The measurements of health-related quality-of-life and pain assessment in the preoperative patients with low back pain
Bibliographic record
Abstract
OBJECTIVE: This prospective observational study of the Short-Form Health Survey (SF-36), Oswestry Disability Index, Lithuanian version of the McGill Pain Questionnaire, and Visual Analogue Scale (VAS) for pain was performed to evaluate their effectiveness in the additional preoperative screening of patients with disc herniation disease. PATIENTS AND METHODS: In the present study, we investigated a cohort of 100 patients with lumbar disc herniation causing low back pain and the second one of 100 patients with nonspecific low back pain by applying physical activity, pain scales and Short-Form 36 General Health Questionnaire. RESULTS: The quantitative analysis of SF-36 domain scores showed the substantial differences in both examined (herniated and control) groups. In the present study, we estimated moderate but statistically significant (P<0.05) correlations between the bodily pain domain scores and assessment of back and leg pain on the VAS, as well as between the physical function and walking/standing ability (Oswestry). According to appropriate pain assessment instruments (Lithuanian version of the McGill Pain Questionnaire), qualitative and quantitative analysis of the preoperative patients was performed. CONCLUSION: The provided methodology could be used in population-based studies or in clinical samples that focus on specific impairments and seek to control the pain frequency and intensity, for example, follow-up assessments testing the effectiveness of surgical procedures performed, and to elicit the pathways leading to other impairments.
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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 | 0.001 | 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".