Predictors of improvement following early exercises rehabilitation program for patients undergoing open lumbar discectomy
Bibliographic record
Abstract
Background and aims: Low back pain is mostly due to disc herniation and has a burden upon economy and social aspects of life. Failure to improve after open lumbar discectomy is frustrating. Therefore, identifying predictors of improvement is of great clinical benefit. Aims: This research was conducted to evaluate whether an early exercises rehabilitation program using educational booklet would provide benefit to patients following open lumbar discectomy and determine potential factors of improvement.Patients and methods: Design: Single blind randomized controlled trial. Eighty-eight patients scheduled for open lumbar discectomy from January 2017 to January 2019 at Assiut and Ain Shams Universities hospitals in Egypt were randomly assigned to two groups. Control group (n = 44) received routine postoperative instructions while intervention group (n = 44) received routine instructions in addition to early exercises rehabilitation program and were also provided with a specifically designed educational booklet. Patients were followed up after six months using Oswestry disability index.Results: There was significant improvement among intervention group as compared to control group in several domains of Oswestry disability index (walking, sitting, standing, sleeping, travelling and sexual and social life). Better pre-operative Oswestry disability index score and early application of exercises rehabilitation program using an educational booklet predicted better postoperative Oswestry disability index score after six months.Conclusion: Application of an early exercise rehabilitation program and providing patients with a specifically designed educational booklet would be helpful for patients following open lumbar discectomy. Clinical Relevance: Early exercises rehabilitation program can be used by nursing staff as a reference in management of patients following open lumbar discectomy.
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".