Harnessing digital health to objectively assess cognitive impairment in people undergoing hemodialysis process: The Impact of cognitive impairment on mobility performance measured by wearables

Zhou, He; Al-Ali, Fadwa; Wang, Changhong; Hamad, Abdullah; Ibrahim, Rania; Talal, Talal; Najafi, Bijan

doi:10.1371/journal.pone.0225358

Cited by 6 publications

(4 citation statements)

References 62 publications

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“…Assessment of functionality in everyday activities and mobility performance metrics such as the gait speed assessment could also offer hints of cognitive decline. For instance, mobility performance metrics that involved multifaceted coordination between different parts of neuropsychology, such as cumulated posture duration and postural transition, could assist in discriminating those with and without CI [ 14 ]. CI suspicion may lead to a global and comprehensive patient assessment, especially screening for factors affecting cognitive performance.…”

Section: Introductionmentioning

confidence: 99%

Cognitive disorders in patients with chronic kidney disease: specificities of clinical assessment

Arıcı

Bachman

Barbieri

et al. 2021

Nephrology Dialysis Transplantation

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Neurocognitive disorders are frequent among chronic kidney disease (CKD) patients. Identifying and characterizing cognitive impairment (CI) can help to assess the ability of adherence to CKD risk reduction strategy, identify potentially reversible causes of cognitive decline, modify pharmacotherapy, educate the patient and caregiver and provide appropriate patient and caregiver support. Numerous factors are associated with the development and progression of CI in CKD patients and various conditions can influence the results of cognitive assessment in these patients. Here we review clinical warning signs that should lead to cognitive screening; conditions frequent in CKD at risk to interfere with cognitive testing or performance, including specificities of cognitive assessment in dialysis patients or after kidney transplantation; and available tests for screening and observed cognitive patterns in CKD patients.

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Section: Introductionmentioning

confidence: 99%

Cognitive disorders in patients with chronic kidney disease: specificities of clinical assessment

Arıcı

Bachman

Barbieri

et al. 2021

Nephrology Dialysis Transplantation

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“…Even though it has high computational requirements, it delivered consistent accuracy (above 89%) across multiple studies. 33 Moreover, it incorporates characteristics of SVM which is the most commonly adopted AI algorithm, as evaluated in this study.…”

Section: Discussionmentioning

confidence: 99%

The application of artificial intelligence and custom algorithms with inertial wearable devices for gait analysis and detection of gait-altering pathologies in adults: A scoping review of literature

et al. 2022

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Background The purpose of this scoping review was to explore the current applications of objective gait analysis using inertial measurement units, custom algorithms and artificial intelligence algorithms in detecting neurological and musculoskeletal gait altering pathologies from healthy gait patterns. Methods Literature searches were conducted of four electronic databases (Medline, PubMed, Embase and Web of Science) to identify studies that assessed the accuracy of these custom gait analysis models with inputs derived from wearable devices. Data was collected according to the preferred reporting items for systematic reviews and meta-analysis statement guidelines. Results A total of 23 eligible studies were identified for inclusion in the present review, including 10 custom algorithms articles and 13 artificial intelligence algorithms articles. Nine studies evaluated patients with Parkinson’s disease of varying severity and subtypes. Support vector machine was the commonest adopted artificial intelligence algorithm model, followed by random forest and neural networks. Overall classification accuracy was promising for articles that use artificial intelligence algorithms, with nine articles achieving more than 90% accuracy. Conclusions Current applications of artificial intelligence algorithms are reasonably effective discrimination between pathological and non-pathological gait. Of these, machine learning algorithms demonstrate the additional capacity to handle complicated data input, when compared to other custom algorithms. Notably, there has been increasing application of machine learning algorithms for conducting gait analysis. More studies are needed with unsupervised methods and in non-clinical settings to better reflect the community and home-based usage.

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“…HD has yet to be determined but appears to be multifactorial, related to vascular and non-vascular components and HD process (Cleary & Drennan, 2005;Pi et al, 2016;Zhou et al, 2020).…”

Section: The Aetiology Of Cognitive Impairment In Patients Undergoingmentioning

confidence: 99%

“…The aetiology of cognitive impairment in patients undergoing HD has yet to be determined but appears to be multifactorial, related to vascular and non‐vascular components and HD process (Cleary & Drennan, 2005; Pi et al, 2016; Zhou et al, 2020). Cognitive impairment is associated with increased risk of both morbidity and mortality in patients undergoing HD (Angermann et al, 2018; Drew et al, 2015; Kallenberg et al, 2016).…”

Section: Introductionmentioning

confidence: 99%

Effect of exercise on cognitive impairment in patients undergoing haemodialyses: A systematic review and meta‐analysis of randomised controlled trials

Liu

Song

Zhao

et al. 2022

Journal of Renal Care

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Background: The influence of exercise on cognition in patients undergoing haemodialysis has been examined. However, evidence elucidating the effects in this patient group is scarce.Objective: To examine the effect of exercise on cognitive impairment in patients undergoing haemodialysis and provide insight into the effects of various characteristics of exercise on cognitive impairment in this population.Design: A systematic review and meta-analysis, following the guidance of PRISMA was undertaken.Participants: Adult patients undergoing haemodialysis.Results: This review found that exercise significantly improved cognitive impairment in patients undergoing haemodialysis (SMD = 0.37, 95% CI: 0.13, 0.60, p = 0.002). Subgroup analyses demonstrated that both intradialytic exercise (SMD = 0.82, 95% CI: 0.37, 1.26, p < 0.001) and interdialytic exercise (SMD = 0.24, 95% CI: 0.01, 0.47, p = 0.038), exercise for 16 weeks or over (SMD = 0.33, 95% CI: 0.07, 0.58, p = 0.012), and lasting for more than 30 minutes (SMD = 0.52, 95% CI: 0.17, 0.86, p = 0.004) significantly alleviated cognitive impairment. The effect of exercise on cognitive impairment in patients less than 65 years of age (SMD = 0.39, 95% CI: 0.10, 0.68, p = 0.009) was significantly better than those over 65. Conclusion:Exercise significantly improves cognitive impairment in patients undergoing haemodialysis. Both Intradialytic and interdialytic exercise of at least 30 minutes duration, 3 times weekly, and at least for 16 weeks may play a significant role in alleviating cognitive impairment in patients under 65 years of age.

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Harnessing digital health to objectively assess cognitive impairment in people undergoing hemodialysis process: The Impact of cognitive impairment on mobility performance measured by wearables

Cited by 6 publications

References 62 publications

Cognitive disorders in patients with chronic kidney disease: specificities of clinical assessment

Cognitive disorders in patients with chronic kidney disease: specificities of clinical assessment

The application of artificial intelligence and custom algorithms with inertial wearable devices for gait analysis and detection of gait-altering pathologies in adults: A scoping review of literature

Effect of exercise on cognitive impairment in patients undergoing haemodialyses: A systematic review and meta‐analysis of randomised controlled trials

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