Longitudinal changes in BMD in adults with cystic fibrosis
Bibliographic record
Abstract
Improved survival in people with cystic fibrosis (pwCF) presents new complexities of care, including CF-related bone disease, a common complication in older pwCF. The trajectory of bone loss with age in this population remains unclear. The objective of this study was to estimate the average rate of change in BMD in adults with CF. This retrospective study included adults with CF, aged 25-48 yr, followed between January 2000 and December 2021. Subjects with at least one DXA scan were included. Scans obtained posttransplantation, after the initiation of bisphosphonates or cystic fibrosis transmembrane conductance regulator modulator therapy was excluded. The primary outcome was BMD (g/cm2) at the LS and FN. A linear mixed-effects model with both random intercept and random slope terms was used to estimate the average annual change in BMD. A total of 1502 DXA scans in 500 adults (average age 28.4 y) were included. There was a statistically significant annual decline in BMD of -0.008 gm/cm2/yr (95% CI, -0.009 to -0.007) at the FN and -0.006 gm/cm2/yr (95% CI, -0.007 to -0.004) at the LS. Relative to BMD at age 25, there was a 18.8% decline at the FN by age 48 yr and a 11% decline at the LS. Pancreatic insufficient subjects had a faster rate of decline in BMD compared with pancreatic sufficient subjects. After adjusting for markers of disease severity, the annual rate of decline remained significant. Individuals with CF experience bone loss at an age when it is not anticipated, thereby entering early adulthood, where further bone loss is inevitable especially with the decrease in estrogen during menopause, with suboptimal BMD. As the CF population ages, it will become very important to consider interventions to maximize bone health.
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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 | 0.004 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| 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".