Ventilatory parameters and maximal respiratory pressure changes with age in Duchenne muscular dystrophy patients
Bibliographic record
Abstract
The aim of this longitudinal study was to precise, in children with Duchenne muscular dystrophy, the respective functional interest of ventilatory parameters (Vital capacity, total lung capacity and forced expiratory volume in one second [FEV(1)]) in comparison to maximal inspiratory pressure (Pimax) during growth. In ten boys the mean age of 9.1 +/- 1 years) to mean age of 16 +/- 1.4 years followed over a period of 7 years, we found that: (1) ventilatory parameters expressed in percentage of predicted value, after a normal ascending phase, start to decrease between 11 and 12 years, (2) Pimax presented only a decreasing phase since the beginning of the study and thus was already at 67% of predicted value at 12 years while ventilatory parameters was still normal, (3) after 12 years the mean slopes of decrease per year of vital capacity and FEV1 were higher (10.7 and 10.4%) than that of Pimax (6.9%), (4) at 15 years mean values of vital capacity and FEV1 (53.3 and 49.5% of predicted values) was simlar to that of Pimax (48.3%). In conclusion, if at early stages of the disease, Pimax is a more reliable index of respiratory impaiment than ventilatory parameters, the follow-up of ventilatory parameters, when they start to decrease, is a better indicator of disease progression and, at advanced stages they provided same information about the functional impact of disease.
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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 | 0.002 |
| 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 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| 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".