Bisphosphonates in Patients with Glucocorticoids: Time for Implementation
Bibliographic record
Abstract
Use of glucocorticoids (GC) may have devastating effects on bone quality1. From earlier histomorphometric data, we know that bone formation is inhibited by direct suppression of osteoblast function during the use of GC, while bone resorption is unchanged or even elevated, at least partly related to decreased intestinal calcium absorption, elevated urinary calcium excretion, and a tendency to secondary hyperparathyroidism2,3. However, exciting new data provide additional insights into the pathogenesis of Glucocorticoid Induced OsteoPorosis (GIOP)2,3: (1) upregulation of the Wnt inhibitor Dickkopf-1, leading to inhibition of bone formation; (2) increased apoptosis of osteoblasts and osteocytes; (3) differentiation of mesenchymal stem cells into the direction of adipocytes, instead of into osteoblasts; (4) elevated lifespan of osteoclasts, due to decreased apoptosis; and (5) upregulation of expression of RANKL in osteoblasts (and downregulation of osteoprotegerin). Nevertheless, it is important to realize that the (negative) direct and indirect effects of GC on bone are counteracted by the immunosuppressive effects of GC on the underlying disease2,3. Another complicating factor is that use of GC and the underlying disease may both be associated with muscular weakness and, subsequently, increased risk of falling. Use of GC is associated with bone loss, particularly in the early phase of treatment, when the dosage of GC is usually high and the underlying disease for which the GC are prescribed is active. In contrast, in the chronic phase, bone loss may be mild in GC-treated patients, related to the use of lower dosages of GC and to low or preferably absent disease activity. In addition, use of GC is also associated with elevated risk of fracture: In a retrospective cohort study with 244,235 GC-treated patients and the same number of age and sex matched controls, the fracture … Address correspondence to Prof. Lems. E-mail: wf.lems{at}vumc.nl
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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 | 0.002 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.024 | 0.005 |
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".