Influence of Cigarette Smoking on Osteonecrosis of the Femoral Head (ONFH): A Systematic Review and Meta-Analysis
Bibliographic record
Abstract
BACKGROUND: Current studies demonstrate controversy regarding the relationship between cigarette smoking and osteonecrosis of the femoral head (ONFH). METHODS: We conducted a meta-analysis to evaluate the association between smoking and ONFH. Relevant articles published before September 2016 were identified by a systematic search of EMBASE and MEDLINE via Ovid. Summary odds ratios (OR) were calculated using random effects models, and study quality was assessed using a modified Newcastle-Ottawa scale. RESULTS: 102 citations were screened and 7 case-control studies were identified and included in the review. When compared with nonsmokers, current smokers had a higher risk of developing ONFH (OR 2.53; 95% confidence interval [CI] 1.68-3.79), as did former smokers (OR 1.82; 95% CI, 1.10-3.00). Within the group of current smokers, those classified as heavy smokers (with a daily number >20 cigarettes/day) demonstrated higher risks of ONFH (OR 2.03; 95% CI, 1.29-3.19), and light smokers classified as smoking <20 cigarettes/day, also demonstrated a higher risk of ONFH when compared with nonsmokers (OR 1.73; 95% CI, 1.06-2.83). When smoking was classified by pack-years, heavy smokers (>20 pack-years) were at a higher risk of ONFH (OR 2.26; 95% CI, 1.24-4.13), but no significant difference in risk was identified in light smokers (<20 pack-years) (OR 1.81; 95% CI, 0.88-3.71) when compared with nonsmokers. CONCLUSIONS: Our meta-analysis showed that current smokers were at a higher risk of ONFH, this high risk can also be found in former smokers. And heavy cigarette smoking showed a higher risk of ONFH than light smoking.
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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 | 0.010 | 0.026 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.016 | 0.029 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".