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Abstract 2322: Validity of the NINDS-CSN VCI Neuropsychological Protocols is Supported in a Sample of Ischemic Stroke Patients

2012· article· en· W109852696 on OpenAlexaffabout
David L. Nyenhuis, Anoop Ganda, Fuqiang Gao, Erin Gibson, Simon J. Graham, Kia Honjo, Nancy J. Lobaugh, Jennifer Marola, Laura Pedelty, Novena Rangwala, Christopher J.M. Scott, Glenn T. Stebbins, Donald T. Stuss, Joe Zhou, Sandra E. Black

Bibliographic record

VenueStroke · 2012
Typearticle
Languageen
FieldMedicine
TopicDementia and Cognitive Impairment Research
Canadian institutionsSunnybrook Health Science Centre
Fundersnot available
KeywordsMedicineNeuropsychologyStroke (engine)DementiaProtocol (science)Clinical Dementia RatingCognitionInternal medicineCognitive impairmentPsychiatryPathologyDisease

Abstract

fetched live from OpenAlex

Introduction: The NINDS and the Canadian Stroke Network co-sponsored a 2005 meeting to harmonize data collection methods for patients with suspected vascular cognitive impairment (VCI). At this meeting, the neuropsychology group proposed 60 Minute (60M), 30 Minute (30M) and 5 Minute (5M) neuropsychological protocols. This study tests the validity of the protocols by comparing protocol performance of an ischemic stroke patient sample to matched controls. Hypotheses: 1. The 60M, 30M and 5M protocol scores will be more impaired in the ischemic stroke group than the matched controls; 2. The 60M Executive subscale score will be a more sensitive and specific factor in differentiating the two groups than the 60M Memory, Language and Spatial subscale scores, as measured by ROC area under the curve scores; and 3. The 60M protocols will be inversely related to ADL function, as measured by the Functional Rating Scale (FRS) and the Disability Assessment for Dementia (DAD) Methods: 1. ANCOVA and ROC analyses are used to compare 46 ischemic stroke patients (mean age: 66.4 (12.8), 62% male, 14.4 (3.0) years of education, 60% LH strokes, mean Rankin score: 2.14 (0.69), mean MMSE score: 27.2 (2.9)) with 76 controls of similar age, gender ratio, education, and Barona (estimate of premorbid IQ) score on the 60M, 30M and 5M protocols. Because patients reported more CESD-depression symptoms than controls (12.33 vs. 7.3, p < .01), it is entered as a covariate. 2. 60M protocol scores are entered for correlation with FRS and DAD scores Results: 1. All three protocol scores are significantly lower in patients than in matched controls (F statistics range from 15.7 to 50.5; all p values < .000; partial eta2 values range from .14 to .31). 2. ROC analyses show the 60M Executive subtest to be the most sensitive and specific, followed by the Memory, Language, and Spatial subtests (AUC values: .86, .75, .70, .67, respectively). 3. The 60M protocol score correlates with DAD Total (p < .05) and DAD IADL (p < .01) scores and is inversely correlated with FRS Total (p < .05) score 4. Domain specific cognitive and functional score relationships are noted between 60M Executive score and FRS Problem Solving rating score (p < .05), and between 60M Memory and FRS Memory rating score (p < .05). The correlation between 60M Language and FRS Language rating is not significant. Conclusions: 1. The validity of the VCI Harmonization protocols is supported by their ability to differentiate an ischemic stroke group from a matched normal control group. 2. The 60M Executive subscale shows higher sensitivity and specificity than the Memory, Language and Spatial subscales, which supports the important role of executive function in VCI and further validates the scale 3. The 60M scale and its Executive and Memory subscales relate to functional disability in a post-ischemic stroke sample, further supporting the validity of these scales.

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)0.006
metaresearch head score (Gemma)0.021
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 score0.006
Threshold uncertainty score0.031

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.021
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.001

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 head0.063
GPT teacher head0.373
Teacher spread0.310 · 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".

Quick stats

Citations1
Published2012
Admission routes2
Has abstractyes

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