Computerised cognitive assessment in patients with traumatic brain injury: an observational study of feasibility and sensitivity relative to established clinical scales

Background

Online technology could potentially revolutionise how patients are cognitively assessed and monitored. However, it remains unclear whether assessments conducted remotely can match established pen-and-paper neuropsychological tests in terms of sensitivity and specificity.

Methods

This observational study aimed to optimise an online cognitive assessment for use in traumatic brain injury (TBI) clinics. The tertiary referral clinic in which this tool has been clinically implemented typically sees patients a minimum of 6 months post-injury in the chronic phase. Between March and August 2019, we conducted a cross-group, cross-device and factor analyses at the St. Mary's Hospital TBI clinic and major trauma wards at Imperial College NHS trust and St. George's Hospital in London (UK), to identify a battery of tasks that assess aspects of cognition affected by TBI. Between September 2019 and February 2020, we evaluated the online battery against standard face-to-face neuropsychological tests at the Imperial College London research centre. Canonical Correlation Analysis (CCA) determined the shared variance between the online battery and standard neuropsychological tests. Finally, between October 2020 and December 2021, the tests were integrated into a framework that automatically generates a results report where patients' performance is compared to a large normative dataset. We piloted this as a practical tool to be used under supervised and unsupervised conditions at the St. Mary's Hospital TBI clinic in London (UK).

Findings

The online assessment discriminated processing-speed, visual-attention, working-memory, and executive-function deficits in TBI. CCA identified two significant modes indicating shared variance with standard neuropsychological tests (r = 0.86, p < 0.001 and r = 0.81, p = 0.02). Sensitivity to cognitive deficits after TBI was evident in the TBI clinic setting under supervised and unsupervised conditions (F (15,555) = 3.99; p < 0.001).

Interpretation

Online cognitive assessment of TBI patients is feasible, sensitive, and efficient. When combined with normative sociodemographic models and autogenerated reports, it has the potential to transform cognitive assessment in the healthcare setting.

Funding

This work was funded by a National Institute for Health Research (NIHR) Invention for Innovation (i4i) grant awarded to DJS and AH (II-LB-0715-20006).

Remote Monitoring of Physiology in People Living With Dementia: An Observational Cohort Study

BACKGROUND

Internet of Things (IoT) technology enables physiological measurements to be recorded at home from people living with dementia and monitored remotely. However, measurements from people with dementia in this context have not been previously studied. We report on the distribution of physiological measurements from 82 people with dementia over approximately 2 years.

OBJECTIVE

Our objective was to characterize the physiology of people with dementia when measured in the context of their own homes. We also wanted to explore the possible use of an alerts-based system for detecting health deterioration and discuss the potential applications and limitations of this kind of system.

METHODS

We performed a longitudinal community-based cohort study of people with dementia using "Minder," our IoT remote monitoring platform. All people with dementia received a blood pressure machine for systolic and diastolic blood pressure, a pulse oximeter measuring oxygen saturation and heart rate, body weight scales, and a thermometer, and were asked to use each device once a day at any time. Timings, distributions, and abnormalities in measurements were examined, including the rate of significant abnormalities ("alerts") defined by various standardized criteria. We used our own study criteria for alerts and compared them with the National Early Warning Score 2 criteria.

RESULTS

A total of 82 people with dementia, with a mean age of 80.4 (SD 7.8) years, recorded 147,203 measurements over 958,000 participant-hours. The median percentage of days when any participant took any measurements (ie, any device) was 56.2% (IQR 33.2%-83.7%, range 2.3%-100%). Reassuringly, engagement of people with dementia with the system did not wane with time, reflected in there being no change in the weekly number of measurements with respect to time (1-sample t-test on slopes of linear fit, P=.45). A total of 45% of people with dementia met criteria for hypertension. People with dementia with α-synuclein-related dementia had lower systolic blood pressure; 30% had clinically significant weight loss. Depending on the criteria used, 3.03%-9.46% of measurements generated alerts, at 0.066-0.233 per day per person with dementia. We also report 4 case studies, highlighting the potential benefits and challenges of remote physiological monitoring in people with dementia. These include case studies of people with dementia developing acute infections and one of a person with dementia developing symptomatic bradycardia while taking donepezil.

CONCLUSIONS

We present findings from a study of the physiology of people with dementia recorded remotely on a large scale. People with dementia and their carers showed acceptable compliance throughout, supporting the feasibility of the system. Our findings inform the development of technologies, care pathways, and policies for IoT-based remote monitoring. We show how IoT-based monitoring could improve the management of acute and chronic comorbidities in this clinically vulnerable group. Future randomized trials are required to establish if a system like this has measurable long-term benefits on health and quality of life outcomes.

041 Cognitive and neuropsychiatric effects of noradrenergic treatment in Alzheimer’s disease: systematic review and meta-analysis

Background

Dysfunction of the locus coeruleus-noradrenergic system occurs early in Alzheimer’s disease. This results in a low-noradrenergic state in some patients, which contributes to cognitive and neuropsychi- atric symptoms. We aimed to assess the efficacy of noradrenergic drugs for improving these symptoms.

Methods

The MEDLINE, Embase, and ClinicalTrials.gov databases were searched from 1980 to December 2021. We generated pooled estimates using random effects meta-analyses.

Results

19 randomised controlled trials, of which six studies were of ‘good’ quality, with seven ‘fair’ and six ‘poor’, included 1811 patients. Meta-analysis of 10 studies showed a small, significant positive effect of noradrenergic drugs on patients’ global cognition, as measured using the MMSE or ADAS-Cog compared to placebo (SMD:0.14, 95%CI:0.03 to 0.25, p=0.01; I2=0%). No significant effect was seen on measures of attention (SMD:0.01, 95%CI:-0.17 to 0.19, p=0.91; I2=0). The apathy meta-analysis included eight trials and detected a large positive effect of noradrenergic drugs (SMD:0.45, 95%CI:0.16 to 0.73, p=0.002; I2=58%), although results were limited by potentially substantial heterogeneity.

Discussion

Drug repurposing with established noradrenergic drugs, may offer safe and effective treatment in Alzheimer’s disease, for both cognition and apathy. However, there are number of factors that should be considered before the design of much needed future clinical trials. Including, targeting the correct patient sub-groups and using the correct medications, at the optimal dose, possibly in combination with other treatments, in order to maximise therapeutic effect.

Cognitive and neuropsychiatric effects of noradrenergic treatment in Alzheimer's disease: systematic review and meta-analysis

BACKGROUND

Dysfunction of the locus coeruleus-noradrenergic system occurs early in Alzheimer's disease, contributing to cognitive and neuropsychiatric symptoms in some patients. This system offers a potential therapeutic target, although noradrenergic treatments are not currently used in clinical practice.

OBJECTIVE

To assess the efficacy of drugs with principally noradrenergic action in improving cognitive and neuropsychiatric symptoms in Alzheimer's disease.

METHODS

The MEDLINE, Embase and ClinicalTrials.gov databases were searched from 1980 to December 2021. We generated pooled estimates using random effects meta-analyses.

RESULTS

We included 19 randomised controlled trials (1811 patients), of which six were judged as 'good' quality, seven as 'fair' and six 'poor'. Meta-analysis of 10 of these studies (1300 patients) showed a significant small positive effect of noradrenergic drugs on global cognition, measured using the Mini-Mental State Examination or Alzheimer's Disease Assessment Scale-Cognitive Subscale (standardised mean difference (SMD): 0.14, 95% CI: 0.03 to 0.25, p=0.01; I2=0%). No significant effect was seen on measures of attention (SMD: 0.01, 95% CI: -0.17 to 0.19, p=0.91; I2=0). The apathy meta-analysis included eight trials (425 patients) and detected a large positive effect of noradrenergic drugs (SMD: 0.45, 95% CI: 0.16 to 0.73, p=0.002; I2=58%). This positive effect was still present following removal of outliers to account for heterogeneity across studies.

DISCUSSION

Repurposing of established noradrenergic drugs is most likely to offer effective treatment in Alzheimer's disease for general cognition and apathy. However, several factors should be considered before designing future clinical trials. These include targeting of appropriate patient subgroups and understanding the dose effects of individual drugs and their interactions with other treatments to minimise risks and maximise therapeutic effects.

PROSPERO REGISTERATION NUMBER

CRD42021277500.

Autonomic dysfunction after moderate-to-severe traumatic brain injury: symptom spectrum and clinical testing outcomes

Background

Survivors of moderate-to-severe traumatic brain injury (msTBI) frequently experience troublesome unexplained somatic symptoms. Autonomic dysfunction may contribute to these symptoms. However, there is no previous study of clinical subjective and objective autonomic dysfunction in msTBI.

Methods

We present results from two groups of patients with msTBI. The first, a case–control comparative study, comprises prospectively recruited msTBI outpatients, in whom we measured burden of autonomic symptoms using the Composite Autonomic Symptom Score (COMPASS31) questionnaire. The second, a descriptive case series, comprises retrospectively identified msTBI outpatients who had formal clinical autonomic function testing at a national referral autonomics unit.

Results

Group 1 comprises 39 patients with msTBI (10F:20M, median age 40 years, range 19–76), median time from injury 19 months (range 6–299) and 44 controls (22F:22M, median age 45, range 25–71). Patients had significantly higher mean weighted total COMPASS-31 score than controls (p<0.001), and higher gastrointestinal, orthostatic and secretomotor subscores (corrected p<0.05). Total COMPASS31 score inversely correlated with subjective rating of general health (p<0.001, r_s=−0.84). Group 2 comprises 18 patients with msTBI (7F:11M, median age 44 years, range 21–64), median time from injury 57.5 months (range 2–416). Clinical autonomic function testing revealed a broad spectrum of autonomic dysfunction in 13/18 patients.

Conclusions

There is clinically relevant autonomic dysfunction after msTBI, even at the chronic stage. We advocate for routine enquiry about potential autonomic symptoms, and demonstrate the utility of formal autonomic testing in providing diagnoses. Larger prospective studies are warranted, which should explore the causes and clinical correlates of post-TBI autonomic dysfunction.

Multivariate profile and acute-phase correlates of cognitive deficits in a COVID-19 hospitalised cohort

Background

Preliminary evidence has highlighted a possible association between severe COVID-19 and persistent cognitive deficits. Further research is required to confirm this association, determine whether cognitive deficits relate to clinical features from the acute phase or to mental health status at the point of assessment, and quantify rate of recovery.

Methods

46 individuals who received critical care for COVID-19 at Addenbrooke's hospital between 10th March 2020 and 31st July 2020 (16 mechanically ventilated) underwent detailed computerised cognitive assessment alongside scales measuring anxiety, depression and post-traumatic stress disorder under supervised conditions at a mean follow up of 6.0 (± 2.1) months following acute illness. Patient and matched control (N = 460) performances were transformed into standard deviation from expected scores, accounting for age and demographic factors using N = 66,008 normative datasets. Global accuracy and response time composites were calculated (G_SScore & G_RT). Linear modelling predicted composite score deficits from acute severity, mental-health status at assessment, and time from hospital admission. The pattern of deficits across tasks was qualitatively compared with normal age-related decline, and early-stage dementia.

Findings

COVID-19 survivors were less accurate (G_SScore=-0.53SDs) and slower (G_RT=+0.89SDs) in their responses than expected compared to their matched controls. Acute illness, but not chronic mental health, significantly predicted cognitive deviation from expected scores (G_SScore (p=​​0.0037) and G_RT (p = 0.0366)). The most prominent task associations with COVID-19 were for higher cognition and processing speed, which was qualitatively distinct from the profiles of normal ageing and dementia and similar in magnitude to the effects of ageing between 50 and 70 years of age. A trend towards reduced deficits with time from illness (r∼=0.15) did not reach statistical significance.

Interpretation

Cognitive deficits after severe COVID-19 relate most strongly to acute illness severity, persist long into the chronic phase, and recover slowly if at all, with a characteristic profile highlighting higher cognitive functions and processing speed.

Funding

This work was funded by the National Institute for Health Research (NIHR) Cambridge Biomedical Research Centre (BRC), NIHR Cambridge Clinical Research Facility (BRC-1215-20014), the Addenbrooke's Charities Trust and NIHR COVID-19 BioResource RG9402. AH is funded by the UK Dementia Research Institute Care Research and Technology Centre and Imperial College London Biomedical Research Centre. ETB and DKM are supported by NIHR Senior Investigator awards. JBR is supported by the Wellcome Trust (220258) and Medical Research Council (SUAG/051 G101400). VFJN is funded by an Academy of Medical Sciences/ The Health Foundation Clinician Scientist Fellowship. The views expressed are those of the authors and not necessarily those of the NHS, the NIHR or the Department of Health and Social Care.