165. RISK STRATIFICATION FOR STRICTURE FORMATION AFTER ENDOSCOPIC SUBMUCOSAL DISSECTION FOR ESOPHAGEAL DYSPLASIA
Bibliographic record
Abstract
Abstract Background Endoscopic submucosal dissection (ESD) is increasingly employed for early esophageal dysplasia, including squamous cell (SCD) and Barrett’s esophagus-related (BE) dysplasia. A major drawback of this strategy is stricture formation, which can lead to significant morbidity and require repeated interventions. We aimed to evaluate demographic, clinical, procedural, and histopathologic factors associated with stricture development following esophageal ESD. Methods We conducted a retrospective cohort study, analyzing data from 126 patients undergoing ESD for esophageal lesions from 2019–2024. Of these, 18 were excluded from follow-up due adverse pathology prompting esophagectomy (15 patients) or loss to follow-up (3 patients), resulting in 108 patients for analysis. Among these, 20 (18.52%) had SCD, and 88 (81.48%) had BE dysplasia. Demographic data, comorbidities, lesion characteristics, procedure details, postprocedural management and histopathological findings were collected. The primary outcome was stricture formation, defined as a symptomatic luminal narrowing at the ESD site confirmed on follow-up endoscopy, requiring intervention. Results Strictures developed in 24% of patients; 85% were impassable with a 9.9 mm gastroscope. Stricture rates increased with defect circumferential involvement, >90% (42%). On univariate analysis, BE was associated with lower stricture formation (OR0.30, 95% CI 0.11–0.81). Lesion size (OR1.21), lesion circumferential involvement (OR 1.03), defect size (OR1.16), defect circumferential involvement (OR1.05), deep mural injury (OR 9.29), clips to treat a DMI (OR 9.29), and length of hospitalization (OR 2.04) were associated with increased stricture rates. Independent predictors included defect circumferential involvement (OR 1.07, 95%CI 1.03–1.12), LOH (OR 1.88, 95%CI 1.11–3.16), and DMI (OR 6.28, 95%CI 1.10–35.88). Conclusion Stricture formation post-ESD is strongly associated with lesion and procedural characteristics, including defect circumferential involvement, deep mural injury and length of hospitalization. These findings showcase the importance of individualized risk stratification to guide tailored prophylactic and therapeutic strategies. Aggressive use of interventions, such as prophylactic steroids or other adjunctive measures, based on specific risk factors, may help mitigate the risk of stricture formation and improve patient outcomes in those at highest risk.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.002 | 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".