Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2020 Apr 3:11:558.
doi: 10.3389/fpsyg.2020.00558. eCollection 2020.

Screening for Cognitive Frailty Using Short Cognitive Screening Instruments: Comparison of the Chinese Versions of the MoCA and Q mci Screen

Affiliations

Screening for Cognitive Frailty Using Short Cognitive Screening Instruments: Comparison of the Chinese Versions of the MoCA and Q mci Screen

Yangfan Xu et al. Front Psychol. .

Abstract

Background: Cognitive frailty describes cognitive impairment associated with physical decline. Few studies have explored whether short cognitive screens identify frailty. We examined the diagnostic accuracy of the Chinese versions of the Quick Mild Cognitive Impairment (Qmci-CN) screen and Montreal Cognitive Assessment (MoCA-CN) in identifying cognitive frailty.

Methods: Ninety-five participants with cognitive symptoms [47 with mild cognitive impairment (MCI), 34 with subjective cognitive disorder, and 14 with dementia] were included from two outpatient rehabilitation clinics. Energy (work intensity) and physical activity levels were recorded. Cognitive frailty was diagnosed by an interdisciplinary team using the IANA/IAGG consensus criteria, stratified on the Clinical Frailty Scale (CFS). Instruments were administered sequentially and randomly by trained assessors, blind to the diagnosis.

Results: The mean age of the sample was 62.6 ± 10.2 years; median CFS score was 4 ± 1 and 36 (38%) were cognitively frail. The Qmci-CN had similar accuracy in differentiating the non-frail from cognitively frail compared to the MoCA-CN, AUC 0.82 versus 0.74, respectively (p = 0.19). At its optimal cut-off (≤55/100), the Qmci-CN provided a sensitivity of 83% and specificity of 67% versus 91% and 51%, respectively, for the MoCA-CN (≤23/30). Neither was accurate in separating MCI from cognitive frailty but both accurately separated cognitive frailty from dementia.

Conclusion: Established short cognitive screens may be useful in identifying cognitive frailty in Chinese adults with cognitive complaints but not in separating MCI from cognitive frailty. The Qmci-CN had similar accuracy to the MoCA-CN and a shorter administration time in this small and under-powered study, necessitating the need for adequately powered studies in different healthcare settings.

Keywords: China; cognitive frailty; cognitive screen; dementia; frailty; mild cognition impairment.

PubMed Disclaimer

Figures

FIGURE 1
FIGURE 1
Scatterplots showing the relationship between administration time and scores on the (A) Chinese versions of the Quick Mild Cognitive Impairment (Qmci-CN) screen and (B) Montreal Cognitive Assessment (MoCA-CN).
FIGURE 2
FIGURE 2
Receiver Operating Characteristic (ROC) curve analysis comparing the Chinese versions of the Quick Mild Cognitive Impairment (Qmci-CN) screen and Montreal Cognitive Assessment (MoCA-CN) in identifying (A) cognitive frailty from non-frailty and (B) cognitive frailty from other patients presenting with symptomatic memory loss.
FIGURE 3
FIGURE 3
Receiver Operating Characteristic (ROC) curve analysis comparing the Chinese versions of the Quick Mild Cognitive Impairment (Qmci-CN) screen and Montreal Cognitive Assessment (MoCA-CN) in separating subjective cognitive disorder (SCD), mild cognitive impairment (MCI) and dementia. (A) Cognitive impairment (MCI/Dementia vs. SCD). (B) Dementia (vs. MCI/SCD). (C) Dementia vs. SCD. (D) Dementia vs. MCI. (E) MCI vs. SCD.

References

    1. Albert M. S., DeKosky S. T., Dickson D., Dubois D., Feldman H. H., Fox N. C., et al. (2011). The diagnosis of mild cognitive impairment due to Alzheimer’s disease: recommendations from the National Institute on Aging-Alzheimer’s Association workgroups on diagnostic guidelines for Alzheimer’s disease. Alzheimers Dement. 7 270–279. - PMC - PubMed
    1. Amanzio M., Palermo S., Zucca M., Rosato R., Rubino E., Leotta D., et al. (2017). Neuropsychological correlates of pre-Frailty in neurocognitive disorders: a possible role for metacognitive dysfunction and mood changes. Front. Med. 4:199. 10.3389/fmed.2017.00199 - DOI - PMC - PubMed
    1. American Psychiatric Association [APA], (1994). Diagnostic and Statistical Manual of Mental Disorders, 4thed Edn Washington, DC: American Psychiatric Association.
    1. Apóstolo J., Cooke R., Bobrowicz-Campos E., Santana S., Holland C. (2018). Effectiveness of interventions to prevent pre-frailty and frailty progression in older adults: a systematic review. JBI Database System. Rev. Implement. Rep. 16 1282–1283. 10.11124/jbisrir-2017-003761 - DOI - PMC - PubMed
    1. Avila-Funes J. A., Amieva H., Barberger-Gateau P., Le Goff M., Raoux N., Ritchie K., et al. (2009). Cognitive impairment improves the predictive validity of the phenotype of frailty for adverse health outcomes: the three-city study. J. Am. Geriatr. Soc. 57 453–461. 10.1111/j.1532-5415.2008.02136.x - DOI - PubMed

LinkOut - more resources