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Record W3010251966 · doi:10.1186/s12883-020-01657-9

A comparative study on the validations of three cognitive screening tests in identifying subtle cognitive decline

2020· article· en· W3010251966 on OpenAlex
Fengfeng Pan, Lin Huang, Keliang Chen, Qianhua Zhao, Qihao Guo

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueBMC Neurology · 2020
Typearticle
Languageen
FieldMedicine
TopicDementia and Cognitive Impairment Research
Canadian institutionsnot available
FundersKey Technologies Research and Development Program
KeywordsNeurochemistryNeurologyMedicineCognitive declineCognitionNeurosurgeryCognitive testPsychiatryDementiaPathologyDisease

Abstract

fetched live from OpenAlex

BACKGROUND: Subtle cognitive decline (SCD) may represent a very early stage of objective cognitive impairment before mild cognitive impairment (MCI), with less neuronal damage and more functional reservation. Detecting individuals with SCD is imperative for dementia prevention and treatment. In this study, we aimed to compare the validations of three cognitive screening tests, Mini-Mental State Examination (MMSE), Montreal Cognitive Assessment-Chinese Version (MoCA-CV), and Memory and Executive Screening (MES), in identifying subtle cognitive decline. METHODS: A total of 407 individuals were recruited, including 147 cognitively normal controls (NC), 102 individuals with subtle cognitive decline (SCD) and 158 individuals with mild cognitive impairment (MCI) according to the operational neuropsychological criteria proposed by Jak and Bondi's. All participants underwent standardized comprehensive neuropsychological tests and the three cognitive screening tests. Chi-square analysis was used to compare the cognitive performance among the groups of NC, SCD and MCI. Receiver operating characteristic (ROC) curves were used to evaluate the abilities of MMSE, MoCA-CV and MES in discriminating NC, SCD and MCI. RESULTS: Compared with NC, SCD showed a significant decline only in the tests of memory, such as Auditory Verbal Learning Test (AVLT), Rey-Osterrieth Complex Figure Test (CFT) and Prospective Memory Test (PrM) (P < 0.01). However, MCI showed significant decline in all cognitive performances (P < 0.01). The scores of MMSE, MoCA-CV and MES all showed a progressive downward trend within the groups of NC, SCD and MCI (P < 0.001). In ROC Analyses for discriminating individuals with SCD from NC, the most appropriate MES cutoff was 84, with a sensitivity of 74.3%, a specificity of 60.8% and 0.738 for AUC (95%CI, 0.675-0.801). By contrast, MMSE and MOCA-CV had poor sensitivity (67.4 and 70.8%, respectively) and specificity (51.0 and 52.9%, respectively), and smaller AUCs (0.643 and 0.644, respectively) than the MES. CONCLUSION: As a screening test, MES is more efficacious in identifying SCD from normal controls than MMSE and MoCA-CV.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.012
Threshold uncertainty score0.479

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.244
GPT teacher head0.427
Teacher spread0.182 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it