Evidence map›Paper›PMID 41999484›Full record

ArticleEuropean geriatric medicine2026

A multidomain sleep-brain vulnerability index predicts delirium and long-term cognitive decline in hospitalized older adults.

Shengjie Pan, Gang Wang

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Article in European geriatric medicine, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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5 · Who and what money

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2 authors.

Shengjie PanDepartment of Neurology, The First Affiliated Hospital of Soochow University, Suzhou, 215006, Jiangsu, China.
Gang WangDepartment of General Surgery, The First Affiliated Hospital of Soochow University, Suzhou, 215006, Jiangsu, China. 286651551@qq.com.ORCID http://orcid.org/0009-0009-8864-7688

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundDelirium is a frequent complication among hospitalized older adults and is associated with prolonged recovery, increased mortality, and long-term cognitive decline. However, traditional risk models rely largely on baseline clinical characteristics and often fail to capture dynamic physiologic vulnerability during hospitalization. We therefore aimed to develop a multidomain physiologic index integrating sleep, circadian, autonomic, and environmental disturbances to improve delirium risk prediction.

methodsIn this prospective cohort study, 600 hospitalized adults aged ≥ 60 years admitted to surgical wards or intensive care units in a tertiary hospital were enrolled. Participants underwent multimodal monitoring including actigraphy, heart rate variability, and bedside noise-light sensors; 96 also completed overnight EEG. Eighteen physiologic and environmental variables were standardised and reduced using principal component analysis. The first component, reflecting sleep fragmentation, circadian instability, autonomic imbalance, and environmental load, was prespecified as the Sleep-Brain Vulnerability Index (SBVI). Delirium was assessed daily, and cognition at baseline, 3 months, and 12 months. Associations between SBVI and outcomes were examined using multivariable logistic, Cox, and linear mixed-effects models.

resultsDelirium occurred in 148 participants (24.7%). Higher SBVI was independently associated with delirium (adjusted OR per SD 1.94; 95% CI 1.48-2.56) and showed graded risk across tertiles (12.3%, 23.7%, 39.8%). Adding SBVI to a clinical model improved discrimination (AUC 0.72 to 0.81). SBVI predicted slower discharge (HR 0.86; 95% CI 0.80-0.93) and greater 12-month cognitive decline (β - 0.47 MoCA points per SD; 95% CI - 0.70 to - 0.25). EEG analyses showed reduced slow-wave activity among individuals with higher SBVI.

conclusionsSBVI provides a multidomain physiologic measure that predicts delirium, recovery, and long-term cognitive decline in hospitalized older adults. Because its components can be obtained using feasible bedside monitoring, SBVI may enable early identification of vulnerable patients and support targeted geriatric interventions.

Indexed as

BrainCognitive DysfunctionDeliriumSleepActigraphyAgedAged, 80 and overCircadian RhythmElectroencephalographyFemaleHospitalizationHumansMaleMiddle AgedProspective StudiesRisk FactorsAgingCircadian rhythmCognitive declineDeliriumHeart rate variabilityMultimodal monitoringPredictive modelingSleep fragmentation

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.