The risk of osteoporosis and fracture in patients with multiple sclerosis: a literature review
Bibliographic record
Abstract
Multiple sclerosis (MS) is a neurodegenerative and autoimmune disease of the brain and spinal cord. It is characterised by gradual demyelination of the brain frequently resulting in relapsing or progressive neurological dysfunction of the body. Worldwide, the disease affects about 1.5 million people, including 630,000 Europeans, 520,000 Americans and 66,000 Eastern Mediterranean patients. Osteoporosis and the subsequent consequences of risk fracture are a major cause of morbidity and mortality worldwide. A recent Canadian study on fractures and mortality found a 4.19-fold increased risk of death in the first year after experiencing a hip fracture and a 2.53-fold for vertebral fractures. Estimated health expenditure due to osteoporotic fractures in Europe by the year 2015 are € 47.3 billion. A meta-analysis by the World Health Organization showed that a combination of bone mineral density (BMD) measurements and clinical risk factors obtained by questionnaires had a higher performance in predicting the risk of fractures than BMD measurements alone. Next to chronic or recurrent glucocorticoid therapy, age, female gender, a personal history or parental history of fracture, current smoking, rheumatoid arthritis, low body mass index (BMI) and alcohol use of more than 3 units per day. Based on these risk factors FRAX ®, a web-based tool, to assess the ten-year risk of an osteoporotic fracture on an individual level was developed. Currently, MS has not been identified as one of those risk factors and is not part of the FRAX ® tool. In addition, falling and inadequate levels of vitamin D have been reported to increase the risk of osteoporosis or osteoporotic fractures. MS patients may suffer from, or may develop one or more of these risk factors during the course of the disease predisposing them to osteoporosis. Disease progression leads to significant disability in multiple neurologic systems. The result is a decreased mobility, which can reduce the likelihood of sunlight exposure necessary to maintain sufficient vitamin D levels for healthy bones. This literature review evaluates the current evidence on the risk of osteoporosis in patients with MS looking at the risk of fractures, the role of bone mineral density and the risk of falling.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.008 | 0.011 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".