Management of Degenerative Lumbar Spinal Stenosis in the Elderly
Bibliographic record
Abstract
BACKGROUND: Lumbar spinal stenosis can cause symptomatic neurogenic claudication alongside radicular pain and weakness. In appropriately selected patients, surgical intervention has been demonstrated to provide for improvement in pain, disability, and quality of life. This systematic review sought to define the utility and safety of such decompression with or without arthrodesis in the management of symptomatic lumbar spinal stenosis for elderly patients older than 65 years of age. METHODS: A systematic review was conducted using MEDLINE for literature published through December 2014. The first question focused on the effectiveness of lumbar spinal surgery for symptomatic lumbar spinal stenosis in elderly patients (over age 65 y). The second question focused on safety of surgical intervention on this elderly population with emphasis on perioperative complication rates. RESULTS: Review of 11 studies reveals that the majority of elderly patients exhibit significant symptomatic improvement, with overall benefits observed for pain (change visual analog scale 4.4 points) and disability (change Oswestry Disability Index 23 points). Review of 11 studies reveals that perioperative complications were infrequent and acceptable with pooled estimates of mortality (0.5%), inadvertent durotomy (5%), and wound infection (2%). Outcomes seem less favorable with greater complication rates among patients with diabetes or obesity. CONCLUSION: Based on largely low-quality, retrospective evidence, we recommend that elderly patients should not be excluded from surgical intervention for symptomatic lumbar spinal stenosis.
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 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 | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".