Evidence map›Paper›PMID 36443753›Full record

ArticleHealth research policy and systems2022

Implication of using cognitive function-related simple questions to stratify the risk of long-term care need: population-based prospective study in Kobe, Japan.

Shinsuke Kojima, Takashi Kikuchi, Yasumasa Kakei, Hisatomo Kowa, Yasuji Yamamoto, Hiroyuki Kajita, Tohmi Osaki, Masanori Fukushima, Ryoma Kayano, Yoji Nagai

Open access · goldAbstract read
In one paragraph

Article in Health research policy and systems, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
1.6field-weighted citation impact, top 14% 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

4 citing papers in PubMed, 3 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 5 institutions in 1 country.

Shinsuke KojimaTranslational Research Center for Medical Innovation, Foundation for Biomedical Research and Innovation, Kobe, Hyogo, Japan.
Takashi KikuchiTranslational Research Center for Medical Innovation, Foundation for Biomedical Research and Innovation, Kobe, Hyogo, Japan.
Yasumasa KakeiClinical and Translational Research Center, Kobe University Hospital, Kobe, Hyogo, Japan.
Hisatomo KowaDivision of Cognitive and Psychiatric Rehabilitation, Department of Rehabilitation Science, Kobe University Graduate School of Health Sciences, Kobe, Hyogo, Japan.
Yasuji YamamotoDepartment of Biosignal Pathophysiology, Kobe University Graduate School of Medicine, Kobe, Hyogo, Japan.
Hiroyuki KajitaFaculty of Rehabilitation, Kobe Gakuin University, Kobe, Hyogo, Japan.
Tohmi OsakiFaculty of Rehabilitation, Kobe Gakuin University, Kobe, Hyogo, Japan.
Masanori FukushimaLearning Health Society Institute, Nagoya, Aichi, Japan.
Ryoma KayanoWorld Health Organization Centre for Health Development, Kobe, Hyogo, Japan.
Yoji NagaiDepartment of Clinical Research Facilitation, Institute for Advancement of Clinical and Translational Science, Kyoto University Hospital, 54 Kawaharacho, Shogoin, Sakyo-Ku, Kyoto, 606-8507, Japan. yoji6846@gmail.com.ORCID http://orcid.org/0000-0002-0836-0495
Foundation for Biomedical Research and Innovation · JPKobe Gakuin University · JPKobe University · JPKobe University Hospital · JPKyoto University Hospital · JP

Funding

World Health Organization 001World Health Organization Center for Health Development K18001
6 · The paper itself

Abstract

backgroundThis study investigated how cognitive function-related simple questions can be used to identify older individuals who are at risk of needing long-term care.

methodsThis cohort study was conducted in Kobe city, Japan. In 2015, the municipal office distributed the Kihon Checklist by post, a 25-item questionnaire including three cognitive function-related questions (questions 18, 19, 20) to citizens aged ≥ 70 years. Need certification is routinely done by Kobe city as part of the national Long-Term Care Insurance Act. The answers to the 2015 questionnaire were merged with need certification data between the questionnaire delivery and the end of December 2019.

resultsOf the 77,877 citizens (age: 72.9 ± 2.7 years) who received the questionnaire, 50,154 responded (response rate: 64.4%). During the study period, the cumulative incidence of the need for long-term care was higher in those who did not respond than in those who did (12.5% vs 8.4%; P < 0.001). Among those who responded, the incidence of the need for long-term care was progressively greater as the number of negative answers to cognitive function-related questions increased (5.0%, 8.4%, 15.7% and 30.2% at 4 years' follow-up, for respondents with, respectively, 0, 1, 2 and 3 negative answers). Similarly, when the need certification for long-term care was confined to that accompanied by dementia, the incidence also rose as the number of negative responses to the cognitive function-related questions increased (3.4%, 6.5%, 13.7% and 27.9% for respondents with, respectively, 0, 1, 2 and 3 negative answers). Using multivariate Cox regression analysis, all three cognitive function-related questions were predictive of the need for long-term care, and question 18 (about memory loss) had the highest hazard ratio for predicting the need for long-term care accompanied by dementia.

conclusionsUse of cognitive function-related simple questions may help identify older adults at risk for needing long-term care, suggesting their potential value for use in administrative and policy approaches aimed at reducing the societal burden of dementia.

Indexed as

DementiaLong-Term CareAgedCognitionCohort StudiesHumansJapanProspective StudiesAdministrative dataDementiaFrailtyLong-term carePopulation-based study

Identifiers

PMID36443753
PMCPMC9706818
OpenAlexW4310588943

What OpenQuestion holds

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LicenceCC BY
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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.