Does the implementation of a novel intensive care discharge risk score and nurse-led inpatient review tool improve outcome? A prospective cohort study in two intensive care units in the UK

Direct Discharge from the Critical Care Resuscitation Unit: Results from a Longitudinal Assessment

Background

The critical care resuscitation unit (CCRU) facilitates interhospital transfer (IHT) of critically ill patients for immediate interventions. Due to these patients' acuity, it is uncommon for patients to be directly discharged home from this unit, but it does happen on occasion. Since there is no literature regarding outcomes of patients being discharged from a resuscitation unit, our study investigated these patients' outcome at greater than 12 months after being discharged directly from the CCRU.

Methods

We performed a retrospective cohort study of all adult patients directly discharged from the CCRU between January 01, 2017, and December 31, 2020. The primary outcome was number of ED visits or hospitalizations within 6 months. Secondary outcomes were number of ED visits or hospitalizations within 6, 12, and >12 months from CCRU discharge.

Results

We analyzed 145 patients' records. Mean age was 56 (standard deviation [SD] ± 19), with a majority being male (72%) and Caucasian (58%). The most common discharge destination was home (139 patients, 96% of total subjects) versus hospice (2%) or nursing facilities (2%). Most patients (55%) did not have any hospital revisits within the first 6 months of discharge, while 31% had 1-2 revisits, and 14% had ≥3 revisits. The most common discharge diagnoses were soft tissue infection (16.5%), aortic dissection (14%), and stroke (11%). Factors which were associated with a greater likelihood of any return hospital visit within 6 months receiving mechanical ventilation during CCRU stay (coefficient -2.23, 95% CI 0.01-0.87, P=0.036), while high hemoglobin on CCRU discharge was associated with no ED revisit (coeff. 0.42, 95% CI 1.15-2.06, P=0.004).

Conclusions

Most patients who were discharged from the CCRU did not require any hospital revisits in the first 6 months. Requiring mechanical ventilation and having soft tissue infection were associated with high unplanned hospital revisits following discharge. Further research is needed to validate these findings.

Nursing Implications of the Updated 2021 Surviving Sepsis Campaign Guidelines

Sepsis is a life-threatening illness that affects millions of people worldwide. Early recognition and timely treatment are essential for decreasing mortality from sepsis. The Surviving Sepsis Campaign: International Guidelines for Management of Sepsis and Septic Shock 2021, the fifth iteration of the guidelines, was released in October 2021 and includes 93 recommendations for the management of sepsis. The evidence-based guidelines include recommendations and rationales for screening and early treatment, initial resuscitation, mean arterial pressure targets, admission to intensive care, management of infection, hemodynamic monitoring, ventilation, and additional therapies. A new section addresses long-term outcomes and goals of care. This article presents several recommendations, changes, and updates in the 2021 guidelines and highlights the important contributions nurses have in delivering timely and evidence-based care to patients with sepsis. Recommendations may be for or against an intervention, according to the evidence. Although many recommendations are unchanged, several new recommendations directly affect nursing care and may require specialized training (eg, venovenous extracorporeal membrane oxygenation). The newest section, long-term outcomes and goals of care, is aimed at using available resources to provide care that is aligned with the patient and the patient's family through goals-of-care discussions and shared decision-making. Interventions aimed at improving recovery across the continuum of care should include attention to long-term outcomes. Nurses are essential in identifying patients with sepsis, administering and assessing response to treatment, supporting the patient and family, and limiting sequelae from sepsis. This article highlights the 2021 recommendations that influence nursing care for patients with sepsis.

Temperature Profile and Adverse Outcomes After Discharge From the Intensive Care Unit

BACKGROUND

A predictive model that uses the rhythmicity of core body temperature (CBT) could be an easily accessible clinical tool to ultimately improve outcomes among critically ill patients.

OBJECTIVES

To assess the relation between the 24-hour CBT profile (CBT-24) before intensive care unit (ICU) discharge and clinical events in the step-down unit within 7 days of ICU discharge.

METHODS

This retrospective cohort study in a tertiary ICU at a single center included adult patients requiring acute invasive ventilation for more than 48 hours and assessed major clinical adverse events (MCAEs) and rapid response system activations (RRSAs) within 7 days of ICU discharge (MCAE-7 and RRSA-7, respectively).

RESULTS

The 291 enrolled patients had a median mechanical ventilation duration of 139 hours (IQR, 50-862 hours) and at admission had a median Acute Physiology and Chronic Health Evaluation II score of 22 (IQR, 7-42). At least 1 MCAE or RRSA occurred in 64% and 22% of patients, respectively. Independent predictors of an MCAE-7 were absence of CBT-24 rhythmicity (odds ratio, 1.78 [95% CI, 1.07-2.98]; P = .03), Sequential Organ Failure Assessment score at ICU discharge (1.10 [1.00-1.21]; P = .05), male sex (1.72 [1.04-2.86]; P = .04), age (1.02 [1.00-1.04]; P = .02), and Charlson Comorbidity Index (0.87 [0.76-0.99]; P = .03). Age (1.03 [1.01-1.05]; P = .006), sepsis at ICU admission (2.02 [1.13-3.63]; P = .02), and Charlson Comorbidity Index (1.18 [1.02-1.36]; P = .02) were independent predictors of an RRSA-7.

CONCLUSIONS

Use of CBT-24 rhythmicity can assist in stratifying a patient's risk of subsequent deterioration during general care within 7 days of ICU discharge.

Explainable Machine Learning on AmsterdamUMCdb for ICU Discharge Decision Support: Uniting Intensivists and Data Scientists

Unexpected ICU readmission is associated with longer length of stay and increased mortality. To prevent ICU readmission and death after ICU discharge, our team of intensivists and data scientists aimed to use AmsterdamUMCdb to develop an explainable machine learning–based real-time bedside decision support tool.