Bibliographic record
Abstract
Motor neuron disease (MND) is a set of neuromuscular diseases that affect the upper and/or lower motor neurons, resulting in progressive disability. Amyotrophic lateral sclerosis (ALS) and Primary lateral sclerosis (PLS) are two forms of MND that both involve upper motor neuron degeneration, which can also accompany extra-motor changes in cognitive, behavioral, and/or emotional functioning for some individuals. Characterization of the cognitive profile of MND is still evolving, with growing interest in cognitive subtypes. The development of cognitive screens targeted to the MND cognitive profile aim to provide efficient and accurate brief assessments. However, empirical evaluation of tailored MND cognitive screens is needed for cross-validation independent of tests’ original developers. The present study addresses the cognitive profile of MND and the utility of brief cognitive screens with a focus on impairments in the language domain. The two primary aims include: (1) comprehensive assessment and characterization of language dysfunction in MND, and (2) empirical evaluation of brief cognitive screens with regard to detecting language impairments. Forty-one patients with MND (ALS n = 36; PLS n = 5) were administered a comprehensive language battery to classify cognitive impairment (MND/ALSci; Strong et al., 2017) in the language domain and/or verbal fluency. Patients also completed two tailored cognitive screens [ALS Cognitive Behavioral Screen (ALS-CBS), Edinburgh Cognitive and Behavioral ALS Screen (ECAS)] and one general screen (Montreal Cognitive Assessment; MoCA). The current preliminary results suggest language dysfunction in MND is characterized by prominent difficulties with word retrieval (confrontation naming) and/or syntax comprehension. However, evidence of reduced word production resembling nonfluent/agrammatic aphasia was not found. In total, 19.5% of the sample met criteria for MND/ALSci in the language domain (n = 8, all ALS); 22.0% met criteria for MND/ALSci in the verbal fluency domain (n = 9). Patients were classified into three subgroups, those with broad language impairments (ALSci-L n = 4, 9.8%), phonemic fluency impairments (MNDci-VF n = 5, 12.2%), or both impairments (ALSci-L+VF n = 4, 9.8%). Results also revealed existing challenges in accurately classifying patients with language dysfunction using brief cognitive screens. The ECAS Language subscore offered limited classification of broad language impairments in the present MND sample (sensitivity 50%, specificity 70%). Among the broader cognitive screens, sensitivities to language impairments were: ALS-CBS (100%), ECAS ALS-Specific Score (75%), and MoCA (71%). Convergent validity was demonstrated between outcomes on the ALS-CBS and ECAS ALS-Specific Score (rФ = .59). Discriminant validity was also demonstrated between outcomes on ALS-CBS compared to the MoCA (rФ = .11). Future research is needed to assess whether language dysfunction reflects a distinct MND cognitive phenotype(s) and potential relationships with disease prognosis. Naming and syntax comprehension may be fruitful language screening targets for future research.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".