Association of Blood Pressure Variability with Delirium in Patients with Critical Illness.

BACKGROUND: The objective was to examine the association of blood pressure variability (BPV) during the first 24 h after intensive care unit admission with the likelihood of delirium and depressed alertness without delirium ("depressed alertness"). METHODS: This retrospective, observational, cohort study included all consecutive adult patients admitted to an intensive care unit at Mayo Clinic, Rochester, Minnesota, from July 1, 2004, through October 31, 2015. The primary outcomes were delirium and delirium-free days, and the secondary outcomes included depressed alertness and depressed alertness-free days. Logistic regression was performed to determine the association of BPV with delirium and depressed alertness. Proportional odds regression was used to assess the association of BPV with delirium-free days and depressed alertness-free days. RESULTS: Among 66,549 intensive care unit admissions, delirium was documented in 20.2% and depressed alertness was documented in 24.4%. Preserved cognition was documented in 55.4% of intensive care unit admissions. Increased systolic and diastolic BPV was associated with an increased odds of delirium and depressed alertness. The magnitude of the association per 5-mm Hg increase in systolic average real variability (the average of absolute value of changes between consecutive systolic blood pressure readings) was greater for delirium (odds ratio 1.34; 95% confidence interval 1.29-1.40; P < 0.001) than for depressed alertness (odds ratio 1.06; 95% confidence interval 1.02-1.10; P = 0.004). Increased systolic and diastolic BPV was associated with fewer delirium-free days but not with depressed alertness-free days. CONCLUSIONS: BPV in the first 24 h after intensive care unit admission is associated with an increased likelihood of delirium and fewer delirium-free days.

Implementation of a Virtual Interprofessional ICU Learning Collaborative: Successes, Challenges, and Initial Reactions From the Structured Team-Based Optimal Patient-Centered Care for Virus COVID-19 Collaborators.

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.

Development and Validation of an Acute Respiratory Distress Syndrome Prediction Model in Coronavirus Disease 2019: Updated Lung Injury Prediction Score.

OBJECTIVE: To develop and validate an updated lung injury prediction score for coronavirus disease 2019 (COVID-19) (c-LIPS) tailored for predicting acute respiratory distress syndrome (ARDS) in COVID-19. PATIENTS AND METHODS: This was a registry-based cohort study using the Viral Infection and Respiratory Illness Universal Study. Hospitalized adult patients between January 2020 and January 2022 were screened. Patients who qualified for ARDS within the first day of admission were excluded. Development cohort consisted of patients enrolled from participating Mayo Clinic sites. The validation analyses were performed on remaining patients enrolled from more than 120 hospitals in 15 countries. The original lung injury prediction score (LIPS) was calculated and enhanced using reported COVID-19-specific laboratory risk factors, constituting c-LIPS. The main outcome was ARDS development and secondary outcomes included hospital mortality, invasive mechanical ventilation, and progression in WHO ordinal scale. RESULTS: The derivation cohort consisted of 3710 patients, of whom 1041 (28.1%) developed ARDS. The c-LIPS discriminated COVID-19 patients who developed ARDS with an area under the curve (AUC) of 0.79 compared with original LIPS (AUC, 0.74; P<.001) with good calibration accuracy (Hosmer-Lemeshow P=.50). Despite different characteristics of the two cohorts, the c-LIPS's performance was comparable in the validation cohort of 5426 patients (15.9% ARDS), with an AUC of 0.74; and its discriminatory performance was significantly higher than the LIPS (AUC, 0.68; P<.001). The c-LIPS's performance in predicting the requirement for invasive mechanical ventilation in derivation and validation cohorts had an AUC of 0.74 and 0.72, respectively. CONCLUSION: In this large patient sample c-LIPS was successfully tailored to predict ARDS in COVID-19 patients.