Evidence map›Paper›PMID 42687507›Full record

ReviewCNS neuroscience & therapeutics2026

Mild Cognitive Impairment Diagnosis and Care Algorithms and the Role of Digital Interventions: Expert Consensus.

Nagaendran Kandiah, Yee Fai Chan, Darwin Dasig, Jacqueline Dominguez, Kar Chai Koh, Si Ching Lim, Paulus Anam Ong, Encarnita Raya-Ampil, Raymond Chee Seong Seet, Vorapun Senanarong and 7 more

Abstract readConsensus StatementReview
In one paragraph

Review in CNS neuroscience & therapeutics, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

17 authors.

Nagaendran KandiahDementia Research Centre, Singapore, Singapore.ORCID https://orcid.org/0000-0001-9244-4298
Yee Fai ChanHospital Kuala Lumpur, Wilayah Persekutuan Kuala Lumpur, Malaysia.ORCID https://orcid.org/0009-0003-5639-7182
Darwin DasigMakati Medical Centre, Makati, Philippines.
Jacqueline DominguezSt Luke's Medical Center Bonafacio Global City, Makati, Philippines.ORCID https://orcid.org/0000-0003-2017-7797
Kar Chai KohPoliklinik Kepong Baru, Wilayah Persekutuan Kuala Lumpur, Malaysia.ORCID https://orcid.org/0000-0001-8615-0760
Si Ching LimChangi General Hospital, Singapore, Singapore.
Paulus Anam OngHasan Sadikin Hospital, Bandung, Indonesia.
Encarnita Raya-AmpilSt Luke's Medical Center Bonafacio Global City, Makati, Philippines.ORCID https://orcid.org/0000-0003-2068-1088
Raymond Chee Seong SeetYong Loo Lin School of Medicine, National University of Singapore, and National University Hospital, Singapore, Singapore.ORCID https://orcid.org/0000-0001-8946-3578
Vorapun SenanarongFaculty of Medicine Siriraj Hospital, Mahidol University, Bangkok, Thailand.ORCID https://orcid.org/0009-0006-0389-4793
Kit Mun TanUniversiti Malaya, Wilayah Persekutuan Kuala Lumpur, Malaysia.ORCID https://orcid.org/0000-0003-1611-3109
Maw Pin TanUniversiti Malaya, Wilayah Persekutuan Kuala Lumpur, Malaysia.ORCID https://orcid.org/0000-0002-3400-8540
Trần Công ThắngUniversity Medical Center HCMC, Ho Chi Minh City, Vietnam.ORCID https://orcid.org/0000-0001-7467-9261
Tong Mai TrangUniversity Medical Center HCMC, Ho Chi Minh City, Vietnam.ORCID https://orcid.org/0000-0001-7210-785X
Yuda TuranaSchool of Medicine and Health Sciences, Atma Jaya Catholic University of Indonesia, North Jakarta, Indonesia.ORCID https://orcid.org/0000-0003-4527-0285
Cuibai WeiXuanwu Hospital Capital Medical University, Beijing, China.ORCID https://orcid.org/0009-0004-7380-7451
Ralf IhlUniversity of Duesseldorf, Düsseldorf, Germany.ORCID https://orcid.org/0000-0002-8074-5437

Funding

Schwabe Pharma Asia Pacific Pte Ltd
6 · The paper itself

Abstract

backgroundMild cognitive impairment (MCI) is a clinically recognized condition, often being a prodromal dementia state with a risk of further cognitive decline. While there is currently no definitive diagnostic test for MCI, early identification and intervention are important.

methodsTo assist clinicians in the diagnosis and treatment of MCI, the ASian Clinical Expert group on Neurocognitive Disorders (ASCEND) convened to identify ongoing gaps in MCI management primarily in Asia, and to discuss the existing body of literature with a view to providing evidence-based expert recommendations.

resultsTwo novel algorithms and a set of expert recommendations were formulated, addressing the cognitive assessment and clinical diagnosis of MCI, and optimal MCI management approaches. Because many risk factors for cognitive decline are modifiable, the mainstay of intervention comprises a multi-domain approach involving optimizing metabolic health, mitigating cerebrovascular risk, correcting hearing and vision loss, treating depression, encouraging engagement in cognitive exercises and social connection, and avoiding harmful substances. Digital interventions are becoming increasingly important as tools for cognitive assessment, as well as for cognitive stimulation and to help patients self-manage and maintain their independence. Pharmacologic approaches for MCI management include medical management of cardiovascular risk, reducing cholinergic burden and the use of drugs known to sedate or affect cognitive function, and evidence-based medications that have demonstrated benefit specifically in MCI.

conclusionsThese evidence-based recommendations are intended to support clinicians, particularly in primary care, to identify MCI and plan an intervention strategy to help slow age-related cognitive decline.

Indexed as

AlgorithmsCognitive DysfunctionCognitive TrainingDigital HealthDigital MediaHumansdementiageriatricsGinkgo bilobamemory disordersmild cognitive impairmentneurocognitive disorders

Identifiers

PMID42687507
PMCPMC13539218

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.