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Introduction: Life-support limits (i.e., code status), the first step in the continuum of palliation and end-of-life (EoL) care, stem from decisions made by patients and their providers to align care near the EoL with patients’ wishes. The pandemic created health care strain that may have influenced life-support limitation practices among patients with serious COVID-19. In this study, we examine variations in life-support limitations (do-not-resuscitate, DNR; do-not-intubate, DNI) depending on the hospital and period of hospitalization. Methods: We included all adults admitted to a hospital in the United States with COVID-19 from January 2020 to December 2021 using the VIRUS registry. Our outcome was any life-support limitation on admission (DNR, DNI, or both) using regression modeling. Main exposures were hospital and period of hospitalization (early vs. late pandemic). Covariates included age, sex, race/ethnicity, comorbidities, and hospitalization diagnoses. Results: There were 42,383 patients from 75 hospitals in the US. The median age was 63 (interquartile range: 50–75), 46.5% were female, and 37.5% were non-Hispanic White. The life-support limitation rate was 7.9%, and the palliative care consultation rate was 2.3%. The odds of life-support limitation were 1.86 (95% CI: 1.6–2.1) depending on the hospital, but the period of hospitalization was not associated with odds of life-support limitation. Older age was associated with the greatest increased odds (4.1 per standard deviation ∼ 17.9 years, 95% CI: 3.9–4.4), followed by comorbidities including paralysis (2.4, 95% CI: 1.8–3.0) and dementia (2.3, 95% CI: 2.0–2.6). Conclusions: After adjusting for patient-level factors, we report significant inter-hospital but no temporal variation in life-support limitation upon admission with COVID-19. Future studies should investigate specific practices that led to health care resilience to temporal practice variations in life-support limitation during the pandemic.

OBJECTIVES: This study aimed to establish a set of guiding principles for data sharing and harmonization in critical care, focusing on the use of real-world data (RWD) and real-world evidence (RWE) to improve patient outcomes and research efficacy. The principles were developed through a systematic literature review and a modified Delphi process, with the goal of enhancing data accessibility, standardization, and interoperability across critical care settings. DATA SOURCES: Data sources included a comprehensive search of peer-reviewed literature, specifically studies related to the use of RWD and RWE in healthcare, guidelines, best practices, and recommendations on data sharing and harmonization. A total of 8150 articles were initially identified through databases such as MEDLINE and Web of Science, with 257 studies meeting inclusion criteria. STUDY SELECTION: Inclusion criteria focused on publications discussing health-related informatics, recommendations for RWD/RWE usage, data sharing, and harmonization principles. Exclusion criteria ruled out non-human studies, case studies, conference abstracts, and articles published before 2013, as well as those not available in English. DATA EXTRACTION: From the 257 selected studies, 322 statements were extracted. After removing irrelevant definitions and off-topic content, 232 statements underwent content validation and thematic analysis. These statements were then consolidated into 24 candidate guiding principles after rigorous review and consensus-building among the expert panel. DATA SYNTHESIS: A three-phase modified Delphi process was employed, involving a conceptualization group, a review group, and a Delphi group. In phase 1, experts identified key themes and search terms for the systematic review. Phase 2 involved validating and refining the prospective guiding principles, while phase 3 employed a Delphi panel to rate principles on acceptability, importance, and feasibility. This process resulted in 24 guiding principles, with high consensus achieved in rounds 2 and 3 on their relevance and applicability. CONCLUSIONS: The systematic review and Delphi process resulted in 24 guiding principles to improve data sharing and harmonization in critical care. These principles address challenges across the data lifecycle, including generation, storage, access, and usage of RWD and RWE. This framework is designed to promote more effective and equitable data practices, with relevance for the development of artificial intelligence-based decision support tools and clinical research. The principles are intended to guide the responsible use of data science in critical care, with emphasis on ethics and equity, while acknowledging the variability of resources across settings.

OBJECTIVES: Telecritical care (TCC) refers to the delivery of critical care using telehealth technologies. Despite increasing utilization, significant practice variation exists and literature regarding efficacy remains sparse. The Telecritical Care Collaborative Network sought to provide expert, consensus-based best practice recommendations for the design and delivery of TCC. DESIGN: We used a modified Delphi methodology. Following literature review, an oversight panel identified core domains and developed declarative statements for review by an expert voting panel. During three voting rounds, voters agreed or disagreed with statements and provided open-ended feedback, which the oversight panel used to revise statements. Statements met criteria for consensus when accepted by greater than or equal to 85% of voters. SETTING/SUBJECTS: The oversight panel included 18 multidisciplinary members of the TCC Collaborative Network, and the voting panel included 32 invited experts in TCC, emphasizing diversity of discipline, care delivery models, and geography. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: We identified ten core domains: definitions/terminology; care delivery models; staffing and coverage models; technological considerations; ergonomics and workplace safety; licensing, credentialing, and certification; trust and relationship building; quality, safety, and efficiency, research agenda; and advocacy, leading to 79 practice statements. Of 79 original statements, 67 were accepted in round 1. After revision, nine were accepted in round 2 and two in round 3 (two statements were merged). In total, 78 practice statements achieved expert consensus. CONCLUSIONS: These expert consensus recommendations cover a broad range of topics relevant to delivery of TCC. Experts agreed that TCC is most effective when delivered by care teams with specific expertise and by programs with explicit protocols focusing on effective communication, technical reliability, and real-time availability. Interventions should be tailored to local conditions. Although further research is needed to guide future best practice statements, these results provide valuable and actionable recommendations for the delivery of high-quality TCC.

The COVID-19 pandemic caused tremendous disruption to the U.S. healthcare system and nearly crippled some hospitals during large patient surges. Limited ICU beds across the country further exacerbated these challenges. Telemedicine, specifically tele-critical care (TCC), can expand a hospital’s clinical capabilities through remote expertise and increase capacity by offloading some monitoring to remote teams. Unfortunately, the rapid deployment of telemedicine, especially TCC, is constrained by multiple barriers. In the summer of 2020, to support the National Emergency Tele-Critical Care Network (NETCCN) deployment, more than 50 national leaders in applying telemedicine technologies to critical care assembled to provide their opinions about barriers to NETCCN implementation and strategies to overcome them. Through consensus, these experts developed white papers that formed the basis of this article. Herein, the authors share their experience and propose multiple solutions to barriers presented by laws, local policies and cultures, and individual perspectives according to a minimum, better, best paradigm for TCC delivery in the setting of a national disaster. Cross-state licensure and local privileging of virtual experts were identified as the most significant barriers to rapid deployment of services, whereas refining the model of TCC to achieve the best outcomes and defining the best financial model is the most significant for long-term success. Ultimately, we conclude that a rapidly deployable national telemedicine response system is achievable.

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.

The study’s objective was to assess facilitators and barriers of Tele-Critical Care (TCC) perceived by SCCM members. By utilizing a survey distributed to SCCM members, a cross-sectional study was developed to analyze survey results from December 2019 and July 2020. SCCM members responded to the survey (n = 15,502) with a 1.9% response rate for the first distribution and a 2.54% response rate for the second survey (n = 9985). Participants (n = 286 and n = 254) were almost equally distributed between non-users, providers, users, and potential users of TCC services. The care delivery models for TCC were similar across most participants. Some consumers of TCC services preferred algorithmic coverage and scheduled rounds, while reactive and on-demand models were less utilized. The surveys revealed that outcome-driven measures were the principal form of TCC performance evaluation. A 1:100 (provider: patients) ratio was reported to be optimal. Factors related to costs, perceived lack of need for services, and workflow challenges were described by those who terminated TCC services. Barriers to implementation revolved around lack of reimbursement and adequate training. Interpersonal communication was identified as an essential TCC provider skill. The second survey introduced after the onset pandemic demonstrated more frequent use of advanced practice providers and focus on performance measures. Priorities for effective TCC deployment include communication, knowledge, optimal operationalization, and outcomes measurement at the organizational level. The potential effect of COVID-19 during the early stages of the pandemic on survey responses was limited and focused on the need to demonstrate TCC value.

OBJECTIVES: To determine the association of prior use of renin-angiotensin-aldosterone system inhibitors (RAASIs) with mortality and outcomes in hospitalized patients with COVID-19. DESIGN: Retrospective observational study. SETTING: Multicenter, international COVID-19 registry. Subjects: Adult hospitalized COVID-19 patients on antihypertensive agents (AHAs) prior to admission, admitted from March 31, 2020, to March 10, 2021. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: Data were compared between three groups: patients on RAASIs only, other AHAs only, and those on both medications. Multivariable logistic and linear regressions were performed after controlling for prehospitalization characteristics to estimate the effect of RAASIs on mortality and other outcomes during hospitalization. Of 26,652 patients, 7,975 patients were on AHAs prior to hospitalization. Of these, 1,542 patients (19.3%) were on RAASIs only, 3,765 patients (47.2%) were on other AHAs only, and 2,668 (33.5%) patients were on both medications. Compared with those taking other AHAs only, patients on RAASIs only were younger (mean age 63.3 vs 66.9 yr; p < 0.0001), more often male (58.2% vs 52.4%; p = 0.0001) and more often White (55.1% vs 47.2%; p < 0.0001). After adjusting for age, gender, race, location, and comorbidities, patients on combination of RAASIs and other AHAs had higher in-hospital mortality than those on RAASIs only (odds ratio [OR] = 1.28; 95% CI [1.19–1.38]; p < 0.0001) and higher mortality than those on other AHAs only (OR = 1.09; 95% CI [1.03–1.15]; p = 0.0017). Patients on RAASIs only had lower mortality than those on other AHAs only (OR = 0.87; 95% CI [0.81–0.94]; p = 0.0003). Patients on ACEIs only had higher mortality compared with those on ARBs only (OR = 1.37; 95% CI [1.20–1.56]; p < 0.0001). CONCLUSIONS: Among patients hospitalized for COVID-19 who were taking AHAs, prior use of a combination of RAASIs and other AHAs was associated with higher in-hospital mortality than the use of RAASIs alone. When compared with ARBs, ACEIs were associated with significantly higher mortality in hospitalized COVID-19 patients.

OBJECTIVES: To describe the prevalence, associated risk factors, and outcomes of serious neurologic manifestations (encephalopathy, stroke, seizure, and meningitis/encephalitis) among patients hospitalized with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. DESIGN: Prospective observational study. SETTING: One hundred seventy-nine hospitals in 24 countries within the Society of Critical Care Medicine Discovery Viral Infection and Respiratory Illness Universal Study COVID-19 Registry. PATIENTS: Hospitalized adults with laboratory-confirmed SARS-CoV-2 infection. INTERVENTIONS: None. RESULTS: Of 16,225 patients enrolled in the registry with hospital discharge status available, 2,092 (12.9%) developed serious neurologic manifestations including 1,656 (10.2%) with encephalopathy at admission, 331 (2.0%) with stroke, 243 (1.5%) with seizure, and 73 (0.5%) with meningitis/encephalitis at admission or during hospitalization. Patients with serious neurologic manifestations of COVID-19 were older with median (interquartile range) age 72 years (61.0–81.0 yr) versus 61 years (48.0–72.0 yr) and had higher prevalence of chronic medical conditions, including vascular risk factors. Adjusting for age, sex, and time since the onset of the pandemic, serious neurologic manifestations were associated with more severe disease (odds ratio [OR], 1.49; p < 0.001) as defined by the World Health Organization ordinal disease severity scale for COVID-19 infection. Patients with neurologic manifestations were more likely to be admitted to the ICU (OR, 1.45; p < 0.001) and require critical care interventions (extracorporeal membrane oxygenation: OR, 1.78; p = 0.009 and renal replacement therapy: OR, 1.99; p < 0.001). Hospital, ICU, and 28-day mortality for patients with neurologic manifestations was higher (OR, 1.51, 1.37, and 1.58; p < 0.001), and patients had fewer ICU-free, hospital-free, and ventilator-free days (estimated difference in days, –0.84, –1.34, and –0.84; p < 0.001). CONCLUSIONS: Encephalopathy at admission is common in hospitalized patients with SARS-CoV-2 infection and is associated with worse outcomes. While serious neurologic manifestations including stroke, seizure, and meningitis/encephalitis were less common, all were associated with increased ICU support utilization, more severe disease, and worse outcomes.