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Record W822126731 · doi:10.1007/s12603-015-0564-2

The Rapid Cognitive Screen (RCS): A point-of-care screening for dementia and mild cognitive impairment

2015· article· en· W822126731 on OpenAlexaboutno aff
Theodore K. Malmstrom, Vanessa Voss, Dulce M. Cruz‐Oliver, Lenise Cummings‐Vaughn, Nina Tumosa, George T. Grossberg, John E. Morley

Bibliographic record

VenueThe journal of nutrition health & aging · 2015
Typearticle
Languageen
FieldMedicine
TopicDementia and Cognitive Impairment Research
Canadian institutionsnot available
Fundersnot available
KeywordsDementiaMontreal Cognitive AssessmentMedicineReceiver operating characteristicCognitionVeterans AffairsCognitive impairmentGerontologyPsychiatryPhysical therapyInternal medicine

Abstract

fetched live from OpenAlex

OBJECTIVES: There is a need for a rapid screening test for mild cognitive impairment (MCI) and dementia to be used by primary care physicians. The Rapid Cognitive Screen (RCS) is a brief screening tool (< 3 min) for cognitive dysfunction. RCS includes 3-items from the Veterans Affairs Saint Louis University Mental Status (SLUMS) exam: recall, clock drawing, and insight. Study objectives were to: 1) examine the RCS sensitivity and specificity for MCI and dementia, 2) evaluate the RCS predictive validity for nursing home placement and mortality, and 3) compare the RCS to the clock drawing test (CDT) plus recall. METHODS: Patients were recruited from the St. Louis, MO Geriatric Research Education and Clinical Center (GRECC), Veterans Affairs Medical Center (VAMC) hospitals (study 1) or the Saint Louis University Geriatric Medicine and Psychiatry outpatient clinics (study 2). Study 1 participants (N=702; ages 65-92) completed cognitive evaluations and 76% (n=533/706) were followed up to 7.5 years for nursing home placement and mortality. Receiver operator characteristic (ROC) curves were computed to determine sensitivity and specificity for MCI (n=180) and dementia (n=82). Logistic regressions were computed for nursing home placement (n=31) and mortality (n=176). Study 2 participants (N=168; ages 60-90) completed the RCS and SLUMS exam. ROC curves were computed to determine sensitivity and specificity for MCI (n=61) and dementia (n=74). RESULTS: RCS predicted dementia and MCI in study 1 with optimal cutoff scores of ≤ 5 for dementia (sensitivity=0.89, specificity=0.94) and ≤ 7 for MCI (sensitivity=0.87, specificity=0.70). The CDT plus recall predicted dementia and MCI in study 1 with optimal cutoff scores of ≤ 2 for dementia (sensitivity=0.87, specificity=0.85) and ≤ 3 for MCI (sensitivity=0.62, specificity=0.62). Higher RCS scores were protective against nursing home placement and mortality. The RCS predicted dementia and MCI in study 2. CONCLUSIONS: The 3-item RCS exhibits good sensitivity and specificity for the detection of MCI and dementia, and higher cognitive function on the RCS is protective against nursing home placement and mortality. The RCS may be a useful screening instrument for the detection of cognitive dysfunction in the primary care setting.

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.016
Threshold uncertainty score0.033

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0020.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0050.002
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.002

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 head0.061
GPT teacher head0.386
Teacher spread0.325 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations137
Published2015
Admission routes1
Has abstractno

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