Evidence map›Paper›PMID 31420690›Full record

ReviewDer Nervenarzt2019

[Innovation in diagnostics-mobile technologies].

Emrah Düzel, Jochen René Thyrian, David Berron

Abstract readReview
PubMed Publisher
In one paragraph

Review in Der Nervenarzt, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
–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

5 citing papers in PubMed.

  1. Article
  2. Article
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  4. Article
  5. Review
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

3 authors.

Emrah DüzelInstitut für Kognitive Neurologie und Demenzforschung (IKND), Magdeburg, Deutschland. Emrah.duezel@dzne.de.
Jochen René ThyrianDeutsches Zentrum für Neurodegenerative Erkrankungen (DZNE), Standort Greifswald, Greifswald, Deutschland.
David BerronInstitut für Kognitive Neurologie und Demenzforschung (IKND), Magdeburg, Deutschland.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundProgressive cognitive deficits are the main clinical symptom of Alzheimer's disease; however, the precise recording of cognitive deficits and assessment of their progression pose major problems in patient care and early interventions.

objectiveWhich problems for care and early intervention result from the current practice of cognitive assessment of patients with memory problems and which opportunities arise from the use of mobile apps? MATERIAL AND

methodsEvaluation of current care structures, discussion of basic work, expert recommendations and current developments.

resultsThe current practice of the pencil and paper-based diagnostics of cognitive deficits, which is temporally and spatially bound to a clinical environment, constrains the feasibility, validity and reliability of cognitive assessment and the quantification of progression. This limits the meaningful use of further diagnostic measures, such as magnetic resonance imaging (MRI) and cerebrospinal fluid (CSF) analyses. Recent progress in mobile app-based technologies, illustrated here with the example of the neotiv app, can help to overcome these problems.

conclusionMobile app-based technologies can help to improve the cognitive assessment of patients with the main symptom of memory complaints. They can reduce overuse and underuse of diagnostic and therapeutic pathways and enable a targeted and meaningful use of advanced diagnostics. In addition, they can structure risk-modifying preventive measures, identify iatrogenic impairment of cognition and in this respect also strengthen patient competence.

Indexed as

Alzheimer DiseaseCognitive DysfunctionMobile ApplicationsDisease ProgressionHumansReproducibility of ResultsAlzheimer’s diseaseCognitionMild cognitive impairmentMobile appsNeuropsychology

Identifiers

What OpenQuestion holds

Textmetadata
Read underepoch 390

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.