Examining cognitive decline over time in Iranian ALS patients: Adapting successive versions B and C of the Edinburgh cognitive and behavioral screen to Persian
Bibliographic record
Abstract
OBJECTIVE: To adapt successive versions B and C of the Edinburgh Cognitive and Behavioral Screen (ECAS) into Persian and evaluate cognitive and behavioral changes over time in Iranian ALS patients. METHODS: This study included 38 ALS patients in the ECAS-B group and 29 in the ECAS-C group, diagnosed between May 2021 and February 2023 at the Iranian Center of Neurological Research, Imam Khomeini Hospital, Tehran, Iran. Additionally, 59 age- and education-matched healthy controls were enrolled (30 for ECAS-B and 29 for ECAS-C). The Montreal Cognitive Assessment (MoCA) was used to validate the ECAS versions. RESULTS: The Persian versions of ECAS-B and ECAS-C demonstrated strong internal consistency (Cronbach's alpha: 0.88 for ECAS-B and 0.89 for ECAS-C) and a positive correlation with MoCA and ALS-FRS-r scores. The area under the ROC curve was 0.851 for ECAS-B and 0.861 for ECAS-C. ECAS-C scores were significantly lower than ECAS-B scores, suggesting a faster cognitive decline over time. Optimal cutoff values of 72 for ECAS-B and 78 for ECAS-C were identified for detecting cognitive impairment. Cognitive impairment was observed in 10 patients (26.31%) in the ECAS-B group and 15 patients (51.72%) in the ECAS-C group. CONCLUSIONS: The Persian versions of ECAS-B and ECAS-C demonstrate good validity and reliability for detecting cognitive impairment and tracking cognitive decline in ALS 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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.000 | 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".