Determinants and functional impacts of diaphragmatic involvement in patients with inclusion body myositis
Bibliographic record
Abstract
BACKGROUND: We evaluated the functional consequences of diaphragm involvement in patients with inclusion body myositis (IBM). METHODS: Ultrasound diaphragm thickening fraction (TFdi), lung function and dyspnea levels were compared between IBM patients and matched controls. Patients with IBM were grouped into "low" and "high" diaphragm activity based on TFdi values (with cutoff value being the lowest observed TFdi in the control group), and clinical characteristics were compared between groups. RESULTS: 20 IBM patients were included. TFdi was significantly lower in patients and correlated with time since symptom onset (rho = 0.74, P < .001). Patients had significantly lower forced vital capacity and higher dyspnea scores than controls. IBM patients with "low" diaphragm activity (n = 9) had lower 6-min walking distance, higher resting and exertional dyspnea and a larger positional decrease in vital capacity (all P ≤ .03) than patients with 'high' activity. Timed Up and Go time and St. George's Respiratory Questionnaire were not different between groups. CONCLUSIONS: Diaphragm involvement in IBM is related to disease duration and has detrimental effects on lung function, dyspnea and exercise capacity. Further studies are required to investigate its potential as a therapeutic target.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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".