Influence of thoracic spine postural disorders on cardiorespiratory parameters in children and adolescents with cystic fibrosis
Bibliographic record
Abstract
OBJECTIVES: To assess the impact of increased thoracic kyphosis on pulmonary function and functional capacity in children and adolescents with cystic fibrosis (CF) and to verify the influence of disease severity, age and nutritional status on this deformity. METHOD: This was a cross-sectional, analytical study conducted at a university hospital. It included CF patients with confirmed diagnosis and without pulmonary exacerbation. The sample was submitted to postural assessment, spirometry (FEV1, FVC and FEV1/FVC) and 6-minute walk test distance (6-MWT distance). Data were analyzed using the Mann Whitney test, Spearman correlation and logistic regression. RESULTS: Forty-two patients were enrolled, 61.9% presented increase of thoracic kyphosis. There was no difference in values of FEV1, FVC, FEV1/FVC and 6-MWT distance between the groups with or without thoracic kyphosis (p = 0.407; p = 0.756; p = 0.415; p = 0.294). In the group without alteration, patients with more disease severity had a mean FEV1 of 74.1±21.9% and FVC of 79.8±18.7% while in those of lesser severity higher values were found (95.6±12.2% and 97.6±13.2%, respectively) (p = 0.027 and p = 0.027). The presence of kyphosis was correlated with age (p = 0.048) but not with severity (p = 0.151) and body mass index (p = 0.088). CONCLUSIONS: There was a high prevalence of increased thoracic kyphosis in children and adolescents with CF. The deformity did not affect pulmonary function and functional capacity and there was no relationship with disease severity. Regardless of posture, worsening of disease severity determined worsening of pulmonary 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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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 | 0.001 |
| 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".