Effectiveness and safety of decompression alone versus decompression plus fusion for lumbar spinal stenosis with degenerative spondylolisthesis: a systematic review and meta-analysis
Bibliographic record
Abstract
Background: There have been lingering controversies reported decompression and plus fusion. And the relative safety of fusion in addition to standard decompression remains unclear. This study aimed to assess the effectiveness and safety of decompression alone or combined with fusion in lumbar spinal stenosis (LSS) with degenerative spondylolisthesis (DS). Methods: In this systematic review and meta-analysis, we searched the databases of PubMed, Embase, Cochrane Library, and Web of Science for relevant literature from their inception to 28th December 2021. We identified the eligible studies based on the PICOS principles, populations (LSS with DS), interventions (decompression alone), controls (decompression combined with fusion), outcomes [overall reoperation rate, complications, Oswestry Disability Index (ODI), operative time, the amount of blood lost, length of stay (LOS), and visual analog scales (VAS)], study design (cohort studies). Quality assessment for individual study was performed with the Newcastle-Ottawa Scale (NOS). Results: In all, 12 articles involving a total of 14,693 patients were finally included in the study, the majority of patients underwent decompression alone (DA group: n=11,598) and the rest underwent decompression associated with fusion (FU group: n=3,095). The quality of most of the included studies was regarded as high quality. The results indicated that the FU group had a higher rate of complication [relative risk (RR): 1.770, 95% confidence interval (CI): 1.485 to 2.110], longer operative time [weighted mean difference (WMD): 51.037, 95% CI: 13.743 to 88.330], and increased blood loss (WMD: 258.354, 95% CI: 150.468 to 366.239) than the DA group (all P<0.05), with no significant differences for overall reoperation rate (RR: 0.879, 95% CI: 0.432 to 1.786), ODI (WMD: -2.569, 95% CI: -6.548 to 1.409), LOS (WMD: 3.838, 95% CI: -2.172 to 9.848), and VAS found between the two groups (P>0.05). Conclusions: In patients with LSS + DS, the effectiveness and safety of decompression alone may be superior to decompression plus fusion in terms of complication rate, operative time, and the amount of bleeding. However, more high-quality literature is needed in the future to confirm the best treatment choice for patients with LSS + DS.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.010 | 0.001 |
| 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 | 0.000 | 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".