Highlights
- •A residual clinical instability and functional deficit is fully expected for patients discharge from ICU.
- •Patients at high risk for adverse events can be effectively identified before ICU discharge based on routinely collected data.
- •The level of acuity and nursing complexity can independently predict the risk of adverse events.
- •Using such information to support the discharge decision-making could prevent adverse events and improve patient's outcome.
Abstract
Background
Patients discharged from intensive care units (ICUs) are at risk for adverse events
(AEs). Establishing safe discharge criteria is challenging. No available criteria
consider nursing complexity among risk factors.
Objectives
To investigate whether nursing complexity upon ICU discharge is an independent predictor
for AEs.
Methods
Prospective observational study. The Patient Acuity and Complexity Score (PACS) was
developed to measure nursing complexity. Its predictive power for AEs was tested using
multivariate regression analysis.
Results
The final regression model showed a very-good discrimination power (AUC 0.881; p<0.001) for identifying patients who experienced AEs. Age, ICU admission reason, PACS,
cough strength, PaCO2, serum creatinine and sodium, and transfer to Internal Medicine showed to be predictive
of AEs. Exceeding the identified PACS threshold increased by 3.3 times the AEs risk.
Conclusions
The level of nursing complexity independently predicts AEs risk and should be considered
in establishing patient's eligibility for a safe ICU discharge.
Keywords
Abbreviations:
ADL (Activities of Daily Living), APACHE II (Acute Physiology And Chronic Health Evaluation), ATP (adenosine triphosphate), AUC (area under receiver operating characteristics curve), AVPU (alert, verbal, pain, unresponsive), CI (confidence interval), CVI (content validity index), FiO2 (fraction of inspired oxygen), ICU (intensive care units), IQR (interquartile range), NEWS (National Early Warning Score), OR (odds ratio), PaCO2 (partial pressure of arterial carbon dioxide), PACS (Patient Acuity and Complexity Score), PaO2 (partial pressure of oxygen)To read this article in full you will need to make a payment
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Article info
Publication history
Published online: February 14, 2020
Accepted:
February 3,
2020
Received in revised form:
January 24,
2020
Received:
October 16,
2019
Identification
Copyright
© 2020 Elsevier Inc. All rights reserved.
