Mortality risk in osteoarthritis patients: a meta-analysis of observational studies
Bibliographic record
Abstract
OBJECTIVES: This study aimed to evaluate the relationship between osteoarthritis (OA) and all-cause mortality, as well as cause-specific mortality. METHODS: This study was registered with PROSPERO (ID: CRD42024542643). A comprehensive literature search was conducted using Medical Subject Headings (MeSH) and keywords across PubMed, Embase, and the Cochrane Library databases, from inception to May 16, 2024. Study quality was assessed using the Newcastle-Ottawa Scale (NOS) and the Agency for Healthcare Research and Quality (AHRQ) criteria. Funnel plots and Egger’s test were used to assess publication bias. Statistical analyses were performed using STATA software version 14.0. RESULTS: Twenty-four observational studies (2003–2023) involving 465,555 OA patients were included. The pooled analysis revealed no significant association with all-cause mortality based on pooled estimates, although with very high heterogeneity [OR = 1.14, 95% CI (0.97, 1.35), I² = 98.2%, P = 0.119], but appeared to be associated with increased (CVD) mortality [OR = 1.15, 95% CI (1.07, 1.24), I² = 73.5%, P < 0.001]. There was no increased risk of cancer mortality [OR = 1.02, 95% CI (0.94, 1.11), I² = 69.4%, P = 0.000]. Subgroup analysis indicated no significant gender-based differences in all-cause mortality, nor in radiographic OA. However, symptomatic OA and knee/foot OA were associated with a markedly higher risk of all-cause mortality. Regional analysis showed no significant variation across Europe, Asia, or North America. Sensitivity and subgroup analyses confirmed the results, with no evidence of publication bias. CONCLUSIONS: This meta-analysis suggests that osteoarthritis is not associated with all-cause mortality but is but is associated with a modest increase in CVD mortality. There is no relationship between OA and cancer mortality. These findings emphasize the importance of focused care and lifestyle modifications to mitigate cardiovascular risks in OA 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 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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.002 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".