The Utility of the Functional Sphincter Area: A Novel Functional Lumen Imaging Probe Parameter for the Assessment of Anal Sphincter Structure and Function in Fecal Incontinence
Bibliographic record
Abstract
Background/Aims The functional lumen imaging probe (FLIP) is a unique tool to measure the anal sphincter during distension. Using detailed geometric data generated by FLIP, we present the functional sphincter area (FSA), a novel measurement of sphincter morphology with potential clinical utility in the investigation of fecal incontinence (FI). Methods Parous female patients with FI presenting to a tertiary pelvic floor unit were prospectively recruited. FLIP measurements were obtained alongside endoanal ultrasound and high-resolution anorectal manometry. Results Thirty-one parous female patients with FI (median age: 62) were recruited. On endoanal ultrasound, 14 (45.2%) were found to have a sphincter defect in either the external sphincter (n = 10), or in both the external and internal sphincter (n = 4). The FSA demonstrated a consistent pattern of change during distension of the FLIP bag in all patients. At rest, the FSA was greater in those without anal sphincter defects at 30 ml (72.6 vs 53.2 mm2; p = 0.029) and 40ml (71.5 vs 45.5 mm2; p = 0.048) bag volumes. The same pattern was observed during voluntary squeeze at 30 ml (67.8 vs 42.8 mm2; p = 0.044) and 40ml (61.2 vs 38.6 mm2; p = 0.040) bag volumes. By contrast, there were no differences in symptom severity or manometry measurements between the two groups. Conclusions The FSA may offer a clinically useful parameter and, in combination with other FLIP measurements, could become a useful tool to assess the structure and function of the anal canal in FI.
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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 | 0.001 | 0.003 |
| 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 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".