ArticleNursing in critical care2025
A Data-Driven Model to Predict Delirium Based on Dynamic Patterns of Clinical Deterioration in Critically Ill Patients.
Article in Nursing in critical care, 2025. 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.
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Who cites it
2 citing papers in PubMed.
- Nomogram and machine learning models for predicting the risk of delirium in ICU patients with NSTEMI.Medicine · 2026Article
- A Data-Driven Model to Predict Delirium Based on Dynamic Patterns of Clinical Deterioration in Critically Ill Patients.Nursing in critical care · 2025Article
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Authors and funding
5 authors.
Funding
Abstract
backgroundAlthough many risk factors for delirium have been identified, the contribution of dynamic patterns of clinical deterioration remains underexplored.
aimsTo explore the risk of delirium based on changes in clinical parameters. STUDY
designA retrospective study based on electronic health records (EHRs) was conducted. The EHRs of 3600 patients, including 827 with delirium and 2773 without delirium, who were admitted to the medical and surgical intensive care unit (ICU) between January 2017 and February 2020, were analysed. Data involving changes in clinical parameters recorded from admission until the day before the onset of delirium were categorised as 'worsen to or persist worsen' or 'recovered to or persist normal.' Logistic regression was conducted to identify the significant risk factors for delirium development.
resultsThe model's C-statistic, which is equivalent to the area under the ROC curve (AUC) in this context, was 0.88, suggesting excellent ability to discriminate patients who developed delirium. Among 14 variables, 8 were associated with changes in patient conditions: diastolic blood pressure (< 60 mmHg, OR: 2.01 [1.68-2.48]), heart rate (> 100/min, OR: 1.55 [1.23-1.95]), respiratory rate (> 25/min, OR: 1.26 [0.92-1.72]), partial pressure of carbon dioxide (PaCO
conclusionsPersistent or worsening physiological derangements were significantly associated with delirium onset in critically ill patients. RELEVANCE TO CLINICAL PRACTICE: Recognising and concurrently addressing worsening clinical trends such as haemodynamic instability, acid-base imbalance and electrolyte disturbance can support earlier, tailored interventions to prevent delirium in high-risk ICU patients.
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