Ultrasound Imaging in Postpartum Women With Diastasis Recti: Intrarater Between-Session Reliability
Bibliographic record
Abstract
STUDY DESIGN: Clinimetrics. OBJECTIVES: To investigate the intrarater between-session reliability of inter-rectus distance (IRD) measurement using ultrasound imaging in postpartum women with diastasis recti. BACKGROUND: Diastasis recti, a separation of the rectus abdominis muscles at the linea alba, occurs as a result of pregnancy and is characterized by increased IRD. The measurement of IRD in this population is of interest to determine changes in diastasis recti severity over time, or in response to treatment. Ultrasound imaging has been proposed as a useful tool to measure IRD in women with diastasis recti; however, the consistency of IRD measurement in this population using ultrasound imaging has, to our knowledge, never been investigated. METHODS: Ultrasound imaging was used to measure IRD in 20 women with diastasis recti on 2 different occasions. On each testing occasion, images were acquired at 4 locations along the linea alba while participants remained relaxed and while they performed a head lift to activate the rectus abdominis muscles. Reliability statistics included intraclass correlation coefficients, Bland-Altman analyses, minimum clinically important difference, and standard error of the measurement. RESULTS: Between-session reliability of IRD measurement was high, particularly when measuring IRD at or above the umbilicus, as indicated by intraclass correlation coefficients greater than 0.90 and low standard error of the measurement and minimum clinically important difference values (below 0.17 cm and 0.46 cm, respectively). Reliability coefficients were poorer when measuring IRD below the umbilicus. CONCLUSION: When performed by an experienced investigator, ultrasound imaging is a reliable tool by which to measure IRD in postpartum women who have diastasis recti.
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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 | 0.001 | 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".