Risk Factors for Subclavian Vein Thrombosis in Cancer Patients With Total Parenteral Nutrition
Bibliographic record
Abstract
BACKGROUND: There are few reports on total parenteral nutrition (TPN) and its possible prothrombotic effect. The purpose of this study was to identify risk factors for subclavian vein thrombosis (SVT) in patients receiving TPN. METHOD: Cancer patients with indwelling subclavian catheters and TPN were followed in a cohort study. Doppler ultrasound examination was performed 8 and 30 days after catheter placement. RESULTS: One hundred twenty-one patients were included, with a mean of 61 (± 11.8) years of age. We detected 36 SVT events at day 8 (29.8%) and 47 (38.8%) at day 30 after central catheter placement. Mean length of subclavian catheterization was 17.2 (± 8.2) days. Fifty-three point three percent of patients receiving ≥ 3,050 mOsm TPN in 24 hours developed SVT (relative risk (RR) = 2.01, 95% CI, 1.14 - 3.57; P = 0.016) at day 8 and 60% (RR = 1.67, 95% CI, 1.30 - 2.71; P = 0.038) at day 30 post-catheter placement. Protein administration of > 97.5 g/day was shown to be a risk factor for early thrombosis with a mean of 16.88 days for the development of SVT (95% CI, 10 - 23.7) versus 27.8 days (95% CI, 25.8 - 29.9) in the group with nutritional protein content < 97.5 g/day (P = 0.000). CONCLUSION: High-osmolarity and high-protein nutrition formulas were shown to be risk factors for SVT in cancer patients receiving TPN.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".