Evidence map›Paper›PMID 38495786›Full record

Observational studyFrontiers in endocrinology2024

Unveiling peripheral neuropathy and cognitive dysfunction in diabetes: an observational and proof-of-concept study with video games and sensor-equipped insoles.

Antao Ming, Elisabeth Lorek, Janina Wall, Tanja Schubert, Nils Ebert, Imke Galatzky, Anne-Katrin Baum, Wenzel Glanz, Sebastian Stober, Peter R Mertens

Open access · goldAbstract readObservational Study
In one paragraph

Observational study in Frontiers in endocrinology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
2.2field-weighted citation impact, top 13% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

7 citing papers in PubMed, 6 citations in OpenAlex.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors at 2 institutions in 1 country.

Antao MingUniversity Clinic for Nephrology and Hypertension, Diabetology and Endocrinology, Otto-von-Guericke University Magdeburg, Magdeburg, Germany.
Elisabeth LorekUniversity Clinic for Nephrology and Hypertension, Diabetology and Endocrinology, Otto-von-Guericke University Magdeburg, Magdeburg, Germany.
Janina WallUniversity Clinic for Nephrology and Hypertension, Diabetology and Endocrinology, Otto-von-Guericke University Magdeburg, Magdeburg, Germany.
Tanja SchubertUniversity Clinic for Nephrology and Hypertension, Diabetology and Endocrinology, Otto-von-Guericke University Magdeburg, Magdeburg, Germany.
Nils EbertUniversity Clinic for Nephrology and Hypertension, Diabetology and Endocrinology, Otto-von-Guericke University Magdeburg, Magdeburg, Germany.
Imke GalatzkyUniversity Clinic for Neurology, Otto-von-Guericke University Magdeburg, Magdeburg, Germany.
Anne-Katrin BaumUniversity Clinic for Neurology, Otto-von-Guericke University Magdeburg, Magdeburg, Germany.
Wenzel GlanzInstitute of Cognitive Neurology and Dementia Research, Otto-von-Guericke University Magdeburg, Magdeburg, Germany.
Sebastian StoberArtificial Intelligence Lab, Otto-von-Guericke University Magdeburg, Magdeburg, Germany.
Peter R MertensUniversity Clinic for Nephrology and Hypertension, Diabetology and Endocrinology, Otto-von-Guericke University Magdeburg, Magdeburg, Germany.
Otto-von-Guericke University Magdeburg · DEUniversity Clinic for Nephrology and Hypertension, Diabetology and Endocrinology · DE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Proactive screening for cognitive dysfunction (CD) and peripheral neuropathy (PNP) in elderly patients with diabetes mellitus is essential for early intervention, yet clinical examination is time-consuming and prone to bias. Objective: We aimed to investigate PNP and CD in a diabetes cohort and explore the possibility of identifying key features linked with the respective conditions by machine learning algorithms applied to data sets obtained in playful games controlled by sensor-equipped insoles. Methods: In a cohort of patients diagnosed with diabetes (n=261) aged over 50 years PNP and CD were diagnosed based on complete physical examination (neuropathy symptom and disability scores, and Montreal Cognitive Assessment). In an observational and proof-of-concept study patients performed a 15 min lasting gaming session encompassing tutorials and four video games with 5,244 predefined features. The steering of video games was solely achieved by modulating plantar pressure values, which were measured by sensor-equipped insoles in real-time. Data sets were used to identify key features indicating game performance with correlation regarding CD and PNP findings. Thereby, machine learning models (e.g. gradient boosting and lasso and elastic-net regularized generalized linear models) were set up to distinguish patients in the different groups. Results: PNP was diagnosed in 59% (n=153), CD in 34% (n=89) of participants, and 23% (n=61) suffered from both conditions. Multivariable regression analyses suggested that PNP was positively associated with CD in patients with diabetes (adjusted odds ratio = 1.95; 95% confidence interval: 1.03-3.76; Conclusions: The video game-based assessment was able to categorize patients with CD and/or PNP with high accuracy. Future studies with larger cohorts are needed to validate these results and potentially enhance the discriminative power of video games.

Indexed as

Cognitive DysfunctionDiabetes MellitusPeripheral Nervous System DiseasesVideo GamesAgedHumansMiddle Agedcognitive dysfunctiondiabetes mellitusmachine learningperipheral neuropathysensor-equipped insolesvideo games

Identifiers

PMID38495786
PMCPMC10941030
OpenAlexW4392356853

What OpenQuestion holds

Textmetadata
LicenceCC BY
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Registered trials

None linked

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 OpenQuestion graph.