Test‐retest reliability of clitoral blood flow measurements using color Doppler ultrasonography at rest and after a pelvic floor contraction task in healthy adult women
Bibliographic record
Abstract
AIMS: Test-retest reliability assessment of the dorsal clitoral artery's blood flow at rest and after muscle activation has never been documented. If this outcome measure is to be used in conditions impeding vascularity, it requires a psychometric evaluation. The aim of this study was to assess the inter-session test-retest reliability of clitoral blood flow in healthy women using color Doppler ultrasonography at rest and after a pelvic floor muscle (PFM) contraction task. METHODS: Two assessment sessions were conducted using a clinical ultrasound system. Clitoral blood flow measurements were repeated at rest and after a PFM contraction task. Measurements of the peak systolic velocity (PSV), time-averaged maximum velocity (TAMX), end-diastolic velocity (EDV), pulsatility index (PI), and resistance index (RI) were taken. The test-retest reliability was assessed using paired t-test, intraclass correlation coefficient (ICC), and Bland-Altman plots. RESULTS: For reliability at rest, ICC values were 0.95 for PSV, 0.87 for TAMX, and 0.67 for both PI and RI. The variability between measurements, as per Bland-Altman plots, was small for PSV, TAMX, and RI and acceptable for PI. For reliability after the PFM contractions task, ICC values were 0.85 for PSV, 0.77 for TAMX, 0.79 for PI, and 0.81 for RI. The variability between measurements was small for PSV and RI and acceptable for TAMX and PI. EDV parameter did not perform as well in both conditions. CONCLUSIONS: Assessment of the clitoral blood flow with color Doppler ultrasound is reliable at rest and after a PFM contraction task.
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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 | 0.005 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".