Abstract NS16: The Discriminant Validity of the AD8 in Detecting Post-stroke Vascular Cognitive Impairment
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".