Patients with Systemic Sclerosis Seeking Metabolic and Bariatric Surgery: Which Operation to Perform?
Bibliographic record
Abstract
Background: Systemic sclerosis (scleroderma) is a rare progressive autoimmune disease that affects the gastrointestinal (GI) system. Given the increasing prevalence of obesity, selecting the appropriate metabolic and bariatric operation (MBS) in these patients present a unique challenge to bariatric surgeons. Objectives: To evaluate the long-term outcomes of MBS in patients with scleroderma. Methods: We report 1-year outcomes (esophageal dysmotility, weight loss, and complications) of two patients with scleroderma and obesity who underwent sleeve gastrectomy (SG) and Roux-en-Y gastric bypass (RYGB) at our institution. We also review the literature regarding benign upper GI surgery in patients with scleroderma. Setting: This study was performed in University hospital settings at Kingston Health Sciences Center, Canada. Results: We identified two patients with severe obesity and scleroderma. Patient #1 was a 61-year-old female with a body mass index (BMI) of 41.6 kg/m 2 . She had mild esophageal dysmotility without clear evidence of scleroderma esophagus and underwent a SG. On follow-up, she developed scleroderma esophagus with progressive dysphagia and recurrent aspirations. She was converted to RYGB with satisfactory weight loss and improvement in her GI symptoms. Patient #2 was a 61-year-old female with a BMI of 46 kg/m 2 . She had scleroderma esophagus on initial assessment and underwent a RYGB with excellent control of her GI symptoms and satisfactory weight loss. Conclusion: RYGB is the preferred MBS in patients with scleroderma and obesity given the progressive nature of scleroderma. SG should be avoided as patients will likely go on to develop scleroderma esophagus and present with worsening reflux, dysphagia, and aspirations.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".