Citations

OBJECTIVES: 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.

IMPORTANCE: The scientific community debates Generative Pre-trained Transformer (GPT)-3.5’s article quality, authorship merit, originality, and ethical use in scientific writing. OBJECTIVES: Assess GPT-3.5’s ability to craft the background section of critical care clinical research questions compared to medical researchers with H-indices of 22 and 13. DESIGN: Observational cross-sectional study. SETTING: Researchers from 20 countries from six continents evaluated the backgrounds. PARTICIPANTS: Researchers with a Scopus index greater than 1 were included. MAIN OUTCOMES AND MEASURES: In this study, we generated a background section of a critical care clinical research question on “acute kidney injury in sepsis” using three different methods: researcher with H-index greater than 20, researcher with H-index greater than 10, and GPT-3.5. The three background sections were presented in a blinded survey to researchers with an H-index range between 1 and 96. First, the researchers evaluated the main components of the background using a 5-point Likert scale. Second, they were asked to identify which background was written by humans only or with large language model-generated tools. RESULTS: A total of 80 researchers completed the survey. The median H-index was 3 (interquartile range, 1–7.25) and most (36%) researchers were from the Critical Care specialty. When compared with researchers with an H-index of 22 and 13, GPT-3.5 was marked high on the Likert scale ranking on main background components (median 4.5 vs. 3.82 vs. 3.6 vs. 4.5, respectively; p < 0.001). The sensitivity and specificity to detect researchers writing versus GPT-3.5 writing were poor, 22.4% and 57.6%, respectively. CONCLUSIONS AND RELEVANCE: GPT-3.5 could create background research content indistinguishable from the writing of a medical researcher. It was marked higher compared with medical researchers with an H-index of 22 and 13 in writing the background section of a critical care clinical research question.

Objective To provide insights into the nature, risk factors, impact and existing measures for reporting and preventing violence in the healthcare system. The under-reporting of violence against healthcare workers (HCWs) globally highlights the need for increased public awareness and education. Methods The Violence Study of Healthcare Workers and Systems study used a survey questionnaire created using Research Electronic Data Capture (REDCap) forms and distributed from 6 June to 9 August 2022. Logistic regression analysis evaluated violence predictors, including gender, age, years of experience, institution type, respondent profession and night shift frequency. A χ 2 test was performed to determine the association between gender and different violence forms. Results A total of 5405 responses from 79 countries were analysed. India, the USA and Venezuela were the top three contributors. Female respondents comprised 53%. The majority (45%) fell within the 26–35 age group. Medical students (21%), consultants (20%), residents/fellows (15%) and nurses (10%) constituted highest responders. Nearly 55% HCWs reported firsthand violence experience, and 16% reported violence against their colleagues. Perpetrators were identified as patients or family members in over 50% of cases, while supervisor-incited violence accounted for 16%. Around 80% stated that violence incidence either remained constant or increased during the COVID-19 pandemic. Among HCWs who experienced violence, 55% felt less motivated or more dissatisfied with their jobs afterward, and 25% expressed willingness to quit. Univariate analysis revealed that HCWs aged 26–65 years, nurses, physicians, ancillary staff, those working in public settings, with >1 year of experience, and frequent night shift workers were at significantly higher risk of experiencing violence. These results remained significant in multivariate analysis, except for the 55–65 age group, which lost statistical significance. Conclusion This global cross-sectional study highlights that a majority of HCWs have experienced violence, and the incidence either increased or remained the same during the COVID-19 pandemic. This has resulted in decreased job satisfaction.

Background and Objective: The association of non-alcoholic fatty liver disease (NAFLD) and metabolic-associated fatty liver disease (MAFLD) with intensive care unit (ICU) admissions and the need for mechanical ventilation and disease severity in COVID-19 patients. Material and Methods: A systematic literature review was conducted on the databases: Cochrane, Embase, PubMed, ScienceDirect, and the Web of Science from January 2019 to June 2022. Studies evaluating MAFLD using laboratory methods, non-invasive imaging, or liver biopsy were included. The study protocol was registered in PROSPERO (ID CRD42022313259), and PRISMA guidelines were followed. The NIH quality assessment tool was used for quality assessment. RevMan version 5.3 software was used for pooled analysis. A sensitivity analysis was performed to assess the result’s stability. Results: A total of 37,974 patients from 17 studies were assessed for the association between MAFLD and ICU admission. A total of 3396 COVID-19 patients required ICU admission: 1236 (20.41%) in the MAFLD group and 2160 (6.77%) in the non-MAFLD group. The odds ratio was 1.86 for ICU admission, p = 0.007, and a (95% CI) of [1.18–2.91]. A total of 37,166 patients from 13 studies were included in the need for invasive mechanical ventilation analysis. A total of 1676 patients required mechanical ventilation: 805 in the MAFLD group (14.20% of all MAFLD patients) and 871 patients in the non-MAFLD group (2.76% of all non-MAFLD patients). The odds ratio was 2.05, p = 0.02, and a (95% CI) of [1.12–3.74]. A total of 5286 patients from 14 studies were included in the COVID-19 disease severity analysis. Severe COVID-19 was seen in 1623 patients, with 33.17% (901/2716) of MAFLD patients and 28.09% (722/2570) of non-MAFLD patients having severe disease. The odds ratio was 1.59 for disease severity, p = 0.010, and a (95% CI) of [1.12–2.26]. Conclusions: Our meta-analysis suggests that there are significantly increased odds of ICU admissions, a need for invasive mechanical ventilation, and disease severity in MAFLD patients who acquire COVID-19.

IMPORTANCE: Initial Society of Critical Care Medicine Discovery Viral Infection and Respiratory illness Universal Study (VIRUS) Registry analysis suggested that improvements in critical care processes offered the greatest modifiable opportunity to improve critically ill COVID-19 patient outcomes. OBJECTIVES: The Structured Team-based Optimal Patient-Centered Care for Virus COVID-19 ICU Collaborative was created to identify and speed implementation of best evidence based COVID-19 practices. DESIGN, SETTING, AND PARTICIPANTS: This 6-month project included volunteer interprofessional teams from VIRUS Registry sites, who received online training on the Checklist for Early Recognition and Treatment of Acute Illness and iNjury approach, a structured and systematic method for delivering evidence based critical care. Collaborators participated in weekly 1-hour videoconference sessions on high impact topics, monthly quality improvement (QI) coaching sessions, and received extensive additional resources for asynchronous learning. MAIN OUTCOMES AND MEASURES: Outcomes included learner engagement, satisfaction, and number of QI projects initiated by participating teams. RESULTS: Eleven of 13 initial sites participated in the Collaborative from March 2, 2021, to September 29, 2021. A total of 67 learners participated in the Collaborative, including 23 nurses, 22 physicians, 10 pharmacists, nine respiratory therapists, and three nonclinicians. Site attendance among the 11 sites in the 25 videoconference sessions ranged between 82% and 100%, with three sites providing at least one team member for 100% of sessions. The majority reported that topics matched their scope of practice (69%) and would highly recommend the program to colleagues (77%). A total of nine QI projects were initiated across three clinical domains and focused on improving adherence to established critical care practice bundles, reducing nosocomial complications, and strengthening patient- and family-centered care in the ICU. Major factors impacting successful Collaborative engagement included an engaged interprofessional team; an established culture of engagement; opportunities to benchmark performance and accelerate institutional innovation, networking, and acclaim; and ready access to data that could be leveraged for QI purposes. CONCLUSIONS AND RELEVANCE: Use of a virtual platform to establish a learning collaborative to accelerate the identification, dissemination, and implementation of critical care best practices for COVID-19 is feasible. Our experience offers important lessons for future collaborative efforts focused on improving ICU processes of care.

Objectives To describe incidence and risk factors of loss of previous independent living through nonhome discharge or discharge home with health assistance in survivors of intensive care unit (ICU) admission for coronavirus disease 2019 (COVID-19). Design Multicenter observational study including patients admitted to the ICU from January 2020 till June 30, 2021. Hypothesis We hypothesized that there is a high risk of nonhome discharge in patients surviving ICU admission due to COVID-19. Setting Data were included from 306 hospitals in 28 countries participating in the SCCM Discovery Viral Infection and Respiratory Illness Universal Study COVID-19 registry. Patients Previously independently living adult ICU survivors of COVID-19. Interventions None. Measurements and Main Results The primary outcome was nonhome discharge. Secondary outcome was the requirement of health assistance among patients who were discharged home. Out of 10 820 patients, 7101 (66%) were discharged alive; 3791 (53%) of these survivors lost their previous independent living status, out of those 2071 (29%) through nonhome discharge, and 1720 (24%) through discharge home requiring health assistance. In adjusted analyses, loss of independence on discharge among survivors was predicted by patient age ≥ 65 years (adjusted odds ratio [aOR] 2.78, 95% confidence interval [CI] 2.47-3.14, P < .0001), former and current smoking status (aOR 1.25, 95% CI 1.08-1.46, P = .003 and 1.60 (95% CI 1.18-2.16), P = .003, respectively), substance use disorder (aOR 1.52, 95% CI 1.12-2.06, P = .007), requirement for mechanical ventilation (aOR 4.17, 95% CI 3.69-4.71, P < .0001), prone positioning (aOR 1.19, 95% CI 1.03-1.38, P = .02), and requirement for extracorporeal membrane oxygenation (aOR 2.28, 95% CI 1.55-3.34, P < .0001). Conclusions More than half of ICU survivors hospitalized for COVID-19 are unable to return to independent living status, thereby imposing a significant secondary strain on health care systems worldwide.