Reliability of Ultrasound Measures of the Transversus Abdominis: Effect of Task and Transducer Position
Bibliographic record
Abstract
OBJECTIVE: To assess the reliability of ultrasound (US) measures of the transversus abdominis (TrA) muscle in a sample of subjects with and without specific chronic low back pain and to test whether reliability is enhanced by using different abdominal muscle activation tasks, with use of a foam cube for US transducer stabilization or by averaging 3 measures on the same image. DESIGN: Cross-sectional repeated-measures design. SETTING: Laboratory setting. PATIENTS: Fifteen subjects with chronic low back pain and 15 control subjects. METHODS: Subjects (n = 30) performed 3 tasks in the supine position: (1) contralateral straight leg raise (SLR), (2) bilateral hook-lying leg raising (HLR), and (3) abdominal drawing-in maneuver (ADIM) (control subjects only). Two 7-second videos of the right and left abdominal wall (from rest to contraction) were collected, with and without use of the foam cube. One of the 2 raters repeated the testing 7 to 14 days later to assess intrarater reliability. MAIN OUTCOME MEASUREMENTS: US imaging of abdominal muscles thickness. RESULTS: The TrA muscle was recruited preferentially in the ADIM task compared with the automatic tasks (SLR and HLR). The reliability was comparable among the 3 tasks, with intrarater reliability results being better than interrater reliability results. The use of the foam cube or averaging measures on the same image was generally not effective to increase reliability. CONCLUSIONS: Although they are not as preferential in TrA recruitment as the ADIM, the SLR and HLR tasks showed comparable reliability results. The foam cube used to control transducer orientation and pressure and averaging measures on the same image had limited effect on reliability.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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 | 0.000 |
| 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".