The link between traumatic stress and autoimmune rheumatic diseases: A systematic scoping review
Bibliographic record
Abstract
BACKGROUND: The impact of traumatic stress on autoimmune rheumatic diseases (ARDs) has been largely overlooked in existing research. This scoping review aimed to systematically examine the research literature relating to the relationship between traumatic stress and ARDs, by identifying study designs, methodologies, and gaps in the current research landscape. METHODS: The following databases and search interfaces were searched on 15th December 2023: Embase (via Embase.com), Medline (via PubMed), and Web of Science. Additional references were identified via bibliographies of included studies. The following studies were included, with no publication date limit and language restricted to English: targeting the association between traumatic stress and ARDs, observational methodologies, including cohort, case-control, and cross-sectional studies, exclusively focusing on self-reported psychological trauma impacts, such as adverse childhood experiences (ACEs), Post-traumatic Stress Disorder (PTSD), or major life stressors. Two authors independently assessed the studies for inclusion criteria and extracted the data. RESULTS: This scoping review revealed connections between traumatic stress and ARDs through an analysis of 21 included studies, highlighting the scarcity of research in this area. The studies, primarily from high-income countries and especially the USA, span from 2000 to 2023, indicating a growing interest in recent years and employing a range of methodologies. Traumas such as ACEs, PTSD, and major life events were frequently examined, showing a strong association with an increased risk and severity of ARDs, particularly rheumatoid arthritis (RA) and systemic lupus erythematosus (SLE). CONCLUSION: This scoping review reveals a notable dearth in research on the impact of traumatic stress, such as ACEs, PTSD, and major life events, on ARDs, especially on rare diseases, yet underscores a significant association between trauma and ARD severity or incidence. It highlights the critical need for future investigations to broaden the scope of ARDs studied, extend research to less represented regions, and utilize diverse, standardized methodologies to deepen our understanding of the trauma-ARD association.
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.
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 | 0.019 | 0.089 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.007 |
| Bibliometrics | 0.025 | 0.023 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.004 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".