Medical Therapy Following Urgent/Emergent Revascularization in Peripheral Artery Disease Patients (Canadian Acute Limb Ischemia Registry [CANALISE I])
Bibliographic record
Abstract
Background Following severe limb ischemia requiring urgent/emergent revascularization, peripheral arterial disease patients suffer a high risk of recurrent atherothrombosis. Methods Patients discharged from Hamilton General Hospital (Hamilton, Ontario) between April 2016 and September 2017 following severe limb ischemia requiring urgent/emergent revascularization were identified via the Local Health Integration Network CorHealth database, with supplemental information from chart review. Results A total of 158 patients admitted for urgent/emergent revascularization were identified (148 alive at discharge). Among patients without a pre-existing indication for anticoagulation, 38.8% ( n = 47) were discharged on single-antiplatelet therapy, 27.3% ( n = 33) on dual-antiplatelet therapy, 19.8% ( n = 24) on anticoagulants plus antiplatelet therapy, 6.6% ( n = 8) on anticoagulants alone, and 2.6% ( n = 3) on unknown therapy. Patients who received angioplasty with stenting were more likely be discharged on dual-antiplatelet therapy (hazard ratio [HR]: 7.14; 95% confidence interval [CI]: 2.87-17.76; P < 0.01); patients who received an embolectomy/thrombectomy were more likely be discharged on an anticoagulant alone (HR: 2.61; 95% CI: 1.00-6.81; P = 0.049); and patients who received peripheral bypass grafting were more likely be discharged on single-antiplatelet therapy (HR: 2.28; 95% CI: 1.11-4.69; P = 0.024). Neither statins (60.8% vs 56.3%; P = 0.23) nor renin–angiotensin–aldosterone system inhibitors (48.7% vs 50.6%; P = 0.58) were prescribed at higher rates at discharge, compared with the rate at admission. Conclusions Substantial heterogeneity exists in antithrombotic prescription following urgent/emergent revascularization. No intensification of non-antithrombotic vascular protective medications occurred during hospitalization. Clinical trials and health system interventions to optimize medical therapy in peripheral arterial disease patients are urgently needed.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".