MRI signs of multiple system atrophy preceding the clinical diagnosis: the case for an imaging-supported probable MSA diagnostic category
Bibliographic record
Abstract
Multiple system atrophy (MSA) is a neurodegenerative disorder characterised by autonomic failure in the form of orthostatic hypotension, neurogenic bladder and impotence, in association with a variable combination of parkinsonism, cerebellar ataxia and pyramidal signs.1 MSA is divided into predominant parkinsonism (MSA-P) and cerebellar (MSA-C) forms. Current clinical diagnostic criteria for ‘probable MSA’ require prominent autonomic failure. However, it is widely recognised that these symptoms may develop long after motor features.2 In the case of MSA-P, early parkinsonism in the absence of significant autonomic failure may be impossible to differentiate from Parkinson's disease. Establishing a correct diagnosis early in the course of MSA has direct implications for prognosis and counselling of patients and family. The clinical research implications are broad, including exclusion of such patients from studies of Parkinson's disease and inclusion in studies on MSA, particularly those that would benefit from early diagnosis, such as trials of experimental disease-modifying therapies. The potential of brain MRI as a diagnostic tool for MSA has been studied3 and it has been incorporated in the current diagnostic criteria, though only as supportive criteria of ‘possible MSA’.4 It is unclear how brain MRI signs of MSA can predate its clinical diagnosis and …
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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 | 0.010 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.002 | 0.004 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.015 | 0.010 |
| Insufficient payload (model declined to judge) | 0.006 | 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".