Methodological quality of cohort study on rheumatic diseases in China: A systematic review
Bibliographic record
Abstract
OBJECTIVE: To evaluate systematically the quality of the cohort studies on rheumatic diseases in China. METHODS: Relevant databases were searched to find cohort studies on rheumatic diseases in China, and the basic information included in the literature was extracted and analyzed. Chinese and English literature were then compared with regard to methodological quality, according to the Newcastle-Ottawa Scale (NOS). RESULTS: In total, we included 46 cohort studies, with 19 studies published in English and 27 studies published in Chinese. With regard to the basic characteristics of the literature, 78.26% of the studies were published in the past four years; 16 studies were associated with hyperuricemia, followed by eight studies involving systemic lupus erythematosus. The sample size of the studies in Chinese was lower than that in English studies (P< 0.05). The English literature was superior to the Chinese literature in terms of informed consent, ethical review and selection of statistical analysis methods. The methodology quality of the 46 included studies showed that the English and Chinese NOS scores were 5.59 ± 1.25 and 6.06 ± 1.11, respectively, and the difference was significant (P< 0.01). The "representativeness of the exposed group", "demonstration that outcome of interest was not present at start of study", and the "adequacy of follow up of cohorts" scores were relatively low in Chinese and English studies. The score for "was follow-up long enough for outcomes to occur" item in English was higher than that in the Chinese studies; however, the "study controls for the most important factor" score for Chinese papers was better than that for the English papers. CONCLUSION: The Chinese rheumatic disease cohort studies started late, with a small sample size and fewer types of rheumatism. The quality of Chinese studies was better than English studies, and all reports were insufficient. In particular, "selecting exposed groups", "controlling the outcomes before study implementation" and "adequacy of follow-up" needed improvement.
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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 | 0.136 | 0.291 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.013 | 0.013 |
| Bibliometrics | 0.018 | 0.016 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.004 | 0.004 |
| Research integrity | 0.003 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".