Inferior vena cava tumor thrombus: clinical outcomes at a canadian tertiary center
Bibliographic record
Abstract
OBJECTIVE: This study reports the surgical management and outcomes of patients with malignancies affecting the IVC. METHODS: This was a retrospective study that considered patients undergoing surgery for IVC thrombectomy in Calgary, Canada, from 1 January 2010 to 31 December 2021. Parameters of interest included primary malignancy, the extent of IVC involvement, surgical strategy, and medium-term outcomes. RESULTS: Six patients underwent surgical intervention for malignancies that affected the IVC. One patient had a retroperitoneal leiomyosarcoma, 1 had hepatocellular carcinoma with thrombus extending into the IVC and right atrium, 1 had adrenocortical carcinoma with IVC thrombus extending into the right atrium, and 3 had clear cell renal cell carcinoma with thrombus extending into the IVC. Surgical strategy for the IVC thrombectomy varied where 5 patients required the institution of cardiopulmonary bypass and underwent deep hypothermic circulatory arrest. No patient died perioperatively. One patient died 15-months post-operatively from aggressive malignancy. CONCLUSION: Different types of malignancy can affect the IVC and surgical intervention is usually indicated for these patients. Herein, we have reported the outcomes of IVC thrombectomy at our center.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".