Diagnostic test accuracy of a novel smartphone application for the assessment of attention deficits in delirium in older hospitalised patients: a prospective cohort study protocol

A narrative review of the development and performance characteristics of electronic delirium-screening tools

BACKGROUND

Electronic delirium-screening tools are an emergent area of research.

OBJECTIVE

The objective of this study was to summarise the development and performance characteristics of electronic screening tools in delirium.

METHODS

Searches were conducted in Pubmed, Embase, and CINAHL Complete databases to identify electronic delirium-screening tools.

RESULTS

Five electronic delirium-screening tools were identified and reviewed. Two were designed for and tested within a medical setting, and three were applied to intensive care. Adaptive design features, such as skip function to reduce test burden, were variably integrated into instrument design. All tools were shown to have acceptable psychometric properties, but validation studies were largely incomplete.

CONCLUSIONS

Electronic delirium-screening tools are an exciting area of development and may offer hope for improved uptake of delirium screening.

An update on mobile applications collecting data among subjects with or at risk of Alzheimer's disease

Smart mobile phone use is increasing worldwide, as is the ability of mobile devices to monitor daily routines, behaviors, and even cognitive changes. There is a growing opportunity for users to share the data collected with their medical providers which may serve as an accessible cognitive impairment screening tool. Data logged or tracked in an app and analyzed with machine learning (ML) could identify subtle cognitive changes and lead to more timely diagnoses on an individual and population level. This review comments on existing evidence of mobile device applications designed to passively and/or actively collect data on cognition relevant for early detection and diagnosis of Alzheimer's disease (AD). The PubMed database was searched to identify existing literature on apps related to dementia and cognitive health data collection. The initial search deadline was December 1, 2022. Additional literature published in 2023 was accounted for with a follow-up search prior to publication. Criteria for inclusion was limited to articles in English which referenced data collection via mobile app from adults 50+ concerned, at risk of, or diagnosed with AD dementia. We identified relevant literature (n = 25) which fit our criteria. Many publications were excluded because they focused on apps which fail to collect data and simply provide users with cognitive health information. We found that although data collecting cognition-related apps have existed for years, the use of these apps as screening tools remains underdeveloped; however, it may serve as proof of concept and feasibility as there is much supporting evidence on their predictive utility. Concerns about the validity of mobile apps for cognitive screening and privacy issues remain prevalent. Mobile applications and use of ML is widely considered a financially and socially viable method of compiling symptomatic data but currently this large potential dataset, screening tool, and research resource is still largely untapped.

Computerized tool and interdisciplinary care for older patients with delirium in the emergency department: a novel model in Taiwan

AIMS

A computerized tool and interdisciplinary care were implemented to develop a novel model for older patients with delirium in the emergency department (ED).

METHODS

We developed a computerized tool using a delirium triage screen and brief confusion assessment in the hospital information system, performed education for the healthcare providers, and developed a continuous care protocol. Comparisons for outcomes between pre- and post-intervention periods were performed.

RESULTS

Compared with the pre-intervention period, patients in the post-intervention period had shorter hospitalization stay, lower expenditure of hospitalization, more likely to return home, lower ED revisits of ≤ 3 days, re-hospitalization of ≤ 14 days, and mortality of ≤ 1 month. All mentioned differences were not statistically significant.

CONCLUSIONS

A novel model was successfully developed for delirium management in older patients in the ED. Outcome differences were not significant; however, the result is promising, which gives us an important reference in the future.

Validation of the 4AT tool for delirium assessment in specialist palliative care settings: protocol of a prospective diagnostic test accuracy study [version 1; peer review: 2 approved]

BACKGROUND

Delirium is a serious and distressing neuropsychiatric condition, which is prevalent across all palliative care settings. Hypoactive delirium is particularly common, but difficult to recognize, partly due to overlapping symptoms with depression and dementia. Delirium screening tools can lead to earlier identification and hence better management of patients. The 4AT (4 'A's Test) is a brief tool for delirium detection, designed for use in clinical practice. It has been validated in 17 studies in over 3,700 patients. The test is currently used in specialist palliative care units, but has not been validated in this setting. The aim of the study is to determine the diagnostic accuracy of the 4AT for delirium detection against a reference standard, in hospice inpatients.

METHODS

240 participants will be recruited from the inpatient units of two hospices in Scotland. If a patient lacks capacity to consent, agreement will be sought from a legal proxy. Each participant will complete the 4AT and a reference standard assessment based on the diagnostic delirium criteria in the fifth edition of the Diagnostic and Statistical Manual of Mental Disorders (DSM-5). This will be supplemented by tests of cognition and attention, including reverse days of the week, counting down from 20 to 1, Vigilance 'A', the Observational Scale for Level of Arousal, the modified Richmond Agitation Sedation Scale and the Delirium Rating Scale-Revised-98. The assessments will be conducted in a randomized order by two independent clinicians, who will be blinded to the results until both are complete. Primary outcomes will be the sensitivity and specificity of the 4AT in detecting delirium.

DISCUSSION

The findings will inform clinical practice regarding delirium assessment in palliative care settings.

TRIAL REGISTRATION

ISRCTN ISRCTN97417474 (21/02/2020).

A roadmap to advance delirium research: Recommendations from the NIDUS Scientific Think Tank

Delirium is an acute disorder of attention and cognition. It occurs across the life span, yet it is particularly common among older adults, and is closely linked with underlying neurocognitive disorders. Evidence is mounting that intervening on delirium may represent an important opportunity for delaying the onset or progression of dementia. To accelerate the current understanding of delirium, the Network for Investigation of Delirium: Unifying Scientists (NIDUS) held a conference "Advancing Delirium Research: A Scientific Think Tank" in June 2019. This White Paper encompasses the major knowledge and research gaps identified at the conference: advancing delirium definition and measurement, understanding delirium pathophysiology, and prevention and treatment of delirium. A roadmap of research priorities is proposed to advance the field in a systematic, interdisciplinary, and coordinated fashion. A call is made for an international consortium and biobank targeted to delirium, as well as a public health campaign to advance the field.

Biosensors for Personal Mobile Health: A System Architecture Perspective

Advances in mobile biosensors, integrating developments in materials science and instrumentation, are fueling an expansion in health data being collected and analyzed in decentralized settings. For example, semiconductor-based sensors are enabling measurement of vital signs, and microfluidic-based sensors are enabling measurement of biochemical markers. As biosensors for mobile health are becoming increasingly paired with smart devices, it will become critical for researchers to design biosensors - with appropriate functionalities and specifications - to work seamlessly with accompanying connected hardware and software. This article describes recent research in biosensors, as well as current mobile health devices in use, as classified into four distinct system architectures that take into account the biosensing and data processing functions required in personal mobile health devices. We also discuss the path forward for integrating biosensors into smartphone-based mobile health devices.

A software to prevent delirium in hospitalised older adults: development and feasibility assessment

BACKGROUND

non-pharmacological interventions to prevent delirium are useful in hospitalised older adults. However, they are poorly implemented in clinical practice. We aimed to develop a software for bedside use by hospitalised older adults and to improve their access to these interventions.

METHODS

a transdisciplinary team composed of healthcare professionals, designers, engineers and older adults participated in the development of the software. Scrum methodology was used to coordinate the work of the team, and the software was evaluated in a feasibility study.

RESULTS

a software for touchscreen mobile devices that supports Android 5.0 or later was produced, including modules for time-spatial re-orientation, cognitive stimulation, early mobilisation, sensorial support use promotion, sleep hygiene and pain management optimisation. Horizontal disposition, use of colour contrast and large interaction areas were used to improve accessibility. The software's usability and accessibility were evaluated in 34 older adults (average age 73.2 ± 9.1 years) showing that 91.1% of them got access to all the software functions without previous instructions. The clinical feasibility assessment showed that 83.3% of the 30 enrolled hospitalised patients (76 ± 8 years) completed the 5-day protocol of software usage during hospitalisation. Software use was associated with a decreased trend in delirium incidence of 5 of 32 (15.6%) at baseline to 2 of 30 (6.6%) after its implementation.

CONCLUSION

a highly accessible and implementable software, designed to improve access to non-pharmacological interventions to prevent delirium in hospitalised older adults, was developed. The effectiveness of the software will be evaluated in a randomised clinical trial.

A smartphone-based test for the assessment of attention deficits in delirium: A case-control diagnostic test accuracy study in older hospitalised patients

BACKGROUND

Delirium is a common and serious acute neuropsychiatric syndrome which is often missed in routine clinical care. Inattention is the core cognitive feature. Diagnostic test accuracy (including cut-points) of a smartphone Delirium App (DelApp) for assessing attention deficits was assessed in older hospital inpatients.

METHODS

This was a case-control study of hospitalised patients aged ≥65 years with delirium (with or without pre-existing cognitive impairment), who were compared to patients with dementia without delirium, and patients without cognitive impairment. Reference standard delirium assessment, which included a neuropsychological test battery, was based on Diagnostic and Statistical Manual of Mental Disorders-5 criteria. A separate blinded assessor administered the DelApp arousal assessment (score 0-4) and attention task (0-6) yielding an overall score of 0 to 10 (lower scores indicate poorer performance). Analyses included receiver operating characteristic curves and sensitivity and specificity. Optimal cut-points for delirium detection were determined using Youden's index.

RESULTS

A total of 187 patients were recruited, mean age 83.8 (range 67-98) years, 152 (81%) women; n = 61 with delirium; n = 61 with dementia without delirium; and n = 65 without cognitive impairment. Patients with delirium performed poorly on the DelApp (median score = 4/10; inter-quartile range 3.0, 5.5) compared to patients with dementia (9.0; 5.5, 10.0) and those without cognitive impairment (10.0; 10.0, 10.0). Area under the curve for detecting delirium was 0.89 (95% Confidence Interval 0.84, 0.94). At an optimal cut-point of ≤8, sensitivity was 91.7% (84.7%, 98.7%) and specificity 74.2% (66.5%, 81.9%) for discriminating delirium from the other groups. Specificity was 68.3% (56.6%, 80.1%) for discriminating delirium from dementia (cut-point ≤6).

CONCLUSION

Patients with delirium (with or without pre-existing cognitive impairment) perform poorly on the DelApp compared to patients with dementia and those without cognitive impairment. A cut-point of ≤8/10 is suggested as having optimal sensitivity and specificity. The DelApp is a promising tool for assessment of attention deficits associated with delirium in older hospitalised adults, many of whom have prior cognitive impairment, and should be further validated in representative patient cohorts.

Delirium in an Acute Stroke Setting, Occurrence, and Risk Factors

Background and Purpose—

Delirium is a common and serious complication of acute illness. We describe delirium occurrence in an unselected, acute stroke population.

Methods—

We collected data from consecutive stroke admissions. We performed comprehensive cognitive assessment within the first week including Diagnostic Statistical Manual-5–based delirium diagnosis. We reported proportion with delirium and the clinical and demographic associations with delirium using multiple logistic regression.

Results—

Of 708 patients, median age of 71 years (interquartile range, 59–80), we recorded delirium in 187 of 708 (26.4%; 95% CI, 23.0–30.0). Across 395 patients with complete risk factor data (105 delirium), factors independently associated with delirium were: age (odds ratio, 1.05; 95% CI, 1.03–1.08), drug/alcohol misuse (odds ratio, 2.64; 95% CI, 1.10–6.26), and stroke severity (odds ratio, 1.22; 95% CI, 1.14–1.31).

Conclusions—

Delirium is common in acute stroke, affecting 1 in 4. It may be possible to predict those at risk using prestroke and stroke-specific factors.

Clinical Trial Registration—

URL: researchregistry.com . Protocol: 1147.

Delirium detection in older acute medical inpatients: a multicentre prospective comparative diagnostic test accuracy study of the 4AT and the confusion assessment method

BACKGROUND

Delirium affects > 15% of hospitalised patients but is grossly underdetected, contributing to poor care. The 4 'A's Test (4AT, www.the4AT.com ) is a short delirium assessment tool designed for routine use without special training. The primary objective was to assess the accuracy of the 4AT for delirium detection. The secondary objective was to compare the 4AT with another commonly used delirium assessment tool, the Confusion Assessment Method (CAM).

METHODS

This was a prospective diagnostic test accuracy study set in emergency departments or acute medical wards involving acute medical patients aged ≥ 70. All those without acutely life-threatening illness or coma were eligible. Patients underwent (1) reference standard delirium assessment based on DSM-IV criteria and (2) were randomised to either the index test (4AT, scores 0-12; prespecified score of > 3 considered positive) or the comparator (CAM; scored positive or negative), in a random order, using computer-generated pseudo-random numbers, stratified by study site, with block allocation. Reference standard and 4AT or CAM assessments were performed by pairs of independent raters blinded to the results of the other assessment.

RESULTS

Eight hundred forty-three individuals were randomised: 21 withdrew, 3 lost contact, 32 indeterminate diagnosis, 2 missing outcome, and 785 were included in the analysis. Mean age was 81.4 (SD 6.4) years. 12.1% (95/785) had delirium by reference standard assessment, 14.3% (56/392) by 4AT, and 4.7% (18/384) by CAM. The 4AT had an area under the receiver operating characteristic curve of 0.90 (95% CI 0.84-0.96). The 4AT had a sensitivity of 76% (95% CI 61-87%) and a specificity of 94% (95% CI 92-97%). The CAM had a sensitivity of 40% (95% CI 26-57%) and a specificity of 100% (95% CI 98-100%).

CONCLUSIONS

The 4AT is a short, pragmatic tool which can help improving detection rates of delirium in routine clinical care.

TRIAL REGISTRATION

International standard randomised controlled trial number (ISRCTN) 53388093 . Date applied 30/05/2014; date assigned 02/06/2014.