Impact of diabetes in the Friedreich ataxia clinical outcome measures study
Bibliographic record
Abstract
Abstract Objective Friedreich ataxia (FA) is a progressive neuromuscular disorder caused byGAAtriplet repeat expansions or point mutations in theFXNgene.FAis associated with increased risk of diabetes mellitus (DM). This study assessed the age‐specific prevalence ofFA‐associatedDMand its impact on neurologic outcomes. Research Design and Methods Participants were 811 individuals withFAfrom 12 international sites in a prospective natural history study (FAClinical Outcome Measures Study,FACOMS). Physical function was assessed, using validated instruments. Multivariable regression analyses examined the independent association ofDMwith outcomes. Results Mean age of participants was 30.1 years (SD15.3, range: 7–82), 50% were female, and 94% were non‐Hispanic white. 9% (42/459) of adults and 3% (10/352) of children hadDM. Individuals withFA‐associatedDMwere older (P< 0.001), had longerGAArepeat length on the least affectedFXNallele (P= 0.037), and more severeFA(P= 0.0001). Of individuals withDM, 65% (34/52) were taking insulin. Even after accounting statistically for both age andGAArepeat length,DMwas independently associated with greaterFAsymptom burden (P= 0.010), reduced capacity to perform activities of daily living (P= 0.021), and a decrease of 0.33SDs on a composite performance measure (95%CI: −0.56–0.11,P= 0.004); the relative impact ofDMwas most apparent in younger individuals. Conclusions DM‐associatedFAhas an independent adverse impact on well‐being in affected individuals, particularly at younger ages. In future, evidence‐based approaches for identification and management ofFA‐relatedDMmay improve both health and function.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".