Determining the association between systematic lupus erythematosus and the occurrence of primary biliary cirrhosis: a systematic review and meta-analysis
Bibliographic record
Abstract
BACKGROUND: Autoimmune diseases often coexist; however, the concomitant occurrence of systemic lupus erythematosus (SLE) and primary biliary cirrhosis (PBC) is rare. Therefore, this study aims to provide a comprehensive summary of evidence regarding the co-occurrence of SLE and PBC. METHODS: PubMed, Web of Science, ScienceDirect , and Google Scholar databases were systematically and comprehensively searched for records published up to February 2024. Full-text articles that aligned with the study's aim were included, while those published in languages other than English and those designed as case reports, reviews, conference abstracts, or editorials were excluded. Statistical analyses were performed using Comprehensive Meta-Analysis software, and methodological quality was assessed using the Newcastle-Ottawa Scale. RESULTS: Only 14 studies that met the inclusion criteria with 3944 PBC and 9414 SLE patients were included for review and analysis. Pooled data analysis revealed that approximately 1.1% of SLE patients have concomitant PBC (range: 0.02-7.5%), while around 2.7% of PBC patients concurrently have SLE (range: 1.3-7.5%). Furthermore, qualitative data analysis indicated that the prevalence of PBC in SLE patients presenting with hepatic dysfunction or abnormal liver enzymes ranges from 2 to 7.5%. CONCLUSION: Although the concomitant occurrence of SLE and PBC is rare, the small proportion of patients where these diseases coexist warrants close monitoring by clinicians. This underscores the importance of surveillance to prevent their co-occurrence.
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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 | 0.014 | 0.035 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.016 | 0.031 |
| Bibliometrics | 0.010 | 0.011 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 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".