A Case-control Study about the Pain in the Patients with Protrusion of Lumbar Intervertebral Disc
Bibliographic record
Abstract
目的 通过对腰椎间盘突出症患者疼痛的病例对照研究,对腰椎间盘突出症患者的疼痛及其后果进行评价.方法采用McGill疼痛调查表对94名腰椎间盘突出症患者和398名对照者进行疼痛调查.结果腰椎间盘突出症患者感觉性疼痛总分值为(5.22±2.22)分,情感性疼痛评分值为(2.68±0.81)分,VAS评分值为(7.79±1.42)分,均高于对照组,P＜0.01,差异有极显著性.典型相关分析结果表明疼痛的强度与日常生活自理能力受损程度有正相关,r=0.76296,P＜0.01.结论腰椎间盘突出症患者疼痛非常严重,且疼痛的强度与患者日常生活能力受损有关,情感性疼痛评分值和VAS评分值越高,对腰椎间盘突出症患者上下床起坐的影响越严重。
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".