A multisite exploration of the association between critical care implementation factors and clinical outcomes during the COVID-19 pandemic.

Background: Little is known about strategies to implement new critical care practices in response to COVID-19. Moreover, the association between differing implementation climates and COVID-19 clinical outcomes has not been examined. The purpose of this study was to evaluate the relationship between implementation determinants and COVID-19 mortality rates. Methods: We used mixed methods guided by the Consolidated Framework for Implementation Research (CFIR). Semi-structured qualitative interviews were conducted with critical care leaders and analyzed to rate the influence of CFIR constructs on the implementation of new care practices. Qualitative and quantitative comparisons of CFIR construct ratings were performed between hospital groups with low- versus high-mortality rates. Results: We found associations between various implementation factors and clinical outcomes of critically ill COVID-19 patients. Three CFIR constructs (implementation climate, leadership engagement, and engaging staff) had both qualitative and statistically significant quantitative correlations with mortality outcomes. An implementation climate governed by a trial-and-error approach was correlated with high COVID-19 mortality, while leadership engagement and engaging staff were correlated with low mortality. Another three constructs (needs of patient; organizational incentives and rewards; and engaging implementation leaders) were qualitatively different across mortality outcome groups, but these differences were not statistically significant. Conclusions: Improving clinical outcomes during future public health emergencies will require reducing identified barriers associated with high mortality and harnessing salient facilitators associated with low mortality. Our findings suggest that collaborative and engaged leadership styles that promote the integration of new yet evidence-based critical care practices best support COVID-19 patients and contribute to lower mortality.

Facilitators and barriers to the implementation of new critical care practices during COVID-19: a multicenter qualitative study using the Consolidated Framework for Implementation Research (CFIR).

BACKGROUND: The COVID-19 pandemic produced unprecedented demands and rapidly changing evidence and practices within critical care settings. The purpose of this study was to identify factors and strategies that hindered and facilitated effective implementation of new critical care practices and policies in response to the pandemic. METHODS: We used a cross-sectional, qualitative study design to conduct semi-structured in-depth interviews with critical care leaders across the United States. The interviews were audio-taped and professionally transcribed verbatim. Guided by the Consolidated Framework for Implementation Research (CFIR), three qualitative researchers used rapid analysis methods to develop relevant codes and identify salient themes. RESULTS: Among the 17 hospitals that agreed to participate in this study, 31 clinical leaders were interviewed. The CFIR-driven rapid analysis of the interview transcripts generated 12 major themes, which included six implementation facilitators (i.e., factors that promoted the implementation of new critical care practices) and six implementation barriers (i.e., factors that hindered the implementation of new critical care practices). These themes spanned the five CFIR domains (Intervention Characteristics, Outer Setting, Inner Setting, Characteristics of Individuals, and Process) and 11 distinct CFIR constructs. Salient facilitators to implementation efforts included staff resilience, commitment, and innovation, which were supported through collaborative feedback and decision-making mechanisms between leadership and frontline staff. Major identified barriers included lack of access to reliable and transferable information, available resources, uncollaborative leadership and communication styles. CONCLUSIONS: Through applying the CFIR to organize and synthesize our qualitative data, this study revealed important insights into implementation determinants that influenced the uptake of new critical care practices during COVID-19. As the pandemic continues to burden critical care units, clinical leaders should consider emulating the effective change management strategies identified. The cultivation of streamlined, engaging, and collaborative leadership and communication mechanisms not only supported implementation of new care practices across sites, but it also helped reduce salient implementation barriers, particularly resource and staffing shortages. Future critical care implementation studies should seek to capitalize on identified facilitators and reduce barriers.

Evaluating the ability of the NLHA2 and artificial neural network models to predict COVID-19 severity, and comparing them with the four existing scoring systems.

To improve the identification and subsequent intervention of COVID-19 patients at risk for ICU admission, we constructed COVID-19 severity prediction models using logistic regression and artificial neural network (ANN) analysis and compared them with the four existing scoring systems (PSI, CURB-65, SMARTCOP, and MuLBSTA). In this prospective multi-center study, 296 patients with COVID-19 pneumonia were enrolled and split into the General-Ward-Care group (N = 238) and the ICU-Admission group (N = 58). The PSI model (AUC = 0.861) had the best results among the existing four scoring systems, followed by SMARTCOP (AUC = 0.770), motified-MuLBSTA (AUC = 0.761), and CURB-65 (AUC = 0.712). Data from 197 patients (training set) were analyzed for modeling. The beta coefficients from logistic regression were used to develop a severity prediction model and risk score calculator. The final model (NLHA2) included five covariates (consumes alcohol, neutrophil count, lymphocyte count, hemoglobin, and AKP). The NLHA2 model (training: AUC = 0.959; testing: AUC = 0.857) had similar results to the PSI model, but with fewer variable items. ANN analysis was used to build another complex model, which had higher accuracy (training: AUC = 1.000; testing: AUC = 0.907). Discrimination and calibration were further verified through bootstrapping (2000 replicates), Hosmer-Lemeshow goodness of fit testing, and Brier score calculation. In conclusion, the PSI model is the best existing system for predicting ICU admission among COVID-19 patients, while two newly-designed models (NLHA2 and ANN) performed better than PSI, and will provide a new approach for the development of prognostic evaluation system in a novel respiratory viral epidemic.

Physical Fitness of Chinese Primary School Students across the Coronavirus (COVID-19) Outbreak: A Retrospective Repeated Cross-Sectional Study.

Social distancing measures against COVID-19 imposed restrictions on students that may have affected their physical health and fitness. The objective of this study was to investigate the change in physical fitness of primary school students across the coronavirus outbreaks from 2019 to 2021. This was a retrospective repeated cross-sectional study. We obtained the annual physical and fitness assessment data measured every November for all students at the same primary school in Guangzhou, China. There was a total of 6371 observations in the dataset for three years. The physical fitness of the students was evaluated with an overall physical fitness score, body mass index (BMI), lung vital capacity, physical flexibility (via a sit-and-reach test) and sports task performances (sprint, shuttle run, rope-jumping, and sit-up). Generalised estimating equations were used to determine any significant changes from 2019 to 2021, adjusted for confounders. After the COVID-19 outbreak in 2021, there was a significant elevation in BMI of 0.64 kg/m2 in 2020 and 0.39 kg/m2 in 2021 (p < 0.001). The overall physical fitness score was significantly increased by 2.1 and 4.1 points, respectively, in 2020 and 2021 (p < 0.001). Lung vital capacity and rope-jumping performance were significantly improved in both 2020 and 2021 compared with 2019, and sit-up performance was marginally significantly improved in 2020 and significantly improved in 2021. However, students demonstrated poorer flexibility and sprint and shuttle run performance in 2021 compared with 2019. A health promotion programme during and after COVID-19, including online physical education classes, television broadcasts, and a rope-jumping campaign, could account for these positive outcomes, along with the ease of administering rope-jumping and sit-ups at home.

A systematic review and meta-analysis of racial disparities in deep vein thrombosis and pulmonary embolism events in patients hospitalized with coronavirus disease 2019.

OBJECTIVE: Coronavirus disease 2019 (COVID-19) is associated with an increased risk of venous thromboembolism (VTE). Recent studies have characterized racial disparities in the incidence of VTE. The aim of our study was to present a systematic review and meta-analysis to assess the association between race and VTE in patients hospitalized with COVID-19. METHODS: We performed a systematic literature review to evaluate the number of deep vein thrombosis (DVT) and pulmonary embolism (PE) events reported by racial groups in patients hospitalized with COVID-19. For the qualitative analysis, independent reviewers extracted the data from eligible studies, and we used the Newcastle-Ottawa scale to assess the quality of design and content for accurate interpretation. For the quantitative analysis, we pooled the odds ratios with Der Simonian and Laird random effects models. RESULTS: The qualitative analysis included 11 studies, with 6 included in the meta-analysis. All studies were observational, retrospective cohort studies, except for one retrospective case-control study. Six studies were eligible for the meta-analysis owing to the high interstudy heterogeneity; thus, the variable reports of racial groups reduced the cohort to Black/African American and White patients (n = 9723) in the analysis. The estimated proportion for DVT and PE events for Black/African American and White patients was 0.07 (95% confidence interval, 0.00-0.10) and 0.04 (95% confidence interval, 0.00-0.07), respectively. The P value of .13 suggested nonsignificant differences in the VTE rates between Black/African American and White patients. CONCLUSIONS: In our study, the proportion of DVT and PE events between Black/African American and White patients with COVID-19 were comparable. Future COVID-19 studies should include systematic racial group reporting to identify any disparities in the setting of VTE events.

International Virtual Simulation Education in Critical Care During COVID-19 Pandemic: Preliminary Description of the Virtual Checklist for Early Recognition and Treatment of Acute Illness and iNjury Program.

SUMMARY STATEMENT: The Checklist for Early Recognition and Treatment of Acute Illness and iNjury program is a well-established, interactive, and simulation-based program designed to improve the quality of care delivered in intensive care units. The COVID-19 pandemic created an overwhelming surge of critically ill patients worldwide, and infection control concerns limited healthcare providers' access to in-person and hands-on simulation training when they needed it the most. Virtual simulation offers an alternative to in-person training but is often complex and expensive. We describe our successful development and initial implementation of an inexpensive, simulation-based virtual Checklist for Early Recognition and Treatment of Acute Illness and iNjury program to address the pressing need for effective critical care training in various resource-limited settings both within and outside of the United States. The overall satisfaction rate ("excellent" or "very good" responses) was 94.4% after the virtual simulation workshop. Our initial experience suggests that virtual interactions can be engaging and build strong relationships, like in-person continuing professional education, even using relatively simple technology. This knowledge-to-practice improvement platform can be readily adapted to other disciplines beyond critical care medicine.

Investigating the cognitive capacity constraints of an ICU care team using a systems engineering approach.

BACKGROUND: ICU operational conditions may contribute to cognitive overload and negatively impact on clinical decision making. We aimed to develop a quantitative model to investigate the association between the operational conditions and the quantity of medication orders as a measurable indicator of the multidisciplinary care team's cognitive capacity. METHODS: The temporal data of patients at one medical ICU (MICU) of Mayo Clinic in Rochester, MN between February 2016 to March 2018 was used. This dataset includes a total of 4822 unique patients admitted to the MICU and a total of 6240 MICU admissions. Guided by the Systems Engineering Initiative for Patient Safety model, quantifiable measures attainable from electronic medical records were identified and a conceptual framework of distributed cognition in ICU was developed. Univariate piecewise Poisson regression models were built to investigate the relationship between system-level workload indicators, including patient census and patient characteristics (severity of illness, new admission, and mortality risk) and the quantity of medication orders, as the output of the care team's decision making. RESULTS: Comparing the coefficients of different line segments obtained from the regression models using a generalized F-test, we identified that, when the ICU was more than 50% occupied (patient census > 18), the number of medication orders per patient per hour was significantly reduced (average = 0.74; standard deviation (SD) = 0.56 vs. average = 0.65; SD = 0.48; p < 0.001). The reduction was more pronounced (average = 0.81; SD = 0.59 vs. average = 0.63; SD = 0.47; p < 0.001), and the breakpoint shifted to a lower patient census (16 patients) when at a higher presence of severely-ill patients requiring invasive mechanical ventilation during their stay, which might be encountered in an ICU treating patients with COVID-19. CONCLUSIONS: Our model suggests that ICU operational factors, such as admission rates and patient severity of illness may impact the critical care team's cognitive function and result in changes in the production of medication orders. The results of this analysis heighten the importance of increasing situational awareness of the care team to detect and react to changing circumstances in the ICU that may contribute to cognitive overload.

STOP-VIRUS COLLABORATIVE: INTERPROFESSIONAL LEARNING COMMUNITY TO IMPROVE COVID-19 PATIENT OUTCOMES

The Structured Team-based Optimal Patient-centered care for COVID-19 VIRUS (STOP-VIRUS) Collaborative was created to identify and implement current best COVID-19 practices using standard quality improvement methodology in a learning community of participating U.S. sites. B Introduction: b Interim SCCM VIRUS Registry analysis demonstrated variation in patient outcomes independent of acuity or comorbidity, suggesting opportunities for critical care process improvement. [Extracted from the article] Copyright of Critical Care Medicine is the property of Lippincott Williams & Wilkins and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full . (Copyright applies to all s.)

Responses of electroactive biofilms to chronic chlorine exposure: Insights from the composition and spatial structure of extracellular polymeric substances.

Extensive amounts of chlorine disinfectants have been applied to wastewater system since the outbreak of coronavirus disease 2019 (COVID-19), which inevitably affects the pollutant degradation via interfering with electron transfer mediated by electroactive bacteria. Herein, the response of electroactive biofilm (EAB) to chronic chlorine exposure was investigated. Results showed the EAB formed without exposure (EAB-0) exhibited a 53% and 123% higher current output than that formed with 0.1 mg L-1 (EAB-0.1) and 0.5 mg L-1 (EAB-0.5) chlorine, respectively. The chronic chlorine exposure of EAB boosted the contents of extracellular polymeric substances (EPS) in EAB-0.1 and EAB-0.5 by over secretion of extracellular polysaccharides. The EAB-0.1 and EAB-0.5 also presented lower electron exchange capacities (EECs) of EPS, coincided with reduced relative abundance of Geobacter from 61% in EAB-0 to 52% in EAB-0.5. This study provided new insights into the application of engineered EAB for wastewater treatment in a disinfection environment.

Public health impact of delaying second dose of BNT162b2 or mRNA-1273 covid-19 vaccine: simulation agent based modeling study.

OBJECTIVE: To estimate population health outcomes with delayed second dose versus standard schedule of SARS-CoV-2 mRNA vaccination. DESIGN: Simulation agent based modeling study. SETTING: Simulated population based on real world US county. PARTICIPANTS: The simulation included 100 000 agents, with a representative distribution of demographics and occupations. Networks of contacts were established to simulate potentially infectious interactions though occupation, household, and random interactions. INTERVENTIONS: Simulation of standard covid-19 vaccination versus delayed second dose vaccination prioritizing the first dose. The simulation runs were replicated 10 times. Sensitivity analyses included first dose vaccine efficacy of 50%, 60%, 70%, 80%, and 90% after day 12 post-vaccination; vaccination rate of 0.1%, 0.3%, and 1% of population per day; assuming the vaccine prevents only symptoms but not asymptomatic spread (that is, non-sterilizing vaccine); and an alternative vaccination strategy that implements delayed second dose for people under 65 years of age, but not until all those above this age have been vaccinated. MAIN OUTCOME MEASURES: Cumulative covid-19 mortality, cumulative SARS-CoV-2 infections, and cumulative hospital admissions due to covid-19 over 180 days. RESULTS: Over all simulation replications, the median cumulative mortality per 100 000 for standard dosing versus delayed second dose was 226 v 179, 233 v 207, and 235 v 236 for 90%, 80%, and 70% first dose efficacy, respectively. The delayed second dose strategy was optimal for vaccine efficacies at or above 80% and vaccination rates at or below 0.3% of the population per day, under both sterilizing and non-sterilizing vaccine assumptions, resulting in absolute cumulative mortality reductions between 26 and 47 per 100 000. The delayed second dose strategy for people under 65 performed consistently well under all vaccination rates tested. CONCLUSIONS: A delayed second dose vaccination strategy, at least for people aged under 65, could result in reduced cumulative mortality under certain conditions.

Clinical Characteristics, Treatment, and Outcomes of Critically Ill Patients With COVID-19: A Scoping Review.

A growing number of studies on coronavirus disease 2019 (COVID-19) are becoming available, but a synthesis of available data focusing on the critically ill population has not been conducted. We performed a scoping review to synthesize clinical characteristics, treatment, and clinical outcomes among critically ill patients with COVID-19. Between January 1, 2020, and May 15, 2020, we identified high-quality clinical studies describing critically ill patients with a sample size of greater than 20 patients by performing daily searches of the World Health Organization and LitCovid databases on COVID-19. Two reviewers independently reviewed all abstracts (2785 unique articles), full text (218 articles), and abstracted data (92 studies). The 92 studies included 61 from Asia, 16 from Europe, 10 from North and South America, and 5 multinational studies. Notable similarities among critically ill populations across all regions included a higher proportion of older males infected and with severe illness, high frequency of comorbidities (hypertension, diabetes, and cardiovascular disease), abnormal chest imaging findings, and death secondary to respiratory failure. Differences in regions included newly identified complications (eg, pulmonary embolism) and epidemiological risk factors (eg, obesity), less chest computed tomography performed, and increased use of invasive mechanical ventilation (70% to 100% vs 15% to 47% of intensive care unit patients) in Europe and the United States compared with Asia. Future research directions should include proof-of-mechanism studies to better understand organ injuries and large-scale collaborative clinical studies to evaluate the efficacy and safety of antivirals, antibiotics, interleukin 6 receptor blockers, and interferon. The current established predictive models require further verification in other regions outside China.

Rapid, multimodal, critical care knowledge-sharing platform for COVID-19 pandemics.

In many areas of the world, critical care providers caring for COVID-19 patients lacked specific knowledge and were exposed to the abundance of new and unfiltered information. With support from the World Health Organization, we created a multimodal tele-education intervention to rapidly share critical care knowledge related to COVID-19 targeting providers in a region of Southeastern Europe. We delivered 60-minute weekly interactive tele-education sessions over YouTubeTM between March 2020 and May 2020, supplemented by a dedicated webpage. The intervention was reinforced using a secure social media platform (ViberTM), providing continuous rapid knowledge exchange among faculty and learners. A high level of engagement was observed, with over 2000 clinicians participating and actively interacting over a 6-week period. Surveyed participants were highly satisfied with the intervention. Tele-education interventions using social media platforms are feasible, low-cost, and effective methods to share knowledge during the COVID-19 pandemic.