Electrodiagnostic assessment of the autonomic nervous system: A consensus statement endorsed by the American Autonomic Society, American Academy of Neurology, and the International Federation of Clinical Neurophysiology
Bibliographic record
Abstract
Evaluation of disorders of the autonomic nervous system is both an art and a science, calling upon the physician's most astute clinical skills as well as knowledge of autonomic neurology and physiology. Over the last three decades, the development of noninvasive clinical tests that assess the function of autonomic nerves, the validation and standardization of these tests, and the growth of a large body of literature characterizing test results in patients with autonomic disorders have equipped clinical practice further with a valuable set of objective tools to assist diagnosis and prognosis. This review, based on current evidence, outlines an international expert consensus set of recommendations to guide clinical electrodiagnostic autonomic testing. Grading and localization of autonomic deficits incorporates scores from sympathetic cardiovascular adrenergic, parasympathetic cardiovagal, and sudomotor testing, as no single test alone is sufficient to diagnose the degree or distribution of autonomic failure. The composite autonomic severity score (CASS) is a useful score of autonomic failure that is normalized for age and gender. Valid indications for autonomic testing include generalized autonomic failure, regional or selective system syndromes of autonomic impairment, peripheral autonomic neuropathy and ganglionopathy, small fiber neuropathy, orthostatic hypotension, orthostatic intolerance, syncope, neurodegenerative disorders, autonomic hyperactivity, and anhidrosis.
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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 | 0.008 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.006 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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".