pediatric population based on a large cohort of children and adolescents residing in Spain, Italy, and Norway. • Incidence of severe COVID-19 in children and adolescents with comorbidities was up to 3 to 4 times higher than in the general pediatric population during the SARS-CoV-2 high transmission wave of Omicron BA.1-2 variant in winter 2021-2022 in Italy and Spain.

Despite the end of the global Coronavirus Disease 2019 (COVID-19) pandemic, the risk factors for COVID-19 severity continue to be a pivotal area of research. Specifically, studying the impact of the genomic diversity of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) on COVID-19 severity is crucial for predicting severe outcomes. Therefore, this study aimed to investigate the impact of the SARS-CoV-2 genome sequence, genotype, patient age, gender, and vaccination status on the severity of COVID-19, and to develop accurate and robust prediction models. The training set (n = 12,038), primary testing set (n = 4,006), and secondary testing set (n = 2,845) consist of SARS-CoV-2 genome sequences with patient information, which were obtained from Global Initiative on Sharing all Individual Data (GISAID) spanning over four years. Four machine learning methods were employed to construct prediction models. By extracting SARS-CoV-2 genomic features, optimizing model parameters, and integrating models, this study improved the prediction accuracy. Furthermore, Shapley Additive exPlanes (SHAP) was applied to analyze the interpretability of the model and to identify risk factors, providing insights for the management of severe cases. The proposed ensemble model achieved an F-score of 88.842% and an Area Under the Curve (AUC) of 0.956 on the global testing dataset. In addition to factors such as patient age, gender, and vaccination status, over 40 amino acid site mutation characteristics were identified to have a significant impact on the severity of COVID-19. This work has the potential to facilitate the early identification of COVID-19 patients with high risks of severe illness, thus effectively reducing the rates of severe cases and mortality.

Xie Y, Choi T, Al-Aly Z. Postacute sequelae of SARS-CoV-2 infection in the pre-Delta, Delta, and Omicron eras. N Engl J Med. 2024;391:515-525. 39018527.

On December 7, 2022, China switched from dynamic zeroing strategy against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) to reopening. A nationwide SARS-CoV-2 epidemic emerged rapidly. The effect of smoking on SARS-CoV-2 infection remains unclear. We aimed to retrospectively investigate the relationship between smoking and coronavirus disease 2019 (COVID-19) using a community-based cohort of smokers and non-smokers. We included participants from a pre-pandemic cohort with a prolonged follow-up period. Data on smoking status, body mass index, and history of other diseases were collected from health examination and consultation clinic records. Cox regression analysis was used to identify the relationship between groups and SARS-CoV-2 infection over time. We analysed 218 male patients with varied smoking statuses (46.3% current or ex-smokers; average age 68.63 ± 9.81 years). Two peaks in the epidemic were observed following the December 2022 outbreak. At the end of the second peak, non-smokers, current smokers, and ex-smokers had primary infection rates increase to 88.0%, 65.1%, and 81.0%, respectively, with a significant difference between the groups. Current smoking significantly protected against SARS-CoV-2 infection (HR 0.625, 95% CI 0.402-0.970, p = 0.036). Further analyses showed that the prevalence of pneumonia in the unvaccinated, older, diabetic, and non-smoking groups was significantly higher than that in the other groups (p < 0.05). Our study suggests a potential association between smoking and a reduced risk of SARS-CoV-2 infection and pneumonia. This indicates that nicotine and ACE2 play important roles in preventing COVID-19 and its progression. We suggest smokers use nicotine replacement therapy during hospitalization for COVID-19.

The emergence of the COVID-19 pandemic required an immediate global clinical research response. The ACTIV (Accelerating COVID-19 Therapeutic Interventions and Vaccines)-3 trials and the ACTIV-associated Outpatient Treatment with Anti-Coronavirus Immunoglobulin trial used Good Participatory Practices (GPP) to develop materials for study implementation from a global network perspective. GPP guidelines offer a framework for engaging stakeholders throughout the research process. This paper provides an overview of the materials developed and their applicability in various settings, reports results from a survey of study site personnel on the materials' usefulness, summarizes important lessons learned, and serves as a reference for networks eager to apply GPP. Survey results showed that flipbooks and overview videos were highly ranked. Stakeholder input was valuable in developing easily understandable participant-facing materials with culturally appropriate images. Materials should be available to submit with the initial protocol submissions to ethics committees, and in formats that accommodate a wide range of institutional resources, policies, and infection-control practices. This article emphasizes the importance of GPP, including stakeholder consultation, in developing materials that support clinical research and address language, cultural, and sociopolitical barriers during a pandemic. The findings will be used to optimize efforts and resource allocation for new and ongoing studies.

To identify characteristics of SARS-CoV-2 infection that are associated with hospitalization in children initially evaluated in a Pediatric Emergency Department (ED).

We identified cases of SARS-CoV-2 positive patients seen in the Arkansas Children's Hospital (ACH) ED or hospitalized between May 27, 2020, and April 28, 2022, using ICD-10 codes within the Pediatric Hospital Information System (PHIS) Database. We compared infection waves for differences in patient characteristics and used logistic regressions to examine which features led to a higher chance of hospitalization.

We included 681 pre-Delta cases, 673 Delta cases, and 970 Omicron cases. Almost 17% of patients were admitted to the hospital. Compared to Omicron-infected children, pre-Delta and Delta-infected children were twice as likely hospitalized (OR = 2.2 and 2.0, respectively; p<0.0001). Infants under one year were >3 times as likely to be hospitalized than children ages 5-14 years regardless of wave (OR = 3.42; 95%CI = 2.36-4.94). Rural children were almost three times as likely than urban children to be hospitalized across all waves (OR = 2.73; 95%CI = 1.97-3.78). Finally, those with a complex condition had nearly a 15-fold increase in odds of admission (OR = 14.6; 95%CI = 10.6-20.0).

Children diagnosed during the pre-Delta or Delta waves were more likely to be hospitalized than those diagnosed during the Omicron wave. Younger and rural patients were more likely to be hospitalized regardless of the wave. We suspect lower vaccination rates and larger distances from medical care influenced higher hospitalization rates.

The aim of the investigation was to compare patients hospitalized with SARS-CoV-2 infection during 2020/2021 and 2022 with respect to the reason for hospitalization as well as severity of disease at admission, during follow-up and clinical outcomes.

The data of all patients patients hospitalized with SARS-CoV-2 infection during the periods of interest were collected. Severity of disease at admission and during follow-up was compared in all patients who were hospitalized because of SARS-CoV-2 infection.

During the period of 2020 to 2021, overall n=1281 patients with SARS-CoV-2 infection were hospitalized as compared to n=580 in 2022. Of these, 90% and 42%, respectively, were admitted because of SARS-CoV-2 infection. The rates of nosocomial transmission increased from 5 to 18%. Severity of disease at admission and during follow-up was higher across all age groups in the first period. More patients were admitted to the ICU (25 versus 4%). Accordingly, hospital mortality was higher (17 versus 10%). Intubated patients had a high mortality of 74 and 80%, respectively, in both periods.

The severity at admission and during follow-up was much higher in the first period. In the second period, the burden of health care systems was only in part driven by disease severity but more by the need for isolation and nosocomial infections. Mortality of intubated patients was high.

There is lack of research on corticosteroid use for severe and critical COVID-19 patients with Omicron variant infection.

This multi-center retrospective cohort study involved 1167 patients from 59 ICUs across the mainland of China diagnosed with severe or critical SARS-CoV-2 Omicron variant infection between November 1, 2022, and February 11, 2023. Patients were segregated into two groups based on their corticosteroid treatment-usual dose (equivalent prednisone dose 30-50 mg/day) and higher dose (equivalent prednisone dose > 50 mg/day). The primary outcome was 28-day ICU mortality. Propensity score matching was used to compare outcomes between cohorts.

After propensity score matching, 520 patients in the usual dose corticosteroid group and 260 patients in the higher dose corticosteroid group were included in the analysis, respectively. The mortality was significantly higher in the higher dose corticosteroid group (67.3%, 175/260) compared to the usual dose group (56.0%, 291/520). Logistic regression showed that higher doses of corticosteroids were significantly associated with increased mortality at 28-day (OR = 1.62,95% CI 1.19-2.21, p = 0.002) and mortality in ICU stay (OR = 1.66,95% CI 1.21-2.28, p = 0.002). Different types of corticosteroids did not affect the effect.

The study suggests that higher-dose corticosteroids may lead to a poorer prognosis for severe and critical COVID-19 patients with Omicron variant infection in the ICU. Further research is needed to determine the appropriate corticosteroid dosage for these patients.

Colorectal cancer (CRC) screening is underused, particularly among low-income and minoritized populations, for whom the coronavirus disease 2019 (COVID-19) pandemic has challenged progress in achieving equity.

A hub-and-spoke model was used. The hub was a nonacademic organization and the spokes were three community health center (CHC) systems overseeing numerous clinic sites. Via a cluster-randomized trial design, nine clinic sites were randomized to intervention and 16 clinic sites were randomized to usual care. Patient-level interventions included invitation letters, mailed fecal immunochemical tests (FITs), and call/text-based reminders. Year 1 intervention impact, which took place during the COVID-19 pandemic, was assessed as the proportion completing screening among individuals not up to date at baseline, which compared intervention and nonintervention clinics accounting for intraclinic cluster variation; confidence intervals (CIs) around differences not including 0 were interpreted as statistically significant.

Among 26,736 patients who met eligibility criteria, approximately 58% were female, 55% were Hispanic individuals, and 44% were Spanish speaking. The proportion completing screening was 11.5 percentage points (ppts) (95% CI, 6.1-16.9 ppts) higher in intervention versus usual care clinics. Variation in differences between intervention and usual care clinics was observed by sex (12.6 ppts [95% CI, 7.2-18.0 ppts] for females; 8.8 ppts [95% CI, 4.7-13.9 ppts] for males) and by racial and ethnic group (13.8 ppts [95% CI, 7.0-20.6 ppts] for Hispanic individuals; 13.0 ppts [95% CI, 3.6-22.4 ppts] for Asian individuals; 11.3 ppts [95% CI, 5.8-16.8 ppts] for non-Hispanic White individuals; 6.1 ppts [95% CI, 0.8-10.4 ppts] for Black individuals).

A regional mailed FIT intervention was effective for increasing CRC screening rates across CHC systems serving diverse, low-income populations.

The COVID-19 pandemic, caused by SARS-CoV-2, disproportionately affected certain segments of society, particularly the elderly population (which suffered the brunt of the burden of the pandemic in terms of severity of the disease, hospitalization, and death). This study presents a generalized multigroup model, with m heterogeneous sub-populations, to assess the population-level impact of age heterogeneity and vaccination on the transmission dynamics and control of the SARS-CoV-2 pandemic in the United States. Rigorous analysis of the model for the homogeneous case (i.e., the model with m = 1) reveal that its disease-free equilibrium is globally-asymptotically stable for two special cases (with perfect vaccine efficacy or negligible disease-induced mortality) whenever the associated reproduction number is less than one. The model has a unique and globally-asymptotically stable endemic equilibrium, for special a case, when the associated reproduction threshold exceeds one. The homogeneous model was fitted using the observed cumulative mortality data for the United States during three distinct waves (Waves A (October 17, 2020 to April 5, 2021), B (July 9, 2021 to November 7, 2021) and C (January 1, 2022 to May 7, 2022)) chosen to align with time periods when the Alpha, Delta and Omicron were, respectively, the predominant variants in the United States. The calibrated model was used to derive a theoretical expression for achieving vaccine-derived herd immunity (needed to eliminate the disease in the United States). It was shown that, using the one-group homogeneous model, vaccine-derived herd immunity is not attainable during Wave C of the pandemic in the United States, regardless of the coverage level of the fully-vaccinated individuals. Global sensitivity analysis was carried out to determine the parameters of the model that have the most influence on the disease dynamics and burden. These analyses reveal that control and mitigation strategies that may be very effective during one wave may not be so very effective during the other wave or waves. However, strategies that target asymptomatic and pre-symptomatic infectious individuals are shown to be consistently effective across all waves. To study the impact of the disproportionate effect of COVID-19 on the elderly population, we considered the heterogeneous model for the case where the total population is subdivided into the sub-populations of individuals under 65 years of age and those that are 65 and older. The resulting two-group heterogeneous model, which was also fitted using the cumulative mortality data for wave C, was also rigorously analysed. Unlike for the case of the one-group model, it was shown, for the two-group model, that vaccine-derived herd immunity can indeed be achieved during Wave C of the pandemic if at least 61% of the populace is fully vaccinated. Thus, this study shows that adding age heterogeneity into a SARS-CoV-2 vaccination model with homogeneous mixing significantly reduces the level of vaccination coverage needed to achieve vaccine-derived herd immunity (specifically, for the heterogeneous model, herd-immunity can be attained during Wave C if a moderate proportion of susceptible individuals are fully vaccinated). The consequence of this result is that vaccination models for SARS-CoV-2 that do not explicitly account for age heterogeneity may be overestimating the level of vaccine-derived herd immunity threshold needed to eliminate the SARS-CoV-2 pandemic.

With coronavirus disease 2019 (COVID-19) vaccination no longer mandated by many businesses/organizations, it is now up to individuals to decide whether to get any new boosters/updated vaccines going forward.

We developed a Markov model representing the potential clinical/economic outcomes from an individual perspective in the United States of getting versus not getting an annual COVID-19 vaccine.

For an 18-49 year old, getting vaccinated at its current price ($60) can save the individual on average $30-$603 if the individual is uninsured and $4-$437 if the individual has private insurance, as long as the starting vaccine efficacy against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection is ≥50% and the weekly risk of getting infected is ≥0.2%, corresponding to an individual interacting with 9 other people in a day under Winter 2023-2024 Omicron SARS-CoV-2 variant conditions with an average infection prevalence of 10%. For a 50-64 year old, these cost-savings increase to $111-$1278 and $119-$1706 for someone without and with insurance, respectively. The risk threshold increases to ≥0.4% (interacting with 19 people/day), when the individual has 13.4% preexisting protection against infection (eg, vaccinated 9 months earlier).

There is both clinical and economic incentive for the individual to continue to get vaccinated against COVID-19 each year.