The Effects of Long-term Administration of rhPTH(1-84) in Hypoparathyroidism by Bone Histomorphometry
Bibliographic record
Abstract
ABSTRACT Hypoparathyroidism is a rare disorder that is associated with abnormal bone properties. Recombinant human parathyroid hormone (1-84) [rhPTH(1-84)] in short-term studies has beneficial skeletal effects. Although rhPTH(1-84) will likely be used indefinitely, long-term effects on skeletal microstructure are unknown. We therefore studied histomorphometric changes with transiliac crest bone biopsies before and after 8.3 ± 1 years of rhPTH(1-84) in 13 hypoparathyroid subjects compared with 45 controls. Before institution of rhPTH(1-84), skeletal remodeling indices were markedly suppressed. With long-term treatment, indices of bone remodeling increased. Mineralizing surface increased by 26-fold (0.3 ± 1 to 7.9 ± 7%, p = 0.003), bone formation rate increased by 15-fold (0.003 ± 0.01 to 0.047 ± 0.05 μm2/μm/day, p = 0.007), osteoid width doubled (1.9 ± 1 to 4.3 ± 1 lamellae, p = 0.017), and osteoid surface tripled (3.3 ± 3 to 10.8 ± 6%, p = 0.011). Bone resorption as measured by eroded surface increased (4.6 ± 2 to 7.5 ± 3%, p = 0.021). Structural changes demonstrated intratrabecular tunneling, with increases in cancellous bone volume (19.6 ± 5 to 29.1 ± 11%, p = 0.017) and trabecular number (1.8 ± 1 to 2.5 ± 1 #/mm, p = 0.025). Cortical porosity tended to increase (6.3 ± 5 to 9.5 ± 3%, p = 0.07). Mineralizing surface, osteoid surface, and eroded surface surpassed control levels, as did cancellous bone volume, trabecular number, and cortical porosity. These data, the first to reflect such long exposure of any PTH for any disease, illustrate that PTH establishes and maintains a new skeletal state for at least 8 years in hypoparathyroidism. © 2018 American Society for Bone and Mineral Research.
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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 | 0.000 |
| 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".