Patient experiences of an intensive care Liaison Nurse support service.

OBJECTIVES: To illuminate patients' experiences of being a part of an liaison nurse support service focused on supporting recently transferred intensive care unit patients. RESEARCH METHODOLOGY/DESIGN: A qualitative inductive descriptive design including in-depth interviews was chosen. SETTING: A project including an liaison nurse support service-intervention was undertaken during a 16-week period at a University hospital in Sweden. The liaison nurse support service was available Monday-Friday 10 am - 6 pm and nurses visited the patient 1-4 times after transfer to the ward. MAIN OUTCOME MEASURES: Of the 109 patients who were visited by the liaison nurse support service, 14 agreed to be interviewed about their experiences of the transfer. Data was analysed by inductive content analysis. FINDINGS: One overall theme, An advocate in a vulnerable situation emerged from the data. Four subthemes were identified: Ensures transfer of information between the intensive care unit and the general ward, Makes the circumstances understandable and coordinates between the care levels and Offers emotional support and stability in an uncertain situation. CONCLUSION: The liaison nurse support service contributed to ensuring accurate transfer of information, solved problems when the patient themselves did not have control or strength and provided emotional support.

Patient outcomes following transfer between intensive care units during the COVID-19 pandemic.

Transferring critically ill patients between intensive care units (ICU) is often required in the UK, particularly during the COVID-19 pandemic. However, there is a paucity of data examining clinical outcomes following transfer of patients with COVID-19 and whether this strategy affects their acute physiology or outcome. We investigated all transfers of critically ill patients with COVID-19 between three different hospital ICUs, between March 2020 and March 2021. We focused on inter-hospital ICU transfers (those patients transferred between ICUs from different hospitals) and compared this cohort with intra-hospital ICU transfers (patients moved between different ICUs within the same hospital). A total of 507 transfers were assessed, of which 137 met the inclusion criteria. Forty-five patients underwent inter-hospital transfers compared with 92 intra-hospital transfers. There was no significant change in median compliance 6 h pre-transfer, immediately post-transfer and 24 h post-transfer in patients who underwent either intra-hospital or inter-hospital transfers. For inter-hospital transfers, there was an initial drop in median PaO2 /FI O2 ratio: from median (IQR [range]) 25.1 (17.8-33.7 [12.1-78.0]) kPa 6 h pre-transfer to 19.5 (14.6-28.9 [9.8-52.0]) kPa immediately post-transfer (p < 0.05). However, this had resolved at 24 h post-transfer: 25.4 (16.2-32.9 [9.4-51.9]) kPa. For intra-hospital transfers, there was no significant change in PaO2 /FI O2 ratio. We also found no meaningful difference in pH; PaCO2 ;, base excess; bicarbonate; or norepinephrine requirements. Our data demonstrate that patients with COVID-19 undergoing mechanical ventilation of the lungs may have short-term physiological deterioration when transferred between nearby hospitals but this resolves within 24 h. This finding is relevant to the UK critical care strategy in the face of unprecedented demand during the COVID-19 pandemic.

Risk factors for transfer from Respiratory Intermediate Care Unit to Intensive Care Unit in COVID-19.

BACKGROUND: Patients hospitalized for COVID-19-related pneumonia often need several degrees of ventilatory support, which are performed between Respiratory Intermediate Care Units (RICUs) and Intensive Care Units (ICUs), and which depend on the severity of acute respiratory distress syndrome. There is no firm consensus on transfer predictors from the RICU to the ICU. METHODS: In this retrospective observational single center study, we evaluated 96 COVID-19 patients referred to the RICU for acute respiratory failure (ARF) according to their transferal to the ICU or their stay at the RICU. We compared demographic data, baseline laboratory profile, and final clinical outcomes to identify early risk factors for transfer. RESULTS: The best predictors for transfer to the ICU were elevated C-reactive protein and lymphopenia. The mortality rate was lower in the RICU than in the ICU, where transferred patients who died were mostly younger men and with less comorbidities than those in the RICU. CONCLUSIONS: Few inflammatory markers can predict the need for transfer from the RICU to the ICU. Due to the ongoing COVID-19 pandemic, we urge better clinical stratification by early and meaningful profiles in patients admitted to the RICU who are at risk of transferal to the ICU.

Simple nomogram based on initial laboratory data for predicting the probability of ICU transfer of COVID-19 patients: Multicenter retrospective study.

This retrospective, multicenter study investigated the risk factors associated with intensive care unit (ICU) admission and transfer in 461 adult patients with confirmed coronavirus disease 2019 (COVID-19) hospitalized from 22 January to 14 March 2020 in Hunan, China. Outcomes of ICU and non-ICU patients were compared, and a simple nomogram for predicting the probability of ICU transfer after hospital admission was developed based on initial laboratory data using a Cox proportional hazards regression model. Differences in laboratory indices were observed between patients admitted to the ICU and those who were not admitted. Several independent predictors of ICU transfer in COVID-19 patients were identified including older age (≥65 years) (hazard ratio [HR] = 4.02), hypertension (HR = 2.65), neutrophil count (HR = 1.11), procalcitonin level (HR = 3.67), prothrombin time (HR = 1.28), and D-dimer level (HR = 1.25). The lymphocyte count and albumin level were negatively associated with mortality (HR = 0.08 and 0.86, respectively). The developed model provides a means for identifying, at hospital admission, the subset of patients with COVID-19 who are at high risk of progression and would require transfer to the ICU within 3 and 7 days after hospitalization. This method of early patient triage allows a more effective allocation of limited medical resources.

D-Dimer Level and Neutrophils Count as Predictive and Prognostic Factors of Pulmonary Embolism in Severe Non-ICU COVID-19 Patients.

The incidence of pulmonary embolism (PE) is high during severe Coronavirus Disease 2019 (COVID-19). We aimed to identify predictive and prognostic factors of PE in non-ICU hospitalized COVID-19 patients. In the retrospective multicenter observational CLOTVID cohort, we enrolled patients with confirmed RT-PCR COVID-19 who were hospitalized in a medicine ward and also underwent a CT pulmonary angiography for a PE suspicion. Baseline data, laboratory biomarkers, treatments, and outcomes were collected. Predictive and prognostics factors of PE were identified by using logistic multivariate and by Cox regression models, respectively. A total of 174 patients were enrolled, among whom 86 (median [IQR] age of 66 years [55-77]) had post-admission PE suspicion, with 30/86 (34.9%) PE being confirmed. PE occurrence was independently associated with the lack of long-term anticoagulation or thromboprophylaxis (OR [95%CI], 72.3 [3.6-4384.8]) D-dimers ≥ 2000 ng/mL (26.3 [4.1-537.8]) and neutrophils ≥ 7.0 G/L (5.8 [1.4-29.5]). The presence of these two biomarkers was associated with a higher risk of PE (p = 0.0002) and death or ICU transfer (HR [95%CI], 12.9 [2.5-67.8], p < 0.01). In hospitalized non-ICU severe COVID-19 patients with clinical PE suspicion, the lack of anticoagulation, D-dimers ≥ 2000 ng/mL, neutrophils ≥ 7.0 G/L, and these two biomarkers combined might be useful predictive markers of PE and prognosis, respectively.