A meta‐analysis of the effects of bariatric surgery on fracture risk
Bibliographic record
Abstract
Bariatric surgery effectively treats morbid obesity. However, the negative effect of this surgery on the bone is concerning. The aim of this meta-analysis was to investigate the fracture risk associated with bariatric surgery in morbidly obese subjects. Relevant studies published from database inception to September 2017 were identified in PubMed, Embase and the Cochrane Library. The Newcastle-Ottawa Scale was used to evaluate the quality of the observational studies, and the Jadad score evaluated randomized controlled trials. Among the 1003 studies initially identified, five observational trials and one randomized controlled trial were eligible for inclusion. All studies included in the meta-analysis were considered high quality. Risk for any type of fracture was higher in the surgical group than in the non-surgical group (risk ratio [RR] 1.29, 95% confidence interval [CI] 1.18-1.42). After surgery, the fracture risk in non-vertebral sites was significantly increased, especially in the upper limbs (RR 1.42, 95% CI 1.08-1.87; and RR 1.68, 95% CI 1.15-2.45). Compared with those with restrictive procedures, subjects who underwent mixed restrictive and malabsorptive procedures tended to have an increased fracture risk (RR 1.54, 95% CI 0.96-2.46). To conclude, bariatric surgery is associated with an increased risk of total and non-vertebral fractures, especially in the upper limbs.
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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 | 0.012 | 0.028 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.015 | 0.055 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| 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".