Osteoporosis in Canadian adult cystic fibrosis patients: A descriptive study
Bibliographic record
Abstract
BACKGROUND: Cystic fibrosis is the most common fatal autosomal recessive genetic disease in the Caucasian population. Osteoporosis is increasingly being recognised as an important complication in people with cystic fibrosis. METHODS: A descriptive study of adult cystic fibrosis patients receiving care at a Canadian tertiary care hospital was conducted to evaluate the prevalence of osteoporosis, the prevalence of non-vertebral fractures, and the change in bone mineral density during the course of a year. Data on bone mineral density were obtained for 40 adult cystic fibrosis patients by reviewing dual x-ray absorptiometry scans taken at baseline (when annual scans became standard clinical practice) and one year prior to baseline. Data on prevalent fractures were obtained by reviewing all available patient charts. Clinical and laboratory data were collected from an existing clinic database. RESULTS: Over half of the 40 patients had reduced T- and Z-scores at baseline. For the 27 patients who had data available one year prior to baseline, total hip and lumbar spine bone mineral density had decreased by 3.04% and 0.86% after one year while total body bone mineral density had not changed significantly. Four prior non-vertebral fractures were reported in three patients (1,146 patient-years). CONCLUSION: This study confirms that osteoporosis is a significant problem in adult cystic fibrosis patients, and constitutes the first published evidence of cystic fibrosis bone disease in Canadians.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".