Supplementary File 5: Diagnostic Algorithm for Episodic Ataxia Types 1 and 2

Supplementary file 5 presents a proposed diagnostic algorithm for episodic ataxia types 1 and 2, developed by Claudio M. de Gusmao. The 42.9 KB PDF document contains results from a systematized literature review and statistical analysis of clinical features to inform decision-making in resource-limited settings. The file was last updated on April 21, 2026.

Use Cases

• Developing a clinical decision support tool based on the proposed diagnostic algorithm.
• Training machine learning models for differential diagnosis using the described clinical features like attack duration and triggers.
• Validating the algorithm's reported 87.5% sensitivity for identifying EA2 cases in new patient cohorts.

Strengths

• Algorithm is based on statistical analysis of clinical features with reported high specificity (e.g., 99.6% for myokymia in EA1).
• The proposed management algorithm was tested on a case cohort, yielding a sensitivity of 87.5% for EA2.
• Document is openly licensed under CC-BY-4.0 for reuse and distribution.

Limitations

• The dataset is a 42.9 KB PDF; the underlying statistical data or patient records are not provided as a structured table.
• Row count and column-level documentation are unknown, limiting direct analysis of the source data.
• Data may reflect publication bias inherent to the literature review methodology.

Provenance

Source

Claudio M. de Gusmao via figshare

Collection Method

Systematized literature review and statistical analysis of confirmed pathogenic variant cases.

Time Range

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Freshness

Last updated 2026-04-21 14:38:16; freshness should be verified.

Geography

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