Catheter-related thrombosis: lifeline or a pain in the neck?
Bibliographic record
Abstract
Abstract Central venous catheters (CVCs) are used extensively in cancer patients for the administration of therapy and phlebotomy. An important complication of CVCs is the development of catheter-related thrombosis (CRT), which becomes symptomatic in approximately 5% of the patients. Several factors, such as insertion location and position of the catheter tip, increase the risk of CRT. Prevention of CRT with systemic anticoagulant prophylaxis has largely been ineffective. In addition, the optimal diagnostic strategy and anticoagulant treatment are unclear due to the lack of well-designed studies. The most recent American College of Chest Physicians guidelines recommend (color) Doppler ultrasound more than venography as the initial diagnostic test in patients with suspected arm thrombosis. Only if the ultrasound is negative and clinical suspicion is high is further testing with D-dimer, serial ultrasound, or venography advocated. In case of CRT, removal of the catheter is not necessary if it is functional and needed for chemotherapy. Anticoagulant treatment of CRT consists of treatment with low-molecular-weight heparin (LMWH) followed by vitamin K antagonists for at least 3 months. Whether long-term treatment with LMWH is more effective than vitamin K antagonists in cancer patients with CRT is unknown, but LMWH may be advocated following the recommendations in lower limb thrombosis and cancer. In addition, the effect of new anticoagulants in CRT has not been studied.
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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.016 | 0.003 |
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".