View clinical trials related to Delirium.
Filter by:Postoperative delirium (POD) is a common surgical complication. The incidence is 10% to 22% in neurological procedures, and advanced age is a risk factor for neurological procedures. Many studies have shown that dexmedetomidine(DEX) may reduce the incidence of delirium in non-cardiac surgery patients and elderly patients. However, there are few studies focus on the effect of DEX on POD in elderly patients undergoing neurosurgery. The purpose of this study was to investigate the effect of DEX on POD in in elderly patients undergoing craniotomy.
Postoperative delirium in older adults is a common and costly complication after surgery. Propofol and sevoflurane are commonly used anesthetics to maintain sedation during spine surgery, and have different sedative and anti-inflammatory effects. The aim of this trial will be compare the impact of propofol versus sevoflurane on incidence of postoperative delirium in elderly patients after spine surgery.
Postoperative delirium is common and associated with significant adverse outcomes. Its etiology is unknown, and little is known about associated risk factors. The investigatorea aim to test whether providing emotional and orientation support can reduce the risk of postoperative delirium in elderly patients undergoing elective non-cardiac surgery. Specifically, the investigators will test whether allowing such patients to keep their hearing and visual aids and be escorted into the operating room by a family member until anesthesia induction reduces the incidence of postoperative delirium. Delirium will be actively screened as part of our institution's clinical practice starting at PACU admission and for a minimum of 2 postoperative days. The investigators will use a multiple cross-over design to enroll all eligible patients and alternate between the intervention and our common practice (removing sensorial aids in the preoperative area and not allowing patients' escort beyond that point) every 2 weeks for up to 2 years.
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.
Cognitive complications, that is problems with thinking and memory, are incredibly common after surgery, occurring in 10-50% of all older surgical patients. These complications can take different forms, but one of the most common is postoperative delirium (POD), a short-term state of confusion. In addition to being stressful for patients and their families, POD is linked to longer hospital stays, increased costs, higher mortality rates and other problems after surgery. Despite this, POD is often not recognized by doctors and there are currently no effective medications to treat POD. However, simple strategies such as helping patients to sleep properly and remain hydrated, have been shown to help. This study is testing if a delirium-reduction program will reduce postoperative delirium (POD) in older surgical patients. The investigators will first test memory and thought processes before surgery to find people who are most likely to develop POD. Once these people have been identified, they will be enrolled in a program which includes recommendations for their care team (e.g. surgeon, anesthesiologist, nurses) as well as educational materials for them and their family related to things that can be done to prevent delirium. By identifying at-risk patients and making sure that their doctors and caregivers are aware of how to prevent delirium, the investigators expect that this study will make surgery safer for older surgical patients.
- Identify the degree of delirium in subjects with mild cognitive impairment and find the risk factors of delirium. Mortality, hospital stay, and medical expenses are analyzed as clinical consequences related to delirium incidence. - Dementia conversion rate and conversion period of subjects with mild cognitive impairment with delirium and it identifies the effect of delirium on dementia conversion. - Develop an AI(Artificial intelligence) algorithm for predicting dementia transition in subjects with mild cognitive impairment based on the research results of the 1st, 2nd, and 3rd years.
Background Delirium, is a clinical condition characterized by acute and fluctuating deterioration of the cognitive state, generally secondary to an acute pathology. It is a common condition in hospitalized older adults and it develops in 20-30% of patients hospitalized in a general ward and up to 80% of those hospitalized in critical care units. Delirium is associated with negative outcomes in older adults, such as longer hospitalizations, higher mortality, and short and medium-term institutionalization. Randomized clinical trials have shown that delirium is preventable through non-pharmacological prevention measures, decreasing its incidence by 30 to 50%. These interventions include promoting physical activity, facilitating the use of glasses and hearing aids, cognitive stimulation, and providing frequent reorientation of time and space, among others. These measures are currently seldom applied in hospitals in Chile and around the world for various reasons some of which include the heavy workload of clinical staff, the lack of trained personnel, and, in general, the absence of systematic implementation processes. The main objective is to evaluate whether cognitive stimulation guided by PREVEDEL software prevents delirium status(full/subsyncromal delirium) in hospitalized older adults. Method/Design: randomized controlled trial, parallel groups, multicenter. Participants: patients 65 years or older who have been hospitalized for less than 48 hours in the general ward or in the intermediate care unit of 4 hospitals in Santiago, Chile. Intervention: participants in the intervention group will use a tablet with cognitive stimulation software for delirium prevention for 5 continuous days versus the control group who will use the tablet without the software. Evaluations: The incidence of delirium and subsyndromal delirium, duration, density of delirium, cognitive and functional status at discharge, adherence to prevention measures, as well as demographic variables of interest will be evaluated.
The primary endpoint of the study is the appearance of Post Operative Delirium within the first 3 months. The secondary endpoints are the development of POCD, dementia of any type of new onset at 12 months, mortality at 30 days, postoperative hospitalization time (including rehabilitation performed within the Polyclinic).. The analysis of the risk factors of POD and their correlation with the development of POCD/Dementia in the post-surgery period will provide important information for the optimization of the management path of these patients at an individual level , with inevitable repercussions on the possibility of reintegration into social and family life
An investigation of the change in inflammation marker levels across hip fracture surgery and an exploration of any association with change in self reported health status and incidence of postoperative delirium
Delirium is frequently observed among critically ill patients and is associated with detrimental outcomes. Currently, no evidence-based prevention or treatment exists for delirium, and especially, the inability to identify effective preventive measures of delirium has increased the focus on identifying patients with a high risk of delirium through prediction models. Two prediction models have been developed to estimate the risk of delirium in ICU patients: the prediction model for delirium (PRE-DELIRIC) and the early prediction model for delirium (E-PRE-DELIRIC). These robust and well-calibrated prediction models have the potential of assisting in identifying patients with the highest risk for delirium and thereby to focusing preventive strategies on the most vulnerable group. However further validation is needed in a Danish population.