Clinical Significance of Resistin Expression in Osteoarthritis: A Meta-Analysis
Post-publication record
Source: Retraction Watch, joined by DOI. OpenAlex records retraction as is_retracted, a boolean over a state space with at least four values, so it cannot express an expression of concern, a correction or a reinstatement; it reports them as false, which reads as “fine”.
Bibliographic record
Abstract
BACKGROUND: The objective of this study was to conduct a systematic review of literature evaluating human resistin expression as a diagnostic factor in osteoarthritis development and to quantify the overall diagnostic effect. METHOD: Relevant studies were identified and evaluated for quality through multiple search strategies. Studies analyzing resistin expression in the development of OA were eligible for inclusion. Data from eligible studies were extracted and included into the meta-analysis using a random-effects model. RESULTS: Four case-control studies consisting of a total of 375 OA patients and 214 controls as well as three sex-stratified analyses composed of 53 males and 104 females were incorporated into our meta-analysis. Our results revealed that resistin levels were significantly higher in male OA subjects and OA patients overall. Country-stratified analysis yielded significantly different estimates in resistin levels between male OA subjects and female OA subjects in the Canadian subgroup but not among the French and USA subgroups. Based on the resistin levels in OA cases and controls, resistin levels were heightened in OA patients in the Dutch population. CONCLUSION: These results support the hypothesis that high expression of resistin represents a significant and reproducible marker of poor progression in OA patients, especially in males.
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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 | 0.011 | 0.022 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.013 | 0.025 |
| Bibliometrics | 0.007 | 0.007 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 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".