Title

Early hemodynamic assessment using NICOM in patients at risk of developing Sepsis immediately after emergency department triage

Affiliations

Advocate Sherman Hospital

Abstract

BACKGROUND: One factor leading to the high mortality rate seen in sepsis is the subtle, dynamic nature of the disease, which can lead to delayed detection and under-resuscitation. This study investigated whether serial hemodynamic parameters obtained from a non-invasive cardiac output monitor (NICOM) predicts disease severity in patients at risk for sepsis.

METHODS: Prospective clinical trial of the NICOM device in a convenience sample of adult ED patients at risk for sepsis who did not have obvious organ dysfunction at the time of triage. Hemodynamic data were collected immediately following triage and 2 hours after initial measurement and compared in two outcome groupings: (1) admitted vs. dehydrated, febrile, hypovolemicdischarged patients; (2) infectious vs. non-infectious sources. Receiver operator characteristic (ROC) curves were calculated to determine whether the NICOM values predict hospital admission better than a serum lactate.

RESULTS: 50 patients were enrolled, 32 (64 %) were admitted to the hospital. Mean age was 49.5 (± 16.5) years and 62 % were female. There were no significant associations between changes in hemodynamic variables and patient disposition from the ED or diagnosis of infection. Lactate was significantly higher in admitted patients and those with infection (p = 0.01, p = 0.01 respectively). The area under the ROC [95 % Confidence Intervals] for lactate was 0.83 [0.64-0.92] compared to 0.59 [0.41-0.73] for cardiac output (CO), 0.68 [0.49-0.80] for cardiac index (CI), and 0.63 [0.36-0.80] for heart rate (HR) for predicting hospital admission.

CONCLUSIONS: CO and CI, obtained at two separate time points, do not help with early disease severity differentiation of patients at risk for severe sepsis. Although mean HR was higher in those patients who were admitted, a serum lactate still served as a better predictor of patient admission from the ED.

Document Type

Article

PubMed ID

33509242

DOI

10.1186/s13049-021-00833-1

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