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Record W2260212147 · doi:10.1161/str.44.suppl_1.ans16

Abstract NS16: The Discriminant Validity of the AD8 in Detecting Post-stroke Vascular Cognitive Impairment

2013· article· en· W2260212147 on OpenAlexaboutno aff
YanHong Dong, Wan Shin Pang, Bernard P.L. Chan, Vijay K. Sharma, Narayanaswamy Venketasubramanian, Christopher Chen

Bibliographic record

VenueStroke · 2013
Typearticle
Languageen
FieldMedicine
TopicDementia and Cognitive Impairment Research
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineDiscriminant validityReceiver operating characteristicDementiaCognitionStroke (engine)Mini–Mental State ExaminationNeuropsychologyPsychiatryClinical psychologyCognitive impairmentPsychometricsInternal medicineDisease

Abstract

fetched live from OpenAlex

Background: The AD8 is an informant-based brief cognitive screening instrument, which can be administered to the patient in the absence of an informant in detecting patients with dementia at the memory clinic or in the community. However, its discriminant validity in detecting post-stroke Vascular Cognitive Impairment (VCI) has not been reported. Purpose: Our aims were to examine the discriminant validity of the AD8 for the detection of VCI by comparing the AD8 (both informant-rated and patient-rated) to the Montreal Cognitive Assessment (MoCA) and the Mini-Mental State Examination (MMSE). Method: Patients with ischemic stroke and TIA were recruited from the stroke neurology service of the National University Health System in Singapore. Their consensus diagnoses of VCI and no cognitive impairment (NCI) were established by clinical assessment including formal neuropsychological evaluation and neuroimaging according to the internationally accepted criteria. Patients received the AD8, MMSE and MoCA whilst their informants received AD8. Area under the receiver operating characteristic curve (ROC) analysis was employed to examine the discriminant validity of the informant AD8 in detecting VCI. Results: Sixty patient-informant dyads were recruited (34 VCI and 26 NCI). There were no significant differences in age between patients with VCI and NCI (69.5 ±9.4 vs 66.8±6.8, p>.05). Informant AD8 had shown a trend of superior discriminant validity compared to patient AD8 in detecting VCI (Area Under the Curve (95% Confident Interval): .81 (.70- .93), .67 (.54- .81), p=.06). At the respective optimal cutoff points, the informant AD8 (≥1) had acceptable sensitivity and specificity whilst the patient AD8 (≥3) had poor sensitivity and good specificity (sensitivity: .79 vs .32; specificity: .73 vs .96, correctly classified 76.7% vs 60.0%). In addition, the informant AD8 was equivalent to the MMSE and inferior to the MoCA in detecting VCI. Conclusions: The informant AD8 has demonstrated a trend of superior discriminant validity compares to the patient AD8 in detecting post-stroke VCI. Stroke nurses may adopt this brief instrument for targeted cognitive screening of older patients with stroke/TIA.

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)0.003
metaresearch head score (Gemma)0.009
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 score0.003
Threshold uncertainty score0.018

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.009
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.001
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 head0.024
GPT teacher head0.298
Teacher spread0.274 · 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

Citations0
Published2013
Admission routes1
Has abstractyes

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