Related Experiment Video
Updated: May 13, 2026

A Middle Cerebral Artery Occlusion Technique for Inducing Post-stroke Depression in Rats
Published on: May 22, 2019
Systematic Review and Meta-Analysis of Post-Stroke Delirium Risk Prediction Models
Qiushuang Yu1, Liu Han2,3, Hong Guo1
1School of Nursing, Beijing University of Chinese Medicine, Beijing, China.
Aim:
To systematically review published studies on the post stroke delirium risk prediction models; and to provide the evidence for developing and updating the clinically available prediction models.
Design:
Systematic review.
Data Sources:
Systematically searched studies on 10 databases, which were conducted from inception to 9 January 2025. The studies of post-stroke delirium risk prediction models were included.
Methods:
Extracted the data from the selected studies. The Prediction Model Risk of Bias Assessment Tool checklist was used to evaluate the risk of bias of the models. The meta-analysis of model performance and common predictors was performed by Revman 5.4 and Medcalc.
Results:
A total of 12 studies were included, and 21 risk prediction models for post-stroke delirium were constructed. The combined effect size of area under the receiver operating characteristic curve was 0.84. All studies were found to have a high risk of bias and good applicability. Meta-analysis showed: National Institutes of Health Stroke Scale score, age, neutrophil-to-lymphocyte ratio, neglect, visual impairment and atrial fibrillation were independent predictors of post-stroke delirium.
Conclusion:
The included studies all found to have a high risk of bias; future studies should focus on adopting more scientifically rigorous study designs and following the standardised reporting guidelines to enhance extrapolation and facilitate its clinical application.
Implications For The Profession:
This review may promote clinical healthcare workers to develop and update clinically available prediction models, thereby establishing risk prediction models with strong clinical utility.
Impact:
This study presents the first systematic evaluation of delirium risk prediction models in stroke patients, thereby facilitating the choice, use and develop of the clinical usable post stroke delirium risk prediction models.
Reporting Method:
This review adhered to the PRISMA guidelines.
Patient Or Public Contribution:
No patient or public contribution.
Review Registration:
RD42024620360 (PROSPERO According to JAN Guidelines).
More Related Videos
Related Concept Videos
Wind Turbine Machine Models
Induction machines interact through the rotating magnetic field generated by the stator and the rotor. The key parameter is slip, which is the difference between synchronous speed and rotor speed relative to synchronous speed. Slip is...
Mechanistic Models: Compartment Models in Individual and Population Analysis
Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving
In individual population analyses, different algorithms are employed, such as Cauchy's method, which uses a...
Typical Model Studies
First Derivative Test: Problem Solving
Self-Evaluation Maintenance Model

