ABSTRACT
INTRODUCTION: ICU-acquired delirium results in increased LOS, duration of mechanical ventilation, and mortality. Patients with COVID are at increased risk. Current literature suggests that delirium without coma occurs in at least about 30 % of COVID patients admitted to ICU. In our ICU we use an EPIC EMR-based daily ICU checklist with ABCDEF bundle during our rounds and utilized virtual ICU during the daytime in addition to the nights with peak surges. With our study, we wanted to evaluate the incidence of Delirium during our COVID year of 2021 and its relation to Mortality rate and ICU Length of stay (LOS). METHOD(S): A retrospective evaluation of patients admitted to Houston Methodist Baytown ICU from January to December 2021. Patients with covid positive were included. Data were obtained from the EPIC and ICU dashboard. Compliance with the ABCDEF ICU checklist was reviewed by auditing 20 patient charts per month. Delirium screening compliance was evaluated on AM and PM shifts for all ICU patients. Hospital ICU acquired delirium % was defined as all patients discharged from the ICU unit in that month that didn't have a positive CAM-ICU in the first 48 hrs. and then had a positive CAM-ICU after 48 hrs. in the ICU. ICU Mortality rate is defined as the percentage of patients with ICU stays who expired during ICU stay. Descriptive statistics and linear regression were used to compare and correlate. RESULT(S): In 2021, we had 377 ICU patients with COVID positive, an Average CMI of 4.986, and a LOS index of 1.24. Compliance with the daily ABCDEF ICU Checklist was 98%. Compliance to am screening was 89.41% vs. pm screening 90.56%. Mean Incidence of ICU acquired Delirium in COVID patients was only 7.14 % (2.77- 15.22) with peaks occurring during COVID surges. Linear regression analysis predicted a strong direct relationship between Delirium % and ICU Mortality rate (P< 0.05), and ICU Length of Stay(P< 0.05). CONCLUSION(S): Our data from 2021 shows Delirium % that is significantly less than the incidence. The lower % might have been from continuing to adhere to the ABCDEF bundle, utilization of the ICU checklist, and effective use of virtual ICU. Hospital ICU acquired delirium % correlated with ICU mortality and ICU length of stay. Hence, it is important to continue to focus on ways to decrease ICU delirium.
ABSTRACT
RATIONALE: Pre-pandemic, ARDS accounted for approximately 10% of all ICU admissions and 25% of ICU patients requiring mechanical ventilation (MV). Surges in severe Covid-19 cases have increased the number of ICU patients requiring MV for ARDS. It has been estimated that only 60% of ARDS cases are identified at any time during the clinical course, and only 34% of ARDS cases are identified when initial criteria are met. Additionally, it is estimated that only 60% of ARDS patients are managed with evidence based MV settings, including low tidal volume ventilation (LTV) of <6 cc/kg ideal body weight, plateau pressure <30 cm H2O, and low driving pressure <15 cm H2O. Adherence to lung protective ventilation strategies have been linked to decreased mortality in ARDS. We implemented a clinical decision support tool (CDST) to aid clinicians in the early recognition of ARDS and aid in implementation of lung protective ventilation strategies. METHODS: From March 2020 to March 2021 we used medical informatics (SickbayTM) to identify ICU patients requiring MV that met criteria for ARDS based on the Berlin Criteria. We monitored documentation of ARDS, MV tidal volume as cc/kg ideal body weight, plateau pressure, driving pressure, MV settings, arterial blood gas values (ABG), and PaO2 / FiO2. From March 2021 to October 2021, we implemented a CDST outlining above variables to aide ICU clinicians in 1) recognition of ARDS and 2) utilization of MV and ABG data to make evidence based MV changes. Lung protective strategies were automatically recorded every two hours via informatics software. The results were analyzed using a chi-squared test. RESULTS: There were 207 patients reviewed preimplementation of the CDST and 88 patients reviewed during implementation of the CDST. Implementation of the CDST resulted in improved detection and documentation of ARDS (63.8% vs 100%, p=.0001), improved adherence to LTV (53.9% vs 64.9%, p = .0005), and improved adherence to low plateau pressure (67.7% vs 71.8%, p=.20). There was a decrease in adherence to low driving pressure (36.6% vs 23.9%, p=.0003).CONCLUSIONS: Implementation of CDST is a low-cost, efficacious measure to aide clinicians in the detection and documentation of ARDS. Using CDST was associated with improved adherence to LTV and low plateau pressure MV strategies. We hypothesize that difficulty with adherence to low driving pressure is related to the respiratory mechanics of Covid-19 ARDS differing from other forms of ARDS. A validation cohort is needed to further support our findings.