Factors Associated With Renal Involvement in Primary Sjögren's Syndrome: A Meta-Analysis
Bibliographic record
Abstract
Background: Renal impairment is a critical complication in primary Sjögren's syndrome (pSS), resulting in chronic renal disease and even death. This meta-analysis was designed to find out the relevant factors of renal involvement in pSS. Methods: PubMed, EMBASE, Cochrane Library, Scopus, and Web of Science were systemically searched until August 30, 2019. Studies were selected according to inclusion criteria, and data was extracted by two researchers independently. The Newcastle-Ottawa Scale was applied for quality assessment. Random- and fixed-effects models were used in this meta-analysis based on the result of the heterogeneity test. Meanwhile, a sensitivity analysis was conducted to investigate the cause of heterogeneity. Publication bias was shown in the funnel plot and evaluated further by Begg's and Egger's tests. Results: Of the 9,989 articles identified, five articles enrolling 1,867 pSS patients were included in the final analysis, 533 with and 1,334 without renal involvement. There was no statistical significance in age and gender between these two groups. According to the meta-analysis, anti-SSB antibody, and arthralgia showed a significant association with renal involvement in pSS, the overall odds ratio (OR) values of which were 1.51 (95% CI, 1.16–1.95) and 0.59 (95% CI, 0.46–0.74), respectively. On the other hand, the overall OR values of anti-SSA antibody, rheumatoid factor, dry eyes, and labial salivary gland biopsy were just 0.90 (95% CI, 0.49–1.64), 1.05 (95% CI, 0.59–1.86), 0.60 (95% CI, 0.34–1.06), and 1.38 (95% CI, 0.98–1.95), respectively. Conclusion: The presence of anti-SSB antibody is positively associated with renal involvement in pSS, while arthralgia is inversely associated. Large-scale prospective cohort studies are needed in the future to identify further risk factors.
Stored with the screening record, where it is evidence for the labels above.
How this classification was reachedexpand
The three-model screen
all 5,600 screened works →All three models called this out of scope.
Meta-analysis of factors associated with renal involvement in Sjogren's syndrome; synthesis used to answer a clinical question.
It uses meta-analysis to answer a clinical question about Sjögren's syndrome, not to study synthesis methods.
Clinical meta-analysis of renal involvement factors in primary Sjögren syndrome.
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 | 0.022 |
| Meta-epidemiology (narrow) | 0.004 | 0.002 |
| Meta-epidemiology (broad) | 0.017 | 0.067 |
| Bibliometrics | 0.007 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| 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".