The clinical utility of the prone hip extension test in the diagnosis of motor control impairments associated with low back pain: A cross-sectional study using motion capture and electromyography
Bibliographic record
Abstract
BACKGROUND: The prone hip extension test is used as a clinical tool to diagnose specific motor control impairments that have been identified in individuals with chronic low back pain. However, conventional protocols for performing the test are subjective and lack evidence for their effectiveness. The objective of the current study was to quantify lumbopelvic motion and muscle activation during this test and identify which motor control patterns best distinguish individuals with low back pain from asymptomatic controls. METHODS: 18 individuals with sub-acute or chronic low back pain and 32 asymptomatic controls performed the prone hip extension test while a 3D motion capture system measured lumbar and pelvic movement patterns and an electromyography system measured the muscle activation patterns of the paraspinal, gluteus maximus, and hamstring muscles. A three-stage statistical analysis was performed, the final stage being a stepwise logistic regression analysis aimed at identifying the movement and muscle activation pattern variables that best distinguished the two groups. FINDINGS: The final regression model included three lumbar kinematic variables and several electromyographic amplitude variables for the gluteus maximus and hamstring muscles during right-sided prone hip extension. The final model correctly classified 86.7 % of the control group and 83.3 % of the low back pain group. INTERPRETATION: The subject of asymmetrical gluteus maximus and hamstring muscle activation appears to be a potentially interesting area for future research on the utility of the prone hip extension test as a clinical tool in diagnosing motor control impairments associated with low back pain.
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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 | 0.014 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".