Evidence map›Paper›PMID 32145744›Full record

ArticleBMC neurology2020

Sensor-based systems for early detection of dementia (SENDA): a study protocol for a prospective cohort sequential study.

Katrin Müller, Stephanie Fröhlich, Andresa M C Germano, Jyothsna Kondragunta, Maria Fernanda Del Carmen Agoitia Hurtado, Julian Rudisch, Daniel Schmidt, Gangolf Hirtz, Peter Stollmann, Claudia Voelcker-Rehage

Abstract readClinical Trial Protocol
PubMed Full text at PMC Publisher
In one paragraph

Article in BMC neurology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed, 1 pooled it
–field-weighted citation impact
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

15 citing papers in PubMed, 1 synthesis or guideline pooled it.

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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.

Katrin MüllerDepartment of Sports Psychology (with focus on prevention and rehabilitation), Institute of Human Movement Science and Health, Faculty of Behavioural and Social Sciences, Chemnitz University of Technology, Thüringer Weg 11, 09126, Chemnitz, Germany. katrin.mueller@hsw.tu-chemnitz.de.
Stephanie FröhlichDepartment of Sports Psychology (with focus on prevention and rehabilitation), Institute of Human Movement Science and Health, Faculty of Behavioural and Social Sciences, Chemnitz University of Technology, Thüringer Weg 11, 09126, Chemnitz, Germany.
Andresa M C GermanoDepartment of Human Locomotion, Institute of Human Movement Science and Health, Faculty of Behavioural and Social Sciences, Chemnitz University of Technology, Chemnitz, Germany.
Jyothsna KondraguntaDepartment of Digital Signal Processing and Circuit Technology, Faculty of Electrical Engineering and Information Technology, Chemnitz University of Technology, Chemnitz, Germany.
Maria Fernanda Del Carmen Agoitia HurtadoDepartment of Analysis, Faculty of Mathematics, Chemnitz University of Technology, Chemnitz, Germany.
Julian RudischDepartment of Sports Psychology (with focus on prevention and rehabilitation), Institute of Human Movement Science and Health, Faculty of Behavioural and Social Sciences, Chemnitz University of Technology, Thüringer Weg 11, 09126, Chemnitz, Germany.
Daniel SchmidtDepartment of Human Locomotion, Institute of Human Movement Science and Health, Faculty of Behavioural and Social Sciences, Chemnitz University of Technology, Chemnitz, Germany.
Gangolf HirtzDepartment of Digital Signal Processing and Circuit Technology, Faculty of Electrical Engineering and Information Technology, Chemnitz University of Technology, Chemnitz, Germany.
Peter StollmannDepartment of Analysis, Faculty of Mathematics, Chemnitz University of Technology, Chemnitz, Germany.
Claudia Voelcker-RehageDepartment of Sports Psychology (with focus on prevention and rehabilitation), Institute of Human Movement Science and Health, Faculty of Behavioural and Social Sciences, Chemnitz University of Technology, Thüringer Weg 11, 09126, Chemnitz, Germany.

Funding

European Social Fund for Germany and the Sächsische Aufbaubank-Förderbank (SAB) of the Free State of Saxony 100310502
6 · The paper itself

Abstract

backgroundDementia and cognitive decline are serious social and economic burdens. An increase in the population of older people, as well as longer lifespans mean that numbers of dementia cases are exponentially rising. Neuropathological changes associated with dementia are thought to appear before the clinical manifestation of cognitive symptoms, i.e., memory impairments. Further, some older adults (OA) experience cognitive decline before it can be objectively diagnosed. For optimal care of these patients, it is necessary to detect cognitive decline and dementia at an early stage. In this vein, motor, sensory, and neurophysiological declines could be promising factors if found to be present before the onset of cognitive impairment. Hence, the objective of the SENDA study is to develop a multi-dimensional sensor-based instrument that allows early detection of cognitive decline or dementia in OA with the help of cognitive, sensory, motor, and neurophysiological parameters before its clinical manifestation. METHODS/

designIn the cohort sequential study, participants are assigned to one of three study groups depending on their cognitive status: 1. cognitively healthy individuals (CHI), 2. subjectively cognitively impaired persons (SCI), or 3. (possible) mildly cognitively impaired persons (pMCI, MCI). All groups take part in the same cognitive (e.g., executive function tests), motor (e.g., gait analyses, balance tests), sensory (e.g., vibration perception threshold test, proprioception tests), and neurophysiological (e.g., electroencephalograms) measurements. Depending on the time at which participants are included into the study, all measurements are repeated up to four times in intervals of 8 months within 3 years to identify associations with cognitive changes over time. DISCUSSION: This study aims to detect possible motor, sensory, neurophysiological, and cognitive predictors to develop an early screening tool for dementia and its pre-stages in OA. Thus, affected persons could receive optimal health care at an earlier time point to maintain their health resources. TRIAL STATUS: The study is ongoing. The recruitment of participants will be continued until May 2020.

Indexed as

Aged, 80 and overCognitive DysfunctionCohort StudiesDementiaEarly DiagnosisExecutive FunctionHumansProspective StudiesDementiaEarly detectionEEGGait analysesMCIMotor performanceProprioceptionSensitivity

Identifiers

PMID32145744
PMCPMC7060588

What OpenQuestion holds

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Registered trials

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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.