Citations

IMPORTANCE: At the start of the coronavirus disease 2019 pandemic, medications repurposed for management of coronavirus disease 2019 were used in the absence of clinical trial evidence. OBJECTIVES: To describe the variation and evolution in use of repurposed medications for coronavirus disease 2019. DESIGN, SETTING, AND PARTICIPANTS: Observational cohort study of adults hospitalized with coronavirus disease 2019 between February 15, 2020, and April 12, 2021, across 76 United States and international hospitals within the Society of Critical Care Medicine’s Discovery Viral Infection and Respiratory Illness Universal Study coronavirus disease 2019 registry. MAIN OUTCOMES AND MEASURES: Hospital variation was quantified using multivariable adjusted random effects logistic regression models and unsupervised clustering. Repurposed medications included antivirals, corticosteroids, hydroxychloroquine, immunomodulators, and therapeutic dose anticoagulants. RESULTS: Among 7,069 adults hospitalized with coronavirus disease 2019, 1,979 (28%) received antivirals, 2,876 (41%) received corticosteroids, 1,779 (25%) received hydroxychloroquine, 620 (9%) received immunomodulators, and 2,154 (31%) received therapeutic dose anticoagulants. Contribution of hospital site to risk-adjusted variation was 46% for antivirals, 30% for corticosteroids, 48% for hydroxychloroquine, 46% for immunomodulators, and 52% for therapeutic dose anticoagulants. Compared with the early pandemic, the later pandemic practice phenotypes converged with increased use of antivirals (odds ratio, 3.14; 95% CI, 2.40–4.10) and corticosteroids (odds ratio, 5.43; 95% CI, 4.23–6.97), with decreased use of hydroxychloroquine (odds ratio, 0.02; 95% CI, 0.01–0.04) and immunomodulators (odds ratio, 0.49; 95% CI, 0.34–0.70). There was no clinically significant change in the use of therapeutic dose anticoagulants (odds ratio, 1.01; 95% CI, 1.01–1.02). There were no differences in risk-adjusted mortality between hospitals with high rates of repurposed medication use compared with hospitals with low rates of use. CONCLUSIONS AND RELEVANCE: Hospital variation in the use of repurposed medications varied widely across hospitals early in the pandemic and later converged with the emergence of randomized clinical trials. Platforms developed for rapid activation and enrollment in clinical trials of repurposed medications are needed prior to the next pandemic to expedite effective, evidence-based practice.

OBJECTIVE To describe the impact of obesity on disease severity and outcomes of coronavirus disease 2019 (COVID-19) among hospitalized children. METHODS This retrospective cohort study from the Society of Critical Care Medicine Viral Respiratory Illness Universal Study registry included all children hospitalized with COVID-19 from March 2020 to January 2021. Obesity was defined by Centers for Disease Control and Prevention BMI or World Health Organization weight for length criteria. Critical illness definition was adapted from National Institutes of Health criteria of critical COVID. Multivariate mixed logistic and linear regression was performed to calculate the adjusted odds ratio of critical illness and the adjusted impact of obesity on hospital length of stay. RESULTS Data from 795 patients (96.4% United States) from 45 sites were analyzed, including 251 (31.5%) with obesity and 544 (68.5%) without. A higher proportion of patients with obesity were adolescents, of Hispanic ethnicity, and had other comorbidities. Those with obesity were also more likely to be diagnosed with multisystem inflammatory syndrome in children (35.7% vs 28.1%, P = .04) and had higher ICU admission rates (57% vs 44%, P < .01) with more critical illness (30.3% vs 18.3%, P < .01). Obesity had more impact on acute COVID-19 severity than on multisystem inflammatory syndrome in children presentation. The adjusted odds ratio for critical illness with obesity was 3.11 (95% confidence interval: 1.8–5.3). Patients with obesity had longer adjusted length of stay (exponentiated parameter estimate 1.3; 95% confidence interval: 1.1–1.5) compared with patients without obesity but did not have increased mortality risk due to COVID-19 (2.4% vs 1.5%, P = .38). CONCLUSION In a large, multicenter cohort, a high proportion of hospitalized children from COVID-19 had obesity as comorbidity. Furthermore, obesity had a significant independent association with critical illness.

IMPORTANCE: Even with its proclivity for older age, coronavirus disease 2019 has been shown to affect all age groups. However, there remains a lack of research focused primarily on the young adult population. OBJECTIVES: To describe the epidemiology and outcomes of coronavirus disease 2019 and identify the risk factors associated with critical illness and mortality in hospitalized young adults. DESIGN, SETTINGS, AND PARTICIPANTS: A retrospective cohort study of the Society of Critical Care Medicine’s Viral Infection and Respiratory Illness Universal Study registry. Patients 18–40 years old, hospitalized from coronavirus disease 2019 from March 2020 to April 2021, were included in the analysis. MAIN OUTCOMES AND MEASURES: Critical illness was defined as a composite of mortality and 21 predefined interventions and complications. Multivariable logistic regression was used to assess associations with critical illness and mortality. RESULTS: Data from 4,005 patients (152 centers, 19 countries, 18.6% non-U.S. patients) were analyzed. The median age was 32 years (interquartile range, 27–37 yr); 51% were female, 29.4% Hispanic, and 42.9% had obesity. Most patients (63.2%) had comorbidities, the most common being hypertension (14.5%) and diabetes (13.7%). Hospital and ICU mortality were 3.2% (129/4,005) and 8.3% (109/1,313), respectively. Critical illness occurred in 25% (n = 996), and 34.3% (n = 1,376) were admitted to the ICU. Older age (p = 0.03), male sex (adjusted odds ratio, 1.83 [95% CI, 1.2–2.6]), and obesity (adjusted odds ratio, 1.6 [95% CI, 1.1–2.4]) were associated with hospital mortality. In addition to the above factors, the presence of any comorbidity was associated with critical illness from coronavirus disease 2019. Multiple sensitivity analyses, including analysis with U.S. patients only and patients admitted to high-volume sites, showed similar risk factors. CONCLUSIONS: Among hospitalized young adults, obese males with comorbidities are at higher risk of developing critical illness or dying from coronavirus disease 2019.

Abstract Background CERTAIN (Checklist for Early Recognition and Treatment of Acute Illness and iNjury) has been shown to improve critical care process and patient outcomes in international ICUs with variable resources. Methods CERTAIN education program derived from this approach is designed, promoted, and implemented following the Logic model. Through the roadmap of the Logic model, we presented a dynamic, longitudinal implementation framework that had sufficient rigor yet offers flexibility to reach the need of the existing and emerging diversified medical education projects. Results Using the Logic model, the delivery of the CERTAIN education program is optimized to deliver relevant education content in various environments. During the COVID-19 outbreak, the implementational framework demonstrated that it could serve as an excellent template for effective response to global pandemics. Conclusions The Logical model is useful as a facilitation tool for planning and evaluating innovative education delivery and dissemination. The CERTAIN program provided an example for other continuous professional education projects.

Introduction: Our goal was to systematically review contemporary literature comparing the relative effectiveness of two mechanical compression devices (LUCAS and AutoPulse) to manual compression for achieving return of spontaneous circulation (ROSC) in patients undergoing cardiopulmonary resuscitation (CPR) after an out-of-hospital cardiac arrest (OHCA). Methods: We searched medical databases systematically for randomized controlled trials (RCT) and observational studies published between January 1, 2000–October 1, 2020 that compared mechanical chest compression (using any device) with manual chest compression following OHCA. We only included studies in the English language that reported ROSC outcomes in adult patients in non-trauma settings to conduct random-effects metanalysis and trial sequence analysis (TSA). Multivariate meta-regression was performed using preselected covariates to account for heterogeneity. We assessed for risk of biases in randomization, allocation sequence concealment, blinding, incomplete outcome data, and selective outcome reporting. Results: A total of 15 studies (n = 18474), including six RCTs, two cluster RCTs, five retrospective case-control, and two phased prospective cohort studies, were pooled for analysis. The pooled estimates’ summary effect did not indicate a significant difference (Mantel-Haenszel odds ratio = 1.16, 95% confidence interval, 0.97 to 1.39, P = 0.11, I2 = 0.83) between mechanical and manual compressions during CPR for ROSC. The TSA showed firm evidence supporting the lack of improvement in ROSC using mechanical compression devices. The Z-curves successfully crossed the TSA futility boundary for ROSC, indicating sufficient evidence to draw firm conclusions regarding these outcomes. Multivariate meta-regression demonstrated that 100% of the between-study variation could be explained by differences in average age, the proportion of females, cardiac arrests with shockable rhythms, witnessed cardiac arrest, bystander CPR, and the average time for emergency medical services (EMS) arrival in the study samples, with the latter three attaining statistical significance. Conclusion: Mechanical compression devices for resuscitation in cardiac arrests are not associated with improved rates of ROSC. Their use may be more beneficial in non-ideal situations such as lack of bystander CPR, unwitnessed arrest, and delayed EMS response times. Studies done to date have enough power to render further studies on this comparison futile.

OBJECTIVES: Accurate identification of acute respiratory distress syndrome is essential for understanding its epidemiology, patterns of care, and outcomes. We aimed to design a computable phenotyping strategy to detect acute respiratory distress syndrome in electronic health records of critically ill patients. DESIGN: This is a retrospective cohort study. Using a near real-time copy of the electronic health record, we developed a computable phenotyping strategy to detect acute respiratory distress syndrome based on the Berlin definition. SETTING: Twenty multidisciplinary ICUs in Mayo Clinic Health System. SUBJECTS: The phenotyping strategy was applied to 196,487 consecutive admissions from year 2009 to 2019. INTERVENTIONS: The acute respiratory distress syndrome cohort generated by this novel strategy was compared with the acute respiratory distress syndrome cohort documented by clinicians during the same period. The sensitivity and specificity of the phenotyping strategy were calculated in randomly selected patient cohort (50 patients) using the results from manual medical record review as gold standard. MEASUREMENTS AND MAIN RESULTS: Among the patients who did not have acute respiratory distress syndrome documented, the computable phenotyping strategy identified 3,169 adult patients who met the Berlin definition, 676 patients (21.3%) were classified to have severe acute respiratory distress syndrome (Pao 2/Fio 2 ratio ≤ 100), 1,535 patients (48.4%) had moderate acute respiratory distress syndrome (100 < Pao 2/Fio 2 ratio ≤ 200), and 958 patients (30.2%) had mild acute respiratory distress syndrome (200 < Pao 2/Fio 2 ratio ≤ 300). The phenotyping strategy achieved a sensitivity of 94.4%, specificity of 96.9%, positive predictive value of 94.4%, and negative predictive value of 96.9% in a randomly selected patient cohort. The clinicians documented acute respiratory distress syndrome in 1,257 adult patients during the study period. The clinician documentation rate of acute respiratory distress syndrome was 28.4%. Compared with the clinicians’ documentation, the phenotyping strategy identified a cohort that had higher acuity and complexity of illness suggested by higher Sequential Organ Failure Assessment score (9 vs 7; p < 0.0001), higher Acute Physiology and Chronic Health Evaluation score (76 vs 63; p < 0.0001), higher rate of requiring invasive mechanical ventilation (99.1% vs 71.8%; p < 0.0001), higher ICU mortality (20.6% vs 16.8%; p < 0.0001), and longer ICU length of stay (5.1 vs 4.2 d; p < 0.0001). CONCLUSIONS: Our rule-based computable phenotyping strategy can accurately detect acute respiratory distress syndrome in critically ill patients in the setting of high clinical complexity. This strategy can be applied to enhance early recognition of acute respiratory distress syndrome and to facilitate best-care delivery and clinical research in acute respiratory distress syndrome.

ABSTRACT Introduction: The impact of albumin resuscitation on sepsis outcomes is debated, particularly in the initial phase of resuscitation. We aimed to investigate the association between albumin use in the initial 6 h of resuscitation and subsequent outcomes in adult septic patients. Methods: This single-center, retrospective, propensity score-matched cohort study included adult patients admitted to intensive care units (ICUs) with sepsis or septic shock from January 1, 2006, to May 4, 2018, at a tertiary referral hospital. We compared two groups based on albumin receipt within the initial six resuscitation hours (albumin group vs. non-albumin group). We performed a 1:2 propensity score matching to assess shock-free time in ICU as the primary outcome. Results: Of 2,732 patients with medical sepsis, 286 cases in the albumin group were matched with 549 individuals in the non-albumin group. Compared to the non-albumin group, the albumin group required more intravenous fluids and had higher net fluid balance, lower mean arterial pressure, and lower serum base excess level in the initial 6 and 24 h of resuscitation. Shock-free time, ICU and hospital length of stay, and 28-day mortality were not different between albumin and non-albumin groups (56 vs. 66 h, P = 0.18; 3.5 days vs. 3.7 days, P = 0.61; 9.1 days vs. 9.5 days, P = 0.27; 36% vs. 32%, P = 0.25, respectively). Conclusions: Using albumin during the initial 6 h of resuscitation was not associated with benefits in clinical outcomes of patients with medical sepsis.

OBJECTIVES: To compare clinical characteristics and outcomes of children admitted to the PICU for severe acute respiratory syndrome coronavirus 2–related illness with or without multisystem inflammatory syndrome in children. The secondary objective was to identify explanatory factors associated with outcome of critical illness defined by a composite index of in-hospital mortality and organ system support requirement. DESIGN: Retrospective cohort study. SETTING: Thirty-eight PICUs within the Viral Infection and Respiratory Illness Universal Study registry from March 2020 to January 2021. PATIENTS: Children less than 18 years with severe acute respiratory syndrome coronavirus 2–related illness with or without multisystem inflammatory syndrome in children. MEASUREMENTS AND MAIN RESULTS: Of 394 patients, 171 (43.4%) had multisystem inflammatory syndrome in children. Children with multisystem inflammatory syndrome in children were more likely younger (2–12 yr vs adolescents; p < 0.01), Black (35.6% vs 21.9%; p < 0.01), present with fever/abdominal pain than cough/dyspnea (p < 0.01), and less likely to have comorbidities (33.3% vs 61.9%; p < 0.01) compared with those without multisystem inflammatory syndrome in children. Inflammatory marker levels, use of inotropes/vasopressors, corticosteroids, and anticoagulants were higher in multisystem inflammatory syndrome in children patients (p < 0.01). Overall mortality was 3.8% (15/394), with no difference in the two groups. Diagnosis of multisystem inflammatory syndrome in children was associated with longer duration of hospitalization as compared to nonmultisystem inflammatory syndrome in children (7.5 d[interquartile range, 5–11] vs 5.3 d [interquartile range, 3–11 d]; p < 0.01). Critical illness occurred in 164 patients (41.6%) and was more common in patients with multisystem inflammatory syndrome in children compared with those without (55.6% vs 30.9%; p < 0.01). Multivariable analysis failed to show an association between critical illness and age, race, sex, greater than or equal to three signs and symptoms, or greater than or equal to two comorbidities among the multisystem inflammatory syndrome in children cohort. Among nonmultisystem inflammatory syndrome in children patients, the presence of greater than or equal to two comorbidities was associated with greater odds of critical illness (odds ratio 2.95 [95% CI, 1.61–5.40]; p < 0.01). CONCLUSIONS: This study delineates significant clinically relevant differences in presentation, explanatory factors, and outcomes among children admitted to PICU with severe acute respiratory syndrome coronavirus 2–related illness stratified by multisystem inflammatory syndrome in children.