Cognitive Assessment of Patients with COVID-19 Disease After Their Intensive Care Unit Stay

Cardiac surgery patients infrequently mobilize during their hospital stay. It is unclear for patients why mobilization is important, and exact progress of mobilization activities is not available. The aim of this study was to select and evaluate accelerometers for objective qualification of in-hospital mobilization after cardiac surgery. Six static and dynamic patient activities were defined to measure patient mobilization during the postoperative hospital stay. Device requirements were formulated, and the available devices reviewed. A triaxial accelerometer (AX3, Axivity) was selected for a clinical pilot in a heart surgery ward and placed on both the upper arm and upper leg. An artificial neural network algorithm was applied to classify lying in bed, sitting in a chair, standing, walking, cycling on an exercise bike, and walking the stairs. The primary endpoint was the daily amount of each activity performed between 7 a.m. and 11 p.m. The secondary endpoints were length of intensive care unit stay and surgical ward stay. A subgroup analysis for male and female patients was planned. In total, 29 patients were classified after cardiac surgery with an intensive care unit stay of 1 (1 to 2) night and surgical ward stay of 5 (3 to 6) nights. Patients spent 41 (20 to 62) min less time in bed for each consecutive hospital day, as determined by a mixed-model analysis (p < 0.001). Standing, walking, and walking the stairs increased during the hospital stay. No differences between men (n = 22) and women (n = 7) were observed for all endpoints in this study. The approach presented in this study is applicable for measuring all six activities and for monitoring postoperative recovery of cardiac surgery patients. A next step is to provide feedback to patients and healthcare professionals, to speed up recovery.

Download Full-text

Carbapenem-resistant Enterobacteriaceae carriage risk for parameterization of a regional healthcare network agent-based model

Infection Control and Hospital Epidemiology ◽

10.1017/ice.2020.667 ◽

2020 ◽

Vol 41 (S1) ◽

pp. s148-s149

Author(s):

Sarah Rhea ◽

Lei Li ◽

Pooja Iyer ◽

Lauren DiBiase ◽

Kasey Jones ◽

...

Keyword(s):

Intensive Care Unit ◽

Intensive Care ◽

Length Of Stay ◽

Intensive Care Unit Stay ◽

Agent Based ◽

Healthcare Network ◽

Transmission Parameters ◽

Carbapenem Resistant ◽

Comorbidity Index ◽

Systemic Antibiotics

Background: Carbapenem-resistant Enterobacteriaceae (CRE) are increasingly common in the United States and have the potential to spread widely across healthcare networks. Only a fraction of patients with CRE carriage (ie, infection or colonization) are identified by clinical cultures. Interventions to reduce CRE transmission can be explored with agent-based models (ABMs) comprised of unique agents (eg, patients) represented by a synthetic population or model-generated representation of the population. We used electronic health record data to determine CRE carriage risk, and we discuss how these results can inform CRE transmission parameters for hospitalized agents in a regional healthcare network ABM. Methods: We reviewed the laboratory data of patients admitted during July 1, 2016−June 30, 2017, to any of 7 short-term acute-care hospitals of a regional healthcare network in North Carolina (N = 118,022 admissions) to find clinically detected cases of CRE carriage. A case was defined as the first occurrence of Enterobacter spp, Escherichia coli, or Klebsiella spp resistant to any carbapenem isolated from a clinical specimen in an admitted patient. We used Poisson regression to estimate clinically detected CRE carriage risk according to variables common to data from both the electronic health records and the ABM synthetic population, including patient demographics, systemic antibiotic administration, intensive care unit stay, comorbidities, length of stay, and admitting hospital size. Results: We identified 58 (0.05%) cases of CRE carriage among all admissions. Among these cases, 30 (52%) were ≥65 years of age and 37 (64%) were female. During their admission, 47 cases (81%) were administered systemic antibiotics and 18 cases (31%) had an intensive care unit stay. Patients administered systemic antibiotics and those with an intensive care unit stay had CRE carriage risk 6.5 times (95% CI, 3.4–12.5) and 4.9 times (95% CI, 2.8–8.5) higher, respectively, than patients without these exposures (Fig. 1). Patients ≥50 years of age and those with a higher Elixhauser comorbidity index score and with longer length of stay also had increased CRE carriage risk. Conclusions: Among admissions in our dataset, CRE carriage risk was associated with systemic antibiotic exposure, intensive care unit stay, higher Elixhauser comorbidity index score, and longer length of stay. We will use these risk estimates in the ABM to inform agents’ CRE carriage status upon hospital admission and the CRE transmission parameters for short-term acute-care hospitals. We will explore CRE transmission interventions in the parameterized regional healthcare network ABM and assess the impact of CRE carriage underestimation.Funding: This work was supported by Centers for Disease Control and Prevention (CDC) Cooperative Agreement number U01CK000527. The conclusions, findings, and opinions expressed do not necessarily reflect the official position of CDC.Disclosures: None

Download Full-text