Impact of overweight and obesity on disease activity and remission in systemic lupus erythematosus: A systematic review and meta-analysis protocol
Bibliographic record
Abstract
BACKGROUND: Systemic lupus erythematosus (SLE) is an autoimmune and inflammatory disease that requires treatment with hydroxychloroquine and glucocorticoids. Glucocorticoids are responsible for adverse effects such as increased weight, which can modify the severity and chronicity of autoimmune pathologies. AIM: To summarize scientific evidence regarding the impact of overweight and obesity on disease activity and remission in SLE. METHODS: The protocol was developed according to the Preferred Reporting Items for Systematic Review and Meta-analysis Protocol (PRISMA-P) and published in the International Prospective Register of Systematic Reviews database (PROSPERO-CRD42021268217). PubMed, Scopus, Embase, and Google Scholar will be searched for observational studies including adult patients with SLE who were overweight and obese or not, that included disease activity or remission as outcomes. The search is planned for May 2023. Three independent authors will select the eligible articles and extract their data. Subsequently, three authors will independently extract data from each included study using an extraction form created by the researchers. Methodological quality analyses will be performed using the modified Newcastle-Ottawa scale. The results will be presented as a narrative synthesis according to the synthesis without a meta-analysis reporting guideline (SWiM). Meta-analysis will be conducted where appropriate using random-effects models. EXPECTED RESULTS: This review will identify the impact of overweight and obesity on the clinical features of SLE, helping clinicians manage disease activity and remission, both important to optimize disease outcomes and patient quality of life.
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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 | 0.066 | 0.088 |
| Meta-epidemiology (narrow) | 0.006 | 0.005 |
| Meta-epidemiology (broad) | 0.020 | 0.024 |
| Bibliometrics | 0.009 | 0.009 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.007 | 0.006 |
| Open science | 0.005 | 0.005 |
| Research integrity | 0.008 | 0.006 |
| Insufficient payload (model declined to judge) | 0.081 | 0.008 |
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".