Association Between Changes in Abdominal and Lumbar Multifidus Muscle Thickness and Clinical Improvement After Spinal Manipulation
Bibliographic record
Abstract
STUDY DESIGN: Prospective case series. OBJECTIVE: To examine the relation between improved disability and changes in abdominal and lumbar multifidus (LM) thickness using ultrasound imaging following spinal manipulative therapy (SMT) in patients with low back pain (LBP). BACKGROUND: Although there is a growing body of literature demonstrating physiologic effects following the application of SMT, few studies have attempted to correlate these changes with clinically relevant outcomes. METHODS: Eighty-one participants with LBP underwent 2 thrust SMT treatments and 3 assessment sessions within 1 week. Transversus abdominis (TrA), internal oblique (IO), and LM muscle thickness was assessed during each session, using ultrasound imaging of the muscles at rest and during submaximal contractions. The Modified Oswestry Disability Index was used to quantify participants' improvement in LBP-related disability. Stepwise hierarchical multiple linear regression and repeated-measures analysis of variance were performed to examine the multivariate relationship between change in muscle thickness and clinical improvement over time. RESULTS: After controlling for the effects of age, sex, and body mass index, change in contracted LM muscle thickness was predictive of improved disability at 1 week (P = .02). As expected, larger increases in contracted LM muscle thickness at 1 week were associated with larger improvements in LBP-related disability. Contrary to our hypothesis, significant decreases in both contracted TrA and IO muscle thickness were observed immediately following SMT; but these changes were transient and unrelated to whether participants experienced clinical improvements. CONCLUSION: These findings provide evidence that clinical improvement following SMT is associated with increased thickening of the LM muscle during a submaximal task. LEVEL OF EVIDENCE: Prognosis, level 4.
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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".