Frequency and risk factors for subsyndromal delirium in an intensive care unit

Yamada, Chikayo; Iwawaki, Yoko; Harada, Kiyomi; Fukui, Michihiko; Morimoto, Masafumi; Yamanaka, Ryuya

doi:10.1016/j.iccn.2018.02.010

Cited by 29 publications

(45 citation statements)

References 27 publications

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“…Recently a study by Yamada and colleagues further supports this idea where they showed that 33.9% of critically ill patient in an ICU setting had SSD and 9.5% of these patients later developed delirium [54]. Our data supports that SSD is clinically relevant.…”

Section: Discussionsupporting

confidence: 83%

Cerebrospinal Fluid Levels of Interleukin-8 in Delirium, Dementia, and Cognitively Healthy Patients

Sajjad

Blennow

Knapskog

et al. 2020

JAD

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Delirium is a common and serious complication in geriatric patients. The pathophysiology of delirium is not known. The objective of the current study was to test the hypothesis that cerebrospinal fluid (CSF) levels of inflammatory markers at the time of spinal anesthesia for hip surgery are associated with delirium. In total 133 hip fracture patients and 125 cognitively healthy controls undergoing elective surgery, together with 73 Alzheimer's disease (AD) dementia patients, were recruited at

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Section: Discussionsupporting

confidence: 83%

Cerebrospinal Fluid Levels of Interleukin-8 in Delirium, Dementia, and Cognitively Healthy Patients

Sajjad

Blennow

Knapskog

et al. 2020

JAD

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“…All studies reported ICU LOS. ere were two studies for which mean LOS was combined from two patient groups: Ouimet et al and Yamada et al, "No delirium" and "Subsyndromal delirium" groups were combined [26,63]. e mean ICU LOS for patients with delirium was 9.40 ± 0.47 days, compared to a mean LOS of 3.39 ± 0.07 days for patients without delirium.…”

Section: Resultsmentioning

confidence: 99%

Delirium and Associated Length of Stay and Costs in Critically Ill Patients

Dziegielewski

Skead

Canturk

et al. 2021

Critical Care Research and Practice

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Purpose. Delirium frequently affects critically ill patients in the intensive care unit (ICU). The purpose of this study is to evaluate the impact of delirium on ICU and hospital length of stay (LOS) and perform a cost analysis. Materials and Methods. Prospective studies and randomized controlled trials of patients in the ICU with delirium published between January 1, 2015, and December 31, 2020, were evaluated. Outcome variables including ICU and hospital LOS were obtained, and ICU and hospital costs were derived from the respective LOS. Results. Forty-one studies met inclusion criteria. The mean difference of ICU LOS between patients with and without delirium was significant at 4.77 days ( p < 0.001 ); for hospital LOS, this was significant at 6.67 days ( p < 0.001 ). Cost data were extractable for 27 studies in which both ICU and hospital LOS were available. The mean difference of ICU costs between patients with and without delirium was significant at $3,921 ( p < 0.001 ); for hospital costs, the mean difference was $5,936 ( p < 0.001 ). Conclusion. ICU and hospital LOS and associated costs were significantly higher for patients with delirium, compared to those without delirium. Further research is necessary to elucidate other determinants of increased costs and cost-reducing strategies for critically ill patients with delirium. This can provide insight into the required resources for the prevention of delirium, which may contribute to decreasing healthcare expenditure while optimizing the quality of care.

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“… Tawadrous et al (2014) demonstrated that compared to a lower dose, initiation of the current standard dose of histamine 2 receptor antagonists (H2RA) in older adults is associated with a small absolute increase in the 30-day risk of altered mental status. Yamada et al (2018) found that steroid use was the determinant of progression to delirium in an intensive care unit, and research by Romain Sonneville et al also found that steroid use was an independent risk factor for SAE ( Yamada et al, 2018 ). These studies supported our study results.…”

Section: Discussionmentioning

confidence: 99%

Mechanical Learning for Prediction of Sepsis-Associated Encephalopathy

Zhao

Wang

et al. 2021

Front. Comput. Neurosci.

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Objective: The study aims to develop a mechanical learning model as a predictive model for predicting the appearance of sepsis-associated encephalopathy (SAE).Materials and Methods: The prediction model was developed in a primary cohort of 2,028 sepsis patients from June 2001 to October 2012, retrieved from the Medical Information Mart for Intensive Care (MIMIC III) database. Least absolute shrinkage and selection operator (LASSO) regression model was used for data dimension reduction and feature selection. The model was developed using multivariable logistic regression analysis. The performance of the nomogram has been evaluated in terms of calibration, discrimination, and clinical utility.Results: There were nine particular features in septic patients that were significantly associated with SAE. Predictors of individualized prediction nomograms included age, rapid sequential evaluation of organ failure (qSOFA), and drugs including carbapenem antibiotics, quinolone antibiotics, steroids, midazolam, H2-antagonist, diphenhydramine hydrochloride, and heparin sodium injection. The area under the curve (AUC) was 0.743, indicating good discrimination. The prediction model showed calibration curves with minor deviations from the ideal predictions. Decision curve analysis (DCA) suggested that the nomogram was clinically useful.Conclusion: We propose a nomogram for the individualized prediction of SAE with satisfactory performance and clinical utility, which could aid the clinician in the early detection and management of SAE.

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Frequency and risk factors for subsyndromal delirium in an intensive care unit

Cited by 29 publications

References 27 publications

Cerebrospinal Fluid Levels of Interleukin-8 in Delirium, Dementia, and Cognitively Healthy Patients

Cerebrospinal Fluid Levels of Interleukin-8 in Delirium, Dementia, and Cognitively Healthy Patients

Delirium and Associated Length of Stay and Costs in Critically Ill Patients

Mechanical Learning for Prediction of Sepsis-Associated Encephalopathy

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