1233 Role of Preoperative Embolization in the Surgical Management of Carotid Body Tumors: A Systematic Review and Meta-Analysis
Bibliographic record
Abstract
Abstract Aim The role of preoperative embolization in the surgical management of carotid body tumors (CBT) remains a topic of debate. The aim of this study was to evaluate the effect of preoperative embolization on CBT resection. Method A systematic review and meta-analysis was conducted following the PRISMA protocol. Pubmed, Scopus and Web of Science were screened for studies published between 2010-2022. Primary outcomes investigated were intraoperative blood loss, operative time, length of hospital stay, and perioperative complications such as TIA/stroke, vascular injury and cranial nerve injury. Quality assessment of selected studies was performed using the Newcastle-Ottawa Scale (NOS). Publication bias was assessed using funnel plots and Egger’s regression test. Results Twenty-five studies were included in the systematic review, involving 1649 patients. Twenty-three studies were eligible for meta-analysis. The incidence of vascular injury necessitating intervention was significantly less in the preoperative embolization group (OR = 0.60; 95% CI: 0.42-0.84; P = .003). There was no statistically significant difference between the two groups with regards to intraoperative blood loss, operative time, length of hospital stay, incidence of TIA/stroke and cranial nerve injury. Subgroup analyses did not show significant difference between Shamblin I, II and III subgroups with regards to operative time. Conclusions This systematic review and meta-analysis found preoperative embolization to be significantly beneficial in reducing vascular injury. No statistically significant difference was found between the two groups regarding intraoperative blood loss, operative time, length of hospital stay and complications such as TIA/stroke and cranial nerve injury.
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 | 0.014 | 0.034 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.016 | 0.036 |
| Bibliometrics | 0.007 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".