A49 PROSPECTIVE PAIRED COMPARISON STUDY OF 2 FRANSEEN-TIP EUS FNB NEEDLES, FLEXIBLE VS STIFF SHEATH
Bibliographic record
Abstract
Abstract Background Variety of needle tips and suction techniques have been trialled to optimize diagnostic yield in EUS-FNB for comprehensive histopathological analysis with some studies suggesting improved performance with franseen tip needle Aims Obtain an objective comparison of diagnostic yield between 2 different 22g franseen-tip needles; novel flexible sheath (FS) franseen tip needle and traditional stiff sheath (SS) needle Methods Sample of patients presenting for outpatient elective EUS-FNB were selected. Underwent EUS-FNB using both a SS and FS FNB needle during same procedure. Equal number of passes was obtained with each needle by same endoscopist with random order of sampling, with a planned number of 2 passes per needle; not obtained for one lesion due to difficulty with puncture. Obtained specimens were sent to pathology; quality of sampling was assessed by the pathologist and cellularity was recorded as a percentage. In procedures where one needle was unable to puncture or an acellular specimen was obtained a score of 0 was given. Paired 2 tailed t-test was performed for comparison of mean cellularity. Hazard ratio was calculated for risk of obtaining a non-diagnostic sample Results SS mean cellularity 45.7% SD 25.7 FS mean cellularity 72.9% SD 17.0 Difference in mean cellularity 27.2% two-tailed p-value=.08 Hazard ratio of obtaining a non-diagnostic sample with SS: HR 5 p=0.28 No statistically significant difference in results but a numerical trend is noted. Analysis demonstrates variability in cellularity of specimens obtained with each needle type; 6/8 specimens showed higher cellularity with FS needle while only 1/8 showed higher cellularity with SS. In 2 cases, both similar lesion types in different patients, non-diagnostic specimens were obtained by SS. One patient due to inability to puncture and in a second due to inadequate cellularity Conclusions Results may suggest presence of tissue characteristics or lesion-specific factors that influenced the sampling efficacy. Findings can provide potential insight into optimizing selection of biopsy needle designs and is a novel look at an uncommonly analyzed aspect of FNB needle design, namely sheath stiffness. Several limitations of this study, primarily the small sample size Further research with larger cohorts is needed to compare the diagnostic yields of needle types. Despite preliminary nature of these results, this study contributes real world paired comparison data Funding Agencies:
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".