Treatment Strategies and Prognostic Outcomes in Acute Limb Ischemia: A Systematic Review and Meta-Analysis Comparing Thrombolytic Therapy and Open Surgical Interventions
Bibliographic record
Abstract
Background and Objectives: Acute limb ischemia (ALI) is a life-threatening vascular emergency that requires immediate intervention to restore perfusion and prevent limb loss or mortality. Management strategies primarily include thrombolysis and surgical revascularization, each with distinct risks and benefits. This review evaluates and compares the outcomes of thrombolysis and surgical revascularization in ALI management, emphasizing their efficacy, safety, and patient selection criteria. Materials and Methods: A systematic review was conducted in adherence to PRISMA guidelines, analyzing data from 15 studies, including randomized controlled trials and large retrospective analyses, encompassing over 3500 patients with varying demographics and clinical presentations. Study quality was assessed using the Cochrane risk of bias tool and the Newcastle–Ottawa Scale. Results: Thrombolysis, utilizing agents such as urokinase or recombinant tissue plasminogen activator (rt-PA), demonstrated limb salvage rates up to 90% in acute cases, with 30-day mortality rates of 4–6%. It was particularly effective in patients with embolic occlusions or short symptom durations. However, bleeding complications associated with thrombolysis were reported in up to 47% of cases. Conversely, surgical revascularization remains crucial for those with advanced ischemia or contraindications to thrombolysis, offering reliable perfusion restoration but with higher perioperative morbidity, especially in older patients with significant comorbidities. Recent advancements, including hybrid approaches combining catheter-directed thrombolysis with percutaneous mechanical thrombectomy, have shown promise in improving outcomes by reducing procedure times and enhancing clot resolution. Conclusions: While thrombolysis and surgical revascularization are effective, optimizing patient selection remains a key challenge. Future research should focus on refining treatment algorithms, investigating novel thrombolytic agents, and expanding the role of minimally invasive techniques to improve long-term outcomes while mitigating complications such as bleeding and reperfusion injuries.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.012 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".