Functional lumen imaging probe in the functional assessment of pyloric sphincter in gastroparesis: a systematic review with meta-analysis of normative values
Bibliographic record
Abstract
Aims The selection of the optimal patient to undergo invasive treatments is one of the major challenges in refractory gastroparesis. The aim of this systematic review was to investigate the role of FLIP in gastroparesis. Meta analysis of normative values and treatment comparative outcomes was also performed. Methods A systematic search was performed until May 2024 on 3 major databases. Studies on post-oncological/bariatric surgery gastroparesis were excluded. Pooled baseline mean of FLIP metrics and mean differences (MDs) pre vs post-treatment were calculated to provide normative values and to assess treatment effect. Random effects meta-analysis with I 2 statistics and subgroup analysis to address heterogeneity were performed. Results Twenty studies (N=805 patients) were included. The majority focused on treatment response, particularly pyloromyotomy (GPOEM). The most assessed FLIP metrics were distensibility index (DI) and cross-sectional area (CSA). Three studies reported a positive correlation between DI and CSA with specific symptoms (dyspepsia spectrum and nausea/vomiting) and their severity at baseline. Ten studies showed an association between FLIP parameters with clinical response but not with gastric emptying. Baseline DI at 30 mL (7.5 mm 2 /mmHg; I 2 38%) and CSA at 30 mL (85.5 mm 2 ; I 2 0%) yielded the lowest heterogeneity. Comparing pre- and post-treatment response, MD of 2.5 mm 2 /mmHg (I 2 24%) for DI at 50 mL, 46.7 mm 2 (I 2 47%) and 68.8 mm 2 (I 2 0%) for CSA at 40 and 50 mL respectively, resulted statistically significant. Conclusions This is the first systematic effort in gathering evidence on FLIP in gastroparesis. CSA and DI significantly changed after pylorus-targeted treatments. Normative values displayed substantial heterogeneity. Further studies to develop and validate models of response prediction are warranted before implementing this technique in routine clinical care. Publication History Article published online: 27 March 2025 © 2025. European Society of Gastrointestinal Endoscopy. All rights reserved. Georg Thieme Verlag KG Oswald-Hesse-Straße 50, 70469 Stuttgart, Germany
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.010 | 0.033 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.013 | 0.020 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".