Perceived Hospital Stress, Severe Acute Respiratory Syndrome Coronavirus 2 Activity, and Care Process Temporal Variance During the COVID-19 Pandemic.

OBJECTIVES: The COVID-19 pandemic threatened standard hospital operations. We sought to understand how this stress was perceived and manifested within individual hospitals and in relation to local viral activity. DESIGN: Prospective weekly hospital stress survey, November 2020-June 2022. SETTING: Society of Critical Care Medicine's Discovery Severe Acute Respiratory Infection-Preparedness multicenter cohort study. SUBJECTS: Thirteen hospitals across seven U.S. health systems. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: We analyzed 839 hospital-weeks of data over 85 pandemic weeks and five viral surges. Perceived overall hospital, ICU, and emergency department (ED) stress due to severe acute respiratory infection patients during the pandemic were reported by a mean of 43% ( sd , 36%), 32% (30%), and 14% (22%) of hospitals per week, respectively, and perceived care deviations in a mean of 36% (33%). Overall hospital stress was highly correlated with ICU stress (ρ = 0.82; p < 0.0001) but only moderately correlated with ED stress (ρ = 0.52; p < 0.0001). A county increase in 10 severe acute respiratory syndrome coronavirus 2 cases per 100,000 residents was associated with an increase in the odds of overall hospital, ICU, and ED stress by 9% (95% CI, 5-12%), 7% (3-10%), and 4% (2-6%), respectively. During the Delta variant surge, overall hospital stress persisted for a median of 11.5 weeks (interquartile range, 9-14 wk) after local case peak. ICU stress had a similar pattern of resolution (median 11 wk [6-14 wk] after local case peak; p = 0.59) while the resolution of ED stress (median 6 wk [5-6 wk] after local case peak; p = 0.003) was earlier. There was a similar but attenuated pattern during the Omicron BA.1 subvariant surge. CONCLUSIONS: During the COVID-19 pandemic, perceived care deviations were common and potentially avoidable patient harm was rare. Perceived hospital stress persisted for weeks after surges peaked.

Centers for Disease Control (CDC) Wound Classification is Prognostic of 30-Day Readmission Following Surgery.

BACKGROUND: The goal of this study was to investigate factors associated with 30-day readmission in a multivariate model, including the CDC wound classes "clean," "clean/contaminated," "contaminated," and "dirty/infected." METHODS: The 2017-2020 American College of Surgeons-National Surgical Quality Improvement Program (ACS-NSQIP) database was queried for all patients undergoing total hip replacement, coronary artery bypass grafting, Ivor Lewis esophagectomy, pancreaticoduodenectomy, distal pancreatectomy, pneumonectomy, and colectomies. ACS-defined wound classes were concordant with CDC definitions. Multivariate linear mixed regression was used to determine risk factors for readmission while adjusting for type of surgery as a random intercept. RESULTS: 477,964 cases were identified, with 38,734 (8.1%) patients having experienced readmission within 30 days of surgery. There were 181,243 (37.9%) cases classified as wound class "clean", 215,729 (45.1%) cases classified as "clean/contaminated", 40,684 cases (8.5%) classified as "contaminated", and 40,308 (8.4%) cases classified as "dirty/infected". In the multivariate generalized mixed linear model adjusting for type of surgery, sex, body mass index, race, American Society of Anesthesiologists class, presence of comorbidity, length of stay, urgency of surgery, and discharge destination, "clean/contaminated" (p < .001), "contaminated" (p < .001), and "dirty/infected" (p < .001) wound classes (when compared to "clean") were significantly associated with 30-day readmission. Organ/space surgical site infection and sepsis were among the most common reasons for readmission in all wound classes. CONCLUSIONS: Wound classification was strongly prognostic for readmission in multivariable models, suggesting that it may serve as a marker of readmissions. Surgical procedures that are "non-clean" are at significantly greater risk for 30-day readmission. Readmissions may be due to infectious complications; optimizing antibiotic use or source control to prevent readmission are areas of future study.

Use of an extended KDIGO definition to diagnose acute kidney injury in patients with COVID-19: A multinational study using the ISARIC-WHO clinical characterisation protocol.

BACKGROUND: Acute kidney injury (AKI) is one of the most common and significant problems in patients with Coronavirus Disease 2019 (COVID-19). However, little is known about the incidence and impact of AKI occurring in the community or early in the hospital admission. The traditional Kidney Disease Improving Global Outcomes (KDIGO) definition can fail to identify patients for whom hospitalisation coincides with recovery of AKI as manifested by a decrease in serum creatinine (sCr). We hypothesised that an extended KDIGO (eKDIGO) definition, adapted from the International Society of Nephrology (ISN) 0by25 studies, would identify more cases of AKI in patients with COVID-19 and that these may correspond to community-acquired AKI (CA-AKI) with similarly poor outcomes as previously reported in this population. METHODS AND FINDINGS: All individuals recruited using the International Severe Acute Respiratory and Emerging Infection Consortium (ISARIC)-World Health Organization (WHO) Clinical Characterisation Protocol (CCP) and admitted to 1,609 hospitals in 54 countries with Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) infection from February 15, 2020 to February 1, 2021 were included in the study. Data were collected and analysed for the duration of a patient's admission. Incidence, staging, and timing of AKI were evaluated using a traditional and eKDIGO definition, which incorporated a commensurate decrease in sCr. Patients within eKDIGO diagnosed with AKI by a decrease in sCr were labelled as deKDIGO. Clinical characteristics and outcomes-intensive care unit (ICU) admission, invasive mechanical ventilation, and in-hospital death-were compared for all 3 groups of patients. The relationship between eKDIGO AKI and in-hospital death was assessed using survival curves and logistic regression, adjusting for disease severity and AKI susceptibility. A total of 75,670 patients were included in the final analysis cohort. Median length of admission was 12 days (interquartile range [IQR] 7, 20). There were twice as many patients with AKI identified by eKDIGO than KDIGO (31.7% versus 16.8%). Those in the eKDIGO group had a greater proportion of stage 1 AKI (58% versus 36% in KDIGO patients). Peak AKI occurred early in the admission more frequently among eKDIGO than KDIGO patients. Compared to those without AKI, patients in the eKDIGO group had worse renal function on admission, more in-hospital complications, higher rates of ICU admission (54% versus 23%) invasive ventilation (45% versus 15%), and increased mortality (38% versus 19%). Patients in the eKDIGO group had a higher risk of in-hospital death than those without AKI (adjusted odds ratio: 1.78, 95% confidence interval: 1.71 to 1.80, p-value < 0.001). Mortality and rate of ICU admission were lower among deKDIGO than KDIGO patients (25% versus 50% death and 35% versus 70% ICU admission) but significantly higher when compared to patients with no AKI (25% versus 19% death and 35% versus 23% ICU admission) (all p-values <5 × 10-5). Limitations include ad hoc sCr sampling, exclusion of patients with less than two sCr measurements, and limited availability of sCr measurements prior to initiation of acute dialysis. CONCLUSIONS: An extended KDIGO definition of AKI resulted in a significantly higher detection rate in this population. These additional cases of AKI occurred early in the hospital admission and were associated with worse outcomes compared to patients without AKI.

Clinical Data Extraction During Public Health Emergencies: A Blockchain Technology Assessment.

OBJECTIVE: We sought to explore the technical and legal readiness of healthcare institutions for novel data-sharing methods that allow clinical information to be extracted from electronic health records (EHRs) and submitted securely to the Food and Drug Administration's (FDA's) blockchain through a secure data broker (SDB). MATERIALS AND METHODS: This assessment was divided into four sections: an institutional EHR readiness assessment, legal consultation, institutional review board application submission, and a test of healthcare data transmission over a blockchain infrastructure. RESULTS: All participating institutions reported the ability to electronically extract data from EHRs for research. Formal legal agreements were deemed unnecessary to the project but would be needed in future tests of real patient data exchange. Data transmission to the FDA blockchain met the success criteria of data connection from within the four institutions' firewalls, externally to the FDA blockchain via a SDB. DISCUSSION: The readiness survey indicated advanced analytic capability in hospital institutions and highlighted inconsistency in Fast Healthcare Interoperability Resources format utilitzation across institutions, despite requirements of the 21st Century Cures Act. Further testing across more institutions and annual exercises leveraging the application of data exchange over a blockchain infrastructure are recommended actions for determining the feasibility of this approach during a public health emergency and broaden the understanding of technical requirements for multisite data extraction. CONCLUSION: The FDA's RAPID (Real-Time Application for Portable Interactive Devices) program, in collaboration with Discovery, the Critical Care Research Network's PREP (Program for Resilience and Emergency Preparedness), identified the technical and legal challenges and requirements for rapid data exchange to a government entity using the FDA blockchain infrastructure.

Genomic responses in mouse models poorly mimic human inflammatory diseases.

A cornerstone of modern biomedical research is the use of mouse models to explore basic pathophysiological mechanisms, evaluate new therapeutic approaches, and make go or no-go decisions to carry new drug candidates forward into clinical trials. Systematic studies evaluating how well murine models mimic human inflammatory diseases are nonexistent. Here, we show that, although acute inflammatory stresses from different etiologies result in highly similar genomic responses in humans, the responses in corresponding mouse models correlate poorly with the human conditions and also, one another. Among genes changed significantly in humans, the murine orthologs are close to random in matching their human counterparts (e.g., R(2) between 0.0 and 0.1). In addition to improvements in the current animal model systems, our study supports higher priority for translational medical research to focus on the more complex human conditions rather than relying on mouse models to study human inflammatory diseases.

Development of a Core Clinical Dataset to Characterize Serious Illness, Injuries, and Resource Requirements for Acute Medical Responses to Public Health Emergencies.

OBJECTIVES: In developed countries, public health systems have become adept at rapidly identifying the etiology and impact of public health emergencies. However, within the time course of clinical responses, shortfalls in readily analyzable patient-level data limit capabilities to understand clinical course, predict outcomes, ensure resource availability, and evaluate the effectiveness of diagnostic and therapeutic strategies for seriously ill and injured patients. To be useful in the timeline of a public health emergency, multi-institutional clinical investigation systems must be in place to rapidly collect, analyze, and disseminate detailed clinical information regarding patients across prehospital, emergency department, and acute care hospital settings, including ICUs. As an initial step to near real-time clinical learning during public health emergencies, we sought to develop an "all-hazards" core dataset to characterize serious illness and injuries and the resource requirements for acute medical response across the care continuum. SUBJECTS: A multidisciplinary panel of clinicians, public health professionals, and researchers with expertise in public health emergencies. DESIGN: Group consensus process. INTERVENTIONS: The consensus process included regularly scheduled conference calls, electronic communications, and an in-person meeting to generate candidate variables. Candidate variables were then reviewed by the group to meet the competing criteria of utility and feasibility resulting in the core dataset. MEASUREMENTS AND MAIN RESULTS: The 40-member panel generated 215 candidate variables for potential dataset inclusion. The final dataset includes 140 patient-level variables in the domains of demographics and anthropometrics (7), prehospital (11), emergency department (13), diagnosis (8), severity of illness (54), medications and interventions (38), and outcomes (9). CONCLUSIONS: The resulting all-hazard core dataset for seriously ill and injured persons provides a foundation to facilitate rapid collection, analyses, and dissemination of information necessary for clinicians, public health officials, and policymakers to optimize public health emergency response. Further work is needed to validate the effectiveness of the dataset in a variety of emergency settings.

Smooth muscle cells from abdominal aortic aneurysms are unique and can independently and synergistically degrade insoluble elastin.

BACKGROUND: The purpose of this study was to further elucidate the role of the vascular smooth muscle cells (SMCs) in abdominal aortic aneurysm (AAA) disease. We hypothesized that that AAA SMCs are unique and actively participate in the process of degrading the aortic matrix. METHODS: Whole-genome expression profiles of SMCs from AAAs, nondilated abdominal aorta (NAA), and carotid endarterectomy (CEA) were compared. We quantified elastolytic activity by culturing SMCs in [(3)H]elastin-coated plates and measuring solubilized tritium in the media after 7 days. Matrix metalloproteinase (MMP)-2 and MMP-9 production was assessed using real-time polymerase chain reaction, zymography, and Western blotting. RESULTS: Each SMC type exhibited a unique gene expression pattern. AAA SMCs had greater elastolytic activity than NAA-SMCs (+68%; P < .001) and CEA-SMCs (+45%; P < .001). Zymography showed an increase of active MMP-2 (62 kD) in media from AAA SMCs. AAA SMCs demonstrated twofold greater expression of MMP-2 messenger (m)RNA (P < .05) and 7.3-fold greater MMP-9 expression (P < .01) than NAA-SMCs. Culture with U937 monocytes caused a synergistic increase of elastolysis by AAA SMCs (41%; P < .001) but not NAA-SMCs or CEA-SMCs (P = .99). Coculture with U937 caused a large increase in MMP-9 mRNA in AAA-SMCs and NAA-SMCs (P < .001). MMP-2 mRNA expression was not affected. Western blots of culture media showed a fourfold increase of MMP-9 (92 kD) protein only in AAA-SMCs/U937 but not in NAA-SMCs/U937 (P < .001) and a large increase in active-MMP2 (62 kD), which was less apparent in NAA-SMCs/U937 media (P < .01). CONCLUSIONS: AAA-SMCs have a unique gene expression profile and a proelastolytic phenotype that is augmented by macrophages. This may occur by a failure of post-transcriptional control of MMP-9 synthesis.

COVID-19 Across Pandemic Variant Periods: The Severe Acute Respiratory Infection-Preparedness (SARI-PREP) Study.

IMPORTANCE: The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic has evolved through multiple phases in the United States, with significant differences in patient centered outcomes with improvements in hospital strain, medical countermeasures, and overall understanding of the disease. We describe how patient characteristics changed and care progressed over the various pandemic phases; we also emphasize the need for an ongoing clinical network to improve the understanding of known and novel respiratory viral diseases. OBJECTIVES: To describe how patient characteristics and care evolved across the various COVID-19 pandemic periods in those hospitalized with viral severe acute respiratory infection (SARI). DESIGN: Severe Acute Respiratory Infection-Preparedness (SARI-PREP) is a Centers for Disease Control and Prevention Foundation-funded, Society of Critical Care Medicine Discovery-housed, longitudinal multicenter cohort study of viral pneumonia. We defined SARI patients as those hospitalized with laboratory-confirmed respiratory viral infection and an acute syndrome of fever, cough, and radiographic infiltrates or hypoxemia. We collected patient-level data including demographic characteristics, comorbidities, acute physiologic measures, serum and respiratory specimens, therapeutics, and outcomes. Outcomes were described across four pandemic variant periods based on a SARS-CoV-2 sequenced subsample: pre-Delta, Delta, Omicron BA.1, and Omicron post-BA.1. SETTING: Multicenter cohort of adult patients admitted to an acute care ward or ICU from seven hospitals representing diverse geographic regions across the United States. PARTICIPANTS: Patients with SARI caused by infection with respiratory viruses. MAIN OUTCOMES AND RESULTS: Eight hundred seventy-four adult patients with SARI were enrolled at seven study hospitals between March 2020 and April 2023. Most patients (780, 89%) had SARS-CoV-2 infection. Across the COVID-19 cohort, median age was 60 years (interquartile range, 48.0-71.0 yr) and 66% were male. Almost half (430, 49%) of the study population belonged to underserved communities. Most patients (76.5%) were admitted to the ICU, 52.5% received mechanical ventilation, and observed hospital mortality was 25.5%. As the pandemic progressed, we observed decreases in ICU utilization (94% to 58%), hospital length of stay (median, 26.0 to 8.5 d), and hospital mortality (32% to 12%), while the number of comorbid conditions increased. CONCLUSIONS AND RELEVANCE: We describe increasing comorbidities but improved outcomes across pandemic variant periods, in the setting of multiple factors, including evolving care delivery, countermeasures, and viral variants. An understanding of patient-level factors may inform treatment options for subsequent variants and future novel pathogens.

Analysis of factorial time-course microarrays with application to a clinical study of burn injury.

Time-course microarray experiments are capable of capturing dynamic gene expression profiles. It is important to study how these dynamic profiles depend on the multiple factors that characterize the experimental condition under which the time course is observed. Analytic methods are needed to simultaneously handle the time course and factorial structure in the data. We developed a method to evaluate factor effects by pooling information across the time course while accounting for multiple testing and nonnormality of the microarray data. The method effectively extracts gene-specific response features and models their dependency on the experimental factors. Both longitudinal and cross-sectional time-course data can be handled by our approach. The method was used to analyze the impact of age on the temporal gene response to burn injury in a large-scale clinical study. Our analysis reveals that 21% of the genes responsive to burn are age-specific, among which expressions of mitochondria and immunoglobulin genes are differentially perturbed in pediatric and adult patients by burn injury. These new findings in the body's response to burn injury between children and adults support further investigations of therapeutic options targeting specific age groups. The methodology proposed here has been implemented in R package "TANOVA" and submitted to the Comprehensive R Archive Network at http://www.r-project.org/. It is also available for download at http://gluegrant1.stanford.edu/TANOVA/.

The impact of rounds with a psychiatry team in the intensive care unit: A prospective observational pilot study evaluating the effects on delirium incidence and outcomes.

BACKGROUND: Delirium in the intensive care unit (ICU) is a common but serious condition that has been associated with in-hospital mortality and post-discharge psychological dysfunction. The aim of this before and after study is to determine the effect of a multidisciplinary care model entailing daily ICU rounds with a psychiatrist on the incidence of delirium and clinical outcomes. OBJECTIVE: To assess the impact of a proactive psychiatry consultation model in the surgical ICU on the incidence and duration of delirium. METHODS: This was a prospective, single institution, observational controlled cohort pilot study of adult patients admitted to a surgical ICU. A control group that received standard of care (SOC) with daily delirium prevention care bundles in the pre-intervention period was compared to an intervention group, which had a psychiatrist participate in daily ICU rounds (post-intervention period). The primary outcome was delirium incidence. The secondary outcomes were: delirium duration, ventilator days, hospital and ICU length of stay, and in-hospital mortality. RESULTS: A total of 104 patients were enrolled and equally split between SOC and intervention groups; 95 contributed to analysis. The overall incidence of ICU delirium was 19%. SOC and intervention groups had similar rates of delirium (21% vs 18%, p = 0.72). None of the secondary outcomes statistically significantly differed between the two groups. CONCLUSION: Delirium in ICU patients is a potentially preventable condition with serious sequelae. There was no difference in delirium incidence or duration between patients receiving SOC or patients who had multidisciplinary rounds with a psychiatrist.

Angiopoietin-Like4 Is a Novel Marker of COVID-19 Severity.

Vascular dysfunction and capillary leak are common in critically ill COVID-19 patients, but identification of endothelial pathways involved in COVID-19 pathogenesis has been limited. Angiopoietin-like 4 (ANGPTL4) is a protein secreted in response to hypoxic and nutrient-poor conditions that has a variety of biological effects including vascular injury and capillary leak. OBJECTIVES: To assess the role of ANGPTL4 in COVID-19-related outcomes. DESIGN SETTING AND PARTICIPANTS: Two hundred twenty-five COVID-19 ICU patients were enrolled from April 2020 to May 2021 in a prospective, multicenter cohort study from three different medical centers, University of Washington, University of Southern California and New York University. MAIN OUTCOMES AND MEASURES: Plasma ANGPTL4 was measured on days 1, 7, and 14 after ICU admission. We used previously published tissue proteomic data and lung single nucleus RNA (snRNA) sequencing data from specimens collected from COVID-19 patients to determine the tissues and cells that produce ANGPTL4. RESULTS: Higher plasma ANGPTL4 concentrations were significantly associated with worse hospital mortality (adjusted odds ratio per log2 increase, 1.53; 95% CI, 1.17-2.00; p = 0.002). Higher ANGPTL4 concentrations were also associated with higher proportions of venous thromboembolism and acute respiratory distress syndrome. Longitudinal ANGPTL4 concentrations were significantly different during the first 2 weeks of hospitalization in patients who subsequently died compared with survivors (p for interaction = 8.1 × 10-5). Proteomics analysis demonstrated abundance of ANGPTL4 in lung tissue compared with other organs in COVID-19. ANGPTL4 single-nuclear RNA gene expression was significantly increased in pulmonary alveolar type 2 epithelial cells and fibroblasts in COVID-19 lung tissue compared with controls. CONCLUSIONS AND RELEVANCE: ANGPTL4 is expressed in pulmonary epithelial cells and fibroblasts and is associated with clinical prognosis in critically ill COVID-19 patients.

Benchmarking outcomes in the critically injured trauma patient and the effect of implementing standard operating procedures.

OBJECTIVE: To determine and compare outcomes with accepted benchmarks in trauma care at 7 academic level I trauma centers in which patients were treated on the basis of a series of standard operating procedures (SOPs). BACKGROUND: Injury remains the leading cause of death for those younger than 45 years. This study describes the baseline patient characteristics and well-defined outcomes of persons hospitalized in the United States for severe blunt trauma. METHODS: We followed 1637 trauma patients from 2003 to 2009 up to 28 hospital days using SOPs developed at the onset of the study. An extensive database on patient and injury characteristics, clinical treatment, and outcomes was created. These data were compared with existing trauma benchmarks. RESULTS: The study patients were critically injured and were in shock. SOP compliance improved 10% to 40% during the study period. Multiple organ failure and mortality rates were 34.8% and 16.7%, respectively. Time to recovery, defined as the time until the patient was free of organ failure for at least 2 consecutive days, was developed as a new outcome measure. There was a reduction in mortality rate in the cohort during the study that cannot be explained by changes in the patient population. CONCLUSIONS: This study provides the current benchmark and the overall positive effect of implementing SOPs for severely injured patients. Over the course of the study, there were improvements in morbidity and mortality rates and increasing compliance with SOPs. Mortality was surprisingly low, given the degree of injury, and improved over the duration of the study, which correlated with improved SOP compliance.

The surgical intensive care unit optimal mobility score predicts mortality and length of stay.

OBJECTIVES: To test if the surgical intensive care unit optimal mobility score predicts mortality and intensive care unit and hospital length of stay. DESIGN: Prospective single-center cohort study. SETTING: Surgical intensive care unit of the Massachusetts General Hospital. PATIENTS: One hundred thirteen consecutive patients admitted to the surgical intensive care unit. INVESTIGATIONS: We tested the hypotheses that the surgical intensive care unit optimal mobility score independent of comorbidity index, Acute Physiology and Chronic Health Evaluation II, creatinine, hypotension, hypernatremia, acidosis, hypoxia, and hypercarbia predicts hospital mortality, surgical intensive care unit and total hospital length of stay. MEASUREMENTS AND MAIN RESULTS: Two nurses independently predicted the patients' mobilization capacity by using the surgical intensive care unit optimal mobility score the morning after admission, whereas a third nurse recorded the achieved mobilization levels of patients at the end of the day. A multidisciplinary expert team measured patients' grip strength and assessed their predicted mobilization capacity independently. Multivariate analysis revealed that the surgical intensive care unit optimal mobility score was the only independent predictor of mortality. Surgical intensive care unit optimal mobility score, hypotension, and hypernatremia (>144 mmol/L) independently predicted intensive care unit length of stay, whereas the surgical intensive care unit optimal mobility score and hypernatremia predicted total hospital length of stay. The Acute Physiology and Chronic Health Evaluation II score was not identified in the multivariate analysis. The surgical intensive care unit optimal mobility score was also a reliable and valid instrument in predicting achieved mobilization levels of patients. CONCLUSIONS: In surgical critically ill patients presenting without preexisting impairment of functional mobility, the surgical intensive care unit optimal mobility score is a reliable and valid tool to predict mortality and intensive care unit and hospital length of stay.

Preliminary evidence for leukocyte transcriptional signatures for pediatric ventilator-associated pneumonia.

OBJECTIVE: Ventilator-associated pneumonia (VAP) is a significant contributor to intensive care unit (ICU) morbidity and mortality and presents a significant diagnostic challenge. Our hypothesis was that blood RNA expression profiles can be used to track the response to VAP in children, using the same methods that proved informational in adults. DESIGN: A pilot, nonrandomized, repeated measures case-control study of changes in the abundance of total RNA in buffy coat and clinical scores for VAP. SETTING: A large, multispecialty university-based pediatric ICU and cardiac ICU. PATIENTS: Seven children requiring intubation and mechanical ventilation. INTERVENTIONS: Blood samples were drawn at time of enrollment and every 48 hours for a maximum of 11 samples (21 days). Patients ranged in age from 1 to 18 months (mean 8 months). All patients survived to the end of the study. Of the 7 patients studied, 4 developed VAP. MEASUREMENTS AND MAIN RESULTS: Statistical analysis of the Affymetrix Human Genome Focus GeneChip signal was conducted on normalized expression values of 8793 probe sets using analysis of variance (ANOVA) with a false discovery rate of 0.10. The expression patterns of 48 genes appeared to discriminate between the 2 classes of ventilated children: those with and those without pneumonia. Gene expression network analysis revealed several gene ontologies of interest, including cell proliferation, differentiation, growth, and apoptosis, as well as genes not previously implicated in sepsis. CONCLUSIONS: These preliminary data are the first in critically ill children supporting the hypothesis that there is a detectable VAP signal in gene expression profiles. Larger studies are needed to validate these preliminary findings and test the diagnostic value of longitudinal changes in leukocyte RNA signatures.

An Electronic Data Capture Tool for Data Collection During Public Health Emergencies: Development and Usability Study.

BACKGROUND: The Discovery Critical Care Research Network Program for Resilience and Emergency Preparedness (Discovery PREP) partnered with a third-party technology vendor to design and implement an electronic data capture tool that addressed multisite data collection challenges during public health emergencies (PHE) in the United States. The basis of the work was to design an electronic data capture tool and to prospectively gather data on usability from bedside clinicians during national health system stress queries and influenza observational studies. OBJECTIVE: The aim of this paper is to describe the lessons learned in the design and implementation of a novel electronic data capture tool with the goal of significantly increasing the nation's capability to manage real-time data collection and analysis during PHE. METHODS: A multiyear and multiphase design approach was taken to create an electronic data capture tool, which was used to pilot rapid data capture during a simulated PHE. Following the pilot, the study team retrospectively assessed the feasibility of automating the data captured by the electronic data capture tool directly from the electronic health record. In addition to user feedback during semistructured interviews, the System Usability Scale (SUS) questionnaire was used as a basis to evaluate the usability and performance of the electronic data capture tool. RESULTS: Participants included Discovery PREP physicians, their local administrators, and data collectors from tertiary-level academic medical centers at 5 different institutions. User feedback indicated that the designed system had an intuitive user interface and could be used to automate study communication tasks making for more efficient management of multisite studies. SUS questionnaire results classified the system as highly usable (SUS score 82.5/100). Automation of 17 (61%) of the 28 variables in the influenza observational study was deemed feasible during the exploration of automated versus manual data abstraction. The creation and use of the Project Meridian electronic data capture tool identified 6 key design requirements for multisite data collection, including the need for the following: (1) scalability irrespective of the type of participant; (2) a common data set across sites; (3) automated back end administrative capability (eg, reminders and a self-service status board); (4) multimedia communication pathways (eg, email and SMS text messaging); (5) interoperability and integration with local site information technology infrastructure; and (6) natural language processing to extract nondiscrete data elements. CONCLUSIONS: The use of the electronic data capture tool in multiple multisite Discovery PREP clinical studies proved the feasibility of using the novel, cloud-based platform in practice. The lessons learned from this effort can be used to inform the improvement of ongoing global multisite data collection efforts during the COVID-19 pandemic and transform current manual data abstraction approaches into reliable, real time, and automated information exchange. Future research is needed to expand the ability to perform automated multisite data extraction during a PHE and beyond.

Critical Care Response During the COVID-19 Pandemic.

Hospitals and health care systems with active critical care organizations (CCOs) that unified ICU units before the onset of the COVID-19 Pandemic were better positioned to adapt to the demands of the pandemic, due to their established standardization of care and integration of critical care within the larger structure of the hospital or health care system. CCOs should continue to make changes, based on the real experience of COVID-19 that would lead to improved care during the ongoing pandemic, and beyond.