A systematic review of the correlation between overweight/obesity and osteoarthritis in Chinese population
Bibliographic record
Abstract
Objective To evaluate the correlation between overweight/obesity and osteoarthritis in Chinese population. Methods In both English and Chinese, the terms overweight, obesity, osteoarthritis, case control study, cohort study were used as search terms. The major Chinese biomedical databases (CBM, CNKI, VIP, Wanfang) , PubMed, Embase, Cochrane library and related clinical registry database were searched, and the references of included literatures were also screened. These literatures were selected and the related data were extracted by two authors according to the inclusion and exclusion criteria. The Newcastle-Ottawa Scale(NOS)was used to evaluate the quality of the included studies, and RevMan 5.3 software was used for meta-analysis. Results Four case-control studies which included 12 295 patients were included. Among all the patients, 2 127 were included into the knee osteoarthritis group, and the other 10 168 patients were included into the non-osteoarthritis group. The NOS score indicated that there were one high-quality study, and three low-quality studies. The meta analysis showed that the number of obese people in the knee osteoarthritis group was 2.06 times as high as that of the non knee osteoarthritis group, and there was a statistical difference between the two groups (OR=2.06, 95% confidence interval[1.43, 2.95], P |z|= 0.089 showed that there was an obvious published bias. In Egger test, the index of P>|t| equaled 0.291 which showed that there was no obvious bias in these studies. According to the two test results, it can not be defined whether published bias existed or not. Conclusions Overweight and obesity belong to the factors that can influence the development of knee osteoarthritis. Therefore, prevention of obesity may be a way to reduce knee osteoarthritis. But most of the current domestic research are not well designed, their quality are relatively low, outcomes are not complete and sample sizes are small; so it is necessary to design trials with high quality to improve the level and strength of evidences. Key words: Obesity; Overweight; Osteoarthritis; Case-control study; Meta-analysis
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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 | 0.009 | 0.031 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.010 | 0.009 |
| Bibliometrics | 0.011 | 0.012 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| 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".