Systematic literature review informing the 2022 EULAR recommendations for screening and prophylaxis of chronic and opportunistic infections in adults with autoimmune inflammatory rheumatic diseases
Why this work is in the frame
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Bibliographic record
Abstract
Objective To conduct a systematic literature review (SLR) on the screening and prophylaxis of opportunistic and chronic infections in autoimmune inflammatory rheumatic diseases (AIIRD). Methods SLR (inception-12/2021) based on the following search domains: (1) infectious agents, (2) AIIRD, (3) immunosuppressives/immunomodulators used in rheumatology, (4) screening terms and (5) prophylaxis terms. Articles were retrieved having the terms from (1) AND (2) AND (3) plus terms from (4) OR(5). Databases searched: PubMed, Embase and Cochrane Library. Exclusion criteria: studies on postoperative infections, paediatric AIIRD, COVID-19, vaccinations and non-Εnglish literature. Study quality was assessed with Newcastle-Ottawa scale for non-randomised controlled trials (RCTs), RoB-Cochrane for RCTs, AMSTAR2 for SLRs. Results From 5641 studies were retrieved, 568 full-text articles were assessed for eligibility, with 194 articles finally included. For tuberculosis, tuberculin skin test (TST) is affected by treatment with glucocorticoids and conventional synthetic disease modifying anti-rheumatic drugs (DMARDs) and its performance is inferior to interferon gamma release assay (IGRA). Agreement between TST and IGRA is moderate to low. For hepatitis B virus (HBV): risk of reactivation is increased in patients positive for hepatitis B surface antigen. Anti-HBcore positive patients are at low risk for reactivation but should be monitored periodically with liver function tests and/or HBV-viral load. Risk for Hepatitis C reactivation is existing but low in patients treated with biological DMARDs. For Pneumocystis jirovecii , prophylaxis treatment should be considered in patients treated with prednisolone ≥15–30 mg/day for >2–4 weeks. Conclusions Different screening and prophylaxis approaches are described in the literature, partly determined by individual patient and disease characteristics.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.002 | 0.000 |
| 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 it