30 Dynapenia and risk factors in Immune-Mediated Rheumatic Diseases: A Systematic Review
Bibliographic record
Abstract
Abstract Dynapenia, the age-related decline in muscle strength, poses significant challenges to the quality of life, autonomy, and health of individuals, becoming a major public health concern. Immune-Mediated Rheumatic Diseases (IMRDs) patients often experience dynapenia, regardless of age. Therefore, our aims were to assess the association between changes in muscle strength and changes in clinical features in IMRDs. Additionally, to evaluate risk factors for adverse health outcomes in IMRDs. A systematic review of longitudinal studies published in English was conducted using PubMed, Embase, Web of Science and Scopus to November 2023. Search strategies were based on pre-defined keywords and medical subject headings. The methodological quality of included studies was assessed using the Newcastle-Ottawa Scale. Of 11.692 potential studies (5138 duplicate publication) screened for inclusion in the study, twenty-one were included. Of these 21 studies included, one study was with systematic sclerosis (Ss) patients, two studies were with systemic erythematosus lupus (SLE) patients and eighteen studies were with rheumatoid arthritis (RA) patients. The decrease in muscle strength was associated with worsening clinical features over time in both SLE and RA patients. Lastly, low muscle strength was linked to multiple falls and reduced 5-year survival in RA patients. Therefore, changes in muscle strength are associated with changes in clinical features over time, and low muscle strength is linked to adverse health outcomes. The study emphasizes the importance of targeted exercise interventions aimed at improving muscle strength to mitigate adverse health outcomes and enhance clinical features in IMRDs patients.
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 | 0.007 | 0.029 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.009 | 0.009 |
| Bibliometrics | 0.009 | 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) | 0.006 | 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".