Ataxia and the Role of Antigliadin Antibodies
Bibliographic record
Abstract
BACKGROUND: Although it is acknowledged that patients with celiac disease can develop neurological complications such as ataxia, the association of antigliadin antibodies in the etiology of sporadic ataxia and the usefulness of this testing in diagnosis of ataxia is controversial. METHODS: We investigated this association by testing for the presence of IgG and IgA antigliadin antibodies in 56 ataxic patients and 59 controls. The ataxia patients were subsequently classified into three groups: sporadic, hereditary and MSA. RESULTS: Of the total ataxic patients, 6/56 (11%) were positive for either IgG or IGA antigliadin antibodies compared to the controls of which 5/59 (8%) were positive (p = 0.68). In a subgroup analysis, 4/29 (14%) of the samples in the sporadic ataxic subgroup were positive for antigliadin antibodies (IgG or IgA) compared to control (p = 0.44). Similar negative results were found in the remaining subgroup analyses. CONCLUSIONS: These results do not support an association between antigliadin antibodies and sporadic ataxias.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".