Bibliographic record
Abstract
目的 比较体外冲击波(ESW)与保守治疗应力性骨折(SF)的疗效,并观察ESW治疗的安全性. 方法 对2011年9月至2012年12月收治的45例Ⅱ、Ⅲ型SF男性患者资料进行回顾性研究,根据治疗方法不同分为ESW组(ESW治疗,32例)和石膏组(石膏固定治疗,13例).两组患者治疗前一般资料比较差异均无统计学意义(P＞0.05),具有可比性.观测和比较两组患者治疗后1、2、4周的患者全身状况、X线、CT、延迟性肌肉酸痛症(DOMS)疲劳程度6级评分法、简化McGill疼痛评分表(MPQ)及血清骨特异性碱性磷酸酶(sBAP),从而判定骨折愈合情况. 结果 ESW组经2次治疗后24例患者在2周后出现明显骨痂,骨折间隙密度增高;4周后骨折线基本消失,骨痂致密,髓腔几乎完全再通,最终获得骨性愈合.治疗后1个月ESW组与石膏组相比,DOMS评分、MPQ评分均明显降低,ESW组治疗后1个月的DOMS评分、MPQ评分与治疗前比较均下降,差异均有统计学意义(P＜0.05). 结论 ESW治疗SF可促进骨痂生长、缩短愈合时间,无明显血管、神经损伤及其他全身并发症发生,其治疗方法简单、安全、有效、损伤小,提示ESW是治疗SF的一种有效方法。
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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 | 0.004 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.004 | 0.007 |
| Scholarly communication | 0.011 | 0.010 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.023 | 0.005 |
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".