Articles: intensive-care-units.
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Acta Anaesthesiol Scand · Nov 2024
ICURE: Intensive care unit (ICU) risk evaluation for 30-day mortality. Developing and evaluating a multivariable machine learning prediction model for patients admitted to the general ICU in Sweden.
A prediction model that estimates mortality at admission to the intensive care unit (ICU) is of potential benefit to both patients and society. Logistic regression models like Simplified Acute Physiology Score 3 (SAPS 3) and APACHE are the traditional ICU mortality prediction models. With the emergence of machine learning (machine learning) and artificial intelligence, new possibilities arise to create prediction models that have the potential to sharpen predictive accuracy and reduce the likelihood of misclassification in the prediction of 30-day mortality. ⋯ The ICURE prediction model predicts 30-day mortality rate at first-time ICU admission superiorly compared to the established SAPS 3 score.
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Acta Anaesthesiol Scand · Nov 2024
What would have made work in the COVID-19 ICU less demanding? A qualitative study from 13 Swedish COVID-19 ICUs.
The COVID-19 pandemic stretched Swedish intensive care unit (ICU) resources to an extent never experienced before, but even before the pandemic staffing was difficult and the number of staffed ICU beds was low. Studies have revealed high levels of COVID-19 ICU staff burn-out and fatigue, and as similar situations with high demands are likely to occur in the future a better understanding of resources that improve staff resilience is important. Using the job-demand resource theory as a framework, we explored ICU professionals' views on demands and resources when working in COVID-19 ICUs with the aim to highlight factors that increased the job resources. ⋯ To increase staff health and performance in a long-term crisis our results suggest; maintaining workplace leadership, scheduling work in advance and, when possible, schedule for recovery.
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Eur. J. Intern. Med. · Nov 2024
Prediction of plasma sodium changes in the acutely ill patients: the potential role of tissue sodium content.
Rapid correction of dysnatremias can result in neurological complications. Therefore, various formulas are available to predict changes in plasma sodium concentration ([Na+]) after treatment, but these have been shown to be inaccurate. This could be explained by sodium acumulation in skin and muscle tissue, which is not explicitly considered in these formulas. We assessed the association between clinical and biochemical factors related to tissue sodium accumulation and the discrepancy between predicted and measured plasma [Na+]. ⋯ In this ICU cohort, initial plasma [Na+], total body water, and plasma [Na+] changes, all factors that are related to tissue sodium accumulation, were associated with the inaccurateness of plasma [Na+] prediction.
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Delirium is a common complication in intensive care unit (ICU) patients. It can lead to various adverse events. In this study, we investigated the effectiveness of combining the use of the PREdiction of DELIRium (PRE-DELIRIC) model for delirium risk assessment and the use of a multicomponent care bundle for delirium assessment, prevention, and care in terms of reductions in the incidence of delirium among surgical ICU patients. ⋯ Our findings suggest that the PRE-DELIRIC-guided SMART/SmART care intervention is effective in preventing and managing delirium among surgical ICU patients.
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Although nurses are the primary clinicians in telemedicine intensive care units (tele-ICUs), their experiences remain underresearched. ⋯ Tele-ICU nurses play a transformative role in nursing practice. These findings have implications for nursing practice, education, health policy, enhancement of the current American Association of Critical-Care Nurses (AACN) Tele-ICU Nursing Practice Model, and future research on ICU telemedicine.