Development and validation of a preliminary multivariable diagnostic model for identifying unusual infections in hospitalized patients.

Diagnostic delay leads to poor outcomes in infections, and it occurs more often when the causative agent is unusual. Delays are attributable to failing to consider such diagnoses in a timely fashion. Using routinely collected electronic health record (EHR) data, we built a preliminary multivariable diagnostic model for early identification of unusual fungal infections and tuberculosis in hospitalized patients. We conducted a two-gate case-control study. Cases encompassed adult patients admitted to 19 Mayo Clinic enterprise hospitals between January 2010 and March 2023 diagnosed with blastomycosis, cryptococcosis, histoplasmosis, mucormycosis, pneumocystosis, or tuberculosis. Control groups were drawn from all admitted patients (random controls) and those with community-acquired infections (ID-controls). Development and validation datasets were created using randomization for dividing cases and controls (7:3), with a secondary validation using ID-controls. A logistic regression model was constructed using baseline and laboratory variables, with the unusual infections of interest outcome. The derivation dataset comprised 1043 cases and 7000 random controls, while the 451 cases were compared to 3000 random controls and 1990 ID-controls for validation. Within the derivation dataset, the model achieved an area under the curve (AUC) of 0.88 (95% confidence interval [CI]: 0.87-0.89) with a good calibration accuracy (Hosmer-Lemeshow P = 0.623). Comparable performance was observed in the primary (AUC = 0.88; 95% CI: 0.86-0.9) and secondary validation datasets (AUC = 0.84; 95% CI: 0.82-0.86). In this multicenter study, an EHR-based preliminary diagnostic model accurately identified five unusual fungal infections and tuberculosis in hospitalized patients. With further validation, this model could help decrease time to diagnosis.

Association Between Ethnicity and Mortality Outcomes in Patients with COVID-19: A Mayo Clinic VIRUS Registry Cohort Study.

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.

Using Mobile and Remote Simulation as a Research Methodology for Health Care Delivery Research.

SUMMARY STATEMENT: Mobile and remote simulation can be used as a research methodology to collect data in simulated environments to answer research questions pertaining to health care delivery. This research methodology can exponentially increase the reachable target study participants and provide generalizable conclusions. Using a large-scale national study in the United States as an exemplar, this article outlines the technology and equipment required to conduct mobile and remote simulations for research purposes. The cost associated with using mobile and remote simulations as well as the advantages and challenges of using this research methodology are also discussed.

The Neutrophil/Lymphocyte Ratio and Outcomes in Hospitalized Patients with Community-Acquired Pneumonia: A Retrospective Cohort Study.

We aimed to assess the prognostic role of the neutrophil/lymphocyte ratio (NLR) in community-acquired pneumonia (CAP) via a single-center retrospective cohort of hospitalized adult patients from 1/2009 to 12/2019. Patients were dichotomized into lower NLR (≤12) and higher NLR (>12). The primary outcome was mortality. ICU admission and hospital- and ICU-free days were secondary outcomes. The pneumonia severity index (PSI) and the NLR's ability to predict outcomes was also tested. An NLR ≤12 was observed in 2513 (62.2%) patients and >12 in 1526 (37.8%). After adjusting for PSI, the NLR was not associated with hospital mortality (odds ratio [OR] 1.115; 95% confidence interval [CI] 0.774, 1.606; p = 0.559), but it was associated with a higher risk of ICU admission (OR 1.405; 95% CI 1.216, 1.624; p < 0.001). The PSI demonstrated acceptable discrimination for mortality (area under the receiver operating characteristic curve [AUC] 0.78; 95% CI 0.75, 0.82) which was not improved by adding the NLR (AUC 0.78; 95% CI 0.75, 0.82, p = 0.4476). The PSI's performance in predicting ICU admission was also acceptable (AUC 0.75; 95% CI 0.74, 0.77) and improved by including the NLR (AUC 0.76, 95% CI 0.74, 0.77, p = 0.008), although with limited clinical significance. The NLR was not superior to the PSI for predicting mortality in hospitalized CAP patients.

Early empiric antibiotic use in COVID-19 patients: results from the international VIRUS registry.

OBJECTIVES: COVID-19 escalated inappropriate antibiotic use. We determined the distribution of pathogens causing community-acquired co-infections, the rate, and factors associated with early empiric antibiotic (EEAB) treatment among hospitalized COVID-19 patients. METHODS: The Society of Critical Care Medicine Discovery Viral Infection and Respiratory Illness Universal Study (VIRUS) COVID-19 Registry including 68,428 patients from 28 countries enrolled between January 2020 and October 2021 were screened. After exclusions, 7830 patients were included in the analysis. Azithromycin and/or other antibiotic treatment given within the first 3 days of hospitalization was investigated. Univariate and multivariate analyses were performed to determine factors associated with EEAB use. RESULTS: The majority (6214, 79.4%) of patients received EEAB, with azithromycin combination being the most frequent (3146, 40.2%). As the pandemic advanced, the proportion of patients receiving EEAB regressed from 84.4% (786/931) in January-March 2020 to 65.2% (30/46) in April-June 2021 (P < 0.001). Beta-lactams, especially ceftriaxone was the most commonly used antibiotic. Staphylococcus aureus was the most commonly isolated pathogen. Multivariate analysis showed geographical location and pandemic timeline as the strongest independent predictors of EEAB use. CONCLUSIONS: EEAB administration decreased as pandemic advanced, which may be the result of intensified antimicrobial stewardship efforts. Our study provides worldwide goals for antimicrobial stewardship programs in the post-COVID-19 era.

Impact of SARS-CoV-2 Vaccine Rollout on Hispanic and Non-Hispanic Admission and Mortality Trends: An Interrupted Time Series Analysis.

BACKGROUND: Challenges with SARS-CoV-2 vaccine prioritization, access, and hesitancy have influenced vaccination uptake. RESEARCH QUESTION: Was the impact of SARS-CoV-2 vaccine rollout on COVID-19 monthly admission and mortality trends different between Hispanic and non-Hispanic populations? STUDY DESIGN AND METHODS: We used interrupted time series analysis to conduct an ancillary study of the Viral Infection and Respiratory Illness Universal Study registry supplemented by electronic health record data from five participating Mayo Clinic sites in Florida, Arizona, Minnesota, and Wisconsin. We included hospitalized patients with COVID-19 admitted between April 2020 and December 2021. Our primary outcome was the impact of vaccine rollout on admission trends. Our secondary outcome was the impact of vaccine rollout on mortality trends. RESULTS: This interrupted time series analysis includes 6,442 patients. Vaccine rollout was associated with improved monthly hospital admission trends among both Hispanic and non-Hispanic patients. Among Hispanic patients, pre-vaccine rollout, monthly admissions increased by 12.9% (95% CI, 8.1%-17.9%). Immediately after vaccine rollout, patient admissions declined by -66.3% (95% CI, -75.6% to -53.9%). Post-vaccine rollout, monthly admissions increased by 3.7% (95% CI, 0.2%-7.3%). Among non-Hispanic patients, pre-vaccine rollout, monthly admissions increased by 35.8% (95% CI, 33.4%-38.1%). Immediately after vaccine rollout, patient admissions declined by -75.2% (95% CI, -77.6% to -72.7%). Post-vaccine rollout, monthly admissions increased by 5.6% (95% CI, 4.5%-6.7%). These pre-vaccine rollout admission trends were significantly different (P < .001). Post-vaccine rollout, the change in admission trend was significantly different (P < .001). The associated beneficial impact from vaccine rollout on monthly hospital admission trends among Hispanic patients was significantly lower. The trend in monthly mortality rate was fourfold greater (worse) among Hispanic patients (8.3%; 95% CI, 3.6%-13.4%) vs non-Hispanic patients (2.2%; 95% CI, 0.6%-3.8%), but this was not shown to be related to vaccine rollout. INTERPRETATION: SARS-CoV-2 vaccine rollout was associated with improved COVID-19 admission trends among non-Hispanic vs Hispanic patients. Vaccine rollout was not shown to influence mortality trends in either group, which were four times higher among Hispanic patients. Improved vaccine rollout may have reduced disparities in admission trends for Hispanic patients, but other factors influenced their mortality trends.

Machine Learning for Automated Classification of Abnormal Lung Sounds Obtained from Public Databases: A Systematic Review.

Pulmonary auscultation is essential for detecting abnormal lung sounds during physical assessments, but its reliability depends on the operator. Machine learning (ML) models offer an alternative by automatically classifying lung sounds. ML models require substantial data, and public databases aim to address this limitation. This systematic review compares characteristics, diagnostic accuracy, concerns, and data sources of existing models in the literature. Papers published from five major databases between 1990 and 2022 were assessed. Quality assessment was accomplished with a modified QUADAS-2 tool. The review encompassed 62 studies utilizing ML models and public-access databases for lung sound classification. Artificial neural networks (ANN) and support vector machines (SVM) were frequently employed in the ML classifiers. The accuracy ranged from 49.43% to 100% for discriminating abnormal sound types and 69.40% to 99.62% for disease class classification. Seventeen public databases were identified, with the ICBHI 2017 database being the most used (66%). The majority of studies exhibited a high risk of bias and concerns related to patient selection and reference standards. Summarizing, ML models can effectively classify abnormal lung sounds using publicly available data sources. Nevertheless, inconsistent reporting and methodologies pose limitations to advancing the field, and therefore, public databases should adhere to standardized recording and labeling procedures.

Validation of automated data abstraction for SCCM discovery VIRUS COVID-19 registry: practical EHR export pathways (VIRUS-PEEP).

Background: The gold standard for gathering data from electronic health records (EHR) has been manual data extraction; however, this requires vast resources and personnel. Automation of this process reduces resource burdens and expands research opportunities. Objective: This study aimed to determine the feasibility and reliability of automated data extraction in a large registry of adult COVID-19 patients. Materials and methods: This observational study included data from sites participating in the SCCM Discovery VIRUS COVID-19 registry. Important demographic, comorbidity, and outcome variables were chosen for manual and automated extraction for the feasibility dataset. We quantified the degree of agreement with Cohen's kappa statistics for categorical variables. The sensitivity and specificity were also assessed. Correlations for continuous variables were assessed with Pearson's correlation coefficient and Bland-Altman plots. The strength of agreement was defined as almost perfect (0.81-1.00), substantial (0.61-0.80), and moderate (0.41-0.60) based on kappa statistics. Pearson correlations were classified as trivial (0.00-0.30), low (0.30-0.50), moderate (0.50-0.70), high (0.70-0.90), and extremely high (0.90-1.00). Measurements and main results: The cohort included 652 patients from 11 sites. The agreement between manual and automated extraction for categorical variables was almost perfect in 13 (72.2%) variables (Race, Ethnicity, Sex, Coronary Artery Disease, Hypertension, Congestive Heart Failure, Asthma, Diabetes Mellitus, ICU admission rate, IMV rate, HFNC rate, ICU and Hospital Discharge Status), and substantial in five (27.8%) (COPD, CKD, Dyslipidemia/Hyperlipidemia, NIMV, and ECMO rate). The correlations were extremely high in three (42.9%) variables (age, weight, and hospital LOS) and high in four (57.1%) of the continuous variables (Height, Days to ICU admission, ICU LOS, and IMV days). The average sensitivity and specificity for the categorical data were 90.7 and 96.9%. Conclusion and relevance: Our study confirms the feasibility and validity of an automated process to gather data from the EHR.

The Diagnostic Accuracy of Metagenomic Next-Generation Sequencing in Diagnosing Pneumocystis Pneumonia: A Systemic Review and Meta-analysis.

Background: Pneumocystis pneumonia (PCP) is a growing concern as the immunocompromised population expands. Current laboratory approaches are limited. This systematic review aimed to evaluate metagenomic next-generation sequencing (MNGS) tests' performance in detecting PCP. Methods: Five databases were searched through December 19, 2022, to identify original studies comparing MNGS with clinically diagnosed PCP. To assess the accuracy, symmetric hierarchical summary receiver operating characteristic models were used. Results: Eleven observational studies reporting 1442 patients (424 with PCP) were included. Six studies focused exclusively on recipients of biologic immunosuppression (none with HIV-associated immunosuppression). Six were exclusively on bronchoalveolar lavage, while 1 was on blood samples. The sensitivity of MGNS was 0.96 (95% CI, 0.90-0.99), and specificity was 0.96 (95% CI, 0.92-0.98), with negative and positive likelihood ratios of 0.02 (95% CI, 0.01-0.05) and 19.31 (95% CI, 10.26-36.36), respectively. A subgroup analysis of studies exclusively including bronchoalveolar lavage (BAL) and blood samples demonstrated a sensitivity of 0.94 (95% CI, 0.78-0.99) and 0.93 (95% CI, 0.80-0.98) and a specificity of 0.96 (95% CI, 0.88-0.99) and 0.98 (95% CI, 0.76-1.00), respectively. The sensitivity analysis on recipients of biologic immunosuppression showed a sensitivity and specificity of 0.96 (95% CI, 0.90-0.98) and 0.94 (95% CI, 0.84-0.98), respectively. The overall confidence in the estimates was low. Conclusions: Despite the low certainty of evidence, MNGS detects PCP with high sensitivity and specificity. This also applies to recipients of biologic immunosuppression and tests performed exclusively on blood samples without the need for BAL. Further studies are required in individuals with HIV-associated immunosuppression.

Pneumothorax, pneumomediastinum, and subcutaneous emphysema in hospitalized COVID-19 patients: incidence, clinical characteristics, and outcomes.

BACKGROUND: Limited data is available on the incidence and outcomes of pneumothorax (PTX), pneumomediastinum (PNM), and subcutaneous emphysema (SCE) in COVID-19 patients. This study aimed to investigate the characteristics of these complications in hospitalized COVID-19 patients. RESEARCH DESIGN AND METHODS: A retrospective study was conducted, involving adult COVID-19 patients admitted to Mayo Clinic Florida from 03/2020-06/2022. Patients were divided into two groups based on the presence or absence of PTX/PNM/SCE. RESULTS: 1926 hospitalized patients with COVID-19 were included, of which 518 were admitted to the ICU. The incidence of PTX/PNM/SCE was 6.3%. Patients with these complications were more likely to be male, Asian, and unvaccinated. Conversely, they were less likely to have chronic obstructive pulmonary disease. Patients who developed PTX/PNM/SCE after 72 hours of admission were more likely to receive high-dose corticosteroids and for an extended duration. The affected group had an adjusted odds ratio for in-hospital mortality of 13.32 (95%CI, 8.19-21.59) and ICU admission of 9.14 (95%CI, 5.3-12.78) compared to the unaffected group. CONCLUSION: Although the occurrence of PTX/PNM/SCE in hospitalized COVID-19 patients was rare, it was associated with worse outcomes. Corticosteroids may contribute to the pathogenesis of these complications; however, further studies are needed to investigate this relationship in more detail.

Pre-hospital use of direct oral anticoagulants agents is associated with a lower risk of major bleeding events in critically ill patients: A single academic center experience.

BACKGROUND: The last decade has witnessed significant advancements in direct oral anticoagulants (DOACs), transforming the landscape of anticoagulation therapy. With the uptrend in DOACs use, critical care physicians are encountering more patients with pre-hospital DOACs prescription. Safety and real world outcomes-related data on DOACs use in critically ill patients are scarce. OBJECTIVE: We assess the risk of major bleeding (MB) events and patient-centered outcomes with pre-hospital use of direct oral anticoagulant agents (DOACs) compared to warfarin therapy. METHODS: Observational study in a single large academic center from January 1st, 2012, through May 4th, 2018. We included adult critically ill patients with warfarin or one of the DOACs, as active medications at the time of hospital admission. The primary outcome was major bleeding (MB), based on the ISTH criteria RESULTS: 99,481 patients were screened; 558 and 3037 patients were included in the final analysis for the DOAC and warfarin groups, respectively. Multivariable analysis showed that the pre-hospital use of DOACs was associated with lower odds for major bleeding events, GI bleeding, need for endoscopic intervention, hemorrhagic shock, any blood transfusion; but higher odds of intracranial bleeding, as compared to warfarin use. There was no difference in hospital length of stay or ICU-free days. CONCLUSIONS: Pre-hospital use of DOACs among critically ill patients is associated with lower major bleeding events, GI bleeding, need for endoscopic intervention, and blood transfusion but a higher risk for intracranial bleeding.

Biomarker-Concordant Steroid Administration in Severe Coronavirus Disease-2019.

BACKGROUND: Although corticosteroids have become the standard of care for patients with coronavirus disease-2019 (COVID-19) on supplemental oxygen, there is growing evidence of differential treatment response. This study aimed to evaluate if there was an association between biomarker-concordant corticosteroid treatment and COVID-19 outcomes. METHODS: This registry-based cohort study included adult COVID-19 hospitalized patients between January 2020 and December 2021 from 109 institutions. Patients with available C-reactive protein (CRP) levels within 48 h of admission were evaluated. Those on steroids before admission, stayed in the hospital for <48 h, or were not on oxygen support were excluded. Corticosteroid treatment was biomarker-concordant if given with high baseline CRP ≥150 mg/L or withheld with low CRP (<150 mg/L) and vice-versa was considered discordant (low CRP with steroids, high CRP without steroids). Hospital mortality was the primary outcome. Sensitivity analyses were conducted using varying CRP level thresholds. The model interaction was tested to determine steroid effectiveness with increasing CRP levels. RESULTS: Corticosteroid treatment was biomarker-concordant in 1778 (49%) patients and discordant in 1835 (51%). The concordant group consisted of higher-risk patients than the discordant group. After adjusting for covariates, the odds of in-hospital mortality were significantly lower in the concordant group than the discordant (odds ratio [95% confidence interval (C.I.)] = 0.71 [0.51, 0.98]). Similarly, adjusted mortality difference was significant at the CRP thresholds of 100 and 200 mg/L (odds ratio [95% C.I.] = 0.70 [0.52, 0.95] and 0.57 [0.38, 0.85], respectively), and concordant steroid use was associated with lower need for invasive ventilation for 200 mg/L threshold (odds ratio [95% C.I.] = 0.52 [0.30, 0.91]). In contrast, no outcome benefit was observed at CRP threshold of 50. When the model interaction was tested, steroids were more effective at reducing mortality as CRP levels increased. CONCLUSION: Biomarker-concordant corticosteroid treatment was associated with lower odds of in-hospital mortality in severe COVID-19.

Development and Validation of an Acute Respiratory Distress Syndrome Prediction Model in Coronavirus Disease 2019: Updated Lung Injury Prediction Score.

OBJECTIVE: To develop and validate an updated lung injury prediction score for coronavirus disease 2019 (COVID-19) (c-LIPS) tailored for predicting acute respiratory distress syndrome (ARDS) in COVID-19. PATIENTS AND METHODS: This was a registry-based cohort study using the Viral Infection and Respiratory Illness Universal Study. Hospitalized adult patients between January 2020 and January 2022 were screened. Patients who qualified for ARDS within the first day of admission were excluded. Development cohort consisted of patients enrolled from participating Mayo Clinic sites. The validation analyses were performed on remaining patients enrolled from more than 120 hospitals in 15 countries. The original lung injury prediction score (LIPS) was calculated and enhanced using reported COVID-19-specific laboratory risk factors, constituting c-LIPS. The main outcome was ARDS development and secondary outcomes included hospital mortality, invasive mechanical ventilation, and progression in WHO ordinal scale. RESULTS: The derivation cohort consisted of 3710 patients, of whom 1041 (28.1%) developed ARDS. The c-LIPS discriminated COVID-19 patients who developed ARDS with an area under the curve (AUC) of 0.79 compared with original LIPS (AUC, 0.74; P<.001) with good calibration accuracy (Hosmer-Lemeshow P=.50). Despite different characteristics of the two cohorts, the c-LIPS's performance was comparable in the validation cohort of 5426 patients (15.9% ARDS), with an AUC of 0.74; and its discriminatory performance was significantly higher than the LIPS (AUC, 0.68; P<.001). The c-LIPS's performance in predicting the requirement for invasive mechanical ventilation in derivation and validation cohorts had an AUC of 0.74 and 0.72, respectively. CONCLUSION: In this large patient sample c-LIPS was successfully tailored to predict ARDS in COVID-19 patients.

Implementation of a Multimodal Knowledge-Exchange Platform to Provide Trauma Critical Care Education During the Ongoing Conflict in Ukraine.

Importance: The conflict in Ukraine has forced civilian hospitals with limited trauma and battlefield medicine experience to care for casualties of war, placing significant strain on the health care system. Using the Checklist for Early Recognition and Treatment of Acute Illness and Injury (CERTAIN) program, a multimodal trauma critical care knowledge-exchange platform was created for clinicians practicing in these institutions. Objectives: To describe the development and implementation of the CERTAIN for Ukraine program and to evaluate the reach of this intervention, together with participant engagement and satisfaction. Design, Setting, and Participants: This quality improvement study included clinicians caring for critically ill patients during the ongoing Ukrainian conflict who were part of a community developed using a messaging app. The program was implemented by a group of international trauma and critical care experts in collaboration with critical care leaders from the Shupyk National Healthcare University in Kyiv, Ukraine. This study evaluates data collected from the CERTAIN for Ukraine program from its launch on April 9, 2022, to August 31, 2022. Interventions: The initiative comprised a longitudinal series of interactive tele-education sessions, a webpage containing the CERTAIN approach and current trauma critical care guidelines translated into Ukrainian and Russian, and a private messaging chat for asynchronous discussion. Main Outcomes and Measures: Participant engagement and satisfaction were tracked using multimedia analytics and a post-session survey. Results: Since program launch, 838 participants have joined the messaging group, and 6 tele-education sessions have been delivered, with 1835 total views. The CERTAIN website has had 3527 visits, mainly from Ukraine (1378 [39%]) and the United States (1060 [30%]). Of the 74 completed postsession surveys, 65 respondents (88%) rated the course content excellent or very good, and 73 (99%) recommended it to others. Conclusions and Relevance: The findings of this quality improvement study indicate that, using widely available and low-cost platforms, knowledge was shared rapidly and efficiently to a large community of clinicians practicing in a wartime environment with broad-based engagement and a high level of learner satisfaction.

Diagnostic delay in pulmonary blastomycosis: a case series reflecting a referral center experience.

PURPOSE: The diagnosis of pulmonary blastomycosis is usually delayed because of its non-specific presentation. We aimed to assess the extent of diagnostic delay in hospitalized patients and detect the step in the diagnostic process that requires the most improvement. METHODS: Adult patients diagnosed with pulmonary blastomycosis during a hospital admission between January 2010 through November 2021 were eligible for inclusion. Patients who did not have pulmonary involvement and who were diagnosed before admission were excluded. Demographics and comorbid conditions, specifics of disease presentation, and interventions were evaluated. The timing of the diagnosis, antifungal treatment, and patient outcomes were noted. Descriptive analytical tests were performed. RESULTS: A total of 43 patients were diagnosed with pulmonary blastomycosis during their admissions. The median age was 47 years, with 13 (30%) females. Of all patients, 29 (67%) had isolated pulmonary infection, while 14 (33%) had disseminated disease, affecting mostly skin and musculoskeletal system. The median duration between the initial symptoms and health care encounters was 4 days, and the time to hospital admission was 9 days. The median duration from the initial symptoms to the diagnosis was 20 days. Forty patients (93%) were treated with empirical antibacterials before a definitive diagnosis was made. In addition, corticosteroid treatment was empirically administered to 15 patients (35%) before the diagnosis, with indications such as suspicion of inflammatory processes or symptom relief. In 38 patients (88%), the first performed fungal diagnostic test was positive. Nineteen patients (44%) required admission to the intensive care unit, and 11 patients (26%) died during their hospital stay. CONCLUSION: There was a delay in diagnosis of patients with pulmonary blastomycosis, largely attributable to the lack of consideration of the etiological agent. Novel approaches to assist providers in recognizing the illness earlier and trigger evaluation are needed.

Variations in Administrative Approvals During the COVID-19 Pandemic at Participating Sites in the Society of Critical Care Medicine Discovery Network Viral Infection and Respiratory Illness Universal Study: COVID-19 Registry: A Cross-Sectional Study.

There is a paucity of literature regarding administrative approvals required for clinical studies during a pandemic. We aimed to evaluate variation in duration of administrative approvals within the Viral Infection and Respiratory illness Universal Study (VIRUS): A Global COVID-19 Registry. DESIGN SETTING AND SUBJECTS: Survey analysis of 188 investigators who participated in the VIRUS: COVID-19 registry, a prospective, observational global registry database of 287 sites. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: For each study site approved through December 8, 2020, we assessed the duration in days: 1) from institutional review board (IRB) submission to IRB approval, 2) from IRB approval to Research Electronic Data Capture (REDCap) access, 3) from REDCap access to first patient data entry in REDCap, and 4) total duration from IRB submission to first patient data entry in REDCap. Analysis of variance and Wilcoxon rank-sum test were used to compare time durations. Of 287 sites, 188 sites (United States = 155, non-United States = 33) provided complete administrative data. There was considerable variability in duration from IRB submission to first patient data entry with median (interquartile range) of 28 days (16-50 d), with differences not significantly different by country (United States: 30 [17-50] vs non-United States: 23 d [8-46 d]; p = 0.08) or previous "multisite trial experience" (experienced: 27 [15-51] vs not experienced: 29 d [13-47 d]; p = 0.67). The U.S. sites had a higher proportion of female principal investigators (n = 77; 50%), compared with non-U.S. sites (n = 7; 21%; p = 0.002). Non-U.S. sites had a significantly shorter time to first patient data entry after REDCap access: 7 (1-28) versus 3 days (1-6 d) (p = 0.02). CONCLUSIONS: In this Society of Critical Care Medicine global VIRUS: COVID-19 Registry, we identified considerable variability in time from IRB submission to first patient data entry with no significant differences by country or prior multicenter trial experience. However, there was a significant difference between US and non-U.S. sites in the time from REDCap access to first data entry.

Pre-hospital Aspirin Use and Patient Outcomes in COVID-19: Results from the International Viral Infection and Respiratory Illness Universal Study (VIRUS)

Introduction: The goal of this investigation is to assess the association between prehospital use of aspirin (ASA) and patient-centered outcomes in a large global cohort of hospitalized COVID-19 patients.Methods: This study utilizes data from the Society of Critical Care Medicine Discovery Viral Infection and Respiratory Illness Universal Study (VIRUS) Registry. Adult patients hospitalized from February 15th, 2020, to September 30th, 2021, were included. Multivariable regression analyses were utilized to assess the association between pre-hospital use of ASA and the primary outcome of overall hospital mortality.Results: 21,579 patients were included from 185 hospitals (predominantly US-based, 71.3%), with 4691 (21.7%) receiving pre-hospital ASA. Patients receiving ASA, compared to those without pre-admission ASA use, were generally older (median 70 vs. 59 years), more likely to be male (58.7 vs. 56.0%), caucasian (57.4 vs. 51.6%), and more commonly had higher rates of medical comorbidities. In multivariable analyses, patients receiving pre-hospital ASA had lower mortality (HR: 0.89, 95% CI 0.82–0.97, p=0.01) and reduced hazard for progression to severe disease or death (HR: 0.91, 95% CI 0.84–0.99, p=0.02) and more hospital free days (1.00 days, 95% CI 0.66–1.35, p=0.01) compared to those without pre-hospital ASA use. The overall direction and significance of the results remained the same in sensitivity analysis, after adjusting the multivariable model for time since pandemic.Conclusions: In this large international cohort, pre-hospital use of ASA was associated with a lower hazard for death in hospitalized patients with COVID-19. Randomized controlled trials may be warranted to assess the utility of pre-hospital use of ASA. (AU)

Association of Early Steroid Administration With Outcomes of Children Hospitalized for COVID-19 Without Multisystem Inflammatory Syndrome in Children.

Importance: There is limited evidence for therapeutic options for pediatric COVID-19 outside of multisystem inflammatory syndrome in children (MIS-C). Objective: To determine whether the use of steroids within 2 days of admission for non-MIS-C COVID-19 in children is associated with hospital length of stay (LOS). The secondary objective was to determine their association with intensive care unit (ICU) LOS, inflammation, and fever defervescence. Design, Setting, and Participants: This cohort study analyzed data retrospectively for children (<18 years) who required hospitalization for non-MIS-C COVID-19. Data from March 2020 through September 2021 were provided by 58 hospitals in 7 countries who participate in the Society of Critical Care Medicine Discovery Viral Infection and Respiratory Illness Universal Study (VIRUS) COVID-19 registry. Exposure: Administration of steroids within 2 days of admission. Main Outcomes and Measures: Length of stay in the hospital and ICU. Adjustment for confounders was done by mixed linear regression and propensity score matching. Results: A total of 1163 patients met inclusion criteria and had a median (IQR) age of 7 years (0.9-14.3). Almost half of all patients (601/1163, 51.7%) were male, 33.8% (392/1163) were non-Hispanic White, and 27.9% (324/1163) were Hispanic. Of the study population, 184 patients (15.8%) received steroids within 2 days of admission, and 979 (84.2%) did not receive steroids within the first 2 days. Among 1163 patients, 658 (56.5%) required respiratory support during hospitalization. Overall, patients in the steroids group were older and had greater severity of illness, and a larger proportion required respiratory and vasoactive support. On multivariable linear regression, after controlling for treatment with remdesivir within 2 days, country, race and ethnicity, obesity and comorbidity, number of abnormal inflammatory mediators, age, bacterial or viral coinfection, and disease severity according to ICU admission within first 2 days or World Health Organization ordinal scale of 4 or higher on admission, with a random intercept for the site, early steroid treatment was not significantly associated with hospital LOS (exponentiated coefficient, 0.94; 95% CI, 0.81-1.09; P = .42). Separate analyses for patients with an LOS of 2 days or longer (n = 729), those receiving respiratory support at admission (n = 286), and propensity score-matched patients also showed no significant association between steroids and LOS. Early steroid treatment was not associated with ICU LOS, fever defervescence by day 3, or normalization of inflammatory mediators. Conclusions and Relevance: Steroid treatment within 2 days of hospital admission in a heterogeneous cohort of pediatric patients hospitalized for COVID-19 without MIS-C did not have a statistically significant association with hospital LOS.

Pre-hospital Aspirin Use and Patient Outcomes in COVID-19: Results from the International Viral Infection and Respiratory Illness Universal Study (VIRUS).

INTRODUCTION: The goal of this investigation is to assess the association between prehospital use of aspirin (ASA) and patient-centered outcomes in a large global cohort of hospitalized COVID-19 patients. METHODS: This study utilizes data from the Society of Critical Care Medicine Discovery Viral Infection and Respiratory Illness Universal Study (VIRUS) Registry. Adult patients hospitalized from February 15th, 2020, to September 30th, 2021, were included. Multivariable regression analyses were utilized to assess the association between pre-hospital use of ASA and the primary outcome of overall hospital mortality. RESULTS: 21,579 patients were included from 185 hospitals (predominantly US-based, 71.3%), with 4691 (21.7%) receiving pre-hospital ASA. Patients receiving ASA, compared to those without pre-admission ASA use, were generally older (median 70 vs. 59 years), more likely to be male (58.7 vs. 56.0%), caucasian (57.4 vs. 51.6%), and more commonly had higher rates of medical comorbidities. In multivariable analyses, patients receiving pre-hospital ASA had lower mortality (HR: 0.89, 95% CI 0.82-0.97, p=0.01) and reduced hazard for progression to severe disease or death (HR: 0.91, 95% CI 0.84-0.99, p=0.02) and more hospital free days (1.00 days, 95% CI 0.66-1.35, p=0.01) compared to those without pre-hospital ASA use. The overall direction and significance of the results remained the same in sensitivity analysis, after adjusting the multivariable model for time since pandemic. CONCLUSIONS: In this large international cohort, pre-hospital use of ASA was associated with a lower hazard for death in hospitalized patients with COVID-19. Randomized controlled trials may be warranted to assess the utility of pre-hospital use of ASA.