Discover Community Create You

Loading publication...

Noodle always counts identifier-free feature events for service operation. With your permission, Google Analytics can also estimate audience and engagement. Search text, publication identifiers, cookies, IP addresses and browser fingerprints are never included in Noodle's first-party event counters.

Privacy details

Article

Identifying subphenotypes of patients undergoing post-operative delirium assessment.

Alzheimer's & dementia : the journal of the Alzheimer's Association - 1 Jul 2025

Bowman Emily Margaret Louise, McAuley Daniel F, McGuinness Bernadette, Passmore Anthony P, Beverland David, Zetterberg Henrik, Schott Jonathan M, Heslegrave Amanda, Veleva Elena, Laban Rhiannon, Sweeney Aoife, Cunningham Emma L

Abstract excerpt

INTRODUCTION: Delirium has heterogeneous etiologies and clinical presentations and is often associated with poor outcomes. Its pathophysiological mechanisms remain largely hypothetical and without targeted pharmacological treatment. This work investigates subphenotypes of patients undergoing delirium assessment based on clinical features and fluid biomarkers. METHODS: We performed latent class analysis of an...

Read the complete abstract on PubMed

Topics

Share this publication in a Topic to start or enrich a Post.

Share to Aged
Share to Aged, 80 and over

Methodology Data sources Editorial policy Privacy About Contact Helena Bioinformatics

Share to Amyloid beta-Peptides

Share to Biomarkers

Share to Cohort Studies

Share to Latent Class Analysis

Share to Postoperative Complications

Share to tau Proteins

Source

Open in PubMed Open full text

Identifiers

PMID: 40667953
DOI: 10.1002/alz.70516
PMCID: PMC12265012

Provenance

PubMed metadata and Literature Corpus relationships. Corpus snapshot updated 6 Sept 2026.

Related research

Semantic proximity does not establish scientific evidence.

Research trail→

Click a neighbor to travelStep 1 · 12 closest

Identifying subphenotypes of patients undergoing post-operative delirium assessment.PMID 40667953Read ↗

Phenotypes and subphenotypes of delirium: a review of current categorisations and suggestions for progression.Semantic proximity Read ↗

Development of a Dynamic Multi-Protein Signature of Postoperative DeliriumSemantic proximity Read ↗

Application of Multiple Omics to Understand Postoperative Delirium Pathophysiology in HumansSemantic proximity Read ↗

Edmonton Frailty Scale Score Predicts Postoperative Delirium: A Retrospective Cohort AnalysisSemantic proximity Read ↗

Proteomics for the discovery of clinical delirium biomarkers: A systematic review of Major StudiesSemantic proximity Read ↗

Development and internal validation of a gradient-boosted trees model for prediction of delirium after surgery and anesthesia (the BioCog study)Semantic proximity Read ↗

Development of an Early Prediction Model for Postoperative Delirium in Neurosurgical Patients Admitted to the ICU after Elective Craniotomy (E-PREPOD-NS): A Secondary Analysis of A Prospective Cohort StudySemantic proximity Read ↗

The incidence of delirium in the elderly after surgery and risk factorsSemantic proximity Read ↗

Point-of-care electroencephalography for prediction of postoperative delirium in older adults undergoing elective surgery: protocol for a prospective cohort studySemantic proximity Read ↗

Albumin/Fibrinogen Ratio (AFR): A Significant Predictor of Postoperative Delirium in Older Patients Undergoing Non-Neurosurgical and Non-Cardiac SurgerySemantic proximity Read ↗

Based on machine learning, which part of the perioperative period predicts postoperative delirium better? A retrospective case-control studySemantic proximity Read ↗

Development and validation of a machine learning-based model for predicting delirium risk in postoperative brain tumor patients in the Intensive Care UnitSemantic proximity Read ↗

⌁Select a neighboring publication to make it the new centre.