Impact of Early Reinitiation of Neuropsychiatric Medications on Agitation and Delirium in the Intensive Care Unit: A Retrospective Study.

BACKGROUND: Approximately 17% of intensive care unit (ICU) patients are prescribed at least 1 home neuropsychiatric medication (NPM). When abruptly discontinued, withdrawal symptoms may occur manifesting as agitation or delirium in the ICU setting. OBJECTIVE: To evaluate the impact of early reinitiation of NPMs. METHODS: This was a retrospective, observational cohort of adult ICU patients in a tertiary care hospital. Patients were included if admitted to the ICU and prescribed a NPM prior to arrival. Study groups were based on the timing of reinitiation of at least 50% of NPMs: ≤72 hours (early group) versus >72 hours (late group). RESULTS: The primary outcome was the proportion of patients with at least 1 agitation or delirium episode in the first 72 hours. Agitation and delirium were defined as at least 1 RASS assessment between +2 to +4 and a positive CAM-ICU assessment, respectively. A total of 300 patients were included, with 187 (62%) and 113 (38%) in the early and late groups, respectively. There was no difference in agitation or delirium (late 54 [48%] vs early 62 [33%]; adjusted odds ratio [aOR] = 1.5; 95% CI = 0.8-2.8; P = 0.193). Independent risk factors found to be associated with the primary outcome were restraints (aOR = 12.9; 95% CI = 6.9-24.0; P < 0.001) and benzodiazepines (BZDs; aOR = 2.0; 95% CI = 1.0-3.7; P = 0.038). CONCLUSIONS: After adjustment for baseline differences, there was no difference in agitation or delirium. Independent risk factors were restraint use and newly initiated BZDs.

Leveraging a health information exchange for analyses of COVID-19 outcomes including an example application using smoking history and mortality.

Understanding sociodemographic, behavioral, clinical, and laboratory risk factors in patients diagnosed with COVID-19 is critically important, and requires building large and diverse COVID-19 cohorts with both retrospective information and prospective follow-up. A large Health Information Exchange (HIE) in Southeast Texas, which assembles and shares electronic health information among providers to facilitate patient care, was leveraged to identify COVID-19 patients, create a cohort, and identify risk factors for both favorable and unfavorable outcomes. The initial sample consists of 8,874 COVID-19 patients ascertained from the pandemic's onset to June 12th, 2020 and was created for the analyses shown here. We gathered demographic, lifestyle, laboratory, and clinical data from patient's encounters across the healthcare system. Tobacco use history was examined as a potential risk factor for COVID-19 fatality along with age, gender, race/ethnicity, body mass index (BMI), and number of comorbidities. Of the 8,874 patients included in the cohort, 475 died from COVID-19. Of the 5,356 patients who had information on history of tobacco use, over 26% were current or former tobacco users. Multivariable logistic regression showed that the odds of COVID-19 fatality increased among those who were older (odds ratio = 1.07, 95% CI 1.06, 1.08), male (1.91, 95% CI 1.58, 2.31), and had a history of tobacco use (2.45, 95% CI 1.93, 3.11). History of tobacco use remained significantly associated (1.65, 95% CI 1.27, 2.13) with COVID-19 fatality after adjusting for age, gender, and race/ethnicity. This effort demonstrates the impact of having an HIE to rapidly identify a cohort, aggregate sociodemographic, behavioral, clinical and laboratory data across disparate healthcare providers electronic health record (HER) systems, and follow the cohort over time. These HIE capabilities enable clinical specialists and epidemiologists to conduct outcomes analyses during the current COVID-19 pandemic and beyond. Tobacco use appears to be an important risk factor for COVID-19 related death.