‘Healthier Chinese spine’: an update of osteoporotic fractures in men (MrOS) and in women (MsOS) Hong Kong spine radiograph studies
Bibliographic record
Abstract
For the MrOS (Hong Kong) and MsOS (Hong Kong) baseline (BL) studies, community-dwelling 2,000 Chinese men (mean age: 72.3 years) and 2,000 Chinese women (mean age: 72.5 years) were recruited from 2001 to 2003. These two studies have spanned two decades till now. This review summarizes our spine radiograph results. Senile and post-menopausal osteoporosis were associated with intervertebral disc volume reduction; and in women, menopause accelerates disc degeneration. Elderly women's osteoporotic vertebral fracture (OVF) prevalence was double of that of elderly men. For year-4 follow-up (FU), male participants with BL OVF had little increased risk for further OVF. In our study comparing OVF rates in age-matched Hong Kong Chinese women and Italian Caucasian women (mean age: 74.1 years), endplate and/or cortex fracture (ECF) prevalence was 26% for Chinese and 47% for Italian. OVF with ≥40% vertebral height loss was recorded among 9.5% of the Chinese subjects while among 26% of the Italian subjects. OVFs in Italian subjects were more likely to be multiple and generally severer. Clinical spine fractures were recorded 133 cases/100,000 person-years in MrOS (Hong Kong) participants and 273 cases/100,000 person-years in MsOS (Hong Kong) participants. Literature review suggests the clinical vertebral fracture rates among elderly Hong Kong Chinese subjects are approximately half of those of American, Australian, and Canadian subjects. Data synthesis suggests elderly Caucasians have a higher degenerative spondylolisthesis prevalence, being approximately 70% higher than that of elderly Hong Kong Chinese. Literature review of other authors' publications shows, compared with Caucasians, Chinese have a much lower incident rate of back pain. We conclude that elderly Chinese have a generally healthier spine relative to elderly Caucasians.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.007 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".