Articles: critical-illness.
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Patients requiring emergent endotracheal intubation are at higher risk of post-intubation hypotension due to altered physiology in critical illness. Post-intubation hypotension increases mortality and hospital length of stay, however, the impact of vasopressors on its incidence and outcomes is not known. This scoping review identified studies reporting hemodynamic data in patients undergoing emergent intubation to provide a literature overview on post-intubation hypotension in cohorts that did and did not receive vasopressors. ⋯ Patients requiring emergent intubation have a high rate of post-intubation hypotension and in-hospital mortality. While there is an intuitive rationale for the use of vasopressors during emergent intubation, current evidence is limited to support a definitive change in clinical practice at this time.
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Acta Anaesthesiol Scand · Nov 2024
Observational StudyHealth status and quality of life before critical illness: Northern Finland Birth Cohort 1966 study.
Previous findings support the claim intensive care unit (ICU) patients have a higher rate of comorbidities and reduction of health- and functional status compared with the normal population. ⋯ In this study examining previously un-hospitalized patients, the main factors associated with future critical illness were neurological comorbidities, malignancy, alcohol misuse, smoking, low maximum muscle strength, and less frequent physical exercise compared with those with hospitalization not requiring ICU admission.
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Observational Study
Generalized additive mixed model to evaluate the association between ventilatory ratio and mortality in patients: A retrospective cohort study.
Previous studies have indicated that a higher ventilatory ratio (VR) is associated with mortality. However, it is unknown whether dynamic changes in VR over time affect the prognosis of critically ill patients. This study aims to investigate the significance of VR during the progression of the disease in critically ill patients. ⋯ The generalized additive mixed model results highlighted that the difference in VR between survivors and non-survivors increased by an average of 0.01 per day after adjusting for several covariates. In conclusion, VR dynamically mirrors pathophysiological changes in critically ill patients and its escalation is linked to higher mortality rates. Monitoring VR's dynamic shifts might offer more immediate prognostic information, thus aiding in timely interventions and risk stratification.
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Multicenter Study
Interpretable machine learning model for new-onset atrial fibrillation prediction in critically ill patients: a multi-center study.
New-onset atrial fibrillation (NOAF) is the most common arrhythmia in critically ill patients admitted to intensive care and is associated with poor prognosis and disease burden. Identifying high-risk individuals early is crucial. This study aims to create and validate a NOAF prediction model for critically ill patients using machine learning (ML). ⋯ We developed a ML model to predict the risk of NOAF in critically ill patients without cardiac surgery and validated its potential as a clinically reliable tool. SHAP improves the interpretability of the model, enables clinicians to better understand the causes of NOAF, helps clinicians to prevent it in advance and improves patient outcomes.