Burden of rheumatic diseases among people with diabetes: A systematic review and meta-analysis
Bibliographic record
Abstract
Diabetes mellitus type 2 (DM2) is a prevalent metabolic condition affecting over 500 million people globally and associated with serious comorbidities, including various rheumatologic conditions. Some studies have reported a significant association between rheumatological conditions and DM2. However, the global burden of rheumatological conditions among people with DM2 remains unknown. The aim of this study was to assess the cumulative prevalence of rheumatological conditions in DM2 patients. An extensive electronic search was conducted utilizing multiple databases of studies published until January 2024. The quality of the studies included in the review was evaluated using a modified version of the Newcastle-Ottawa Scale (NOS). The overall quality of the studies included was rated as moderate. The review included a total of 13 studies, with 830,649 DM2 patients reported to have rheumatological conditions. Eleven studies were used to determine the individual results of rheumatoid arthritis (RA), gout, and osteoarthritis (OA). The pooled prevalence of OA was 26% (95%CI: 19-32%) and the prediction interval ranged from 6% to 51%. The pooled prevalence of gout disease was 1% (95%CI: 0.0-5.0%), and the prediction interval ranged from 0% to 99%. For RA, the combined prevalence was 0.3% (95%CI: 0.2-0.5%) and the prediction interval ranged from 0% to 5%. In conclusion, this review suggests a considerable prevalence of OA among DM2 patients, while the prevalence of RA and gout was minimal. Early diagnosis and management of certain rheumatologic conditions in individuals with DM2 may help improve health outcomes and prevent premature mortality. Further research is warranted to explore and understand the mechanisms underlying the association between DM2 and rheumatological conditions.
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 | 0.011 | 0.028 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.016 | 0.028 |
| Bibliometrics | 0.008 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".