Predictive value of bile acids as metabolite biomarkers for gallstones: A protocol of systematic review and meta-analysis
Bibliographic record
Abstract
BACKGROUND: Plenty of studies have focused on the bile acids profile in gallstones. The objective of our systematic review is to provide a comprehensive summary about bile acids profiles in gallstones and analyzes the difference between gallstones and control group in diverse samples, determining the characteristic bile acids as the metabolite biomarkers for predicting gallstone. METHODS: EMBASE, the Cochrane Library, PubMed, Web of Science, Wanfang databases, China National Knowledge Infrastructure (CNKI), VIP Information Resource Integration Service Platform (CQVIP), and China Biology Medicine Disc (SinoMed) will be searched with the keywords of gallstones and metabolomics. The screening process will be performed strictly according to inclusion and exclusion criteria. The CONSORT checklist and the Newcastle-Ottawa Scale (NOS) will assess the risk of bias for randomized controlled trials and observational studies, respectively. The qualitative review will be conducted to summarize the bile acids profile in gallstones. The concentrations of bile acids in both case group and control group will be the primary outcomes to perform the meta-analyses. EXPECTED RESULTS: Our systematic review will find the characteristic bile acids as the candidate metabolite biomarkers which equipped potential value to predict gallstones. CONCLUSION: Expanding the current knowledge on the physiopathology of gallstones and identifying novel predictive biomarkers can help to facilitate the detection and management of gallstones. Consequently, we expect this protocol to be a reasonable method to filtrate candidate differential bile acids which have potential value to predict gallstones. PROSPERO REGISTRATION NUMBER: CRD42022339649.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".