Jejunal angiodysplasia: surgery can be life-saving – a case report
Bibliographic record
Abstract
Introduction: Angiodysplasia, a rare cause of gastrointestinal (GI) bleeding, presents a spectrum of clinical manifestations from anemia to life-threatening hemorrhage. This case study emphasizes the significance of considering intestinal vascular malformations as a differential diagnosis, especially in the context of chronic anemia and GI bleeding. Jejunal angiodysplasia, though infrequent, poses diagnostic challenges due to the hidden nature of the small bowel in the GI system. Case presentation: A 23-year-old male presented with acute hematochezia and melena, necessitating prompt intervention. Despite a normal esophagogastroduodenoscopy, colonoscopy was hindered, CT angiography could not be performed due to the patient's unstable condition, leading to a planned exploratory laparotomy. Surgical exploration revealed a mucosal vascular lesion in the jejunum, prompting resection, and anastomosis. The patient's postoperative course was uneventful, reinforcing the importance of swift diagnosis and intervention. Clinical discussion: Angiodysplasia's pathogenesis remains unclear, with hypotheses implicating vascular endothelial growth factor and submucosal changes. Challenges in management revolve around lesion localization and stabilizing hemodynamics, necessitating a multidisciplinary approach. While endoscopy is often diagnostic and therapeutic, advanced modalities such as CT angiography may be required. Literature review highlights diverse presentations and successful interventions, including embolization and surgical resection. Conclusion: Jejunal angiodysplasia demands a comprehensive diagnostic and therapeutic strategy. The presented case underscores the pivotal role of endoscopy, embolization, and surgery in managing this condition. Timely diagnosis and intervention are crucial for mitigating the impact of angiodysplasia, necessitating further research and collaborative efforts for improved management of this rare condition.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.006 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".