Validity of the Montreal Cognitive Assessment and the HIV Dementia Scale in the assessment of cognitive impairment in HIV-1 infected patients
Bibliographic record
Abstract
The gold standard for evaluating cognitive impairments in HIV-infected patients is to administer an extensive neuropsychological assessment. This may, however, be time-consuming and hence not always feasible in the clinic. Therefore, several brief screening tools have been developed. This study determined the validity of the Montreal Cognitive Assessment (MoCA) and the HIV Dementia Scale (HDS) in detecting cognitive impairment using both the Frascati and cognitive impairment, no dementia (CIND) criteria to classify cognitive impairment in HIV-1 infected patients. The MoCA, HDS, and an extensive neuropsychological assessment, covering nine cognitive domains, were administered in a group of 102 HIV-infected patients who were all on cART and virologically suppressed for at least 1 year. Results show that the areas under the curve (AUCs) for both the MoCA and the HDS were statistically significant, using both the Frascati and the CIND criteria as gold standard. However, the AUCs for the MoCA and HDS did not differ significantly, regardless of the used classification criteria (Frascati: z = 0.37, p = 0.35; CIND: z = -0.62, p = 0.27). Sensitivity of both the MoCA and HDS were low for the recommended cutoff scores (Frascati: MoCA (<26) = 0.56, HDS (<11) = 0.26; CIND: MoCA (<26) = 0.55, HDS (<11) = 0.36). Cutoff scores with good sensitivity and adequate specificity could not be determined for both screening instruments. Therefore, the HDS and MoCA are not recommended as sole instruments to diagnose HIV-associated cognitive impairment.
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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 | 0.011 | 0.025 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
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".