Evidence map›Paper›PMID 37428401›Full record

ReviewCurrent neurology and neuroscience reports2023

Cognitive Interventions for Neurodegenerative Disease.

Jason W Krellman, Giulia Mercuri

Abstract readReview
PubMed Publisher
In one paragraph

Review in Current neurology and neuroscience reports, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed, 2 pooled it
6.1field-weighted citation impact, top 3% 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

13 citing papers in PubMed, 2 syntheses or guidelines pooled it, 24 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

2 authors at 1 institution in 1 country.

Jason W KrellmanDepartment of Neurology, Columbia University Irving Medical Center, 710 West 168Th Street, New York, NY, 10032-3784, USA. jk3878@cumc.columbia.edu.ORCID 0009-0000-1662-2128
Giulia MercuriDepartment of Neurology, Columbia University Irving Medical Center, 710 West 168Th Street, New York, NY, 10032-3784, USA.
Columbia University Irving Medical Center · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purpose of reviewTo critically review recent research in the development of non-pharmacological interventions to improve cognitive functioning in individuals with Alzheimer's disease (AD) or Parkinson's disease (PD). RECENT

findingsCognitive interventions can be grouped into three categories: cognitive stimulation (CS), cognitive training (CT), and cognitive rehabilitation (CR). CS confers temporary, nonspecific benefits and might slightly reduce dementia risk for neurologically healthy individuals. CT can improve discrete cognitive functions, but durability is limited and real-world utility is unclear. CR treatments are holistic and flexible and, therefore, most promising but are difficult to simulate and study under rigorous experimental conditions. Optimally effective CR is unlikely to be found in a single approach or treatment paradigm. Clinicians must be competent in a variety of interventions and select those interventions best tolerated by the patient and most relevant to their needs and goals. The progressive nature of neurodegenerative disease necessitates that treatment be consistent, open-ended in duration, and sufficiently dynamic to meet the patient's changing needs as their disease progresses.

Indexed as

Alzheimer DiseaseCognitive Behavioral TherapyNeurodegenerative DiseasesParkinson DiseaseCognitionHumansCognitive trainingMultidisciplinaryNeurodegenerative diseaseNeuropsychological rehabilitationNon-pharmacological interventions

Identifiers

PMID37428401
OpenAlexW4383710934

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.