Utilization and Complications of Central Venous Access Devices in Oncology Patients
Bibliographic record
Abstract
PURPOSE: To describe how central venous access devices (CVADs) are utilized for ambulatory oncology patients and to evaluate the rate of complications. METHOD: Single institution retrospective study of oncology patients with CVADs who received systemic treatment at the Walker Family Cancer Centre (WFCC) between 1 January and 31 December 2018. RESULTS: A total of 480 CVADS were placed in 305 patients, of which 408 (85%) were peripherally inserted central catheters (PICCs) and 72 (15%) were implanted vascular access devices (PORTs). The incidence of early and late complications was 9% and 24%, respectively. For the entire cohort, the rate of venous thromboembolism (VTE) was 16%, of which 9% were CVAD-related thrombosis (CRTs) and 7% were distant VTE. The CRT rates were similar for PICCs and PORTs (9% vs. 7%). A total of 6% of CVADs were complicated by infection (i.e., localized infections and bacteremia), with a total infection rate of 0.43 and 0.26 per 1000 indwelling days for PICCs and PORTs, respectively. The incidence of central line associated bloodstream infections (CLABSI) was greater for PICCs than PORTs, at a rate of 0.22 compared with 0.08 per 1000 indwelling days, respectively. The premature catheter removal rate was 26% for PICCs and 18% for PORTs. PORTs required more additional hospital visits. CONCLUSIONS: PICCs were utilized more frequently than PORTs and had a higher rate of premature removal. The rates of VTE and CRT were similar for both CVAD types. PORTs had a lower rate of infection per 1000 indwelling days. However, the management of PORT related complications required more visits to the hospital and oncology clinic.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".