Rehabilitation Following Lumbar Total Disc Replacement, With a Focus on Lumbar Multifidus Morphology and Function: A Case Report and Review of the Literature
Bibliographic record
Abstract
Background Lumbar total disc replacement (TDR) is an option for patients with severe low back pain from degenerative disc disease who have failed conservative treatment. Paraspinal muscles have played an important role in clinical outcomes after lumbar surgery. The purpose of this study was to investigate lumbar multifidus morphology and function in a patient following lumbar TDR and a postoperative rehabilitation exercise program. Case Presentation A 52-year-old man underwent TDR surgery at the L5-S1 level to treat his chronic low back pain, which had been present for several years and unresponsive to previous conservative management. Six weeks after the operation, the patient initiated an 8-week postoperative rehabilitation program focusing on motor control and strengthening exercises. Outcome and Follow-Up The patient experienced clinically important improvements in pain and disability, as well as improvements in lumbar multifidus size ranging from 3.17% to 13.84% and changes in thickness contraction ranging from 4.04% to 16.48%, following the postoperative rehabilitation program. However, differences in lumbar multifidus muscle morphology and function were observed when comparing the surgical site to the superior motion segment. Discussion This case report displays limited evidence regarding the effects and implementation of a motor control and strengthening exercise program following lumbar TDR. Some improvements in muscle morphology and function were observed, along with improvements in pain and disability, after the completion of the exercise program. The importance of including lumbar multifidus morphology and function in the postoperative rehabilitation of this population may warrant further research. JOSPT Cases 2022;2(1):34–41. doi:10.2519/josptcases.2022.10163
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".