Patient Care in Rapid-expansion Intensive Care Units During the COVID-19 Pandemic Crisis

Jade I. Basem; Anna F. Roth; Robert S. White; Virginia E. Tangel; Silis Y. Jiang; Jacky M. Choi; Katherine L. Hoffman; Edward J. Schenck; Zachary A. Turnbull; Kane O. Pryor; Natalia S. Ivascu; Stavros G. Memtsoudis; Peter A. Goldstein

Disclosures

BMC Anesthesiol. 2022;22(209) 

In This Article

Methods

Study Design

After determination by the Weill Cornell Medicine IRB that this study was exempt from review (Category 4; Protocol 20–04,021,958), we performed a retrospective observational chart review of COVID-19 patients admitted to an ICU between March 3rd to May 19th, 2020. All patients included for analysis were adults (age ≥ 18 years) and had laboratory-confirmed SARS-CoV-2 infection (i.e., a positive polymerase chain reaction assay of nasal and pharyngeal swabs) admitted or transferred to NYP-WCMC for ICU level care. Patients who spent any amount of time in an Expansion-ICU comprised our exposure cohort, and patients who required intubation at any point during hospitalization but who were never triaged to an Expansion-ICU comprised our referent cohort (i.e., the traditional ICU patients).

Direct admission to an Expansion-ICU was overseen by a critical care intensivist and determined by overall ICU bed availability and the need to stagger admissions to maintain equitable distribution of workload. A handful of patients were selected to move to the Expansion-ICU to provide capacity in the traditional ICUs. These patients were all mechanically ventilated but did not require dialysis. Triage of patients was performed by a central coordinator, a role that rotated among ICU medical directors. The guidelines for placement were: 1) avoidance of multiple admission to the same unit in rapid succession (within 2–3 h) and 2) avoidance of patients requiring or anticipated to require renal replacement therapy as those nurses were not skilled in these areas and the operating rooms did not have easy access to the necessary facilities (water faucet for hemodialysis or a drain to dispose of dialysis effluent). If their needs were escalating, the patients would also be moved to standard ICUs.

Data Collection

Data collection was performed using automated patient data collection and manual chart review of our electronic medical records (EMRs; EPIC—Epic Systems Corporation, Madison, WI; and AllScripts—Allscripts Healthcare Solutions, Chicago, IL). A priori, we planned to examine the characteristics, hospital course, select laboratory results, ICU treatments and interventions, and COVID-19 specific interventions of patients whose care was provided in the Expansion-ICUs compared to critically ill COVID-19 patients who were never cared for in an Expansion-ICU. Various interventions for COVID-19 were retrospectively reviewed as new data were being published during that time for optimal treatments. COVID-specific interventions included use of hydroxychloroquine, remdesivir, tocilizumab, sarilumab, or other immunologics. Laboratory results upon admission to the hospital and maximum and minimum data values throughout the hospitalization were recorded in order to capture disease progression and fluctuations in lab values. All data collected were entered into a REDCap database, which is a secure, browser-based, electronic data capture system used in the design of medical research databases.[17]

Statistical Analyses

Descriptive statistics for all variables were calculated for the entire patient population and were compared by ICU type referent vs. Expansion-ICU). Time to intubation, hospital length of stay (LoS; in days), ICU LoS (in days), and management within the ICU were compared within ICU types and between groups of patients discharged from the hospital (either to home or subacute rehab) and patients who died during their hospitalization. Patient age (categorized as: 18–44, 45–64, 65–74, 75 + years) was additionally analysed as it differed across ICU types for each disposition status. Continuous variables were compared using the Wilcoxon rank-sum test, and categorical ones were compared using the Chi-squared test or Fisher's exact test depending on expected cell frequencies. Results are presented as N (percentage) or median [interquartile range] for nonparametric continuous variables. Results reported for each measure are based on calculations of available (i.e., non-missing) data; percentages reported are based denominators of counts of non-missing values for the given category. P-values were calculated for each test and were subsequently adjusted for the false discovery rate (q-values) based on the distribution of p-values within each table. All tests were two-sided, and significance was evaluated at an alpha level of q ≤ 0.05. Analyses were performed using R version 4.0.1 (R Foundation for Statistical Computing, Vienna, Austria; https://www.R-project.org).

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