ArticleAnesthesiology research and practice2022
Development of a Delirium Risk Predication Model among ICU Patients in Oman.
Article in Anesthesiology research and practice, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
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Who cites it
2 citing papers in PubMed, 2 citations in OpenAlex.
- Barriers to nurse-led delirium management in intensive care units: an integrative systematic review using COM-B model.BMC nursing · 2025Article
- Developing a Nomogram to Predict the Risk of Delirium in ICU Patients: A Retrospective Cohort Study.Risk management and healthcare policy · 2025Article
Corrections and comments
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Authors and funding
4 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Delirium is a common disorder among patients admitted to intensive care units. Identification of the predicators of delirium is very important to improve the patient's quality of life. Methods: This study was conducted in a prospective observational design to build a predictive model for delirium among ICU patients in Oman. A sample of 153 adult ICU patients from two main hospitals participated in the study. The Intensive Care Delirium Screening Checklist (ICDSC) was used to assess the participants for delirium twice daily. Result: The results showed that the incidence of delirium was 26.1%. Multiple logistic regression analysis showed that sepsis (odds ratio (OR) = 9.77; 95% confidence interval (CI) = 1.91-49.92; Conclusion: To prevent delirium in Omani hospitals, it is necessary to work on correcting those predictors and identifying other factors that had effects on delirium development. Designing of a prediction model may help on early delirium detection and implementation of preventative measures.
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Registered trials
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