Utility of white matter disease and atrophy on routinely acquired brain imaging for prediction of long-term delirium risk: population-based cohort study

Protocol for the Development and Analysis of the Oxford and Reading Cognitive Comorbidity, Frailty and Ageing Research Database-Electronic Patient Records (ORCHARD-EPR)

BACKGROUND

Hospital electronic patient records (EPRs) offer the opportunity to exploit large-scale routinely acquired data at relatively low cost and without selection. EPRs provide considerably richer data, and in real-time, than retrospective administrative data sets in which clinical complexity is often poorly captured. With population ageing, a wide range of hospital specialties now manage older people with multimorbidity, frailty and associated poor outcomes. We, therefore, set-up the Oxford and Reading Cognitive Comorbidity, Frailty and Ageing Research Database-Electronic Patient Records (ORCHARD-EPR) to facilitate clinically meaningful research in older hospital patients, including algorithm development, and to aid medical decision-making, implementation of guidelines, and inform policy.

METHODS AND ANALYSIS

ORCHARD-EPR uses routinely acquired individual patient data on all patients aged ≥65 years with unplanned admission or Same Day Emergency Care unit attendance at four acute general hospitals serving a population of >800 000 (Oxfordshire, UK) with planned extension to the neighbouring Berkshire regional hospitals (>1 000 000). Data fields include diagnosis, comorbidities, nursing risk assessments, frailty, observations, illness acuity, laboratory tests and brain scan images. Importantly, ORCHARD-EPR contains the results from mandatory hospital-wide cognitive screening (≥70 years) comprising the 10-point Abbreviated-Mental-Test and dementia and delirium diagnosis (Confusion Assessment Method-CAM). Outcomes include length of stay, delayed transfers of care, discharge destination, readmissions and death. The rich multimodal data are further enhanced by linkage to secondary care electronic mental health records. Selection of appropriate subgroups or linkage to existing cohorts allows disease-specific studies. Over 200 000 patient episodes are included to date with data collection ongoing of which 129 248 are admissions with a length of stay ≥1 day in 64 641 unique patients.

ETHICS AND DISSEMINATION

ORCHARD-EPR is approved by the South Central Oxford C Research Ethics Committee (ref: 23/SC/0258). Results will be widely disseminated through peer-reviewed publications and presentations at conferences, and regional meetings to improve hospital data quality and clinical services.

Hepatic encephalopathy: a neurologist's perspective

Liver disease is increasingly common, estimated to affect over 25% of the world's population. Failure of the liver to maintain a normal metabolic milieu leads to impaired brain function (hepatic encephalopathy), and conditions that cause liver disease can themselves predispose to neurological disease. As neurologists' involvement with the acute take increases, it is important that we are familiar with the neurological complications of liver disease, their investigation and management, and to know which other neurological diseases occur in this patient population. In this article, we review the causes, presentation and treatment of hepatic encephalopathy, and discuss important differential diagnoses in patients with liver disease who present with neurological disturbance.

Reliability of the global cortical atrophy visual rating scale applied to computed tomography versus magnetic resonance imaging scans in acute stroke

INTRODUCTION

Research using magnetic resonance imaging (MRI) suggests regional cerebral atrophy measures (e.g., frontal lobe, temporal lobe) may predict post-stroke outcomes. Clinical CT scans have excellent potential for use in research but it is unclear whether regional atrophy measures from CT are reliable compared to MRI reference standards.

METHODS

We used the Global Cortical Atrophy (GCA) scale to investigate reliability of atrophy measures on CT versus MRI scans from stroke patients originally recruited to the Oxford Cognitive Screening programme. Two raters provided standardised visual ratings at two timepoints. Weighted Kappa statistics assessed the reliability of regional atrophy scores. Spearman's correlation and a two-way repeated measures ANOVA assessed the reliability of the total score.

RESULTS

On clinically acquired neuroimaging from 98 stroke patients (mean/SD age = 70.97/11.99, 42 female, 84 ischaemic stroke), regional GCA scores on CT versus MRI showed fair to almost perfect intra-rater agreement (κ = .50-.87), substantial to almost perfect intra-rater agreement on CT (κ = .67-.88), and moderate to almost perfect intra-rater reliability on MRI (κ = .50-.89). Regional GCA scores showed mostly moderate to substantial inter-rater reliability on both CT and MRI (κ = .43-.69), except the temporal horns and parieto-occipital region. There was a strong correlation between total GCA scores on CT and MRI (r (96) = .87-.88, p < .001).

CONCLUSIONS

These results support the use of cerebral atrophy measures from CT in clinical research, as visual ratings showed generally good agreement between CT and MRI, between raters, and between timepoints.

Poststroke Executive Function in Relation to White Matter Damage on Clinically Acquired CT Brain Imaging

BACKGROUND

Executive function (EF) impairments are prevalent post stroke and are associated with white matter (WM) damage on MRI. However, less is known about the relationship between poststroke EF and WM damage on CT imaging.

OBJECTIVE

To investigate the relationship between poststroke EF and WM damage associated with stroke lesions and WM hypointensities (WMHs) on clinically acquired CT imaging.

METHOD

This study analyzed data from the Oxford Cognitive Screening Program, which recruited individuals aged ≥18 years with a confirmed stroke from an acute stroke unit. The individuals completed a follow-up assessment 6 months post stroke. We included individuals with a CT scan showing a visible stroke who completed follow-up EF assessment using the Oxford Cognitive Screen-Plus rule-finding task. We manually delineated stroke lesions and quantified then dichotomized WM damage caused by the stroke using the HCP-842 atlas. We visually rated then dichotomized WMHs using the Age-Related White Matter Changes Scale.

RESULTS

Among 87 stroke survivors (M age = 73.60 ± 11.75; 41 female; 61 ischemic stroke), multivariable linear regression showed that stroke damage to the medial lemniscus ( B = -8.86, P < 0.001) and the presence of WMHs ( B = -5.42, P = 0.005) were associated with poorer EF 6 months post stroke after adjusting for covariates including age and education.

CONCLUSION

Poorer EF was associated with WM damage caused by stroke lesions and WMHs on CT. These results confirm the importance of WM integrity for EF post stroke and demonstrate the prognostic utility of CT-derived imaging markers for poststroke cognitive outcomes.

Infection, delirium, and risk of dementia in patients with and without white matter disease on previous brain imaging: a population-based study

BACKGROUND

The increased risk of dementia after delirium and infection might be influenced by cerebral white matter disease (WMD). In patients with transient ischaemic attack (TIA) and minor stroke, we assessed associations between hospital admissions with delirium and 5-year dementia risk and between admissions with infection and dementia risk, stratified by WMD severity (moderate or severe vs absent or mild) on baseline brain imaging.

METHODS

We included patients with TIA and minor stroke (National Institutes of Health Stroke Score <3) from the Oxford Vascular Study (OXVASC), a longitudinal population-based study of the incidence and outcomes of acute vascular events in a population of 94 567 individuals, with no age restrictions, attending eight general practices in Oxfordshire, UK. Hospitalisation data were obtained through linkage to the Oxford Cognitive Comorbidity, Frailty, and Ageing Research Database-Electronic Patient Records (ORCHARD-EPR). Brain imaging was done using CT and MRI, and WMD was prospectively graded according to the age-related white matter changes (ARWMC) scale and categorised into absent, mild, moderate, or severe WMD. Delirium and infection were defined by ICD-10 coding supplemented by hand-searching of hospital records. Dementia was diagnosed using clinical or cognitive assessment, medical records, and death certificates. Associations between hospitalisation with delirium and hospitalisation with infection, and post-event dementia were assessed using time-varying Cox analysis with multivariable adjustment, and all models were stratified by WMD severity.

FINDINGS

From April 1, 2002, to March 31, 2012, 1369 individuals were prospectively recruited into the study. Of 1369 patients (655 with TIA and 714 with minor stroke, mean age 72 [SD 13] years, 674 female and 695 male, and 364 with moderate or severe WMD), 209 (15%) developed dementia. Hospitalisation during follow-up occurred in 891 (65%) patients of whom 103 (12%) had at least one delirium episode and 236 (26%) had at least one infection episode. Hospitalisation without delirium or infection did not predict subsequent dementia (HR 1·01, 95% CI 0·86-1·20). In contrast, hospitalisation with delirium predicted subsequent dementia independently of infection in patients with and without WMD (2·64, 1·47-4·74; p=0·0013 vs 3·41, 1·91-6·09; p<0·0001) especially in those with unimpaired baseline cognition (cognitive test score above cutoff; 4·01, 2·23-7·19 vs 3·94, 1·95-7·93; both p≤0·0001). However, hospitalisation with infection only predicted dementia in those with moderate or severe WMD (1·75, 1·04-2·94 vs 0·68, 0·39-1·20; pdiff=0·023).

INTERPRETATION

The increased risk of dementia after delirium is unrelated to the presence of WMD, whereas infection increases risk only in patients with WMD, suggesting differences in underlying mechanisms and in potential preventive strategies.

FUNDING

National Institute for Health and Care Research and Wellcome Trust.

Perivascular spaces visible on magnetic resonance imaging predict subsequent delirium in older patients

Background

It remains unknown whether perivascular spaces (PVS) are associated with delirium in older hospitalized patients. We aimed to determine the association between magnetic resonance imaging (MRI)-visible PVS and the risk of delirium in a cohort of older patients.

Methods

We consecutively recruited older patients (≥70 years) admitted to the Geriatric Department of West China Hospital between March 2016 and July 2017, and their imaging data within one year before admission were reviewed retrospectively. PVS was rated on axial T2-weighted images in the basal ganglia (BG) and centrum semiovale (CS) using the validated semiquantitative 4-point ordinal scale. Delirium was screened within 24 h of admission and three times daily thereafter, using the confusion assessment method. Binary logistic regression analyses were performed to investigate the associations between PVS and delirium.

Results

Among 114 included patients (mean age 84.3 years, 72.8% male), delirium occurred in 20 (17.5%). In patients with MRI examined within 6 months before admission, CS-PVS was found to be associated with delirium (odds ratio [OR] 3.88, 95% confidence interval [CI] 1.07-14.06, unadjusted; and OR 4.24, 95% CI 1.11-16.28, adjusted for age). The associations were enhanced and remained significant even after full adjustment of covariates (OR 7.16, 95% CI 1.16-44.32, adjusted for age, cognitive impairment, smoking, and Charlson Comorbidity Index). Similarly, the relationships between high CS-PVS and delirium were also strengthened after sequentially adjusting all variables of interest, with OR 4.17 (95% CI 1.04-16.73) in unadjusted model and OR 7.95 (95% CI 1.14-55.28) in fully-adjusted model. Adding CS-PVS to the established risk factors improved the risk reclassification for delirium (continuous net reclassification index 62.1%, P = 0.04; and integrated discrimination improvement 12.5%, P = 0.01).

Conclusions

CS-PVS on MRI acquired 6 months earlier predicts subsequent delirium in older patients and may have clinical utility in delirium risk stratification to enable proactive interventions.