Don’t Interrupt! A Case Report of Continuing Peritoneal Dialysis After Endoscopic Gastric Tumor Resection
Bibliographic record
Abstract
RATIONALE: The evidence supporting the safety of restarting peritoneal dialysis (PD) immediately after abdominal surgery and interventions is scant. In particular, there are no reported cases characterizing periprocedural management of PD for patients undergoing endoscopic submucosal dissection for gastric intramucosal tumor removal. PRESENTING CONCERNS OF THE PATIENT: A 66-year-old female with end-stage kidney disease secondary to diabetic nephropathy, currently on nocturnal automatic PD, presented with new iron-deficiency anemia. Workup revealed an intramucosal gastric lesion proximal to the pylorus, without surrounding lymph node involvement. Endoscopic submucosal dissection was performed with en bloc endoscopic resection of a 5-cm, partially flat, partially sessile mass along the posterior wall and lesser curvature of the gastric antrum. Pathology revealed low-grade dysplasia without features of malignancy. There was no evidence of hemorrhage or leak post-dissection. DIAGNOSES: The clinical presentation was consistent with an uncomplicated endoscopic submucosal dissection. INTERVENTIONS: Peritoneal dialysis was held for 48 hours and restarted thereafter with no complications. The patient did not require bridging with hemodialysis. OUTCOMES: The patient had an uncomplicated post-endoscopic course, with no subsequent episodes of PD-associated peritonitis after at least 6-month follow-up. NOVEL FINDING: This is the first reported case of PD reinitiation after endoscopic submucosal dissection of a gastric tumor.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.007 | 0.005 |
| Insufficient payload (model declined to judge) | 0.003 | 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".