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June 22, 2026Neurology and TherapyOpen Access

ECAS-Based Neuropsychological Phenotyping in Amyotrophic Lateral Sclerosis: A Retrospective Study Comparing Different Algorithms

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Authors

BPBarbara PolettiEAEdoardo N. AielloMCMonica Consonni

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Overview

Retrospective study compares algorithms for classifying neuropsychological phenotypes in ALS, indicating classification discrepancies.

Key Points

  • To compare different ECAS-based algorithms for classifying neuropsychological phenotypes in ALS.
  • Retrospective analysis of ECAS-C and ECAS-CI scores from N = 901 ALS patients without dementia.
  • Patients classified according to Strong et al.'s criteria: ALScbn, ALSci/bi/cbi, or Possible ALS-FTD.
  • Comparison of classification algorithms: Abrahams’, Poletti et al.’s, and a Subscale approach.
  • Moderate to high agreement rates among classifications (84–86%; Cohen’s k = 0.78–0.81).
  • Re-classifications of ALScbn to ALSci and vice versa ranged from ~ 11% to ~ 24%.
  • 43% of ALScbi cases had classificatory disagreements between single task-level and total-level algorithms.

Cite This Study

Poletti et al. (2026) studied this question.

synapsesocial.com/papers/6a38d0fdda1bad9caca30acehttps://doi.org/10.1007/s40120-026-00955-7
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