A meta-analysis of prognostic factors in surgical treatment of foot drop due to lumbar degenerative diseases
Bibliographic record
Abstract
Objective: Lumbar decompression surgery is an effective treatment for foot drop caused by LDD, but there is controversy about the prognostic factors affecting its efficacy. This study aimed to investigate the factors influencing the surgical outcome of foot drop due to LDD. Methods: A systematic database search of PubMed, Embase, Web of Science, Cochrane Library and Clinical Trials was performed for relevant articles published until May 2022. Two reviewers independently screened the literature, extracted data, and evaluated the quality of the studies based on the inclusion and exclusion criteria. The quality of the studies was evaluated using the Newcastle-Ottawa Scale (NOS), and STATA 16.0 software was used for meta-analysis. Results: A total of 730 relevant articles were initially identified and 9 articles were finally included in this study for data extraction and mea-analysis. The results of metaanalysis showed that patients with preoperative moderate muscle strength (2-3/5 on the Medical Research Council scale) had better prognosis compared to those with severe muscle weakness. Additionally, the presence of diabetes mellitus was associated with a poorer prognosis for patients with foot drop due to LDD. The OR values (95%CI) of these two factors were 5.882 (4.449, 7.776) and 5.657 (2.094,15.280) respectively. Conclusions: Patients with moderate muscle strength have a better prognosis compared to those with severe muscle weakness. The presence of diabetes mellitus is associated with a poorer prognosis for patients with foot drop due to LDD. These factors should be considered when predicting the surgical outcome of foot drop due to LDD.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.006 | 0.003 |
| Bibliometrics | 0.002 | 0.005 |
| 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) | 0.000 | 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 teacher head, 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".