Dementia associated disorders, cognitive impairment and impact on social roles activities and participation: Patient centric impact
Bibliographic record
Abstract
Abstract Background Dementia associated diseases (DAD) refers to several clinical conditions that are characterized by progressive cognitive impairment that interferes with an individual’s ability to function independently. Cognitive impairments (CI) can vary in degree and combination across multiple cognitive domains (CD) that routine care or tests (MMSE, MOCA) might not adequately identify. Therefore, a clinician may not recognize these varied types of CI or change in CD scores effectively. Enhanced recognition of patient centric CI in routine care can be accomplished improved analytics by incorporating a validated, examiner independent computerized cognitive assessment battery (CAB‐NT). Patient self‐reported outcome measures (PRO) are concurrently incorporated with CAB‐NT to gauge associated disability progression. Ability and participation in social roles and activities and communication ability can adversely affect quality of life (QoL) for people with Dementia associated diseases (PwDAD) and are likely related to CI and other factors. Method Retrospective review of consecutive PwDAD who completed both CAB‐NT and PRO (SSRA, APSRA, and C‐SF) on the same day in the course of routine care. CAB‐NT included 7 cognitive domains: memory (Mem), executive function (Exe), attention (Att), information processing speed (Inf), visual spatial (Vis), verbal function (Ver), motor skills (Mot) as well as a global cognitive summary score (GCS). Results 312 PwDaD, 64.74% female, average age 66 +/‐ 17 years. Simple linear regression analyses were performed with significant correlations (p = <0.05): CAB‐NT vs SSRA: GCS r = 0.2, Exe r = 0.3, Mot r = 0.2, and Att r = 0.3. CAB‐NT vs APSRA: Exe r = 0.3, Att r = 0.2. CAB‐NT vs C‐SF: Exe r = 0.2. Conclusion Social roles and communication in PwDAD are most impacted by CI associated with executive functioning and attention. Impairment in these domains are associated with increased difficulty for PwDaD to effectively interact with others and may lead to reduced QoL for these patients. Identifying the degree and combination of such CI precisely might allow for early and effective targeted proactive behavioral and/or medicinal intervention to improve QOL of these patients.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| 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) | 0.002 | 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".