Histologic and Cost-Benefit Analysis of Laparoscopic Sleeve Gastrectomy Specimens Performed for Morbid Obesity
Bibliographic record
Abstract
CONTEXT.—: Laparoscopic sleeve gastrectomy (LSG) has quickly become the bariatric surgical procedure of choice for patients with obesity who have failed medical management. Laparoscopic sleeve gastrectomy results in a gastric remnant that is routinely subject to pathologic examination. OBJECTIVE.—: To perform a histologic and cost-benefit analysis of gastric remnants post-LSG. DESIGN.—: All LSG cases performed at University Health Network, Toronto, Ontario, Canada, between 2010 and 2019 were reviewed. Specimens that underwent routine histopathologic assessment and ancillary immunohistochemical analysis were analyzed. Baseline patient characteristics and surgical outcomes were obtained from our internal database. The total cost of specimen gross preparation, examination, sampling, and producing and reporting a hematoxylin-eosin slide was calculated. RESULTS.—: A total of 572 patients underwent LSG during the study period and had their specimens examined histologically. A mean of 4.87 blocks generating 4 hematoxylin-eosin slides was produced. The most common histologic findings reported in LSG specimens ranged from no pathologic abnormalities identified together with proton pump inhibitor-related change. A minority of cases demonstrated clinically actionable histologic findings, of which Helicobacter pylori infection was the most common. The total cost for the complete pathologic analysis of these cases amounted to CaD $66 383.10 (US $47 080.21) with a mean of CaD $116.05 (US $82.40) per case. A total of CaD $62 622.75 (US $44 413.30) was spent on full examination of cases that had no further postoperative clinical impact. CONCLUSIONS.—: There is a broad spectrum of pathologic findings in LSG specimens, ranging from clinically nonactionable to more clinically actionable. The vast majority of histologic findings had no clinical impact, with only a minority of cases being clinically significant. This study therefore recommends that LSG specimens be subject to gross pathologic examination in the vast majority of cases. However, sections should be submitted for microscopic analysis if grossly evident lesions are present and if there is a clinical/known history of clinically actionable findings.
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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 | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".