Gajic, Ognjen

OBJECTIVES: To describe the outcomes of hospitalized patients in a multicenter, international coronavirus disease 2019 registry. DESIGN: Cross-sectional observational study including coronavirus disease 2019 patients hospitalized with laboratory-confirmed severe acute respiratory syndrome coronavirus-2 infection between February 15, 2020, and November 30, 2020, according to age and type of organ support therapies. SETTING: About 168 hospitals in 16 countries within the Society of Critical Care Medicine’s Discovery Viral Infection and Respiratory Illness University Study coronavirus disease 2019 registry. PATIENTS: Adult hospitalized coronavirus disease 2019 patients who did and did not require various types and combinations of organ support (mechanical ventilation, renal replacement therapy, vasopressors, and extracorporeal membrane oxygenation). INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: Primary outcome was hospital mortality. Secondary outcomes were discharge home with or without assistance and hospital length of stay. Risk-adjusted variation in hospital mortality for patients receiving invasive mechanical ventilation was assessed by using multilevel models with hospitals as a random effect, adjusted for age, race/ethnicity, sex, and comorbidities. Among 20,608 patients with coronavirus disease 2019, the mean (± sd ) age was 60.5 (±17), 11,1887 (54.3%) were men, 8,745 (42.4%) were admitted to the ICU, and 3,906 (19%) died in the hospital. Hospital mortality was 8.2% for patients receiving no organ support ( n = 15,001). The most common organ support therapy was invasive mechanical ventilation ( n = 5,005; 24.3%), with a hospital mortality of 49.8%. Mortality ranged from 40.8% among patients receiving only invasive mechanical ventilation ( n =1,749) to 71.6% for patients receiving invasive mechanical ventilation, vasoactive drugs, and new renal replacement therapy ( n = 655). Mortality was 39% for patients receiving extracorporeal membrane oxygenation ( n = 389). Rates of discharge home ranged from 73.5% for patients who did not require organ support therapies to 29.8% for patients who only received invasive mechanical ventilation, and 8.8% for invasive mechanical ventilation, vasoactive drugs, and renal replacement; 10.8% of patients older than 74 years who received invasive mechanical ventilation were discharged home. Median hospital length of stay for patients on mechanical ventilation was 17.1 days (9.7-28 d). Adjusted interhospital variation in mortality among patients receiving invasive mechanical ventilation was large (median odds ratio 1.69). CONCLUSIONS: Coronavirus disease 2019 prognosis varies by age and level of organ support. Interhospital variation in mortality of mechanically ventilated patients was not explained by patient characteristics and requires further evaluation.

Abstract Patients hospitalized for pneumonia are at high risk for mortality. Effective therapies are therefore needed. Recent randomized clinical trials suggest that systemic steroids can reduce the length of hospital stays among patients hospitalized for pneumonia. Furthermore, preliminary findings from a feasibility study demonstrated that early treatment with a combination of an inhaled corticosteroid and a bronchodilator can improve oxygenation and reduce risk of respiratory failure in patients at risk of acute respiratory distress syndrome. Whether such a combination administered early is effective in reducing acute respiratory failure (ARF) among patients hospitalized with pneumonia is unknown. Here we describe the ARREST Pneumonia (Arrest Respiratory Failure due to Pneumonia) trial designed to address this question. ARREST Pneumonia is a two-arm, randomized, double-blinded, placebo-controlled trial designed to test the efficacy of a combination of an inhaled corticosteroid and a β-agonist compared with placebo for the prevention of ARF in hospitalized participants with severe pneumonia. The primary outcome is ARF within 7 days of randomization, defined as a composite endpoint of intubation and mechanical ventilation; need for high-flow nasal cannula oxygen therapy or noninvasive ventilation for >36 hours (each alone or combined); or death within 36 hours of being placed on respiratory support. The planned enrollment is 600 adult participants at 10 academic medical centers. In addition, we will measure selected plasma biomarkers to better understand mechanisms of action. The trial is funded by the U.S. National Heart Lung and Blood Institute. Clinical trial registered with www.clinicaltrials.gov (NCT 04193878).

Abstract Rationale Acute respiratory distress syndrome (ARDS) is a common complication after hematopoietic stem cell transplantation (HCT) and is a major contributor to nonrelapse mortality. Objectives To better understand pretransplant risk factors for developing ARDS after HCT. Methods This is a single-center observational study comparing risk factors for ARDS development in 164 patients who went on to develop post-HCT ARDS compared with 492 patients who did not. The patients were matched 1 to 3 on age, sex, type of transplant (allogeneic vs. autologous), and underlying disease. Pertinent risk factors were analyzed separately in multivariable conditional logistic regression after adjustment for a priori variables known to be associated with ARDS development. Results Patients with ARDS were more likely to have a lower pretransplant pulmonary function as measured by forced vital capacity (FVC) (odds ratio [OR], 0.54 [0.42–0.70] per liter increase in FVC; P < 0.001), forced expiratory volume in one second (FEV1) (OR, 0.52 [0.38–0.71] per liter increase in FEV1; P < 0.001) and diffusing capacity (OR, 0.92 [0.88–0.96] per ml/min/mm Hg increase in diffusing capacity; P < 0.001). Several laboratory indices were predictive of subsequent ARDS development including elevated AST (aspartate aminotransferase) (OR, 1.01 [1.00–1.01]; P < 0.008), lower serum albumin (OR, 0.44 [0.30–0.66]; P < 0.001), lower pretransplant hemoglobin (OR, 0.82 [0.73–0.92]; P = 0.001), and lower leukocyte count (OR, 0.88 [0.79–0.99]; P < 0.03). Patients who went on to develop ARDS were more likely to have been hospitalized in the year before the transplant (OR, 1.11 [1.04–1.20]; P = 0.003), and required invasive or noninvasive ventilation during that hospitalization. Lastly, patients with ARDS were significantly more likely to have received carboplatin, thalidomide, methotrexate, and cisplatin than the non-ARDS control subjects. Conclusions Several risk factors for developing ARDS after HCT are identifiable at the time of transplantation, well before the development of critical illness and ARDS. The identification of risk factors long before ARDS develops is relatively unique to the HCT population. Further work is needed to develop usable risk prediction tools in this setting.

Abstract Rationale The periengraftment respiratory distress syndrome (PERDS) is an early important cause of morbidity following autologous hematopoietic cell transplantation (HCT). There are few contemporary data describing PERDS. Objectives To determine prevalence, risk factors, and outcomes of PERDS after autologous HCT. Methods This was a historical cohort study of adults undergoing autologous HCT at Mayo Clinic, Rochester, Minnesota, between 2005 and 2016. PERDS was defined as 1) respiratory failure requiring supplemental oxygen within 5 days on either side of the neutrophil engraftment date, 2) new pulmonary opacities on chest imaging, and 3) exclusion of an infectious or cardiac etiology to explain the clinical presentation. Results Of 3,473 patients undergoing autologous HCT, 167 (4.8%) developed PERDS. Radiographic changes preceded engraftment in 77% of cases. In a multivariable regression model, risk factors for PERDS included female sex (odds ratio [OR], 1.73; P = 0.001), the number of preengraftment platelet transfusions (OR, 1.22; P = 0.002), and more rapid engraftment (OR, 0.72 per day longer; P < 0.001). PERDS cases were more likely to be admitted to the intensive care unit (47.3% vs. 9.5%, P < 0.001) and require intubation (20.4% vs. 1.6%, P < 0.001). In an adjusted 100-day death analysis, those diagnosed with PERDS were more likely to die (hazard ratio, 3.1; 95% confidence interval, 1.5–6.2; P = 0.002). Conclusions PERDS is a common complication of autologous HCT and is associated with increased mortality and healthcare use. Radiographic evidence of pulmonary involvement precedes hematopoietic recovery. A larger number of platelet transfusions and more rapid engraftment appear to increase risk for PERDS.

Objectives: To develop and verify a digital twin model of critically ill patient using the causal artificial intelligence approach to predict the response to specific treatment during the first 24 hours of sepsis. Design: Directed acyclic graphs were used to define explicitly the causal relationship among organ systems and specific treatments used. A hybrid approach of agent-based modeling, discrete-event simulation, and Bayesian network was used to simulate treatment effect across multiple stages and interactions of major organ systems (cardiovascular, neurologic, renal, respiratory, gastrointestinal, inflammatory, and hematology). Organ systems were visualized using relevant clinical markers. The application was iteratively revised and debugged by clinical experts and engineers. Agreement statistics was used to test the performance of the model by comparing the observed patient response versus the expected response (primary and secondary) predicted by digital twin. Setting: Medical ICU of a large quaternary- care academic medical center in the United States. Patients or Subjects: Adult (> 18 year yr old), medical ICU patients were included in the study. Interventions: No additional interventions were made beyond the standard of care for this study. Measurements and Main Results: During the verification phase, model performance was prospectively tested on 145 observations in a convenience sample of 29 patients. Median age was 60 years (54–66 d) with a median Sequential Organ Failure Assessment score of 9.5 (interquartile range, 5.0–14.0). The most common source of sepsis was pneumonia, followed by hepatobiliary. The observations were made during the first 24 hours of the ICU admission with one-step interventions, comparing the output in the digital twin with the real patient response. The agreement between the observed versus and the expected response ranged from fair (kappa coefficient of 0.41) for primary response to good (kappa coefficient of 0.65) for secondary response to the intervention. The most common error detected was coding error in 50 observations (35%), followed by expert rule error in 29 observations (20%) and timing error in seven observations (5%). Conclusions: We confirmed the feasibility of development and prospective testing of causal artificial intelligence model to predict the response to treatment in early stages of critical illness. The availability of qualitative and quantitative data and a relatively short turnaround time makes the ICU an ideal environment for development and testing of digital twin patient models. An accurate digital twin model will allow the effect of an intervention to be tested in a virtual environment prior to use on real patients.