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Is my patient ready for a safe transfer to a lower-intensity care setting? Nursing complexity as an independent predictor of adverse events risk after ICU discharge

Published:February 14, 2020DOI:https://doi.org/10.1016/j.hrtlng.2020.02.003

      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)
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