Active clinical trials for "Critical Illness"

Study objectives: To determine whether, in critically ill patients with Acute Kidney Injury requiring renal replacement therapy (AKI-RRT), randomization to receive intravenous hyperoncotic albumin 20-25% (100 mL X two doses) compared to control/placebo normal saline boluses (100 mL X two doses) given during RRT sessions, leads to: An increase in organ support-free days (primary outcome) at 28 days following initiation of RRT; and An increase in RRT-free days (principal secondary outcome) at 28 days following initiation of RRT.

Many studies have pointed out that patients with vitamin D deficiency have a longer stay in the intensive care unit and a poor prognosis. The investigators' previous multi-center prospective observational study in Taiwan reveals that the prevalence of vitamin D deficiency in critically ill patients in northern Taiwan is 59%, and the prevalence of severe vitamin D deficiency is 18%. The investigators used the data of that observational study to train a predictive model for predicting vitamin D deficiency. In addition, the association between vitamin D and the immune regulation of critically ill patients in Taiwan has not been investigated. This study aims primarily to validate the performance of the prediction model of vitamin D deficiency. Moreover, this study will investigate the association between vitamin D level and inflammatory cytokine levels. This multi-center prospective observational study will enroll critically ill patients admitted to intensive care units (ICUs) less than 28 days. After inform consent, blood will be drawn for examination of vitamin D, interleukin 6, and interleukin 10 levels. The main diagnosis of ICU admission, past medical history, vital signs within 24 hours of admission, disease severity, and laboratory data will be recorded. The predictive model will use the required parameters to predict the patient's risk of vitamin D deficiency and vitamin D severe deficiency.

Important information related to the visual assessment of patients, such as facial expressions, head and extremity movements, posture, and mobility are captured sporadically by overburdened nurses, or are not captured at all. Consequently, these important visual cues, although associated with critical indices such as physical functioning, pain, delirious state, and impending clinical deterioration, often cannot be incorporated into clinical status. The overall objectives of this project are to sense, quantify, and communicate patients' clinical conditions in an autonomous and precise manner, and develop a pervasive intelligent sensing system that combines deep learning algorithms with continuous data from inertial, color, and depth image sensors for autonomous visual assessment of critically ill patients. The central hypothesis is that deep learning models will be superior to existing acuity clinical scores by predicting acuity in a dynamic, precise, and interpretable manner, using autonomous assessment of pain, emotional distress, and physical function, together with clinical and physiologic data.

Ventilator-induced lung injury is associated with increased morbidity and mortality. Despite intense efforts in basic and clinical research, an individualized ventilation strategy for critically ill patients remains a major challenge. However, an individualized mechanical ventilation approach remains a challenging task: A multitude of factors, e.g., lab values, vitals, comorbidities, disease progression, and other clinical data must be taken into consideration when choosing a patient's specific optimal ventilation regime. The aim of this work was to evaluate the machine learning ventilator decision system, which is able to suggest a dynamically optimized mechanical ventilation regime for critically-ill patients. Compare with standard controlled ventilation, to test whether the clinical application of the machine learning ventilator decision system reduces mechanical ventilation time and mortality.

ECMO is associated with significant costs, risks and requires specialist training and expertise. EXCEL is a novel, high-quality, detailed prospective registry of patients requiring ECMO in Australia and New Zealand. The registry provides information on patient selection, complications, costs and patient reported outcome measures. EXCEL uses the Theoretical Domains Framework to identify evidence-practice gaps and explore barriers and enablers to tailor implementation of evidence

Introduction. Initiation of acute kidney replacement therapy (KRT) is common in critically ill adults admitted to the intensive care unit (ICU), and is associated with increased morbidity and mortality. KRT has been linked to poor neurocognitive outcomes, leading to a reduced quality of life, as well as increased utilization of healthcare resources. Adults initiated on dialysis in the ICU may be particularly at risk of neurocognitive impairment, as survivors of critical illness are already predisposed to developing cerebrovascular disease and cognitive dysfunction over the long-term relative to healthy controls. Regional cerebral oxygen saturation (rSO2) may provide a critical early marker of long-term neurocognitive impairment in patients in this population. The INCOGNITO-AKI study aims to understand cerebral oxygenation in patients undergoing KRT, either continuous or intermittent, in the ICU. These findings will be correlated with long-term cognitive and functional outcomes, as well as structural brain pathology. Methods and analysis. 108 patients scheduled to undergo treatment for acute kidney injury with KRT in the Kingston Health Sciences Centre ICU will be recruited into this prospective observational study. Enrolled patients will be assessed with intradialytic cerebral oximetry using near infrared spectroscopy (NIRS). Delirium will be assessed daily with the Confusion Assessment Method-Intensive Care Unit (CAM-ICU) and delirium severity quantified as cumulative CAM-ICU-7 scores. Neurocognitive impairment will be assessed at 3- and 12-months after hospital discharge using the Kinarm and Repeatable Battery for the Assessment of Neuropsychological Status (RBANS). Structural brain pathology on MRI will also be measured at the same timepoints. Driving safety, adverse events, and medication adherence will be assessed at 12-months to evaluate the impact of neurocognitive impairment on functional outcomes. Ethics and dissemination. This study has been approved by the Queen's University Health Sciences and Affiliated Teaching Hospitals Research Ethics Board (Approval number: DMED-2424-20). Results will be presented at critical care scientific conferences and a lay summary will be provided to patients and families in their preferred format.

Tracheal intubation (TI) is associated with a high risk of adverse events in critically ill patients and peri-intubation hemodynamic collapse is the most commonly observed. The primary aim of the PREVENTION trial is to compare the effect of the pre-emptive use of noradrenaline versus no peri-intubation use of noradrenaline on incidence of cardiovascular collapse following TI in adult critically ill patients. Patients with absolute indication or contraindication to vasopressor support will be excluded from this trial. Patients will be randomized 1:1 to a continuous infusion of noradrenaline started before induction titrated according to baseline mean arterial pressure. The primary outcome will be the incidence of cardiovascular collapse. Secondary outcomes will include lowest systolic blood pressure and cardiac arrest within 30 minutes from intubation.

Holter Monitoring is a way to continuously check the electrical activity of the heart . Continuous ECG recording show to be one of the most effective noninvasive clinical tools in the diagnosis of cardiac symptoms prognostic assessment and in the evaluation of many cardiac therapeutic intervention. The clinical utility of ambulatory ECG lies in its ability to examine continuously a patient over an extended period of time, permitting patient ambulatory activity and facilitating the diurnal electrocardiographic examination of a patient in a changing environmental conditions (both physical and psychological) .

Older adults are at risk for ICU-acquired cognitive decline discernible from clinical, biological, and imaging- related changes in the brain following delirium and critical illness. Our Driving Rehabilitation and Innovation for Evaluating Risk in Post Intensive Care Unit Survivors (DRIVE-PICS) application seeks to implement in-vehicle kinematic driving data with neurocognitive assessments for essential formative work to develop data-based insights into driving behaviors. DRIVE-PICS is designed to contribute to a critical gap in health promotion to develop an evidence-based, in-vehicle driving assessment system to provide actionable driving safety data and rehabilitation strategies tailored to older ICU survivors, the participants' care partners, and clinicians.

The intensive care unit (ICU) is recognizably detrimental to sleep and circadian health, and critical survivors frequently report the presence of alterations in this regard after hospital discharge. However, an appropriate evaluation of sleep and circadian rhythms is often neglected given the high associated cost and/or the need of collaboration of the patients. In this project, the investigators propose alternatives to ultimately improve the management of sleep and circadian health after critical illness. The researchers will evaluate the role of microRNA (miRNAs) expression profile in identifying the compromised sleep and circadian health of critical patients during the ICU stay, in the short (3 months after hospital discharge), and in the long-term (12 months after hospital discharge). Also, models based on machine learning techniques will be developed to predict adverse outcomes in this regard after hospital discharge.