Myocardial performance index to assess cardiac function in spondyloarthritis: A systematic review and meta-analysis
Bibliographic record
Abstract
INTRODUCTION: This study aimed to assess cardiac function using the Myocardial Performance Index (MPI) in spondyloarthritis (SpA) patients. MATERIAL AND METHODS: A comprehensive literature search was conducted in databases including Medline, ProQuest, Google Scholar, Scopus, and Cochrane Library, focusing on studies relevant to SpA and MPI from 1995 to 2023. The Newcastle Ottawa Scale (NOS) was employed to assess study quality, and meta-analysis computations were conducted utilizing Review Manager 5.4. RESULTS: A total of 11 studies were included in this systematic review and meta-analysis. The spectrum of SpA covered in this review consisted of 1 study on undifferentiated spondyloarthritis (uSpA) and 10 studies on ankylosing spondylitis (AS). Various MPI assessment methods were utilized, including conventional echocardiography and tissue doppler imaging (TDI). In AS patients, both conventional MPI (cMPI) and tissue doppler MPI (tdMPI) values were significantly higher than those of healthy controls (MD= 0.05, 95% CI: 0.01-0.08, p-value=0.006 and MD=0.08, 95%CI: 0.06-0.10, p value<0.00001, respectively). In the uSpA study, there were no significant differences in MPI values between patients and controls with either cMPI or tdMPI. CONCLUSION: Significant differences in MPI values were observed between AS patients and healthy controls using both cMPI and tdMPI, suggesting that MPI may serve as a useful tool for early detection and management of cardiac dysfunction in AS patients. Further studies were required to validate these findings.
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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 | 0.012 | 0.027 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.014 | 0.026 |
| Bibliometrics | 0.007 | 0.007 |
| 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) | 0.003 | 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".