Results 31 to 40 of about 195,073 (382)

Research progress on risk factors of delirium in burn patients: A narrative review

open access: yesFrontiers in Psychiatry, 2022
Delirium, an acute brain dysfunction, is a common and serious complication in burn patients. The occurrence of delirium increases the difficulty of patient treatment, is associated with various adverse outcomes, and increases the burden on the patient’s ...
Yujie Ren   +5 more
doaj   +1 more source

Identifying Symptoms of Delirium from Clinical Narratives Using Natural Language Processing [PDF]

open access: yesarXiv, 2023
Delirium is an acute decline or fluctuation in attention, awareness, or other cognitive function that can lead to serious adverse outcomes. Despite the severe outcomes, delirium is frequently unrecognized and uncoded in patients' electronic health records (EHRs) due to its transient and diverse nature.
arxiv  

Obstructive sleep apnea as an independent predictor of postoperative delirium and pain: Protocol for an observational study of a surgical cohort [version 2; referees: 2 approved] [PDF]

open access: yes, 2018
Introduction: Postoperative delirium and pain are common complications in adults, and are difficult both to prevent and treat. Obstructive sleep apnea (OSA) is prevalent in surgical patients, and has been suggested to be a risk factor for postoperative ...
Arrington, Brianna   +7 more
core   +2 more sources

Unsupervised Learning to Subphenotype Delirium Patients from Electronic Health Records [PDF]

open access: yesarXiv, 2021
Delirium is a common acute onset brain dysfunction in the emergency setting and is associated with higher mortality. It is difficult to detect and monitor since its presentations and risk factors can be different depending on the underlying medical condition of patients.
arxiv  

Advantages of score-based delirium detection compared to a clinical delirium assessment-a retrospective, monocentric cohort study.

open access: yesPLoS ONE, 2021
PurposeDelirium is an underdiagnosed complication on intensive care units (ICU). We hypothesized that a score-based delirium detection using the Nudesc score identifies more patients compared to a traditional diagnosis of delirium by ICU physicians ...
Markus Jäckel   +11 more
doaj   +1 more source

Causal Discovery on the Effect of Antipsychotic Drugs on Delirium Patients in the ICU using Large EHR Dataset [PDF]

open access: yesarXiv, 2022
Delirium occurs in about 80% cases in the Intensive Care Unit (ICU) and is associated with a longer hospital stay, increased mortality and other related issues. Delirium does not have any biomarker-based diagnosis and is commonly treated with antipsychotic drugs (APD).
arxiv  

Environmental factors and risk of delirium in geriatric patients: an observational study

open access: yesBMC Geriatrics, 2018
Background Patients with delirium have increased risk of death, dementia and institutionalization, and prognosis differs between delirium motor subtypes.
Sigurd Evensen   +5 more
doaj   +1 more source

Detection of delirium by nurses among long-term care residents with dementia

open access: yesBMC Nursing, 2008
Background Delirium is a prevalent problem in long-term care (LTC) facilities where advanced age and cognitive impairment represent two important risk factors for this condition.
Danjou Christine   +4 more
doaj   +1 more source

Delirium-related factors and their prognostic value in patients undergoing craniotomy for brain metastasis

open access: yesFrontiers in Neurology, 2022
BackgroundDelirium is characterized by acute brain dysfunction. Although delirium significantly affects the quality of life of patients with brain metastases, little is known about delirium in patients who undergo craniotomy for brain metastases.
Jihwan Yoo   +10 more
doaj   +1 more source

Predicting risk of delirium from ambient noise and light information in the ICU [PDF]

open access: yesarXiv, 2023
Existing Intensive Care Unit (ICU) delirium prediction models do not consider environmental factors despite strong evidence of their influence on delirium. This study reports the first deep-learning based delirium prediction model for ICU patients using only ambient noise and light information. Ambient light and noise intensities were measured from ICU
arxiv  

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