Is There Any Correlation Between the Systemic Immune Inflammatory Index and Disease Severity in Knee Osteoarthritis?
Bibliographic record
Abstract
Objective:The purpose of this study is to investigate the utility of systemic immune inflammation index as a predictor of disease severity in patients with knee osteoarthritis. Methods: 200 patients diagnosed with knee osteoarthritis according to ACR knee osteoarthritis diagnostic criteria were included in the study. Kellgren-Lawrence staging of knee osteoarthritis, Western Ontario and McMaster University Osteoarthritis (WOMAC) index score and systemic immune-inflammation index score were calculated among all participants Results: There were 152 (%76) female and 48 (%24) male participants and median score of age was 63 (54,25-70). 14 (7%) grade 1 gonarthrosis, 64 (32%) grade 2, 72 (36%) grade 3 and 50 (25%) grade 4 gonarthrosis patients were detected. There was no significant correlation between the systemic immune-inflammation index and the radiological stage of gonarthrosis (Kellgren Lawrens Score) (p=0.238). No statistically significant correlation was found between the systemic immune-inflammation index and WOMAC scores (p=0.593). Conclusion: The systemic immune-inflammation index was not found to be correlated with disease severity in knee OA.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.003 | 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".