Efficiency of the Crile Procedure in the Removal of Thyroid Malignancies Invaded into the Internal Jugular Vein
Bibliographic record
Abstract
Aim: This work aims to determine the effectiveness of the Crile procedure for optimizing the diagnosis and treatment of patients with locally advanced thyroid malignancies. Objects: The objects of the study were the results of treatment of patients with thyroid cancer using two techniques: Crile procedure and vein resection with sealing and preservation of blood flow. Materials and Methods: The research was carried out experimentally using Crile surgical intervention and vein resection with sealing and preservation of blood flow. The effectiveness of the treatment was assessed by observing the recurrence and mortality rates. The patient’s quality of life was assessed through the conversation and questionnaire survey. Results and Findings: It was found that Doppler ultrasonography of the main vessels in the neck helps to establish the internal jugular vein invasion, as well as its tumour thrombosis at the preoperative stage in clinical cases of suspected extrathyroidal extension of thyroid tumours in addition to radiological methods. A thyroid gland with a tumour invaded into the internal jugular vein must be radically removed with simultaneous resection of the affected part of the vein. We proved that the Crile procedure — resection of a vein with sealing of stumps and interruption of blood flow on one side of the neck — is a safe technique. It reduces the trauma and duration of the operation and reduces the likelihood of recurrence as it does not require further plastic surgery or vascular shunting with the restoration of blood flow. At the same time, bilateral interruption of blood flow in cases of resection of both internal jugular veins can lead to serious complications and requires a blood flow restoration operation from the side of the smaller tumour invasion.
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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 | 0.000 |
| 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) | 0.002 | 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".