Delirium risk prediction models for intensive care unit patients: A systematic review

Jun-shan, Chen; Yu, Jintian; Zhang, Aiqin

doi:10.1016/j.iccn.2020.102880

Cited by 13 publications

(10 citation statements)

References 46 publications

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“…Three recent systematic reviews found 26 unique prediction models for predicting delirium in ICU [9,12,13]. Of these models, 4 were identified by the review papers to be "dynamic" models: DYNAMIC-ICU [14], Auto-DelRAS [15], ABD-pm [16], and a model developed by Oh et al [17].…”

Section: Related Workmentioning

confidence: 99%

“…• As opposed to static variables used in models found in the review papers [9,12,13], dynamic laboratory variables were used to provide more up-to-date data for prediction. • The analysis was undertaken using data recorded within the first 21 hours since ICU admission: this is to make sure that delirium is predicted as early as possible (see Section III.B).…”

Section: Related Workmentioning

confidence: 99%

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Predicting the Onset of Delirium on Hourly Basis in an Intensive Care Unit Following Cardiac Surgery

Lapp

Roper

Kavanagh

et al. 2022

2022 IEEE 35th International Symposium on Computer-Based Medical Systems (CBMS)

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Delirium, affecting up to 52% of cardiac surgery patients, can have serious long-term effects on patients by damaging cognitive ability and causing subsequent functional decline. This study reports on the development and evaluation of predictive models aimed at identifying the likely onset of delirium on an hourly basis in intensive care unit following cardiac surgery. Most models achieved a mean AUC > 0.900 across all lead times. A support vector machine achieved the highest performance across all lead times of AUC = 0.941 and Sensitivity = 0.907, and BARTm, where missing values were replaced with missForest imputation, achieved the highest Specificity of 0.892. Being able to predict delirium hours in advance gives clinicians the ability to intervene and optimize treatments for patients who are at risk and avert potentially serious and life-threatening consequences.

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Section: Related Workmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

Predicting the Onset of Delirium on Hourly Basis in an Intensive Care Unit Following Cardiac Surgery

Lapp

Roper

Kavanagh

et al. 2022

2022 IEEE 35th International Symposium on Computer-Based Medical Systems (CBMS)

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“…In order to prove feasible in clinical practice, a predictive model should be reproducible and generalizable. To date, only the PREdiction of DELIRium in ICu patients (PRE-DELIRIC) model has undergone both internal and external validation [36]. This model includes risk factors for delirium at ICU admission and within the first 24 h of ICU stay and has showed moderate power to predict delirium in ICU patients [37,38].…”

Section: Predictionmentioning

confidence: 99%

Delirium in Intensive Care

Poulsen

Estrup

Mortensen

et al. 2021

Curr Anesthesiol Rep

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Purpose of Review Delirium in the intensive care unit (ICU) has become increasingly acknowledged as a significant problem for critically ill patients affecting both the actual course of illness as well as outcomes. In this review, we focus on the current evidence and the gaps in knowledge. Recent Findings This review highlights several areas in which the evidence is weak and further research is needed in both pharmacological and non-pharmacological treatment. A better understanding of subtypes and their different response to therapy is needed and further studies in aetiology are warranted. Larger studies are needed to explore risk factors for developing delirium and for examining long-term consequences. Finally, a stronger focus on experienced delirium and considering the perspectives of both patients and their families is encouraged. Summary With the growing number of studies and a better framework for research leading to stronger evidence, the outcomes for patients suffering from delirium will most definitely improve in the years to come. KeywordsDelirium • Intensive care • CAM-ICU • Risk factors • Non-pharmacological • Pharmacological • Core outcome This article is part of the Topical Collection on Critical Care Anesthesia

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“…We thank Chen and colleagues for their focus on summarising the delirium risk prediction models for intensive care unit (ICU) patients ( Chen et al, 2020 ). In the Implications for Clinical Practice section of their work, the fourth bullet point states: ‘Researchers should not only pay attention to the models’ predictive efficiency but also focus on the application burden for users” We think this is central to implement the delirium risk prediction models in clinical settings and strongly agree with the point that the authors raising.…”

Section: Dear Editormentioning

confidence: 99%

Application of the delirium risk prediction model in the TED ICU smart intensive care system during the current COVID-19 pandemic

Shen

2021

Intensive and Critical Care Nursing

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Delirium risk prediction models for intensive care unit patients: A systematic review

Cited by 13 publications

References 46 publications

Predicting the Onset of Delirium on Hourly Basis in an Intensive Care Unit Following Cardiac Surgery

Predicting the Onset of Delirium on Hourly Basis in an Intensive Care Unit Following Cardiac Surgery

Delirium in Intensive Care

Application of the delirium risk prediction model in the TED ICU smart intensive care system during the current COVID-19 pandemic

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