Abstract TP117: A Systematic Literature Review of Patients With Carotid Free Floating Thrombus and Acute Ischemic Stroke
Bibliographic record
Abstract
Introduction: Carotid Free Floating Thrombus (CFFT) includes numerous pathological entities. It is theorized that CFFT leads to ischemic stroke secondary to embolization with high risk of short-term recurrence. There is uncertainty in diagnosis, prognosis, and optimal medical or surgical management of CFFT. To synthesize the vast recent literature, we performed a systematic literature review (SLR) of CFFT. Methods: Literature search for Thrombus, Carotid and related terms yielded 3126 results. After a preliminary assessment of 3126 retrieved manuscripts, 273 were reviewed in detail. A total of 144 manuscripts met entry criteria. We present the demographics, risk factors (RF), treatment modality and outcome of stroke or death at 30 days of CFFT patients. Acute treatment modalities consisted of surgical (carotid endarterectomy or stenting within 72 hours) or medical interventions. The relationship between treatment modality and outcome was assessed using logistic regression including relevant RF, antithrombotic type, demographic, imaging, and surgical variables. Results: Our SLR yielded 530 CFFT patients with a median age at presentation of 60.5 (IQR 48-71) and 36.2% were females. The majority (64%) of patients had at least one RF. Patients were treated acutely surgically (27.9%) or medically (82.7% with anticoagulation, 16.8% with dual antiplatelet (DA). Thirty-day stroke and death rate was 17.1% in 345 cases with follow-up. Patients receiving dual antiplatelet therapy had an increased risk of stroke or death at 30 days (RRR 30.31, 95% confidence interval, 1.66- 553.22; P =0.02) compared to patients not receiving dual antiplatelet therapy. There was no significant relationship between early anticoagulation or acute surgical approach and primary outcome, although a trend favoring anticoagulation over surgical approach was seen (13.6% vs. 21.9%). Conclusions: CFFT patients are at a short-term high risk for stroke or death. DA was associated with increased short term risk in these patients; however, the optimal treatment approach remains uncertain. Future studies are needed as RCTs are lacking and publication bias limits our findings.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.007 | 0.037 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.005 |
| Bibliometrics | 0.025 | 0.021 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".