Evaluation of Disability and Physical Performance Based on Mechanical and Inflammatory Component in Chronic Low Back Pain.
Bibliographic record
Abstract
Objective: The aim of this study was to perform the validity and reliability analysis of the Turkish-language version of the Mechanical and Inflammatory Low Back Pain Index (MILBPI), which is used to determine mechanical and inflammatory components in chronic low back pain (CLBP). The effects of mechanical and inflammatory components on disability and physical performance in patients with CLBP were investigated. Material and Method: In the first phase of the study, 120 CLBP patients aged 18-65 years were included in the Turkish-language version validity and reliability analysis of MILBPI. In the second phase of the study, the mechanical and inflammatory components of CLBP were determined in 50 patients using the Turkish-language version valid and reliable MILBPI and the effects of these components on disability and physical performance were investigated. Tests for walking, timed get-up and go, sitting and standing and trunk flexion were used to assess physical performance. Quebec Back Pain Disability Scale (QBPDS) was used to assess disability. Results: Factor loadings of the index items were above 0.30 which explained 83.237% of the total variance. Cronbach's alpha coefficient was found 0.735. Test-retest analysis of the index was highly correlated. LBP score of the components was significantly associated with disability (P1 < .05). Inflammatory component had a statistically significant relationship with trunk flexion (P1 < .05), while the mechanical component had no significant effect on walking (P1 > .05). Conclusion: According to the analyses in the first phase of our study, MILBPI is a valid and reliable scale in Turkish-language version. Additionally, the mechanical and inflammatory components of pain determined using MILBPI have an impact on some physical performance parameters and disability.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| 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) | 0.001 | 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".