Evidence map›Paper›PMID 39104490›Full record

ArticleHeliyon2024

Development of cognitive frailty screening tool among community-dwelling older adults.

Nurul Fatin Malek Rivan, Suzana Shahar, Devinder Kaur Ajit Singh, Normah Che Din, Hazlina Mahadzir, Yee Xing You, Mohd Zul Amin Kamaruddin

Abstract read
In one paragraph

Article in Heliyon, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers, 1 of them a synthesis that pooled it.

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

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

  1. Pooled it
  2. Article
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  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

7 authors.

Nurul Fatin Malek RivanNutritional Sciences Programme and Centre for Healthy Ageing and Wellness (H-CARE), Faculty of Health Sciences, Universiti Kebangsaan Malaysia, Jalan Raja Muda Abdul Aziz, 50300, Kuala Lumpur, Malaysia.
Suzana ShaharDietetics Programme and Centre for Healthy Ageing and Wellness (H-CARE), Faculty of Health Sciences, Universiti Kebangsaan Malaysia, Jalan Raja Muda Abdul Aziz, 50300, Kuala Lumpur, Malaysia.
Devinder Kaur Ajit SinghPhysiotherapy Programme & Centre for Healthy Ageing and Wellness (H-CARE), Universiti Kebangsaan Malaysia, Jalan Raja Muda Abdul Aziz, 50300, Kuala Lumpur, Malaysia.
Normah Che DinHealth Psychology Programme and Centre of Rehabilitation Science, Faculty of Health Sciences, Universiti Kebangsaan Malaysia, Jalan Raja Muda Abdul Aziz, 50300, Kuala Lumpur, Malaysia.
Hazlina MahadzirInternal Medicine & Geriatric Department, Pusat Perubatan Universiti Kebangsaan Malaysia, Jalan Yaacob Latif, Bandar Tun Razak, 56000 Batu 9 Cheras, Kuala Lumpur, Malaysia.
Yee Xing YouDietetics Programme and Centre for Healthy Ageing and Wellness (H-CARE), Faculty of Health Sciences, Universiti Kebangsaan Malaysia, Jalan Raja Muda Abdul Aziz, 50300, Kuala Lumpur, Malaysia.
Mohd Zul Amin KamaruddinCentre for Healthy Ageing and Wellness (H-CARE), Faculty of Health Sciences, Universiti Kebangsaan Malaysia, Jalan Raja Muda Abdul Aziz, 50300, Kuala Lumpur, Malaysia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Purpose: To develop a brief screening tool consisting of twelve items that can be self-administered for rapid identification of older adults at risk of cognitive frailty (CF), named as Cognitive Frailty Screening Tool (CFST). Patients and methods: A total of 1318 community-dwelling individuals aged 60 years and above were selected and assessed for cognitive frailty using a set of neuropsychology batteries and physical function tests. A binary logistic regression (BLR) was used to identify predictors of CF to be used as items in the screening tool. A suitable cut-off point was developed using receiver operating characteristic analysis. Results: Twelve items were included in the screening tool, comprising of gender, education years, medical history, depressive symptoms and functional status as well as lifestyle activities. The area under the curve (AUC) was 0.817 (95 % CI:0.774-0.861), indicating an excellent discriminating power. The sensitivity and specificity for cut-off 7 were 80.8 % and 79.0 %, with an acceptable range of positive predictive value (PPV) (73.3 %) and negative predictive value (NPV) (85.2 %) for screening tools. Concurrent validity of CFST score with standard cognitive and frailty assessment tools shows a significant association with the total score of CFST with low to moderate correlation (p < 0.05 for all parameters). Conclusion: CFST had good sensitivity and specificity and was valid for community-dwelling older adults. There is a need to evaluate further the cost-effectiveness of implementing CFST as a screening for the risk of CF in the community. Its usage in clinical settings needs further validation.

Indexed as

Cognitive frailtyScreening toolSensitivitySpecificityValidation

Identifiers

PMID39104490
PMCPMC11298820

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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.