The effectiveness and safety of LMWH for preventing thrombosis in patients with spinal cord injury: a meta-analysis
Bibliographic record
Abstract
Abstract Background Unfractionated heparin (UFH) and low molecular weight heparin (LMWH) are commonly used for preventing venous thrombosis of the lower extremity in patients with traumatic spinal cord injury. Although, LMWH is the most commonly used drug, it has yet to be established whether it is more effective and safer than UFH. Further, a comparison of the effectiveness of LMWH in preventing thrombosis at different locations and different degrees of spinal cord injury has also not been clearly defined. Materials and methods Cohort studies comparing the use of LMWH and UFH in the prevention of lower limb venous thrombosis in patients with spinal cord injury were identified using PubMed. The risk of bias and clinical relevance of the included studies were assessed using forest plots. The Newcastle-Ottawa quality assessment scale was used to evaluate the quality of the included studies. The main results of the study were analyzed using Review Manager 5.3. Results A total of five studies were included in this meta-analysis. Four studies compared the effectiveness and safety of LMWH and UFH in preventing thrombosis in patients with spinal cord injury. No significant differences were found between the therapeutic effects of the two drugs, and the summary RR was 1.33 (95% CI 0.42–4.16; P = 0.63). There was also no significant difference in the risk of bleeding between the two medications, and the aggregate RR was 0.78 (95% CI 0.55–1.12; P = 0.18). When comparing the efficacy of LMWH in preventing thrombosis in different segments and different degrees of spinal cord injury, no significant differences were found. Conclusions The results of this analysis show that compared with UFH, LMWH has no obvious advantages in efficacy nor risk prevention, and there is no evident difference in the prevention of thrombosis for patients with injuries at different spinal cord segments.
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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 | 0.014 | 0.029 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.021 | 0.054 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".