Management of spontaneous and iatrogenic retroperitoneal haemorrhage: conservative management, endovascular intervention or open surgery?
Bibliographic record
Abstract
BACKGROUND: Retroperitoneal haematoma is a rare clinical entity with variable aetiology, which is increasing in incidence mainly due to complications related to interventional procedures. There is no general consensus as to the best management plan for patients with retroperitoneal haematoma. METHODS: A literature review was undertaken using MEDLINE, all relevant papers on retroperitoneal haemorrhage or haematoma were used. RESULTS: The diagnosis is often delayed as symptoms are nonspecific. Retroperitoneal haematoma should be suspected in patients with significant groin, flank, abdominal, back pain or haemodynamic instability following an interventional procedure. Spontaneous haemorrhage usually occurs in patients who are anticoagulated. Multi-slice CT and arteriography are important for diagnosis. Most haemodynamically stable patients can be managed with fluid resuscitation, correction of coagulopathy and blood transfusion. Endovascular treatment involving selective intra-arterial embolisation or the deployment of stent-grafts over the punctured vessel is attaining an increasingly important role. Open repair of retroperitoneal bleeding vessels should be reserved for cases when there is failure of conservative or endovascular measures to control the bleeding. Open repair is also required if endovascular facilities or expertise is unavailable and in cases where the patient is unstable. If treated inappropriately, the mortality of patients with retroperitoneal haematoma remains high. CONCLUSION: There is a lack of level I evidence for the best management plans for retroperitoneal haematoma, and evidence is based on small cohort series or isolated case reports. Conservative management should only be reserved for patients who are stable. Interventional radiology with intra-arterial embolisation or stent-grafting is the treatment of choice. Open surgery is now rarely required.
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| 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".