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This page is alzhub.org's plain-English summary of a published study, not the paper itself. It is generated from the record we hold for this study, sourced and linked below — check the original for the full text and methods.

✓ Peer-reviewed alzhub usefulness score 39 out of 100. Getting a diagnosis

Topic: Risk, prevention and care in population studies

According to the II level neuropsychological evaluation, 4.8 % of MSA patients met criteria for dementia and 53,2 % for MCI. The optimal MMSE cut-off scores were 20.5 for dementia (AUC = 0.915) and 26.5 for MCI (AUC = 0.698). For MoCA, the most accurate cut-offs were 14.0 to detect dementia (AUC = 0.919) and 19.5 to detect MCI (AUC = 0.702).ROC analysis suggested that both tests were more accurate to identify MCI than dementia. The optimal cut-off for MoCA fluency item to identify MCI was 8.5 words (AUC = 0.717). Our findings support MMSE and MoCA as effective and accessible tools to detect MCI and dementia in MSA. MoCA fluency item emerged as a reliable tool to detect MCI.

Key findings

Why it matters

This study found that the MMSE and MoCA are effective tools to detect mild cognitive impairment and dementia in patients with multiple system atrophy, with specific cutoff scores identified for each condition. The MoCA fluency item emerged as a reliable tool to detect mild cognitive impairment.

Study details

How this study scored 39/100
How this study's score is builtJournal tier 7 of 10; Journal's citation record 2 of 4; Study design 0 of 12; Strength of evidence 1 of 5; Peer-review validation 10 of 10; How recent 4 of 5; Sample size 0 of 4; Effect reported 3 of 3; Studied in people 0 of 3; Randomised / blinded 0 of 2; Times cited 1 of 7; Citations per year 1 of 5; Impact for its field and year 2 of 6; Cited by studies here 0 of 6; Still being cited 1 of 4; Senior author's track record 3 of 4; Institution's track record 0 of 3; Multi-centre collaboration 0 of 3; Indexed in PubMed 2 of 2; Free to read 2 of 2. Total 39 of 100.39 of 100 points earned61 not earned

Published in a peer-reviewed journal. Scored zero for study design, sample size, studied in people and randomised / blinded because the record does not state it.

ComponentPointsWhy
Journal tier 7 / 10 Tier 3 — peer-reviewed journal (Parkinsonism & Related Disorders)
Journal's citation record 2 / 4 Parkinsonism & Related Disorders: journal h-index 155 (OpenAlex, 2026-10-29)
Study design 0 / 12 No study design recorded — scores zero, not guessed (not stated in the record — scored 0)
Strength of evidence 1 / 5 Rated “low” in our summary
Peer-review validation 10 / 10 Peer-reviewed. Published as an article in a named peer-reviewed journal.
How recent 4 / 5 2025 — within 3 year(s) of the newest study here
Sample size 0 / 4 Participant count not stated — scores zero (not stated in the record — scored 0)
Effect reported 3 / 3 Effect reported with a statistic (interval, p-value, ratio or similar)
Studied in people 0 / 3 Not stated whether this was studied in people — scores zero (not stated in the record — scored 0)
Randomised / blinded 0 / 2 No randomisation or blinding stated — scores zero (not stated in the record — scored 0)
Times cited 1 / 7 Cited 3 times (OpenAlex, 2026-10-10)
Citations per year 1 / 5 1.0 citations a year over 3 year(s) since 2025
Impact for its field and year 2 / 6 Cited 1.9× the average for papers of its field and year (OpenAlex FWCI)
Cited by studies here 0 / 6 No other study in this library cites it
Still being cited 1 / 4 Cited 3 times in 2024–2026 (2026 still in progress; OpenAlex)
Senior author's track record 3 / 4 Last-listed author Maria Teresa Pellecchia: h-index 55 (OpenAlex, whole career)
Institution's track record 0 / 3 University of Salerno: institution h-index 659 (OpenAlex)
Multi-centre collaboration 0 / 3 OpenAlex lists 1 institution(s) in 1 country — scores zero (affiliation lists can be incomplete)
Indexed in PubMed 2 / 2 Indexed in PubMed (PMID 40752382)
Free to read 2 / 2 Free to read
Total 39 / 100 —

What each of these 20 components measures, and what this score is not →

Read the original

Full text: free to read — OpenAlex lists this copy as free to read: the link above (checked 6 Feb 1020).

Cite this study APA, Vancouver, BibTeX · download .bib or .ris

Built from the record alzhub holds for this paper, not looked up. Volume, issue and page numbers are not held in the record. The record's author list ends in “et al.”, so not every author is named. Check the citation against the original before you use it.

APA 7th

Cuoco, S., Carotenuto, I., Russillo, M. C., Andreozzi, V., Picillo, M., Amboni, M., et al. (2025). Optimal cut-off scores for the Mini Mental State Examination and Montreal Cognitive Assessment to detect MCI and dementia in Multiple System Atrophy. Parkinsonism & Related Disorders. https://doi.org/10.1016/j.parkreldis.2025.107974

Vancouver

Cuoco S, Carotenuto I, Russillo MC, Andreozzi V, Picillo M, Amboni M, et al. Optimal cut-off scores for the Mini Mental State Examination and Montreal Cognitive Assessment to detect MCI and dementia in Multiple System Atrophy. Parkinsonism & Related Disorders. 2025. doi:10.1016/j.parkreldis.2025.107974. PMID: 40752382.

BibTeX

@article{cuoco2025-40752382,
  author  = {Cuoco, Sofia and Carotenuto, Immacolata and Russillo, Maria Claudia and Andreozzi, Valentina and Picillo, Marina and Amboni, Marianna and Erro, Roberto and Soricelli, Andrea and others},
  title   = {{Optimal cut-off scores for the Mini Mental State Examination and Montreal Cognitive Assessment to detect MCI and dementia in Multiple System Atrophy}},
  journal = {Parkinsonism \& Related Disorders},
  year    = {2025},
  doi     = {10.1016/j.parkreldis.2025.107974},
  pmid    = {40752382},
  url     = {https://doi.org/10.1016/j.parkreldis.2025.107974}
}

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