Anaesthesia for vascular emergencies – a state of the art review
Bibliographic record
Abstract
In this state-of-the-art review, we discuss the presenting symptoms and management strategies for vascular emergencies. Although vascular emergencies are best treated at a vascular surgical centre, patients may present to any emergency department and may require both immediate management and safe transport to a vascular centre. We describe the surgical and anaesthetic considerations for management of aortic dissection, aortic rupture, carotid endarterectomy, acute limb ischaemia and mesenteric ischaemia. Important issues to consider in aortic dissection are extent of the dissection and surgical need for bypasses in addition to endovascular repair. From an anaesthetist's perspective, aortic dissection requires infrastructure for massive transfusion, smooth management should an endovascular procedure require conversion to an open procedure, haemodynamic manipulation during stent deployment and prevention of spinal cord ischaemia. Principles in management of aortic rupture, whether open or endovascular treatment is chosen, include immediate transfer to a vascular care centre; minimising haemodynamic changes to reduce aortic shear stress; permissive hypotension in the pre-operative period; and initiation of massive transfusion protocol. Carotid endarterectomy for carotid stenosis is managed with general or regional techniques, and anaesthetists must be prepared to manage haemodynamic, neurological and airway issues peri-operatively. Acute limb ischaemia is a result of embolism, thrombosis, dissection or trauma, and may be treated with open repair or embolectomy, under either general or local anaesthesia. Due to hypercoagulability, there may be higher numbers of acutely ischaemic limbs among patients with COVID-19, which is important to consider in the current pandemic. Mesenteric ischaemia is a rare vascular emergency, but it is challenging to diagnose and associated with high morbidity and mortality. Several peri-operative issues are common to all vascular emergencies: acute renal injury; management of transfusion; need for heparinisation and reversal; and challenging postoperative care. Finally, the important development of endovascular techniques for repair in many vascular emergencies has improved care, and the availability of transoesophageal echocardiography has improved monitoring as well as aids in surgical placement of endovascular grafts and for post-procedural evaluation.
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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 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".